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					                                                               (IJCNS) International Journal of Computer and Network Security, 1
                                                                                                          Vol. 2, No. 3, March 2010




   Cryptanalysis of an efficient biometrics-based
remote user authentication scheme using smart cards
                                            Fuw-Yi Yang 1 and Jian-Sen Wang 2
                                   1
                                    Department of Computer Science and Information Engineering,
                                                Chaoyang University of Technology,
                                   168 Jifong E. Rd., Wufong Township Taichung County, 41349,
                                                          Taiwan, R.O.C.
                                                         yangfy@cyut.edu.tw
                                   2
                                    Department of Computer Science and Information Engineering,
                                                Chaoyang University of Technology,
                                   168 Jifong E. Rd., Wufong Township Taichung County, 41349,
                                                          Taiwan, R.O.C.
                                                       s9827619@cyut.edu.tw


                                                                   2, we give a brief review of Li and Hwang’s proposed
Abstract:     The authors Li and Hwang have proposed an
efficient biometrics-based remote user authentication scheme       scheme, and then, in Section 3, we demonstrate this
using smart cards. Security is provided through one-way hash       scheme’s weaknesses. Finally, we conclude this paper in
functions and biometrics verification. This scheme is more         Section 4.
efficient than other related schemes and enables the users to
change their passwords freely. However, there are some flaws in    2. Review of Li and Hwang’s proposed scheme
it, such as vulnerability to impersonation attacks, password-
guessing attacks, and power analysis attacks. Thus, this paper        Li and Hwang proposed an efficient biometrics-based
shows that the scheme proposed by Li and Hwang can be              remote user authentication scheme using smart cards. The
susceptible to certain types of attacks.                           scheme is divided into three phases: registration phase,
   Keywords: Biometrics, remote user authentication,               login phase, and authentication phase. Here, we briefly
impersonation attacks, password-guessing attacks, power analysis   introduce the three phases. In Table 1, we list the notations
attacks                                                            and abbreviations used in their scheme. The three phases are
                                                                   as follows:
1. Introduction                                                              Table 1: Notations used in their scheme
   In an insecure network environment, user authentication                       Client
                                                                    Ci
is a significant component of security. Remote user
authentication schemes are used to verify the validity of the       Si           Server
user login request. In 1981, Lamport [1] proposed a remote          Ri           Trust registration center
user authentication scheme with verification tables.                 IDi         Identity of the user
However, Hwang and Li pointed out that if the verification
tables were modified or stolen, the remote authentication            PWi         Password of the user between Ci and Si
system would be influenced. Therefore, in 2000, Li and              Bi           Biometrics template of the user
Hwang proposed [2] a remote user authentication scheme              h (.)        One-way hash function
without any verification tables, using smart cards.
                                                                    Xs           Secret information maintained by the Si
   In general, ID-based remote user authentication schemes
are based on passwords [3], [4]. As simple passwords are             Rc          Random number chosen by the Ci
easy to break, many schemes have been proposed to enhance            Rs          Random number chosen by the Si
the security of the remote user authentication. But the
passwords can be lost, forgotten, or shared with other              ||           Concatenation
people, and thus, there is no way to know who the actual            ⊕            XOR operation
user is. Therefore, it cannot provide non repudiation. Hence,
biometric keys have been proposed [5], which are based on            2.1 The Registration Phase
personal characteristics such as fingerprints, palm prints,
and irises.                                                           Before the users login to the system, they must perform
   Li and Hwang have proposed an efficient biometrics-             the following steps, as shown in Figure 1.
based remote user authentication scheme using smart cards             Step 1: The users offer their personal biometrics, Bi , on
[6], which, however, could not withstand the impersonation         the specific device and input the password, PWi , and the
and power consumption attacks. This paper shall point out          user identity, IDi , to the registration center in person.
the flaws of this proposed scheme.
   The rest of this paper is organized as follows. In Section
2                                                                     (IJCNS) International Journal of Computer and Network Security,
                                                                                                                 Vol. 2, No. 3, March 2010

   Step 2: The registration center computes the messages                   Step 1: Si checks if the format of C i ’s IDi is valid or
ri = h ( PWi || fi ) and                                                 not.
 ei = h( IDi || Xs) ⊕ h( PWi || fi ) , where fi = h( Bi ) and Xs is        Step 2: If the above-mentioned holds, Si computes the
the secret information generated by Si .                                 messages           M 3 = h( IDi || Xs) ,     M 4 = M 2 ⊕ M 3 = Rc ,
    Step 3: The registration center stores ( IDi , h (.), fi , ei )       M 5 = M 3 ⊕ Rs , and M 6 = h( M 2 || M 4 ) to provide mutual
into the user’s smart card and then sends it to the user                 authentication between client and server.
through a secure channel.                                                  Step 3: Next, Si sends the messages (M5, M6) to Ci .
                                                                            Step 4: On receiving the Si ’s message, C i checks if
           Ci                    Ri
                IDi , Bi , PWi                                            M 6 = h( M 2 || Rc) .
                                                                            Step 5: If the above-mentioned holds, C i considers that
                             Computes
                                                                          Si is authenticated and then computes the following
                             ri = h(PW || fi )
                                      i
                                                                         messages to offer mutual authentication between client and
                             ei = h(IDi || Xs) ⊕ h(PW || fi )
                                                     i                   server.
                Stores ( ID i , h(.), f i , e i ) in the smart card       M 7 = M 5 ⊕ M 1 = Rs ,
                                                                         M 8 = h( M 5 || M 7 ) ,
                  Smart card                                             where M7 is the random number of the server. The client,
                                                                         which knows M 1 = h ( IDi || Xs) , can send back the message
                                                                         of M 8 = h((h( IDi || Xs ) ⊕ Rs) || Rs) .
                 Figure 1. The registration phase
                                                                            Step 6: Ci sends the message M8 to Si .
   2.2 The Login Phase                                                      Step 7: On receiving C i ’s message, Si checks if
   Whenever the users want to login to the server, they need              M 8 = h( M 5 || Rs) .
to perform the following steps, as shown in Figure 2.
                                                                            Step 8: If it holds, the server accepts C i ’s login
   Step 1: The users insert their smart card into the smart
card reader of a terminal and offer their personal biometrics,           request; otherwise, it rejects it.
 Bi , on the specific device to verify user biometrics. Next,
the system checks if h( Bi ) = f i .                                                   Ci                   Si
                                                                                                    Checks the format of Ci ' s IDi
     Step 2: If it holds, the user passes the biometrics
                                                                                                    Computes M 3 = h(IDi | | Xs)
verification. Then the user inputs the PWi . Otherwise, it
                                                                                                                 M 4 = M 2 ⊕ M 3 = Rc
means the user did not pass the biometrics verification and
the client terminates the session.                                                                               M5 = M 3 ⊕ Rs
     Step 3: After receiving C i ’s password, the smart card                                                     M6 = h(M 2 || M 4 )
will compute the messages                                                                             M5 , M 6
 ri ' = h( PWi || f i ) , M 1 = ei ⊕ ri ' = h( IDi || Xs) , and                                 ?
                                                                                Verifies M 6 = h(M 2 || Rc)
M 2 = M 1 ⊕ Rc , where Rc is a random number generated
                                                                                Computes M 7 = M 5 ⊕ M1
by the user.
   Step 4: Finally, Ci sends the messages ( IDi , M 2 ) to Si .                               M 8 = h(M 5 || M 7 )

                                                                                                          M8
      Ci                              Si
                                                                                                                       ?
     Inserts the smart card and offers Bi                                                                Verifies M 8 = h(M 5 || Rs)
                    ?
     Verifies h(Bi )= fi , Ci inputs PWi
                                                                                       Figure 3. The authentication phase
     Computes ri' = h(PWi || fi )
                  M1 = ei ⊕ ri'                                             2.4 Changing of password
                  M 2 = M1 ⊕ Rc                                            Whenever the users want to change their passwords, they
                                                                         can easily and freely change the password PWi to a new
                                           IDi , M 2                     password, PWi new , as shown in Figure 4.
                                                                              Step 1: The users insert their smart card in the smart
                     Figure 2. The login phase                           card reader and offer their biometrics to the specific device
                                                                         in order to verify the user biometrics.
    2.3 The Authentication Phase                                              Step 2: If it holds, the user can input the old
  On receiving the login request message, Si will                        password, PWi , and the new password, PWi new .
authenticate whether the user is legal or not in the following               Step        3:           The        smart        card  computes
manner, as shown in Figure 3.                                             ri′ = h( PWi || f i ) , ei′ = ei ⊕ ri′ = h( IDi || Xs ) ,     and
                                                                        (IJCNS) International Journal of Computer and Network Security, 3
                                                                                                                   Vol. 2, No. 3, March 2010

ei′′ = ei′ ⊕ h( PWi new || fi ) , the ei will be replaced with ei′′            3.2 It cannot withstand password-guessing attacks
                                                new
                                                                               According to some of the research work [7], [8], storing
and PWi has been changed with PWi                     .                     of data as smart card messages is vulnerable, because the
                                                                            secret information stored in the smart card could be
              Ci                     Si                                     extracted by monitoring its power consumption (power
         Inserts the smart card and offers Bi                               analysis attacks). Using power consumption attacks, the
                                                                            attacker can get the message ( fi , ei ) and intercept the
                        ?
         Verifies h(Bi )= fi , Ci inputs PWi and PWi new
                                                                            message (M2, M6) from the network. Through password-
         Computes ri' = h(PWi || fi )
                                                                            guessing attacks, the attacker can guess the password P Wi′ ,
                    ei' = ei ⊕ ri' = h( IDi || Xs)
                                                                            and compute the value as Rc' = ei ⊕ h( P Wi′ || fi ) ⊕ M 2 to
                    ei'' = ei' ⊕ h( PWi new || fi )
                                                                            check if M 6 = h( M 2 || Rc' ) . If it holds, the attacker can
         The ei will be replaced with ei''                                  masquerade the user. Otherwise, the attacker can try for the
                                                                            next guessed password P Wi′ until M 6 = h( M 2 || Rc' ) is
                                                                            true. A detailed description is given below:
                Figure 4. Change password phase                                Step 1: Using power consumption, the adversary gets the
                                                                            message ( fi , ei ) .
3. The Weaknesses                    of     Li        and      Hwang’s         Step 2: The adversary intercepts the message (M2, M6)
                                                                            from the network.
   Proposed Scheme
                                                                               Step 3: By choosing a password P Wi′ , the adversary
  It can be seen that Li and Hwang’s proposed scheme
                                                                            computes the message of Rc' = ei ⊕ h( P Wi′ || fi ) ⊕ M 2 to
enables users to change their passwords freely and provides
mutual authentication between the user and the server. The                  check if M 6 = h( M 2 || Rc' ) .
most significant feature of this scheme is that its operating                   Step 4: If the above-mentioned holds, it means the
mechanism is based on the users’ personal biometrics.                       password guessed, P Wi′ , is the correct password; thus, the
However, Li and Hwang’s proposed scheme still retains                       adversary can masquerade the user.
three weaknesses, as explained below:
                                                                               Step 5: On the contrary, if it does not hold, the adversary
                                                                            tries for the next password guess until M 6 = h( M 2 || Rc' )
  3.1 It cannot protect against impersonation attacks                       is true.
  In the authentication phase, the server checks the format
                                                                              3.3    Adversary can impersonate not only the client
of the client’s identity; if it holds, the server computes the
                                                                                     but also the server
message (M3, M4, M5, M6), and the server can get the
message ( IDi , M 2 ) from the client in the login phase. The                  Through a power analysis attack and the above-mentioned
                                                                            statement 3.2, the attacker can get the value of h( IDi || Xs) ;
server    can use the message                ( IDi , M 2 )     and secret
                                                                            then, the attacker can masquerade not only the client but
information        Xs    to      masquerade           M2 ' ,   then   get
                                                                            also the server. As the attacker can intercept the
 M 1 = M 3 = h( IDi || Xs) ; therefore, the attacker can                    message ( IDi , M 2 ) from the network, using the message
impersonate the client. The detailed procedure is given                     h( IDi || Xs) ,   it     can     compute        the     message
below:
                                                                            (M 3 , M 4 , M 5 , M 6 ) to masquerade the server as well.
   Step 1: The malicious server can compute the hash value
 h( IDi || Xs) itself, and sends the message h( IDi || Xs) to the
adversary.
   Step 2: After receiving the message h( IDi || Xs) , the                  4. Conclusions
adversary chooses the random number Rc' to compute                             This paper points out that the scheme proposed by Li and
 M 2 ' = h( IDi || Xs) ⊕ Rc ' .    The      adversary        can            Hwang is not secure enough against some weaknesses and
masquerade IDi and sends the login request message                          proves that it is incapable to withstand impersonation and
                                                                            power consumption attacks. The attacker can break in as a
( IDi , M 2 ' ) to the server.                                              legal user and intercept the messages from networks to
   Step 3: The adversary can use the hash value h( IDi || Xs)               masquerade the user. Although Li and Hwang’s proposed
to compute the random number Rs chosen by the server. The                   personal biometrics scheme is practical in some fields, the
adversary will compute M 8 = h((h( IDi || Xs) ⊕ Rs ) || Rs) to              security is substandard.
achieve the validity of the login processes. The drawback
exists because the server does not execute the biometrics
                                                                            Acknowledgment
verification processes, thus causing insider attacks as
mentioned above. Furthermore, the scheme cannot achieve
non repudiation.                                                              This work was partially supported by the National
                                                                            Science Council, Taiwan, R.O.C. under Grant NSC 98-
                                                                            2221-E-324-019.
4                                                          (IJCNS) International Journal of Computer and Network Security,
                                                                                                      Vol. 2, No. 3, March 2010

References
[1] L. Lamport “Password authentication with insecure
     communication”, Communications of the ACM 24, pp.
     770–772, 1981.
[2] M.S. Hwang and L.H. Li, “A new remote user
     authentication scheme using smart cards”, IEEE
     Transactions on Consumer Electronics, vol. 46, pp.
     28–30, 2000.
[3] M. Kim and CK. Koc, “A simple attack on a recently
     introduced hash-based strong-password authentication
     scheme”, International Journal of Network Security,
     vol. 1, pp. 77–80, 2005.
[4] N.Y. Lee and Y.C. Chiu. “Improved remote
     authentication scheme with smart card”, Computer
     Standards and Interfaces, vol. 27, pp. 177–180, 2005.
[5] C.T. Li and M.S. Hwang, “An online biometrics-based
     secret sharing scheme for multiparty cryptosystem
     using smart cards”, International Journal of Innovative
     Computing Information and Control, 2009.
[6] C.T. Li and M.S. Hwang, “An efficient biometrics-based
    remote user authentication scheme using smart cards”,
    Journal of Network and Computer Applications, vol. 33,
    pp. 1-5, 2010.
[7] T.S. Messerges, E.A. Dabbish, and R.H. Sloan,
    “Examining smart-card security under the threat of
    power analysis attacks”, IEEE Transactions on
    Computers, vol. 51, pp. 541–552, 2002.
[8] P. Kocher, J. Jaffe, and B. Jun, “Differential power
    analysis”, Proceedings of Advances in Cryptology, pp.
    388–397, 1999
                                                                     (IJCNS) International Journal of Computer and Network Security, 5
                                                                                                                Vol. 2, No. 3, March 2010


   New Illumination Compensation Method for Face
                    Recognition
                                                     Heng Fui Liau1and Dino Isa2
         1
             Faculty of Engineering, School of Electrical and Electronic Engineering,University of Nottingham Malaysia Campus,
                                             Jalan Broga, 43500 Semenyih, Selangor, Malaysia.
                                                            eyx6lhf@nottingham.edu.my
              2
                  Faculty of Engineering, School of Electrical and Electronic Engineering,University of Nottingham Malaysia Campus,
                                                  Jalan Broga, 43500 Semenyih, Selangor, Malaysia.
                                                             Dino.Isa@nottingham.edu.my

                                                                         of a lambertian surface in fixed pose, under variable lighting
  Abstract: This paper proposes a method for implementing
illumination invariant face recognition based on discrete cosine
                                                                         and without shadowing, is a 3D linear subspace [5]-[7]. One
transform (DCT). This is done to address the effect of varying           of the approaches used to solve the problem is building a 3D
illumination on the performance of appearance based face                 illumination model. Basri et al [5] proposed spherical
recognition systems. The proposed method aims to correct the             harmonic model where illuminated images are represented
illumination variation rather than to simply discard it. In the          in low-dimensional subspace. Lee et al [8] proposed the 9D
proposed method, illumination variation, which lies mainly in            linear subspace approach using nine images captured under
the low frequency band, is normalized in the DCT                         nine different lighting directions. Face images obtained
domain. Other effects of illumination variation which manifest           under different lighting conditions are regarded as a convex
themselves        by       the       formation       of shadows          Lambertian and can be approximated well by a 9D linear
and specular defects are corrected by      manipulating      the         subspace [8]. The illumination convex cone method [9]-[11]
properties of the odd and even components of the DCT. The
                                                                         showed that a set of images of an object in a fixed
proposed method possesses several advantages. First, it does not
                                                                         pose under all possible illumination conditions is a convex
require the use of training images or an illumination
model and can be applied directly to the test image. Second is           cone in the image space. This method requires a number of
the simplicity of the system. It needs only one parameter to be          training images for each face taken with different lighting
determined, making              it           simple           to         directions to build the generative model. Unfortunately, the
implement. Experimental results on Yale face database B using            illumination cone is extremely complex to build. Several
PCA- and support vector machines (SVM)-based face                        simpler models that approximate it in the best possible way
recognition algorithms showed that the proposed method gave              with minimum complexity is presented in [10], such as low
comparable performance compared to other well-known but                  dimension subspace model, and cones-attached and cones-
more complicated methods.                                                cast using extreme rays. Gross et al [12] proposed a 3D
   Keywords: face recognition, illumination invariant, discrete          method based on light-field estimation. It operates by
cosine transform, biometrics.                                            estimating a representation of the light field of the subject
                                                                         head. The light field is then used as the set of features for
                                                                         recognition. Recently, Zhang et al [13] proposed a 3D
1. Introduction                                                          Spherical Harmonic Basis Morphable Model. They showed
                                                                         that any faces under arbitrary unknown lighting condition
Face recognition has gained much attention in the past two               can be simply represented by three low-dimensional vectors
decades, particularly for its potential role in information and          which correspond to shape, spherical harmonic and
forensic    security.    Principal      component      analysis          illumination. One of the major drawbacks of the 3D
(PCA) [1] and linear discriminant analysis (LDA) [2] are                 illumination model-based approach is that a number
the two most well-known and widely-used appearance-based                 of training images of the subject under varying lighting
methods. Existing face recognition systems including PCA                 conditions or information of 3D shapes are needed during
and LDA do not perform well in the presence                              the training phase. Moreover, its application range is
of illumination variation. For example, Adini et al [3] stated           limited by the 3D face model, and has significant drawback
that the variation between the images of the same person                 for real-time system due to its expensive computation
due to illumination inconsistencies is always larger than                requirement.
image variation due to the change in face identity. Due to                   Every single pixel of the illuminated face image can be
the importance of this issue, recent researchers focus on                regarded as a product of reflectance and luminance at that
developing robust face recognition systems. However,                     point. Luminance varies slowly while reflectance can
illumination variation still remains a challenging problem               change abruptly. In other words, luminance, which
[4].                                                                     corresponds to the illumination variation, is located
   The problems associated with Illumination variation for               mainly in low frequency band but reflectance, which
facial image are mainly due to the different appearance of               corresponds to the stable facial features under illumination
the 3D shape of human faces under lighting from different                variation, is located at higher frequency band. Land's
direction. Early work showed that the variability of images              "retinex” model [14] approximates the reflectance as the
6                                                           (IJCNS) International Journal of Computer and Network Security,
                                                                                                       Vol. 2, No. 3, March 2010

ratio of the image and its low-pass version serves as           zero mean and unit variance. The advantage of the method
estimation for luminance. Chen et al [15] discards the low      is low computation complexity.
frequency DCT component in the logarithm domain to                 This paper proposes an new illumination compensation
achieve illumination invariance. They first expand the pixel    method for face recognition . The proposed method aims to
intensity in the dark region using logarithm transform.         correct the illumination variation rather than to simply
Then, discrete cosine transform is applied on the image in      discard it. Compared to existing methods based on the DCT,
logarithm domain. The low frequency components are              the proposed method here does not discard the low
discarded by setting the corresponding coefficients as zero.    frequency components which represent most of the effects of
Nanni and Lumini [16] had investigated discrete wavelet         illumination variations. This allows us to retain more
transform features under different lighting conditions. They    information, which might be useful for face
found that the most useful sub-band are the first level of      recognition. Furthermore, some of the effects of this
decomposition obtained by Biorthogonal wavelet and the          illumination variation lie in the higher frequency band,
horizontal details are the third level of decomposition         approximately the same frequencies as occupied by some
obtained by Reverse Biorthogonal wavelet, which is robust       important facial features. As previously mentioned, the
against illumination variation. Franco and Nanni [17]           effect of these kinds of illumination variation creates
proposed classifiers fusion scheme. PCA is applied to           shadow and specularities in the image. Thus, removing the
extract and reduce the dimensionality of the useful features    low frequency component does not help in this case. The
from DWT domain [16] and DCT domain [15]. The                   proposed method here manipulates the odd and even DCT
individual classifier for each feature is Kernel Laplacian      components to remove these artifacts. Using the DCT
Eigenmap. The output of each classifier is further fused        approach, the complexity of the previously described
using sum rule.                                                 methods is avoided while retaining a comparable
    Generally, human face is similar in shape, have two eyes,   performance [8]-[10], [15], [21]-[24]. The proposed method
a mouth and a nose. Each of these components makes              is based solely on 2D images and does not need to estimate
different distinctive shadows and specularities depending on    the 3D shape. It requires much less computation resource
the direction of the lighting in a fixed pose. By using such    than other methods based on 3D model as stated above.
characteristic, the lighting direction can be estimated and     Besides that, it does not require any prior information on the
illumination variation can be compensated. Quotient image       illumination model and training images. Furthermore, the
(QI) [18] is an effective method to handle illumination         parameter selection is simple. Only one parameter, the cut-
problem. This method is very practical because it               off-frequency of the filter, is required              to be
only requires one training image for each person. The           determined. Experimental results on Yale face database B
authors in literature [19] and [20] further improved the        [11] using PCA- and support vector machines (SVM)--based
original QI method and proposed the self-quotient               face recognition algorithms showed that the proposed
image (SQI) method. The luminance is estimated as the           method has achieved good performance as compared
smoothed version of the image by Gaussian filtering. The        to some of the more complicated methods described above.
illumination           variation        is         eliminated
by dividing the estimated        luminance. However,      the   2. Method
parameter selection for the weighted Gaussian filter is
empirical        and       complicated. Shan        et     al   As aforementioned before, an illuminated face image, I(x,y)
[21] proposed quotient illumination relighting (QIR)            , can be regarded as product of reflectance, R(x,y) , and
method which synthesizes images under a predefined              luminance, L(x,y) , as shown in (1). Taking logarithm
normal lighting condition from the provided face images         transform on (1), we have (2).
captured under non-uniform lighting conditions. Zhao et al
[22] proposed illumination ratio image. One training image
for each lighting conditions is required to simulate the
distribution of the images under varying lighting condition.
Liu et al [23] proposed an illumination restoration method.                                                        (2)
The illuminated image is restored to image under frontal
light source using a ratio-image between the face image         The logarithm transform transforms (1) into linear
under different lighting conditions and a face image under      equation where the logarithm transform of the illuminated
frontal light source, both of which are blurred by Gaussian     image is the sum of the logarithm transformed of reflectance
filter. The image is further enhanced through an iterative      and the logarithm transform of luminance as shown in
algorithm where Gaussian filter with different sizes are        (2). In the image processing field, logarithm transform
applied on different regions of the face image. Vuccini et al   is often employed to expand the values of the dark
[24] adopted Liu et al’s method to restore and enhance the      pixels. Fig. 1 gives a comparison between the original image
illuminated image. LDA is employed as feature extractor.        and the same image following the logarithm transform. The
They proposed an image synthesis method based on QI to          brightness of the right image is spread more uniformly.
generate training images to overcome the small-sample-size
problem. Xie and Lam [25] normalize the lighting effect
using local normalization technique. The face image is
partitioned to blocks with fixed size. For each block, the
pixel intensities are normalized in such a way that it has
                                                             (IJCNS) International Journal of Computer and Network Security, 7
                                                                                                        Vol. 2, No. 3, March 2010

                                                                 number. Furthermore, DCT has lower computation
                                                                 complexity than Discrete Wavelet Transform. For an N×N
                                                                 image, the 2D DCT is given by (5). For υ , ν = 0,1,2,…N-1.
                                                                    and    represent the horizontal component and vertical
                                                                 component respectively is the          is the value of the
                                                                 pixel at coordinate (x,y). For 2D DCT, the frequency is
                                                                 computed as the square root of the sum of      and . The
                                                                 inverse 2D DCT is expressed as (6).

Figure 1. On the left is the original face image. On the right
           is the output of logarithm transform                                                                           (5)


    Luminance component lies mainly in the low frequency
band while the reflectance component lies mainly in the
higher frequency band. The luminance component can be
approximated as the 'low-pass version' of the illuminated            From (6), the uniform luminance component can be
image. The reflectance component of an illuminated face          obtained from the original image by adding a compensation
image represents the stable facial features under varying        term,            which compensates for the nonuniform
lighting conditions. Thus, the illumination variations can be    illumination.
compensated for provided we can estimate them relatively             Generally human faces are almost symmetrical. The left-
well.                                                            half side of the face is almost identical to the right-half side
   Let        be the incident luminance and             be the   of the face in most of the cases. For non-uniformly
uniform luminance. A uniformly illuminated image, , can          illuminated images, part of the face is brightened and the
be expressed as (3). In order to normalize the brightness        others are darkened. The                         component is
across all of the images, the mean value of         are set to   approximated as the 'low-pass version' of                  with
be the same for all image.                                       certain cut-off frequency. The compensation term can be
                                                                 estimated as follow. Firstly, the mean of an             image
                                                   (3)           reconstructed from low frequency DCT components is
                                                                 computed according to (7). Then, each pixel is subtracted by
                                                                 the mean as shown in (8).                is estimated using the
                                                                 low frequency DCT components. A negative value indicates
The luminance component corresponds to the illumination          that a single pixel is 'dark' and positive value indicates that
variation. As previously described, the illumination             the corresponding pixel is 'bright'. Each pixel is adjusted by
variation can be well-approximated by the low frequency          halving the difference between pixel value and mean value
components of the illuminated face image. In section 2.1, an     as shown in (8). In other words, the intensity of each pixel is
illumination compensation method based on low frequency          adjusted according to the difference between the mean
DCT components are presented. In fact, illumination              intensity of the image that is reconstructed using only low
variation cannot be perfectly separated from the original        frequency components. The illumination variations which
image in the frequency domain. Under large and complex           lie mainly in the low frequency band are reduced while
illumination variations, the shadows and specularities are       important facial features are preserved. In other words,
casted on the face due to the unique 3D shape of human           the low-pass version of the image in the DCT domain serves
face. Some shadows and specularities lie in the same             as an estimated of the luminance component. Fig. 2 shows
frequency band as the reflectance, which corresponds to          the effect of illumination normalization in the low frequency
facial features do. In this case, compensation technique         DCT components on a face image. The left-most image is
based on low frequency components will be unable to              the original image. The second, third and forth images are
remove the artifacts. In section 2.2, an illumination            the processed image with the cut-off frequency set at 2, 4
compensation method based on the properties of odd and           and 6 respectively. As you can see, the shadow effects at left
even DCT components in horizontal direction, which has           side of the face are reduced at the increasing value of the
the capability to remove artifacts in the high frequency         cut-off frequency while the facial features are unaffected.
band, is presented.                                              Unlike other similar methods, only one parameter needs to
.                                                                be determined, which is the cut-off frequency of the low-
                                                                 pass filter. However, the normalization may cause some
  2.1 Illumination normalization using low frequency
                                                                 information lost in the process due to wrong estimations of
  DCT components
                                                                 the 'dark' and 'bright' zones.

DCT has been widely used in modern imaging and video
compression. DCT possesses some fine properties, such as
de-correlation and energy compaction. The DCT is chosen
because it only gives real value, unlike Discrete Fourier
Transform       (DFT)      which      gives      complex
8                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                        Vol. 2, No. 3, March 2010

                                                                 is always below 0.5. For the non-uniformly illuminated
                                                                 image, the strong signals (greater than one) are located at
                                                                 the low frequency band. However, the middle and high
                                                                 frequency band contain points that have strength greater
                                                                 than 0.5. This shows that the illumination variation also
                                                                 corrupts the high frequency component, which corresponds
                                                                 to reflectance. Hence, this proves that no features are robust
                                                                 enough to be against the illumination variation.
      Figure 2. Normalization on low frequency DCT
    components. The left most image is the original image


    2.2 Illumination Correction Using Odd and Even DCT
    Components in Horizontal Direction
Under large and complex illumination variation, the effect
of illumination variation occurs across almost the
entire frequency band. Some variations such as shadows           Figure 4. The top and bottom is the odd DCT component of
and specularities lie in the same frequency band as some             original image and illuminated image respectively
important     facial    features   do. In this section, we
propose an illumination correction method which uses the
                                                                    Since human face generally have symmetry property, we
properties of odd and even DCT components to eliminate
                                                                 can easily compensate the illumination variation in the face
the shadows and specularities and to restore the original
                                                                 based on the properties of odd and even components of
features.                                                        DCT. Here, an illumination compensation method based on
                                                                 manipulating even and odd DCT components is proposed.
                                                                 First, two new images,          and      , are reconstructed
                                                                 from the odd and even DCT components in the horizontal
                                                                 direction of the original images. The pixels on the left half
             Figure 3. 2D-DCT basis functions                    are compared with the pixels on the right half. If the left-
                                                                 side pixel is negative and the corresponding right-side pixel
                                                                 is positive, the values of both pixels will be adjusted
In Fig. 3, different images have been produced by varying        according to (10) and (11). is the compensation term. Fig
the DCT components in the horizontal direction. As shown         .5 shows an illuminated image and the corresponding
in the Fig. 3, the second and forth images have                  and .
been reconstructed by different even DCT components in the
horizontal direction and the symmetry is evident. The first
and third asymmetry images are reconstructed by odd DCT
components         in     the       horizontal      direction
are asymmetrical. Non-uniform illumination gives rise
to the     odd      DCT      components        and affects the
magnitude of the even DCT components. (5) can now be
rewritten in that,
                                                                 Figure 5. From left to right: illuminated image,         and


   Odd DCT components can be regarded as noise or
luminance components due to illumination variation and the
even DCT components represent the wanted information
which may or may not be slightly corrupted by non-uniform
luminance. Under such model, the luminance components
can be estimated using odd DCT components thereby giving
estimation for the correction term as well. Fig. 4 shows
the difference between odd DCT components of image under            If the left-side pixel is positive and the corresponding
variable illumination and the image of same person under         right-side pixel is negative, the values of both pixels will be
uniformly illuminated condition. As shown in the top of          adjusted according to (12) and (13).
Fig. 4, the odd components of the illuminated images
fluctuate greatly with the magnitude greater than one. In
contrast, the bottom of Fig. 4 also shows that illumination
variation happens across the entire frequency band. Note
that, the signal strength of the uniformly illuminated image
                                                                (IJCNS) International Journal of Computer and Network Security, 9
                                                                                                           Vol. 2, No. 3, March 2010

                                                                    3. Experiment results on Yale Face database B
                                                                    Yale face database B is commonly used to evaluate the
                                                                    performance of illumination invariant face recognition. The
                                                                    Yale face database B contains 10 individuals in nine
                                                                    different poses. For each pose, there are 64 different
                                                                    illumination conditions. All images were manually aligned.
                                                                    The size of face images are cropped to 64×55 pixels. The
                                                                    face images were divided into 4 subsets according to the
                                                                    [11].The four subsets were, subset 1               ), subset 2
  Figure 6. The sum of the correction term and even DCT
                                                                                ), subset 3             ) and subset 4           ),
    components gives the illumination corrected image
                                                                    where bracketed numbers indicate the angular position
                                                                    of light of incident with respect to the person.
   The new pixel intensity for the compensated image can
then be computed using (14). As shown in Fig. 6, the
                                                                      3.1 Face recognition using principal component
shadow created by the nose has been eliminated. Fig. 7
                                                                      analysis
shows the illumination-corrected image using the proposed
method. Illumination variations are largely reduced while
the important facial features are preserved. Here, we would         PCA is a classical face recognition method. PCA seeks for a
like to emphasize that the proposed method is able to               set of projection vectors which projects the input data in
recover facial feature as long as the specularities or shadow       such a way that the covariance matrix of the training images
regions occur only on one side of the face. The output image        is maximized. Six images in subset 1 were selected to serve
looks different from the original image because the proposed        as training images to build the covariance matrix for PCA
method corrects the illumination variation based on the             [13] and [17]. Eigenvalue decomposition was applied on the
symmetry of human face. The output image is aligned in              covariance matrix to seek for the eigenvector that projected
such a way that the left-half side is identical to the right-half   the data in the direction that maximized the covariance
side. Due to some subtle variations in the two halves of            matrix. The nearest neighbour rule was used as a classifier
every face, a face image is not exactly symmetrical; for            with the Euclidean distance as the distance metric. Fig. 8
example, the two eyes have slightly different sizes, there is a     shows that the largest thirty principal components were
mole at only one side of cheek, etc. Therefore, the output          sufficient to give the best result and to represent the face
images may have an adverse effect. All of the images are            image. Therefore, thirty principal components were used to
normalized to a mean of 0.5.                                        form the projection matrix. Fig. 9 and Fig. 10 show the
                                                                    performance of the proposed method for subset 3 and 4
                                                                    respectively under different values of cut-off frequency.
                                                                    Setting the cut-off frequency at six gave the best results for
                                                                    both subsets.




  Figure 7. Illumination normalization and compensation
                                                                      Figure 8. Recognition rate for subset 3 and subset 4 that
                 based on proposed method
                                                                         correspond to the number of principal components

The flow of the proposed illumination invariant face
recognition system can be summarized as below:
1. Perform logarithm transform on the input images to
expand the values of the dark pixels.
2. Correct the non-uniform luminance in the low frequency
domain using the proposed method in section 2.1.
3. Eliminate the specularities and shadows that lie in the
same frequency band as the reflectance does using the
proposed method in section 2.2.


                                                                     Figure 9. Recognition rate for subset 3 that correspond to
                                                                                      the cut-off frequency
10                                                             (IJCNS) International Journal of Computer and Network Security,
                                                                                                          Vol. 2, No. 3, March 2010

                                                                  of SVM tremendously in Subset 4. Our method scored 100%
                                                                  recognition rate in Subset 3 and 96.4% in subset 4.

                                                                               Table 2: Face recognition using SVM
                                                                                  Method            Subset 3 Subset 4
                                                                                  Original           13.6%       55%
                                                                                 Histogram            100%      61.4%
                                                                                equalization
                                                                              Proposed method         100%      96.4%
 Figure 10. Recognition rate for subset 4 that correspond to
                  the cut-off frequency
                                                                     3.3 Comparison with other methods
                                                                      The results for subset 3 and 4, along with other well-
            Table 1: Face recognition using PCA
                                                                  known methods, are presented in Table 3. From Table 3,
        Method                   Subset 3 Subset 4                it is           shown that            the            proposed
        Histogram                58.4%      15.6%                 method gave results comparable with other well-known but
        equalization                                              more complicated methods. In contrast, the proposed
        Proposed method          100%       92.1%                 method is much simpler to implement with much less
                                                                  computation resource requirement. The baseline system only
   Without illumination normalization in the low frequency        scored 58.4% and 15.6% in subset 3 and subset 4
band, the proposed method was only able to achieve 96.3%          respectively. The proposed method outperformed linear
and 64.1% recognition rate in subset 3 and 4 respectively.        subspace method, cones-attached method, illumination ratio
The poor results were due to the large variation in the low       image method and QIR method. As aforementioned, the
frequency band where the illumination correction algorithm        above stated methods required training images to build the
was unable to cope with. As we increased the value of cut-        illumination model or to estimate the lighting
off frequency, the performance improved steadily although         conditions. The authors in [15] discards low frequency
there were some small fluctuations. It gave the best              components, keeping only the high frequency ones
performance when the cut-off frequency was set at 6 (100%         which correspond to the reflectance component. Fig.
for subset 3). For subset 4, the best performance was 92.1%       11 shows the difference between the proposed method and
when the cut-off frequency was at 6, 7 or 9. Beyond that, the     [15]. The shadows and specular defects remained on the
performance      decreased     because     some    important      image because they lay in the same frequency band as the
features might have lost in the illumination normalization        reflectance component does. Discarding low frequency
process.                                                          components might remove the important facial features that
   Table 1 shows that our method can achieve a better             lie in low frequency band and degrade the performance of
performance level than if only histogram equalization was         the face recognition system when the number of class was
used.                                                             large. The proposed method aims to correct the
                                                                  illumination variation rather than to simply discard it to
   3.2 Face recognition using support vector machine              achieve illumination invariance. However asymmetrically,
                                                                  it was unable to completely remove artifacts that appeared
Support vector machine (SVM) [26]-[28] is a popular
                                                                  on the both sides of the face. This caused the proposed
technique for classification motivated by the results of
                                                                  method to have rather unimpressive performance in subset
statistics learning theory. Unlike traditional methods such as
                                                                  4 compared to [15]. Our method is robust against
neural network that minimize the empirical training error,
                                                                  illumination variation and is easy to implement. It can be a
SVM is designed based structural minimization principal.
                                                                  pre-processing stage for other face recognition algorithms.
SVM maps the training data into a higher dimensional
feature using kernel trick, in which an optimal hyperplane
                                                                    Table 3: Recognition rate comparison with other methods
with large separating margin between two classes of the
                                                                                 Methods                   Recognition rate
labeled data is constructed. The training data of SVM are
                                                                                                                 (%)
the PCA feature set described in the previous section. In this
paper, several types of kernel such as linear kernel, wavelet                                            subset 3 subset 4
kernel, polynomial kernel and radial basis function (RBF)                 Linear Subspace [10]             100         85
kernel are studied. RBF kernel gives the best result. The                  Cones-attached [10]             100        91.4
RBF function is defined as below:                                            Cone-cast [10]                100        100
                                                                      Illumination ratio image [22]        96.7       81.4
                                                                    Quotient Illumination Relighting       100        90.6
                                                                                   [21]
                                                                      illumination restoration [23]        98.3       96.4
where    is the width of the RBF.                                    DCT in logarithm domain [15]          100        99.8
                                                                        Vucini et al’s method [24]         100         95
   Table 2 shows the performance of SVM under different                     Our method+PCA                 100        92.1
types of methods. Our algorithm improved the performance                   Our method +SVM                 100        96.4
                                                            (IJCNS) International Journal of Computer and Network Security, 11
                                                                                                       Vol. 2, No. 3, March 2010

                                                                [5] R. Basri, D.W. Jacobs, “Lambertian reflectance and
                                                                     linear subspaces”, IEEE Transaction on Pattern
                                                                     Analysis and Machine Intelligent, 25(2), pp.218-233,
                                                                     2003.
                                                                [6] S. Nayar, H. Murase, “Dimensionality of illumination
                                                                     manifold in eigenspace”, Technical Report CUCS-021-
                                                                     94 Columbia University.
                                                                [7] S. Amnon, “Photometric issues in 3D visual
                                                                     recognition from a single 2D image”, International
Figure 11. Comparison between proposed method (bottom)
                                                                     Journal of Computer Vision,2, pp. 99-122, 1997.
                    and [10] (top)
                                                                [8] K.C. Lee, J. Ho, D.J. Kriegman, “Nine points of light:
                                                                     acquiring subspaces for face recognition under variable
  3.4 Computation time
                                                                     lighting and pose”, In Proceedings of the IEEE
An efficient and simple illumination compensation method             Conference on Computer Vision and Pattern
in DCT domain is presented. All experiments were                     Recognition, vol.2, pp. 519-526, 2001.
conducted using Matlab 2008a on Core 2 Duo E6750 CPU            [9] P.N. Belhumeur, D.J. Kriegman, “What is the set of
and 2GB RAM. It takes 2.050 seconds and 2.311 seconds to             images of an object under all possible illumination
process all of the face images included in subset 3 and              conditions?”, In Proceedings of the IEEE Conference
subset 4 respectively. The mean computation time for each            on Computer Vision and Pattern Recognition, pp. 270-
image is 0.0167 second. The complexity is low and it can be          277, 1996.
implemented in real-time system.                                [10] A.S. Georghiades, P.N. Belhumeur, D.W. Jacobs,
                                                                     “From few to many: illumination cone models for face
4. Conclusion                                                        recognition under variable lighting and pose”, IEEE
                                                                     Transaction on Pattern Analysis and Machine
This paper proposes a novel illumination compensation
                                                                     Intelligent, 23(6), pp.630-660, 2001.
method in DCT domain. The illumination is normalized
                                                                [11] H.F. Chen, P.N. Belhumeur, D.J. Kriegman, “In search
based on the low frequency components of DCT.
                                                                     of illumination invariants”, iIn Proceedings of the
Subsequently, the illumination variations which create
                                                                     IEEE Conference on Computer Vision and Pattern
shadows and specularities are further corrected by the
                                                                     Recognition, pp. 13-15, 2000.
proposed method which uses the properties of odd and even
                                                                [12] R. Gross, I. Matthews, S. Baker, “Appearance-based
components of DCT. The proposed method is simple in
                                                                     face recognition and light-fields”, IEEE Transaction
terms of design, where there is only one parameter that
                                                                     on Pattern Analysis and Machine Intelligent,26(4),
needs to be determined, which is the cutoff frequency of the
                                                                     pp.449-465, 2004.
filter for the illumination normalization process. The
                                                                [13] L. Zhang, S. Wang, D. Samaras, “Face synthesis and
proposed method gives comparable result with other well-
                                                                     recognition from a single image under arbitrary
known but more complicated methods in Yale face database
                                                                     unknown lighting using a spherical harmonic basic
B. The proposed method has rather unimpressive
                                                                     morphable model”, In Proceedings of the IEEE
performance in subset 4 due to reason that large
                                                                     Computer Society Conference on Computer Vision and
illumination variation creates shadows and specularities that
                                                                     Pattern Recognition, vol.2, pp.209-216, 2005.
occur at both sides of the face. Our method is robust against
                                                                [14] E.H. Land, J.J. McCann, “Lightness and retinex
illumination variation and is easy to implement. It can be a
                                                                     theory”, Journal of the Optical. Society of America,61
pre-processing stage for other face recognition algorithms.
                                                                     (1), pp. 1-11, 1971.
                                                                [15] W. Chen, M.J. Er, S. Wu, “Illumination compensation
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                                                                   (IJCNS) International Journal of Computer and Network Security, 13
                                                                                                              Vol. 2, No. 3, March 2010


      Towards In-Car Ad Hoc Network for Pervasive
                  Multimedia Services
                                 Kamal Sharma1, Hemant Sharma2 and Dr. A K Ramani3
                                       1
                                        Institute of Computer Science & IT, Devi Ahilya University,
                                                            Indore (M.P.), India
                                                      kamal.sharma74@rediffmail.com
                                  2
                                      Software Architect, Delphi Delco Electronics & safety Europe GmbH,
                                             Tec Centre, D 31162 Bad Salzdetfurth, Germany
                                                       hemant.sharma@delphi.com
                             3
                              Prof. & Head, 1Institute of Computer Science & IT, Devi Ahilya University,
                                                          Indore (M.P.), India
                                                       ramani.scs@dauniv.ac.in


Abstract: Pervasive computing systems inside modern                    However, the realization of a fully wireless car bus system is
automobiles are made up of hundreds of interconnected, often           still far away. Fiber optic connections for multimedia bus
replaceable devices and software components. In-vehicle                systems offer advantages regarding costs and bandwidth,
multimedia components and applications are becoming complex            and the demanded reliability of mission-critical networks
artifacts due to advancement in technology and increased               still require wired connections to ensure the safe operation
competition. There is a growing need for software platform to
enable efficient deployment of multimedia services in
                                                                       of the car. Though, cost-effective wireless subsystems which
automotive environment. This paper presents the architecture of        could extend or partly replace wired bus systems are already
a Bluetooth based multimedia ad hoc network in a car. The              nowadays conceivable. A very promising technology in this
architecture is explained and presented together with a prototype      context is specified by the recent Bluetooth 3.0 [1] standard.
implementation running on hand-held devices. Further, the
different fundamental architectural tradeoffs, based on                The provisioning of multimedia streaming applications
measurements, have also been analyzed.                                 using wireless network, inside the vehicle, requires
                                                                       managing differentiated performance levels depending on
  Keywords: Ad Hoc Networks, Pervasive Computing, In                   application/user/device requirements in order to properly
Vehicle Multimedia, Bluetooth.                                         allocate network bandwidth, especially the limited one
                                                                       available in the wireless last-meter [3]. In particular, the
1. Introduction                                                        Bluetooth specification [1] offers limited support to
                                                                       performance differentiation, by allowing to choose which of
During the last few years, the proliferation of miniaturized           the three kind of logical transports to exploit and to
devices with networking capabilities has provided the                  statically configure performance requirements for ACL
technological grounds for pervasive networking even in                 ones.
automotive environments. Growing demand for personal
                                                                       In addition, current implementations of the Bluetooth
device connectivity, mobile Internet access, remote
                                                                       software stack do not allow applications to exploit the
monitoring and diagnostics, as well as enhanced safety and
                                                                       limited performance functions included in the specification
security is driving vehicle manufacturers and suppliers to
                                                                       in a portable way. The result is that the development of
seek out new wireless technologies. Wireless technology
                                                                       Bluetooth operations in multimedia ad hoc applications
integration strategies would enhance the value proposition
                                                                       currently depends on specific implementation details of the
of vehicles by integrating advanced electronics systems such
                                                                       target Bluetooth hardware/software platform. This
as infotainment systems, safety and stability systems, and
                                                                       relevantly complicates service design and implementation,
comfort and convenience enhancement systems.
                                                                       limits the portability of developed applications, and calls for
The evolutionary development of in-car electronic systems              the adequate modeling of performance parameters
has lead to a significant increase of the number of                    corresponding to potential ad hoc applications and services.
connecting cables within a car. To reduce the amount of
                                                                       The design presented in this paper is for a wireless
cabling and to simplify the interworking of dedicated
                                                                       streaming system that offers a means for bringing the
devices, currently appropriate wired bus systems are being
                                                                       participatory media and bulk content distribution into the
considered. These systems are related with high costs and
                                                                       wireless domain. The basis for the service is an
effort regarding the installation of cables and accessory
                                                                       opportunistic distribution of among network. Users in our
components. Thus, wireless systems are a flexible and very
                                                                       system exchange data when their corresponding
advanced alterative to wired connections.
                                                                       application(s) receive trigger. The system is going to be
14                                                          (IJCNS) International Journal of Computer and Network Security,
                                                                                                       Vol. 2, No. 3, March 2010

open to any node who wants to provide and consume the
content. Hence, it is based on unlicensed short-range
communication specifically Bluetooth.




                                    Figure 1. Overview of In- Car Multimedia Network



By relying on short-range communication, the network will       2.1 The Multimedia PAN
be highly disrupted most of time. The communication is
further challenged by relatively short transfer opportunities   Bluetooth technology is based on a master-slave concept
which might be in the range of a few seconds when for           where the master device controls data transmissions through
example two nodes communicate with each other. The              a polling procedure. The master is defined as the device that
contribution of this paper is twofold:                          initiates the connection. A collection of slave devices
                                                                associated with a single master device is referred to as a
        Ø   A mechanism for content streaming based on          piconet. The master dictates packet transmissions within a
            opportunistic communication;                        piconet according to a time-slot process. The channel is
                                                                divided into time slots that are numbered according to an
        Ø   An evaluation of the mechanism through the          internal clock running on the master. A time division
            use of realistic use cases and real traces.
                                                                duplex (TDD) scheme is used where the master and slaves
The rest of the paper is organized as follows: Section 2        alternatively transmit packets, where even numbered time
provides the description of system and potential application    slots are reserved for master-slave transmissions, while odd
scenarios. In section 3, the architecture and design of the     numbered time slots are reserved for slave-master
system has been discussed. Section 4 evaluates the design of    transmissions.
the system. Section 5 provides an overview of related
research and section 6 concludes the paper.


2. System Description

An ad hoc multimedia network in a car and participating
devices are shown in figure 1. The diagram presents an ad
hoc network containing a smart phone, an infotainment
system, and rear seat entertainment system. The devices are
equipped with Bluetooth module and are capable of
establishing a Bluetooth connection. A piconet can be
established between Infotainment system and iPhone when
the driver or any other occupant of the vehicle pairs the
phone. Similarly a piconet could be established between
Infotainment system and rear seat entertainment system.
The piconet shall enable sharing of iPhone data or access to
information from internet, if appropriate application
framework is available at infotainment system.
                                                                              Figure 2. The Multimedia PAN
                                                           (IJCNS) International Journal of Computer and Network Security, 15
                                                                                                      Vol. 2, No. 3, March 2010

Figure 2 provides an overview of the multimedia PAN            up and running, its Bluetooth module is ready to pair with
inside the car with the role of different nodes. The piconet   other available device. Pairing with iPhone or with rear-seat
here consists of a master, the infotainment device, and two    entertainment unit or with both establishes the network.
slaves, the smart phone (iPhone) and rear-seat
entertainment device. As soon as the infotainment system is




                         Figure 3. Overview of Ad Hoc Multimedia Communication Architecture.

                                                               communication of intended data streams. Therefore, every
2.2 Application Scenarios
                                                               application subscribes to the channels that it is interested in,
The ad hoc multimedia network consisting of Infotainment       and his corresponding device node will try to retrieve any
system and the slave devices shall provide following           data belonging to those channels. Following the approach
services:                                                      used in the Internet-based podcasting protocols; the
                                                               framework structures channels into different media streams.
    Ø   Access to audio streams from iPhone to                 To make efficient use of contacts with a small duration, the
        infotainment system that could be played and           streams are further divide into data packets, transport-level
        hearable on the vehicle’s sound system.                data units of a size that can typically be downloaded in an
                                                               individual node encounter. Each data stream is further
    Ø   Access to video streams from iPhone to rear- seat      divided into protocol data units (PDU), the atomic transport
        entertainment unit via the piconet master.             unit of the network.
    Ø   Access to internet from rear-seat unit using iPhone
        via the piconet master.                                The resulting system architecture is illustrated in Figure 3.
                                                               The transport layer acts directly on top of the link-layer
    Ø   Applications based on information received by the      without any routing layer. To distribute information among
        iPhone to help safe driving, such as weather           the communicating nodes, the framework does not rely on
        information or traffic information.                    any explicit multi-hop routing scheme. Instead of explicitly
                                                               routing the data through specific nodes, it relies on a
                                                               receiver-driven application-level dissemination model,
3. System Architecture and Implementation
                                                               where data content are routed implicitly as nodes retrieve
                                                               information that they request from neighboring nodes. It
This section describes the design and implementation of our
                                                               distinguishes between an application layer, a transport layer,
Ad Hoc network system. We first give a brief overview, then
                                                               and the data link layer. In a first level of aggregation, the
describe the system architecture, and finally discuss the
                                                               application organizes the data in media stream channels.
protocols involved in a pair-wise association when devices
in the network communicate.
                                                               Below the application layer, the transport layer organizes
                                                               the data into data streams. Streams are smaller data units
3.1 System Architecture
                                                               that should be able to communicate over short contacts. The
The architecture organizes application data into               use of smaller file blocks is also supported by the idea of
communication channels to facilitate identification and the    integrating forward error correction, for instance the use of
16                                                             (IJCNS) International Journal of Computer and Network Security,
                                                                                                          Vol. 2, No. 3, March 2010

fountain codes, to speed up and secure the data transfer,          synchronization. The transfer mode is based on a client-
specifically when packets are received unordered. The              server model. The communication protocol is a request-
streams packets themselves are then again cut into smaller         response system. It is not a strict system though; some
parts to optimize the interaction with the data link layer;        requests do not generate a response whereas other requests
i.e., the size is set to the PDU size of the data link layer.      can generate several responses. The goal is to send as few
                                                                   data packets as possible to reduce the communication
The proposed system is designed to work on any MAC                 overhead.
architecture, however, to be effective even in the presence of
short contact durations, short setup times and high data            Figure 4 illustrates the state diagram of the transfer mode.
rates are important for achieving high application                 It shows the three most important stages of synchronization
communication throughput. The design is further                    between two device nodes: the negotiation, data query, and
characterized by two fundamental choices.                          data communication stage.

        Ø    First, it allows only pair wise associations even     In the Negotiation stage, both devices determine if some of
             when the MAC layer supports multi-point               the subscribed channels are available on the other device.
             communication.                                        Instead of querying every single channel, the devices
        Ø    Second, it never pushes data in the network and       exchange a channel filter that contains all channel
             relies instead on receiver-driven dissemination.      subscriptions a device offers. The devices then start to test
                                                                   their subscribed channels against the filter of the other
The arguments for these two choices are simplicity and
                                                                   device and create a list of matching channels. This is a local
optimal usage of short contact durations. Furthermore, the
transport layer is able to optimize the flow control between       process and does not involve the exchange of messages.
the nodes and is not constrained by the slowest receiver in
range. Since the framework does not perform multi-hop
routing explicitly, the system performance is mainly
determined by the selection of nodes, it is synchronizing
with and the order by which it transfers data from the peers.
This task is performed by the synchronization service,
depicted in Figure 1. The synchronization service is
responsible for maintaining state about past synchronization
encounters and current devices in the PAN.

3.2 Association Phases

This section next describes the process when two nodes
associate. The framework differentiates two phases: a
discovery phase in which nodes detect that they are in a
range and a data exchange phase in which the nodes
negotiate and perform data transfer.


  1) Device Discovery Phase


We assume that every device that participates in the
opportunistic data sharing belongs to the same network,
e.g., with IEEE 802.15 every device is configured in ad hoc
mode. While the detection of new devices in the network is
handled by the MAC layer, the application in the nodes has
to take care of the discovery of devices that participate in the
wireless communication service.
                                                                           Figure 4. State Diagram – Data Transfer Modes.
The synchronization service keeps track of the discovery
messages received from each peer and maintains a history           In the Data Query stage, a device confirms the channels
list. An important aspect of the discovery process is to           selected in the previous stage and then retrieves a list of
identify peers with a good connection. Since the system is         streams offered by the remote device within those channels.
designed for ad hoc scenarios, it has to consider the specifics    Our implementation supports three different types of stream
of wireless communication.                                         retrievals:
  2) Data Transfer Phase
                                                                      1.      The peer requests any random stream within a
Once a device node has been detected, the synchronization                     channel that the remote peer offers.
services switches to the transfer mode which handles the
                                                             (IJCNS) International Journal of Computer and Network Security, 17
                                                                                                        Vol. 2, No. 3, March 2010

   2.    A peer requests any stream which is newer than a        4.3 Device Synchronization
         given date starting with the newest streams.
                                                                 We next look at the synchronization time. The
   3.    The peer requests any streams that are newer than
                                                                 synchronization time is the time between the moment two
         a given date starting with the oldest stream.
                                                                 devices have discovered each other and associate until they
The actual communication of streams is handled in the Data       start data communication. Figure 5 shows the performance
Communication stage which usually takes up most of the           of the architecture for device synchronization with different
connection time. The device starts to process the list of PDU    number of channels using channel filters compared to the
streams that was created in the previous stage. The              time it would take without filters.
communication itself works analogous to the download
process of BitTorrent [7]. Missing PDUs which are available
at the remote peer are randomly selected and downloaded.
Remark that a stream is divided into several pieces (PDUs)
which are requested


4. Evaluation

This section evaluates important design choices of the
proposed architecture as well as the performance we might
expect from a wireless opportunistic application and content
sharing service. Our evaluation relies on our prototype
implementation and focuses on typical deployment scenarios
in which:                                                           Figure 5. Device Synchronization with and with out
                                                                                      channel filter.
        Ø   the nodes are co-located (e.g., all devices are in
            the car) ; or                                        4.4 Data Transfer
        Ø   When nodes are not co-located (paired iPhone
                                                                 The system limits the association time to ensure that the
            is not in the car).
                                                                 system remains fair when multiple nodes are interested in
                                                                 the data provided by just a few nodes. Without this artificial
4.1 Evaluation Setup and Methodology
                                                                 limit, the first node that associates with the node having
All devices communicated over their integrated Bluetooth         new data content would be able to communicate for an
interface (802.15) turned into ad hoc mode. Our data             indefinite amount of time, letting the other nodes starve for
                                                                 data.
communication application is written in C++. The devices
that participate in the data communication system are
configured in ad hoc mode using the same identifier. .

We evaluated the framework’s accuracy by comparing its
data flows to actual Bluetooth flows between the same
devices. Performing this evaluation on a large-scale is
difficult because it requires control over the software
running at both end-points of a Bluetooth flow. We
performed our evaluation by pre-instrumented Bluetooth
stack of two classes of devices: Infotainment Unit and
iPhone.

4.2 Device Discovery Phase

An important aspect of opportunistic wireless podcasting is
the discovery time. The discovery time is the time between
the moment two nodes move into transmission range until
they discover each other at the application layer and start
the synchronization phase.
                                                                 Figure 6. Average Data Exchange Time between the PAN
This time is directly impacted by the interval at which the                             devices
messages are sent. The more frequent these messages are
sent, the quicker they will discover each other and be able to   To show how our implementation performs on different
transfer data streams.                                           PAN nodes, Figure 6 shows a comparison of the download
18                                                           (IJCNS) International Journal of Computer and Network Security,
                                                                                                        Vol. 2, No. 3, March 2010

time with the iPhone and the Infotainment unit. The results      users who retrieve data act simultaneously as clients and
are from average data communication measurements of              servers. It has post-facto gained interest in the research
around 12 MB video streams showing the download time             community; see for instance [7]. This system has similarities
when two or five devices are part of the PAN inside the car.     to BitTorrent [7], but the mobility assisted delivery means
                                                                 that data are provided in a random order from a random mix
4.5 PAN Accuracy                                                 of peers whereas peer-to-peer content distribution systems
                                                                 like BitTorrent selects peers based on specific rules. The
When sending data to multiple receivers, a Bluetooth master      closest research field is the delay tolerant networking. The
must form a piconet. In a piconet, the master sends data to      Delay Tolerant Network Research Group (DTNRG) [14] has
each receiver one packet at a time in a round-robin fashion.     proposed architecture [13] to support communication that
To evaluate architecture’s accuracy in piconet mode, we          may be used by delay tolerant applications. The architecture
performed the following experiment. We set up a sending          consists mainly of the addition of an overlay, called the
device to transmit a very large video file to each slave         bundle layer, above a network transport layer. Messages of
joining its piconet. We set up two iPhone as slaves to join      any size are transferred in bundles in an atomic fashion that
the piconet one by one, every 90 seconds. We measure the         ensures node-to-node reliability. Multicast for delay-tolerant
transfer rate of the initial flow established between the        networks has been proposed in [12]. In contrast to multicast,
master and the first joining slave and we plot how this rate     our work assumes open user groups. The info-station
changes over time in Figure 7.                                   concept is akin to our proposal and the paper in Ref. [10]
                                                                 studies means for avoiding exploitation of other nodes. We
                                                                 differ in that we make the nodal exchanges governed by a
                                                                 protocol instead of a social contract between users.

                                                                 In reference [9], it has been shown that delay-tolerant
                                                                 broadcasting between mobile nodes results in sufficiently
                                                                 high application level throughput even for streaming. This
                                                                 is the case in urban pedestrian areas with reasonably high
                                                                 densities of users, as well as in public transportation and in
                                                                 places where people gather occasionally (e.g., sport fields,
                                                                 shopping malls, recreational areas). Contact patterns of
                                                                 human mobility have been analyzed in the Haggle project
                                                                 [6]. This project aims at developing an application-
                                                                 independent networking architecture for delay-tolerant
 Figure 7. Data communicate rate in PAN scenario, when           networks. In contrast, we implement the podcasting service
      iPhone and Infotainment Unit has been paired.              directly on top of the link layer to exploit application-
                                                                 specific policies in the way information spreads across the
Our results demonstrate that framework is accurate: its          mobile users.
emulate flows behave similarly to Bluetooth flows with
respect to the number of packets exchanged and packet            BlueTorrent [8] is a cooperative content sharing system for
sizes. Finally, we found that framework is accurate when         Bluetooth. It differs from our approach in the search
running in piconet mode.                                         mechanisms and the content structuring. We rely on a
                                                                 channel-based content structure with a subscription model
                                                                 whereas BlueTorrent employs flat structuring with
5. Related Research                                              traditional query string search. TACO-DTN [11] is a
                                                                 content-based dissemination system for delay tolerant
Bluetooth is a low-cost technology initially designed for        networks. It is implemented as a publish/subscribe system
cable replacement [4] but more generally intended for all        and was mainly designed to distribute temporal events
kinds of Personal Area Network (PAN) applications [5]. It is     whereas our approach is implemented as a pure receiver-
probable that, in the very near future, Bluetooth will be        driven system and optimized for dissemination of streaming
embedded in almost every mobile device. These features           media. We use bloom filters in the searching for data; a
coupled with the interoperability characteristic provided by     survey of the use of bloom filters in networking is given in
Bluetooth specifications [1], make this wireless technology      [15].
very appealing for applications in automotive environments
[2]. As an example, Bluetooth headsets are very popular as
wireless audio link to a mobile phone, also for vehicular use.   6. Conclusions
These reasons make Bluetooth the most suited technology
for the design of the low power Wireless Communication           We presented, in this paper, architecture of wireless
Network (WCN).                                                   opportunistic communication network for In-vehicle
                                                                 multimedia application. The prototype implementation is
There has been substantial work on peer-to-peer content          targeted at devices that communicate over IEEE 802.15. We
distribution for the wireless network and Internet.              have evaluated different tradeoffs in the discovery,
BitTorrent is a successful instance of such systems where        synchronization, and data communication phases.
                                                          (IJCNS) International Journal of Computer and Network Security, 19
                                                                                                     Vol. 2, No. 3, March 2010

The overall resulting performance is promising and shows             ACM SIGCOMM CHANTS Workshop, Pisa, Italy,
the feasibility of wireless opportunistic communication              September 2006.
inside a vehicle. With the proposed opportunistic             [10]   W. H. Yuen, R. D. Yates, and S. C. Sung.
communication system, the scope of multimedia content                Noncooperative content distribution in mobile
exchange may broaden and that new participatory wireless             infostation networks. In Proceedings of the IEEE
broadcasting applications using the proposed concepts will           WCNC, 2003.
emerge in the near future.                                    [11]   G. Sollazzo, M. Musolesi, and C. Mascolo, “TACO-
                                                                     DTN: A Time-Aware COntent-based dissemination
We anticipate two main directions for the future work:               system for Delay Tolerant Networks,” in Proceedings
                                                                     of the First International Workshop on Mobile
      Ø    Develop analytical models for relevant measures           Opportunistic Networking, Puerto Rico, June 2007.
           of performance for the described ad hoc network.   [12]   W. Zhao, M. Ammar, and E. Zegura. Multicasting in
      Ø    Performance analysis of multimedia protocol for           delay tolerant networks: Semantic models and routing
                                                                     algorithms. In Proceedings of the Sigcomm Workshop
           different multimedia resources and performance
                                                                     on Delay Tolerant Networking, August 2005.
           attributes.
                                                              [13]   S. Burleigh, A Hooke, L. Torgerson, K. Fall, V. Cerf,
                                                                     B. Durst, and K. Scott. Delay-tolerant Networking: An
References                                                           Approach      to   Interplanetary    Internet.  IEEE
                                                                     Communications Magazine, 41(6):128–136, 2003.
                                                              [14]   Delay Tolerant Network Research Group (DTNRG).
 [1] Bluetooth Special Interest Group., “Core Specification
                                                                     http://www.dtnrg.org.
      of the Bluetooth System v 3.0”. Apr. 2009.
                                                              [15]   A. Broder and M. Mitzenmacher. Network applications
[2] R. Nüsser, R. Pelz, “Bluetooth-based Wireless
                                                                     of bloom filters: A survey. Proceedings of the 40th
     Connectivity in an Automotive Environment”, Proc. of
                                                                     Annual Allerton Conference, 2002.
     the IEEE Vehicular Technology Conference, Fall
     2000, vol. 4, pp.1935-1942.
[3] S. Burleigh, A Hooke, L. Torgerson, K. Fall, V. Cerf,     Authors Profile
     B. Durst, and K. Scott. Delay-tolerant Networking: An
     Approach      to    Interplanetary   Internet.   IEEE    Kamal Sharma received the M. Sc. (Electronics) and M. Tech.
     Communications Magazine, 41(6):128–136, 2003.            (Future Studies & Planning) degrees from Devi Ahilya University
[4] J.C. Haartsen, “The Bluetooth Radio System,” IEEE         in 2002 and 2005, respectively. He is currently with Devi Ahilya
     Personal Comm., vol. 7, no. 1, pp. 28-36, Feb. 2000.     University, Indore, INDIA.
[5] P. Johansson, M. Kazantzidis, R. Kapoor, and M.
                                                              Hemant Sharma received the M. Sc., M. Tech. and Ph D
     Gerla, “Bluetooth: An Enabler for Personal Area
                                                              degrees from Devi Ahilya University in 1996, 1998 and 2009,
     Networking,” IEEE Network, vol. 15, no. 5, pp. 28-37,    respectively. He is in to designing and developing platform
     Sept.-Oct. 2001.                                         architecture for In-vehicle Infotainment Systems for more than 10
[6] Augustin Chaintreau, Pan Hui, Jon Crowcroft,              years. He is currently with Delphi Delco Electronics Europe
     Christophe Diot, Richard Gass, and James Scott.          GmbH, Germany.
     Impact of Human Mobility on the Design of
     Opportunistic Forwarding Algorithms. In Proceedings      Dr. A. K. Ramani received his Master of Engineering (Digital
     of IEEE INFOCOM, Barcelona, Spain, April 2006.           Systems) and Ph. D, from Devi Ahilya University, Indore. He
[7] M. Izal, G. Urvoy-Keller, E.W. Biersack, P. Felber, A.    worked as a research engineer in ISRO Satellite Center, Dept. of
     Al Hamra, and L. Garcés-Erice. Dissecting BitTorrent:    Space, Bangalore, India, during 1979-83. Since Jan. 1990, he is a
                                                              professor with the School of Computer Science at Devi Ahilya
     Five Months in a Torrent’s Lifetime. In Proceedings of
                                                              University. He was associate professor at University Putra
     Passive and Acrive Measurements Conference, April        Malaysia, Dept. of Computer Science during May95 toMay99.
     2004.                                                    During Sept 2005- July 2006, He was with the College of
[8] Sewook Jung, Uichin Lee, Alexander Chang, Dae-Ki          Computer Science and Information Technology, at King Faisal
     Cho, and Mario Gerla. BlueTorrent: Cooperative           University (KFU), Kingdom of Saudi Arabia. He has guided 13
     Content Sharing for Bluetooth Users,. In Proceedings     PhDs in different areas of Computer Science and Information
     of PerCom, NY, USA, March 2007.                          Technology and has authored about 70 research papers.
[9] Gunnar Karlsson, Vincent Lenders, and Martin May.
     Delay-Tolerant Broadcasting. In Proceedings of the
20                                                               (IJCNS) International Journal of Computer and Network Security,
                                                                                                            Vol. 2, No. 3, March 2010


      An Integrated Approach for Legacy Information
                    System Evolution
                                                   Dr. Shahanawaj Ahamad1
                                                   1
                                                   Department of Computer Science
                                            College of Arts & Science in Wadi Al-Dawasir,
                                                        King Saud University
                                                       Wadi Al-Dawasir-11991
                                                      Kingdom of Saudi Arabia.
                                                         sa_sum@yahoo.com

Abstract: Future legacy evolution has always been a great            This work is motivated by migration approach suggested in
challenge because of continuous changes in business operation        [11] that explains why a module based migration approach
influenced by requirements changes, production of large              can be implemented for software maintenance, paper also
commercial benefits, information and communication
technologies development. Usually legacies are not been made to
                                                                     suggested in this direction but with legacy technical aspects
accommodate these fast changing advancements, this is one of         and implantation procedures.
the basic challenge of legacy evolution and renovation also
requires forward and backward procedures and specific
knowledge generation for renovators. Web enabling legacy and         3. Modularization
COBOL based applications interaction with e-commerce based           Following fig. 1 depicts how the legacy source is divided in
application is potentially hard to maintain and loss huge
                                                                     to interacting modules.
amount of organizational economical assets, this paper proposes
the solutions procedures in this evolutionary direction so that on
demand legacy evolution can be performed through adaptive
maintenances.

Keywords: Legacy Systems; Software Evolution; Legacy
Modules; Legacy Code; Legacy Restructuring.


1. Introduction
This paper presents a closer look at software renovation and
explains how legacy software evolutions take place for
future change. It is based on the view that an organization's                Figure 1: Dividing legacy source in modules
software systems provide valuable functionality that has
been proven in practice. As such, it should be reused                Following are some identified issues associated with this
whenever possible. At the same time, the packaging of this           procedure:
business functionality is usually far from optimal as they are
often based on old languages, database systems, and                      • Availability of legacy sources.
transaction monitors, monolithic in design, and non                      • Language used to develop legacy source.
maintainable as a result of repeated modification without                • Complexity of         source     understanding  and
supporting documents. As a consequence, legacy systems                      comprehension.
are very hard to change.                                                 • Status of documentation and complexity in re-
                                                                            documentation.
A software system can be effectively evolved with following              • Implementation of the tools for analysis and results
procedures:                                                                 description.
    • Modularization                                                     • Check feasibility of division of modules.
    • Restructuring
    • Analysis                                                       If division of source in modules is feasible and above
                                                                     mentioned issues are resolved then undertake next sequence
    • Reformation                                                    of procedural approach.
    • Transformation.
Procedures proposed are explained in the following sections.
                                                                     4. Restructuring
2. Related Work                                                      Intercommunication of the modules using organized of
                                                                     architecture is to replace the internal structure of the legacy
                                                             (IJCNS) International Journal of Computer and Network Security, 21
                                                                                                        Vol. 2, No. 3, March 2010

source. Legacy modules are wrapped to interact with the          The interactive search for modules can have any one of a
organized architecture, appear as modules. This process is       number of different starting points.
only forward process since the only modifications made to
the legacy are:                                                  • The first is to interview, if possible, the users,
     • Division in sub-modules.                                  maintainers, and designers of the legacy system in order to
     • Wrapping of the modules and major parts of the            get a picture of the overall functionality of the system, and,
         legacy remain untouched.                                more specifically, to get an impression which functionality
                                                                 should be preserved and which is redundant.

                                                                 • Another starting point is to use the persistent data stores.
                                                                 Of all the different sorts of data playing a role in the legacy
                                                                 system, it is likely that the data stored in the database
                                                                 represents business (domain-specific) entities. Following
                                                                 such data down to the actual computations as program/data
                                                                 CRUD Analysis which leads to those programs or
                                                                 procedures that could be candidate (domain-specific)
                                                                 modules.

                                                                 • Another starting point consists of the program call
            Figure 2: Restructuring procedure
                                                                 relationships, which is inter-programs relationships
                                                                 analysis, which can disclose about cohesion and coupling of
The issues associated with this procedure are:
                                                                 modules, or about the layers built into the legacy system. If
    • Reengineer the Data Bases
                                                                 one procedure invokes many others (high fan-out), and
    • Build a software access layer to access the Data
                                                                 doesn't get invoked itself, it is likely to be a control
        Bases (Legacy and New)
                                                                 (organized) module, with little built-in functionality.
    • Restore the programs so that they can access the new
                                                                 Likewise, if a procedure is called by many others (high fan-
        Data Bases.
                                                                 in), it is likely to be some sort of utility routine, dealing with
    • Externalize a wrapper for each module.
                                                                 error handling or logging. The procedures with both low
    • Write organized scripts to interconnect the modules.
                                                                 fan-in and low fan-out are the ones that are likely to contain
    • Test the restructured system.
                                                                 business logic.

5. Analysis of Legacy Source                                     • The screen /reports sequence can be identified, together
                                                                 with the key strokes leading to each subsequent
The objective is to examine the sources of the legacy system
                                                                 screen/reports. Such screen/reports sequences are very close
and extract information from them that reveals their purpose
                                                                 to use cases, telling what actions an end user performs.
and architecture.
                                                                 Moreover, following the flow of screen input fields through
                                                                 the program identifies those program slices that implement
                                                                 the given use case. This form of analysis can very well be
5.1 Analysis Methods for Legacy Sources
                                                                 supported by automated, interactive, tools.
The objective of analysis is to extract information from
legacy source that presents their purpose, and architecture.
                                                                 • Techniques for combining legacy elements into original
Analysis techniques are crucial for before and further
                                                                 ways in order to arrive at coherent modules include concept
procedures, this section covers those analysis techniques that
                                                                 analysis and cluster analysis. Such techniques can be used to
can help to find candidate modules for reformation and
                                                                 spot combined usage of pieces of data and functionality. For
development in a legacy system.
                                                                 example, they can be used to group data elements into
                                                                 candidate classes, based on their usage in programs or
Tools collect all classes of information about the system,
                                                                 procedures which can then be made into methods of the
which is used by the renovation engineer to find candidate
                                                                 derived class. In particular concept analysis can be used to
modules. There is no single way to find all good modules
                                                                 display the various combination possibilities in a concise
therefore the tools should provide many different views on
                                                                 and meaningful manner.
one legacy source system, and show potential combinations
of these views. This requires a hypertext-based browsing
                                                                 • Search for modules of specific functions, for example, a
mechanism, potentially supported by intelligent agents and
                                                                 module for valuing insurance options. A hypertext-based
automata producing specialized reports, as well as an on
                                                                 legacy browsing system can provide various starting points
line explanation mechanism.
                                                                 for such a search, such as indexes on words occurring in
                                                                 comments, column names, inferred types, and so on.
22                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010

Moreover typical computations necessary for the behavior of           •   Language knowledge
the module looked may be identified using plan recognition            •   Domain knowledge.
and these computations may then be packaged into the                  •   System Knowledge.
required modules.                                                     •   Requirements and strategy.

                                                                  It is a fact that major parts of the reformation procedure can
6. Reformation
                                                                  be automated by combining human efforts with full
This is reformation of individual modules and this                automation of repetitive tasks as speed, quality,
procedure is to consider the renovation, up gradation of          reproducibility, traceability along with human intelligence.
individual modules as depicted in Figure 3.
                                                                  7.2 Restructuring Support
The issues associated with this procedure are:                    Division of legacy source resulting from modularization,
        • Determine for each module for which renovation          now requires replacing the direct connections between
             strategy is to use.                                  legacy modules into indirect connections that are leveraged
        • Leave as is.                                            by the organized architecture. This procedure is forward
        • Completely replace it by commercial off-the-            process as the system is reorganized into modules but the
             shelve software systems.                             code of each module is hardly affected. The following
        • Perform a very detailed analysis of the component       sequences of operations are needed to achieve this:
             in order to extract its business logic that can be
             used to rebuild or regenerate the modules.               • Reengineer the Data Bases.
        • Apply the selected reformation strategy.                    • Build a software access layer to access the Data
        • Test the modules.                                              Bases legacy and new.
                                                                      • Restore the programs so that they can access the new
                                                                         Data Bases
                                                                      • Identify the level of granularity at which the legacy
                                                                         system will be decomposed.

                                                                  The major issue associated with this are:
                                                                      • The total number of modules should be manageable.
           Figure 3: Reformation with modules                         • Smaller modules with many cross relationships are
                                                                         better handled as a single, larger, module.
7. Transformation                                                     • Wrap the identified module in order to connect them
                                                                         with the organized architecture.
The goal is to technically restructure and improve the                • Write organized scripts that simulate the
sources of the legacy modules. Transformation is forward                 connectivity in the original legacy system.
process as the legacy sources are modified.
                                                                  7.3 Reformation Support
7.1 Transformation Techniques for Legacy Sources                  The reformation can be started with individual modules.
Transformation techniques perform forward, systematic,            This can be originally changes the original code of the
modifications of the legacy module source in order to enable      module. The most interesting properties of this approach
their evolution and increase their flexibility. The legacy        are:
module source is transformed for:
     • Restructure the whole system.                                  • The mutual dependencies between the evolution
     • Restructure the code of individual module.                        projects of the various modules have been
     • Apply uniform comment conventions.                                eliminated or minimized.
     • Eliminate deplore language features.
     • Convert to a new language version.                             • The reformation strategy may differ per module as
     • Translate to another language.                                    some modules may be replaced by COTS.

The reformation automata have usually three inputs:               In those cases that the decision is to perform a detailed
    • The sources of the legacy system.                           reformation based on the existing code modules, typically
    • The repository resulting from the system analysis           when much useful business logic is contained in its
        phase.                                                    transformation techniques may be applied to the code of the
    • A set of Automata Detailed Requirements                     module.
        specifications for Transformation.
                                                                  The issues associated with this procedure are:
The crucial elements in successful reformation tools are:
                                                           (IJCNS) International Journal of Computer and Network Security, 23
                                                                                                      Vol. 2, No. 3, March 2010

    • Transformation intended for code improvement and         [6] M. Fowler, K. Beck, J. Brant, W. Opdyke, and D.
       applying uniform layout conventions, goto                    Roberts. Refactoring: Improving the Design of Existing
       elimination, code restructuring, and dead code,              Code. Addison-Wesley, 1999.
       dead data elimination etc.                              [7] I. Jacobson, M. Griss, and P. Jonsson. Software Reuse;
    • Transformation intended for replacement of certain            Architecture, Process and Organization for Business
       properties of the code and change of the user-               Success. Addison Wesley, 1997.
       interface or the database engine etc.                   [8] C. Jones. Applied Software Measurement: Assuring
    • Full translation of the code to another language or           Productivity and Quality. McGraw-Hill, 1991.
       platform and conversion between COBOL dialects          [9]Oluwaseyi Adeyinka, “Service Oriented Architecture &
       or translation from obsolete 4GL to standard 3GL.            Web Services: Guidelines for Migrating from Legacy
                                                                    Systems and Financial Consideration” Master thesis,
                                                                    Blekinge Institute of Technology, 2008.
8. Conclusion
                                                               [10] M. Simos.Organization domain modelling (ODM)
The work presented in this paper provides the procedural            guidebook version 2.0. Technical Report STARS-VC-
integrated approach to overcome the major challenges for            A025/001/00, Synquiry Technologies, Inc, 1996. URL:
future business operations which are the alignment with             http://www.synquiry.com/. 450 pp.
changing business goals and changing technologies, while       [11]      B. Meyer and C. Mingins. Component-base
retaining the assets legacy systems which supporting today's        development: From buzz to spark. IEEE Computer,
business operations. It is also discussed the automated             23(7):35-37, 1999.
analysis and transformation of legacy systems. The             [12] Dr. Vladimir Bacvanski, An Object-Oriented,
necessary techniques for analysis, transformation, and              Component-based, Approach to Migrating Legacy
reformation of legacy systems were also discussed. Paper            Systems, 2004.
also concludes that the legacy evolution is an economically
motivated task and legacy is a valuable asset for
organization and business operations. Discussed approach       Authors Profile
focuses on modularization of whole legacy system, issues
and propose the successive development procedure for the
affective evolution.                                                                           Dr. Shahanawaj Ahamad is an
                                                                                               active academician and researcher
References                                                                                     in the field of Software Reverse
                                                                                               Engineering with experience of ten
[1] A.V. Aho, R. Sethi, and J.D. Ullman. Compilers.                                            years, working with King Saud
    Principles, Techniques and Tools. Addison Wesley,                                          University’s College of Arts and
    1986.                                                                                      Science in Wadi Al-Dawasir,
[2] G. Visaggio, Value-based decision model for renovation                                     K.S.A. He is the member of various
    processes in software maintenance, Annals of Software      national and international academic and research groups, member
    Engineering, 9, Kluwer Academic Publishers, May            of journal editorial board and reviewer. He is currently working on
    2000, pp 215-233.                                          Legacy Systems Migration, Evolution and Reverse Engineering,
[3]G. Visaggio, Ageing of a Data-Intensive Legacy System:      published more than twenty papers in his credit in national and
    Symptoms and Remedies, Journal of Software                 international journals and conference proceedings. He holds M.
    Maintenance: Research and Practice, John Wiley; vol.       Tech. Degree in Information Technology followed by Ph.D. in
    13, pp. 281-308, 2001.                                     Computer Science major Software Engineering, supervised many
[4]C. Szyperski. Component Software; Beyond Object-            bachelor projects and master thesis.
    Oriented Programming. Addison-Wesley, 1998.
[5] E. Stroulia, M. El-Ramly, L. Kong, P. Sorenson, and B.
    Matichuck. Reverse engineering legacy interfaces: An
    interaction-driven approach. In 6th Working
    Conference on Reverse Engineering, WCRE'99, pages
    292-301. Society, 1999.
24                                                             (IJCNS) International Journal of Computer and Network Security,
                                                                                                          Vol. 2, No. 3, March 2010


          Improving Information Accessibility In
         Maintenance Using Wearable Computers
                                      Lt.Dr.S Santhosh Baboo1 and Nikhil Lobo2
                                                           1
                                                            Reader
                                           P.G. & Research Dept of Computer Science
                                              D.G.Vaishnav College, Chennai 106
                                                        2
                                                            Research Scholar
                                                      Bharathiar University

Abstract: In aerospace and defense, maintenance is being          (Eric Jorgensen, 1994). The information in these manuals is
carried out using technical manuals in hardcopy. Manuals          presented in a window frame with navigation tools for
in hardcopy format are very difficult to carry, access            zooming and panning allowing easy comprehension.
information and understand while carrying out                     Information is displayed based on the
maintenance. This paper brings out the concept of
Interactive Electronic Technical Manuals that can run on
Wearable Computers making maintenance more effective
while reducing the effort involved. Manuals are now
compact and easy to handle, easier to access, can be read
in a systematic manner and easily comprehendible.

Keywords: Wearable Computer, Interactive Electronic Technical
Manual, Manuals, Documentation


1. Introduction
An aircraft is required to be maintained in airworthy
condition. During maintenance of aircrafts, a technician is
often required to refer manuals for maintenance procedures.            Figure 1. Interactive Electronic Technical Manual
These manuals are at present in hardcopy consuming time
to access the relevant information. These hardcopy manuals
can be replaced by Interactive Electronic Technical Manuals       3. Need for Interactive Electronic Technical
(IETM) and accessed using wearable computers improving               Manuals (IETMs) when compared to Paper-
the performance of technicians by increasing accessibility to        Based Manuals
information. Moreover these technicians can receive the
latest information updates electronically without waiting for     •   Information can retrieved easily
the amended manuals in hardcopy. Following are the                •   Since information is presented in electronic form, less
objectives to be obtained by using Interactive Electronic             storage would be required
Technical Manuals instead of paper-based manuals:                 •   As in the case of hardcopies, pages will not be subject to
• 100% identification of causes of problems (fault                    wear and tear
    isolation)                                                    •   IETMs can be easily loaded into portable and wearable
• Time spent in solving the problem (troubleshooting)                 computers which maintenance personnel can take to the
    decreased by 20 - 25%                                             field
• Error reduction in performing removals and                      •   Difficult procedures can be integrated with multimedia
    replacements by 35 - 40%                                          elements like video and animations to make
                                                                      understanding easier
2. Interactive Electronic Technical Manuals                       •   Information on various configurations of equipments can
   (IETMs)                                                            be maintained and displayed by storing only the
                                                                      difference
Interactive Electronic Technical Manuals (IETMs) are
                                                                  •   The IETM can be used as a basis for developing
manuals in electronic format with interactivity designed for
                                                                      Computer based training Packages on the same subject
display on computers. An IETM is intended to be the
functional equivalent of a paper-based Technical Manual
and in most cases a total replacement for the paper manual
                                                             (IJCNS) International Journal of Computer and Network Security, 25
                                                                                                        Vol. 2, No. 3, March 2010

                                                                     data integrity. Cross-references are dynamic and search
                                                                     feature is robust.
                                                                 •   The above IETM is integrated with data from other
                                                                     processes and systems like expert systems, test
                                                                     equipments and diagnostics

                                                                 5. Features of Interactive Electronic Technical
                                                                    Manuals
                                                                 Authoring Module
                                                                      To create manuals with their respective chapters,
                                                                 sections and subsections and incorporate them into the
                                                                 IETM
                                                                      Features:
                                                                 • User Authentication – to enter the Authoring Module a
                                                                     user is prompted to enter the login identification (ID)
                                                                     and password
                                                                 • Manual Description – facility to add or delete manuals
                                                                     and their respective chapters, sections and subsections
                                                                 • Builder – an editor that allows users to create individual
                                                                     pages to be incorporated into the manual
                                                                 • Publishing – publishing a viewer module

                                                                 Viewer Module
                                                                      To view manuals by clicking on their respective
                                                                 chapters, sections and subsections
                                                                 Features:
                                                                 • User Authentication – to enter the Viewer a user is
                                                                    prompted to enter the login identification (ID) and
                                                                    password
                                                                 • Split Window - to view text pages and corresponding
                                                                    illustrations simultaneously
                                                                 • Image Viewer - to pan and zoom illustrations
    Figure 2. IETMs compared to Paper-Based Manuals              • Safety Notes - warnings, cautions and notes used in the
                                                                    manual to be displayed in separate windows to alert
4. Types of Interactive Electronic Technical                        users on their importance
   Manuals                                                       • Acronyms and Abbreviations - Glossary containing the
                                                                    list of acronyms and abbreviations used in the manuals
•   Page images obtained by scanning in rater format with        • Find – to search for a specific word in a page
    the table of contents, list of tables, list of figures and   • Search – to search for a specific word within manuals
    index hyperlinked to the respective contents of the          • Notes – facility for users to create their own notes while
    manual. A user can select a topic from the table of             browsing
    contents and the respective raster page is displayed. The    • History Back and Forward – keeps a track of the order of
    page orientation of the manual is retained and it can be        pages that have been visited by the user
    viewed and directly printed as per format specifications.
                                                                 • Bookmark- allow a user to bookmark a page to return to
•   An ASCII or PDF document in a scrolling text window.            it later
    In addition to the above hyperlinks it also contains
                                                                 • Print - to print a desired chapter, section or subsection
    hyperlinks to sections, tables and figures. This document
                                                                 • Help – to guide the user how to use this Viewer Module
    can be linked to video, audio and external applications.
    May contain raster and vector graphics. Bookmarks,
    search and sticky notes are provided. The manual can be
                                                                 6. Manuals commonly used in IETM
    viewed and directly printed as per format specifications.         Maintenance Manual
•   SGML files with the content structured so that it can be          The description and operation of each aircraft system is
    viewed as smaller logical blocks of text with very limited   explained in this manual with procedures for removal and
    use of scrolling. It is viewed as an indexed PDF file.       installation of assemblies that constitute that system.
•   The information authored is fully structured and             Procedure for repair and cleaning is also included along
    hierarchical. In a relational database data tagged with      with inspection and testing.
    SGML is stored to prevent data redundancy and enforce
                                                                      Illustrated Parts Catalogue
26                                                          (IJCNS) International Journal of Computer and Network Security,
                                                                                                       Vol. 2, No. 3, March 2010

    The assemblies along with their respective parts are             A wearable computer is a potential platform for many
mentioned in this manual. Each part has a unique part           different applications that require privacy, mobility and
number, nomenclature and the quantity of that part in the       continuous access to information (Lehikoinen, 2002).
assembly. Vendor that supplies this part is also mentioned.

     Description and Operation Manual
     The description and operation of each aircraft system is
explained in this manual.

     Flight Manual
     The description and operation of each aircraft system is
explained in this manual. Recommended procedures for
normal operations and emergencies are mentioned.                      Figure 3. WT4000 wearable computer with a scanner
                                                                                        attachment
     Consumable Products Manual
     For each aircraft system, the list of consumables                The WT4000 is 5.7 inches in length, width 3.7 inches
required to carry out maintenance of that system. The part      and height of 1.0 inches, weighing approximately 390.2
number, which is unique along with the nomenclature and         grams. It has a keyboard consisting of 23 alphanumeric keys
quantity, are mentioned in this manual.                         and a memory (FLASH/RAM) of 64/128 MB. The display
                                                                type is a backlit color TFT having a display resolution of
    Master Servicing Schedules                                  QVGA in landscape mode (320x240). The operating system
    This manual covers the preventive maintenance               is Microsoft Windows CE 5.0 Professional Version. It can
operations to be carried out to maintain the aircraft in        be operated in temperatures ranging from -20° to 50° C and
airworthy condition. It also includes basic servicing,          can withstand multiple drops on concrete from a height of 4
component replacements and unconditional inspections and        feet. Optional accessories include wearable scanners RS309
checks.                                                         and RS409.

      Storage and Preservation manual                           8. Creation of Interactive Electronic Technical
      The manual details the procedures to be carried out for      Manuals for a Military Helicopter
storage and preservation of that aircraft and its components.
It also includes instructions for packing and transportation        Interactive electronic technical manuals were
of an aircraft with its on-board components.                    developed and implemented on the field using wearable
                                                                computers for the following manuals
    TTGE                                                        • Description and Operation
    For maintenance of an aircraft, the tools and ground        • Maintenance Manual
support equipment are mentioned in this manual.                 • Fault Isolation Manual
                                                                • Airplane Illustrated Parts Catalog
7. Wearable Computers                                               Following are the metrics collected on the field during
                                                                maintenance of the helicopter
     A computer that is subsumed into the personal space of
the user, controlled by the wearer, and that is always on and       Table 1: Comparison between Paper-Based Manuals and
always accessible (Steve Mann, 1997).                                Interactive Electronic Technical Manuals for a Military
                                                                                            Helicopter
     A portable computer worn around the body of a
technician into which commands can be entered and                             Task              Paper-Based       Interactive
executed while the technician is performing maintenance                                           Manuals         Electronic
operations. These portable computers normally contain                                                         Technical Manuals
voice recognition and head mounted display as input and
output interfaces. The technician is now able to access the
                                                                    Correct identification of
capabilities of a desktop and is in contact with Interactive         causes of 12 problems          7                12
Electronic Technical Manuals containing maintenance                          (faults)
instructions at all times.
                                                                     Time spent in solving
      Three dominant aspects characterize wearable                      the 12 problems          82 hours         63 hours
computers: they are always on and always ready, they are               (troubleshooting)
totally controlled by the user, and they are considered both
by the user and by the others around to belong to the user’s           Number of errors
personal space (Mann, 1997).                                           encountered when             14               9
                                                                    performing 38 removals
                                                                     and 12 replacements
                                                                       The above metrics indicate the following
                                                                •     Improvement in identification of causes of problems
                                                                 (IJCNS) International Journal of Computer and Network Security, 27
                                                                                                            Vol. 2, No. 3, March 2010

      (fault isolation) from 58% to 100%                             to handle, easier to access, can be read in a systematic
•     Time spent in solving the problem (troubleshooting)            manner and easily comprehendible.
      decreased by 23%
•     Error reduction in performing removals and
      replacements by 36%

9. Creation of Interactive Electronic Technical                      References
   Manuals for a Transport Aircraft
                                                                     [1] Steve Mann, “Smart Clothing: The Wearable
    Interactive electronic technical manuals were                        Computer and WearCam”, Personal Technologies,
developed and implemented on the field using wearable                    Vol.1 No.1, Mar. 1997.
computers for the following manuals                                  [2] Eric L. Jorgensen, “The Interactive Electronic
• Maintenance Manual                                                     Technical Manual Overview – Setting the Stage”,
• Fault Isolation Manual                                                 AFEI CALS Expo International, Oct. 1994.
• Airplane Illustrated Parts Catalog                                 [3] Steve Mann, “An Historical Account of the WearComp
                                                                         and WearCam Inventions Developed for Applications
                                                                         in 'Personal Imaging”, The First International
    Following are the metrics collected on the field during
                                                                         Symposium on Wearable Computers: Digest of Papers,
maintenance of the transport aircraft
                                                                         IEEE Computer Society, pp. 66–73, 1997.
                                                                     [4] Lehikoinen J, “Interacting with wearable computers:
    Table 2: Comparison between Paper-Based Manuals and
                                                                         techniques and their application in wayfinding using
    Interactive Electronic Technical Manuals for a Transport
                                                                         digital maps”. Ph.D. Thesis. University of Tampere.
                             Aircraft
                                                                         Department of Computer and Information Sciences,
                                                                         Report A-2002-2, 2002.
            Task                Paper-Based Interactive Electronic
                                 Manuals     Technical Manuals

  Correct identification of          5                 9
causes of 9 problems (faults)


 Time spent in solving the 9     58 hours          46 hours
 problems (troubleshooting)


Number of errors encountered         8                 5
when performing 16 removals
    and 4 replacements

        The above metrics indicate the following
•     Improvement in identification of causes of problems
      (fault isolation) from 56% to 100%
•     Time spent in solving the problem (troubleshooting)
      decreased by 21%
•     Error reduction in performing removals and
      replacements by 38%


10. Conclusion
      The metrics collected for maintenance being carried out
on a Military Helicopter and Transport Aircraft using
IETMs on Wearable Computers are analyzed and following
are the benefits
• 100% identification of causes of problems (fault
    isolation)
• Time spent in solving the problem (troubleshooting)
    decreased by 20 - 25%
• Error reduction in performing removals and
    replacements by 35 - 40%
      In conclusion Interactive Electronic Technical Manuals
run on Wearable result in manuals being compact and easy
28                                                              (IJCNS) International Journal of Computer and Network Security,
                                                                                                           Vol. 2, No. 3, March 2010


     Remote Laboratory for Teaching Mobile Systems
              Adil SAYOUTI1, Adil LEBBAT 1, Hicham MEDROMI1 and Fatima QRICHI ANIBA1
                                  Laboratoire d’Informatique, Systèmes et Énergies Renouvelables
                                   1

                            Team Architecture of Systems, ENSEM, BP 8118, Oasis, Casablanca, Morocco
                         sayouti@gmail.com, adil.lebbat@gmail.com, hmedromi@yahoo.fr and Qrichi_f@yahoo.fr


Abstract: This paper presents the current contribution of
ENSEM (Hassan II University) in the Innovative Educational          •   Remote laboratories (Figure 1), which offer remote
Concepts for Autonomous and Teleoperated Systems project                access to real laboratory equipment and instruments;
which aims at create an innovative educational tool to allow        •   Virtual laboratories (Figure 2), which offer access to a
students to perform remote laboratory experiments on                    virtual environment using for this simulation software.
autonomous and teleoperated mobile systems. Although the
Internet offers a cheap and readily available communication
channel for teleoperation, there are still many problems that
need to be solved before successful real-world applications can
be realized. These problems include its restricted bandwidth and
arbitrarily large transmission delay, which influence the
performance of the remote control over Internet. In this article,
we propose a solution that consists in equipping the mobile
systems with a high degree of local intelligence in order for
them to autonomously handle the uncertainty in the real world
and also the arbitrary network delay.
  Keywords: E-learning, Control Architecture, Software
Architecture, Multi-agents System, Distributed System, Mobile
System, Internet.
                                                                                    Figure 2. Virtual laboratories
1. Introduction
                                                                    2. Multi-Agent          Systems        for     Autonomous
Experimentation is a very important part of education in
                                                                       Control
engineering. This is also true for mechatronic engineering,
which is a relatively new field, combining three engineering        The organization of a system - or its control architecture -
disciplines: mechanical engineering, electrical engineering         determines its capacities to achieve autonomous tasks and to
and software engineering. The equipments needed for                 react to events [2]. The control architecture of an
experiments in mechatronic are generally expensive. One             autonomous mobile system must have both decision-making
solution for expensive equipments is sharing the available          and reactive capabilities: situations must be anticipated and
equipments with other universities around the world [1].            the adequate actions decided by the mobile system
Two are the possibilities to realize it:                            accordingly, tasks must be instantiated and refined at
• Remotely accessible student laboratory facilities - with          execution time according to the actual context, and the
    the advent of the Internet and its rapidly spreading            mobile system must react in a timely fashion to events. This
    adoption in almost all spheres of society - have become         can be defined as a rational behavior, measured by the
    feasible and are increasingly gaining popularity.               mobile system's effectiveness and robustness in carrying out
• Virtual reality (VR) is a system which allows one or              tasks.
    more users to move and react in a computer generated            To meet this global requirement, the control system
    environment.                                                    architecture should have the following properties [3]:
At present, several e-learning laboratories have been               • Programmability: a useful mobile system cannot be
developed. It can be distinguish two categories of them:                designed for a single environment or task, programmed
                                                                        in detail. It should be able to achieve multiple tasks
                                                                        described at an abstract level. The functions should be
                                                                        easily combined according to the task to be executed.
                                                                    • Autonomy and adaptability: the mobile system should be
                                                                        able to carry out its actions and to refine or modify the
                                                                        task and its own behavior according to the current goal
                                                                        and execution context as perceived.
                                                                    • Reactivity: the mobile system has to take into account
                                                                        events with time bounds compatible with the correct and
                                                                        efficient achievement of its goals (including its own
                Figure 1. Remote laboratories                           safety). Consistent behavior: the reactions of the mobile
                                                               (IJCNS) International Journal of Computer and Network Security, 29
                                                                                                          Vol. 2, No. 3, March 2010

     system to events must be guided by the objectives of is       3. System Architecture
     task.
                                                                   The remote laboratories provide a live performance
• Robustness: the control architecture should be able to
                                                                   laboratory accessible via Internet, which can be used to
     exploit the redundancy of the processing functions.
                                                                   cover the experimental issues in any tele-education system.
     Robustness will require the control to be decentralized to
                                                                   Clearly as bandwidth increases and higher speed network
     some extent.
                                                                   access reaches users; these factors play an important role in
• Extensibility: integration of new functions and definition
                                                                   user adoption of remote laboratories.
     of new tasks should be easy. Learning capabilities are
                                                                   The concept of remote laboratories is defined as a
     important to consider here: the architecture should make
                                                                   mechatronic workspace for distance collaboration and
     learning possible.
                                                                   experimentation in research or other creative activity, to
We note an interesting link between the desirable properties
                                                                   generate and deliver results using distributed information
of intelligent control architecture for autonomous mobile
                                                                   and communication technologies. To implement a remote
systems and the behavior of agent-based systems:
                                                                   laboratory, a common Internet-based teleoperation model [5]
• Agent-based approaches to software and algorithm
                                                                   is used as shown in figure3.
     development have received a great deal of research
     attention in recent years and are becoming widely
     utilised in the construction of complex systems.
• Agents use their own localised knowledge for decision-
     making, supplementing this with information gained by
     communication with other agents.
• Remaining independent of any kind of centralised
     control while taking a local view of decisions gives rise
     to a tendency for robust behavior.
• The distributed nature of such an approach also provides
     a degree of tolerance to faults, both those originating in
     the software/hardware system itself and in the wider
     environment.
It is for these reasons that we consider an agent-based
system to be a suitable model on which to base an intelligent
control architecture for complex systems requiring a large
degree of autonomy.
Although widely used, multi-agent systems research has also                       Figure 3. System Architecture
lead to a number of definitions of agency. Once again, in
some cases, these definitions are inconsistent. In our             The Remote user, through his Internet navigator, addresses
context, the terms agent or intelligent agent refer to a           a http request to a Web server and downloads an application
material or software entity with one or more independent           on his work station. A connection is then established
threads of execution, and which is entirely responsible for        towards the server in charge of the management of the
its own input and output from/to the environment in which          mobile system to control. The user is then able to take the
it is situated [4]. It is therefore autonomous. We assume that     remote control of it. In parallel, other connections are also
the agent has well-defined objectives or goals and exercises       established towards multi-media servers broadcasting
problem-solving behavior in pursuit of these goals; reacting       signals (video, sound) of the system to be controlled.
in a timely fashion. It is this behavior that allows us to refer   The Internet network (network without quality of service)
to the agent as intelligent. While being flexible problem          limits the quantity of information that can be transmitted
solvers in their own right, the power of agents is only fully      (bandwidth) and introduces delays which can make the
realised once multiple agents are combined and                     remote control difficult or impossible. The solution
communicating. This is referred to as a multi-agent system         proposed, through this work, to face the limitations of the
(MAS). As agents are equipped with different abilities and         Internet, is founded on the autonomy and the intelligence,
different goals, each agent has a distinct sphere of influence     based on multi-agents systems, granted to the mobile system
within the environment in which all the agents are situated.       in order to interact with its environment and to collaborate
These spheres of influence may overlap, defining a                 with the remote user. The need that consists in wanting to
fundamental relationship between agents. Further                   assign to the mobile system the maximum of autonomy and
relationships may be superimposed through the use of               intelligence brought us to examine in the detail the choice of
communication channels. A MAS, therefore, has all the              a remote control architecture [6].
basic properties of a complex system: autonomy,
asynchronicity, concurrency, reactivity and extensibility.
30                                                             (IJCNS) International Journal of Computer and Network Security,
                                                                                                          Vol. 2, No. 3, March 2010

4. Remote Control Architecture                                     The path planner generates the path using as input the goal,
                                                                   the mobile system localization and the global map of the
   3.4 Control architecture                                        environment.
Humans are sophisticated autonomous agents that are able           The reactive part of our architecture, based on couples of
to function in complex environments through a combination          agents perception / action, allows the mobile system to react
of reactive behavior and deliberative reasoning. Motivated         facing the unforeseen events (Figure 5).
by this observation, we propose a hybrid control
architecture, called EAAS [7] for EAS (Equipe Architecture
des Systèmes) Architecture for Autonomous System. Our
architecture combines a behavior-based reactive component
and a logic-based deliberative component. EAAS is useful in
advanced mobile systems that require or can benefit from
highly autonomous operation in unknown environment,
time-varying surroundings, such as in space robotics and
planetary exploration systems, where large distances and
communication infrastructure limitations render human
teleoperation exceedingly difficult.
The proposed generic architecture consists in associating a
deliberative approach for the high part and a reactive
approach for the low part. The deliberative part or
                                                                        Figure 5. Reactive Part of the EAAS Architecture
hierarchical agent allows decision-making and actions
planning thanks to the use of the agent selection of actions
(Figure 4). This last is composed of three levels: pilot,            3.5 Remote control software architecture
navigator and path planner.                                        A Software architecture has been defined to make remote
                                                                   control of mobile systems possible. Our software
                                                                   architecture is based on a set of independent agents running
                                                                   in parallel.
                                                                   On the left side of figure 6, the server side is represented. It
                                                                   is basically composed of three main agents: “Connection
                                                                   Manager” which manages the different connected clients
                                                                   according to a Control Algorithm. This one is chosen by the
                                                                   designer of the system depending on the application:
                                                                   master/slave, priority, timeout... The “Media” agent
                                                                   communicates with the camera in order to broadcast signals
                                                                   (video, images) of the mobile system in its environment.
                                                                   The “SMA EAAS” (EAS Architecture for Autonomous
                                                                   Systems) which represents our control architecture. EAAS
                                                                   architecture is a hybrid control architecture including a
             Figure 4. Actions Selection Agent                     deliberative part (Actions Selection Agent) and a reactive
                                                                   part. The reactive part is based on direct link between the
The pilot generates the setting points needed for action           sensors (Perception Agent) and the effectors (Action Agent).
agent, based on a trajectory provided as an input. This
trajectory is expressed in a different frame (e.g. Cartesian
frame) from that of the setting points. This trajectory
describes, in time, the position, kinematics and/or dynamic
parameters of the mobile system in its workspace. The pilot
function is to convert these trajectories into setting points to
be performed by the action agent. The navigator generates
the trajectories for the pilot based on data received from the
upper level. These input data are of a geometrical type, still
in a Cartesian frame, but not necessarily in the mobile
system frame. Moreover, these data do not integrate
dynamics or kinematics aspects; contrary to the trajectory,
there is not a strict definition of the velocity, the
acceleration or the force versus time. These input data are
called path – continuous or discontinuous – in cartesian             Figure 6. Remote control software architecture proposed
frame. The navigator must translate a path into a trajectory.
                                                              (IJCNS) International Journal of Computer and Network Security, 31
                                                                                                         Vol. 2, No. 3, March 2010

The right side of the figure represents the client side. Agents   standard Internet protocols. First, the communication is
are loaded in a web navigator. The “Remote Client”                based on the HTTP protocol, through a home page linking
corresponds to a graphical user interface which allows the        the applets used to move the mobile system. These applets
user to send orders to the mobile system and receive              are interpreted by the JVM of the browser. Then, the applets
information about the environment. “Sender” and                   downloaded on the client communicate with the application
“Receiver” agents are used to allow the communication             server through the TCP/IP protocol.
between the client and the server. “Pinger” and “Ponger”
agents are used to observe dynamically the network. If the
connexion is accepted, the “Connection Manager” will
inform the “Local Client” agent which achieves the
interface with the “SMA EAAS” to transmit orders
transmission to the mobile system.

5. Application
The mobile system used in our application is a Lego robot.
Lego Mindstorms [8] is a development kit for
manufacturing a robot using Lego blocks, and is gaining
widespread acceptance in the field of technical education.
By using a Mindstorm, a robot can be manufactured for
various purposes and functions. It is beginning to be
considered as a component of experimental equipment in
robotics research.
The Lego mobile robot (Figure 7) is powered by three
reversible motors coupled to wheels and equipped with four
sensors: sonar sensor, sound sensor, light sensor and touch
sensor. The data produced by these sensors are used by                               Figure 8. Web Interface
perception agent to build a global map of the Lego robot
environment’s. This global map, the goal and the Lego             The remote users can pass online tests of knowledge in
robot localisation are used by the actions selection agent to     order to follow a formation answering to their needs.
define a plan of actions to achieve its mission. The Lego         Different modules of formation (Cursus link) are available
robot is equipped with Bluetooth connection that permits the      on our web site, to know: remote control, multi-agents
communication with the application server and facilitates its     systems, systems architecture, control architecture and
displacement in the environment in order to reach its             autonomous mobile system. We have also set to the remote
objective.                                                        users a discussion forum within our application to
                                                                  interchange their ideas over the remote control subject.

                                                                  6. Conclusion
                                                                  In this paper, we have presented a Web-based remote
                                                                  control application so that Internet users, especially
                                                                  researchers and students, can control the mobile robot to
                                                                  explore a dynamic environment remotely from their home
                                                                  and share this unique robotic system with us. In the first
                                                                  part, an analysis of the existing control architectures and the
                                                                  approaches for their development has guided us to design a
                                                                  hybrid control architecture. It is called EAAS for EAS
                                                                  Architecture for Autonomous System. The proposed generic
               Figure 7. General Architecture                     architecture consists in associating a deliberative approach
                                                                  for the high level and a reactive approach for the low level.
The Web interface of our application is designed with the         The deliberative level allows decision-making and actions
intention of making the remote control easy for researchers       planning thanks to the use of the agent selection of actions.
and students in order to interact with the Lego mobile robot.     The reactive level, based on couples of agents perception /
A simple interface is designed to provide as much                 action, allows the mobile system to react facing the
information as possible for remote control. This user             unforeseen events. Then, the software implementation of our
interface consists of several Java Applets as shown in Figure     architecture was presented. It is achieved under the shape of
8. It can work on any web browser.                                a multi-agents system by reason of its autonomy,
The link between client(s) and server is based on two             intelligence, flexibility and the various possibilities of
32                                                                 (IJCNS) International Journal of Computer and Network Security,
                                                                                                              Vol. 2, No. 3, March 2010

evolution. In the second part, in order to validate the choice                               Adil Lebbat received his Degree in High
of our architecture, we presented one of applications                                        Education Deepened in Network & Telecom
                                                                                             in 2004 from the chouaib doukkali
achieved by the system architecture team of the ENSEM.
                                                                                             university, Eljadida, Morocco. In 2006 he
                                                                                             rejoined the system architecture team of the
                                                                                             ENSEM. Her main research is mainly about
References                                                                                   real time distributed platform based on
                                                                                             multi agents systems: Application based on
[1] P. Le parc, J. Vareille and L. Marce, “E-productique ou                                  the core Linux for products of
      contrôle et supervision distante de systèmes                     telecommunications.
      mécaniques sur l’Internet”, Journal européen des
      systèmes automatisés (JESA), Vol. 38, n° 5, pp. 525-
      558, 2004.
[2] C. Novales, G. Mourioux and G. Poisson, “A multi-                                      Hicham Medromi received the PhD in
      level architecture controlling robots from autonomy                                  engineering science from the Sophia
      to teleoperation”, First National Workshop on                                        Antipolis University in 1996, Nice, France.
                                                                                           He is responsible of the system
      Control Architectures of Robots. Montpellier. April
                                                                                           architecture team of the ENSEM Hassan II
      6,7 2006.                                                                            University, Casablanca, Morocco. His
[3] R. Alami, R. Chatila, S.Fleury, M.Ghallab and                                          actual main research interest concern
      F.Ingrand, “An architecture for autonomy. The                                        Control Architecture of Mobile Systems
      International Journal of Robotics Research”, Special                                 Based on Multi Agents Systems. Since
      Issue on Integrated Architectures for Robot Control                                  2003 he is a full professor for automatic
      and Programming, vol. 17, n° 4, pp. 315-337, 1998.                                   productic and computer sciences at the
[4] J. Ferber, “Multi-Agent Systems: An Introduction to                ENSEM, Hassan II University, Casablanca.
      Distributed Artificial Intelligence”, Addison Wesley
      Longman, Harlow, UK, 1999.                                                             Fatima Qrichi Aniba received an electrical
                                                                                             Engineer’s degree from the ENSAM in 2003
[5] A. Sayouti, F. Qrichi Aniba and H. Medromi, “Remote
                                                                                             Meknes, Morocco. In 2005 she got her
      Control Architecture over Internet Based on Multi                                      Degree in High Education Deepened in
      agents Systems”, International Review on Computers                                     automatic productic from the ENSEM,
      and Software (I.RE.CO.S), Vol 3, n° 6, pp. 666 –                                       Hassan II University, Casablanca, Morocco.
      671, November 2008.                                                                    In 2005 she rejoined the system architecture
[6] A. Sayouti, “Conception et Réalisation d’une                                             team of the ENSEM. Her main research is
      Architecture de Contrôle à Distance Via Internet à                                     mainly about Real Time Architecture Based
      Base des Systèmes Multi-Agents”, Phd. Thesis,                                          on Multi Agents Systems.
      ENSEM, Hassan II University 2009.
[7] A. Sayouti, H. Medromi, F. Qrichi Aniba, S. Benhadou
      and A. Echchahad, “Modeling Autonomous Mobile
      System with an Agent Oriented Approach”,
      International Journal of Computer Science and
      Network Security (IJCSNS), Vol 9, n° 9, pp. 316 –
      321,September 2009.
[8] LEGO Company, “Lego mindstorms official page”,
      http ://mindstorms.lego.com, 1997.

Authors Profile
                        Adil Sayouti received the PhD in
                        computer science from the ENSEM,
                        Hassan II University in July 2009,
                        Casablanca, Morocco. In the same year he
                        received the price of excellence of the best
                        sustained thesis in 2009. In 2003 he
                        obtained the Microsoft Certified Systems
                        Engineer (MCSE). In 2005 he joined the
                        system architecture team of the ENSEM,
                        Casablanca, Morocco. His actual main
research interests concern Remote Control over Internet Based on
Multi agents Systems.
                                                                (IJCNS) International Journal of Computer and Network Security, 33
                                                                                                           Vol. 2, No. 3, March 2010


            Resource Allocation in Wireless Networks
                                      1
                                        Manish Varshney, 2Dr Yashpal Singh, 3Vidushi Gupta
                         1
                             Sr Lecturer Deptt of Computer Science & Engg, SRMSWCET Bareilly, India
                                                Email itsmanishvarshney@gmail.com
                                   2
                                     Reader Deptt of Computer Science & Engg BIET Jhansi, India
                                                     Email yash_biet@yahoo.com
                             3
                               Lecturer Deptt of Computer Science & Engg, SRMSWCET Bareilly, India
                                                      Email vidu.leo@gmail.com


Abstract: In this paper, we study about the resource allocation     same desired range (2) Spacial reuse: since transmission is
techniques in wireless network ,thus describing utility based       focused in a particular direction, the surrounding area in the
functions and various protocols using directional antenna .In       other directions can still be used by other nodes to
other words the stud is based on utility-based maximization for     communicate ,now coming back to the point of throughput
resource allocation. We consider two types of traffic, i.e., best   and fairness required in resource allocation .
effort and hard QoS, and develop some essential theorems for        “Throughput” and “fairness,” however, are conflicting
optimal wireless resource allocation. Directional antenna
                                                                    performance metrics. To maximize system throughput, the
technology provides the capability for considerable increase in
spatial reuse which is essential in the wireless medium. In this
                                                                    system will allocate more resource to the users in better
paper, a bandwidth reservation protocol for QoS routing in          channel conditions. This may cause radio resource
TDMA-based MANETs using directional antennas is presented.          monopolized by a small number of users, leading to
The routing algorithm allows a source node to reserve a path to     unfairness. On the other hand, to provide fairness to all
a particular destination with the needed bandwidth which is         users, the system tends to allocate more resource to the users
represented by the number of slots in the data phase of the         in worse channel conditions so as to compensate for their
TDMA frame. The performance of the proposed schemes is              shares. As a result, the system throughput may be degraded
evaluated via simulations. The results show that optimal            dramatically. The work in [6-7] show that the system can
wireless resource allocation is dependent on traffic types, total   behave either throughput-oriented” or “fairness oriented” by
available resource, and channel quality, rather than solely         adjusting certain parameters. However, they do not describe
dependent on the channel quality or traffic types as assumed in
                                                                    how to determine and justify the value of these parameters,
most existing work. Further optimizations to improve the
                                                                    leaving this trade-off unsolved.
efficiency and resource utilization of the network is provided.
                                                                    In this paper, we focus on basic techniques required for
Keywords: Utility-based maximization, wireless networks,            resource allocation in wireless networks .through the work
resource allocation, , Mobile ad hoc networks (MANETs), quality     we came to the basic two factors which are to be resolved ,
of service (QoS), routing, time division multiple access (TDMA).    1)the first factor relates “user satisfaction” for resource
                                                                    allocation to avoid such a “throughput-fairness” dilemma
                                                                    Since it is unlikely to fully satisfy the different demands of
                                                                    all users, we turn to maximize the total degree of user
1. Introduction                                                     satisfaction. The degree of user satisfaction with a given
RESOURCE allocation is an important research topic in               amount of resource can be described by the utility function
wireless networks [1-7]. In such networks, radio resource is        U(r), a non-decreasing function with respect to the given
limited, and the channel quality of each user may vary with         amount of resource r. The more the resource is allocated, the
time. Given channel conditions and total amount of                  more the user is satisfied. The marginal utility function
available resource, the system may allocate resource to users       defined by u(r) = dU(r) dr is the derivative of the utility
according to some performance metrics such as throughput            function U(r) with respect to the given amount of resource r.
and fairness [1], [2] or according to the types of traffic          The exact expression of a utility function may depend on
[3].but another foremost factor that is required in wireless        traffic types, and can be obtained by studying the behavior
network is spatial reuse of network. In order to                    and feeling of users. We leave the work of finding utility
communicate with another node in a particular location, a           functions to psychologists and economists, and focus on
node that is transmitting using an omnidirectional antenna          maximizing the total utility for a given set of utility
radiates its power equally in all directions. This prevents         functions. and 2) the second factor link to the directional
other nodes located in the area covered by the transmission         antennas There are different models that are presented in
from using the medium simultaneously. For this purpose              the literature for directional antennas [8].In this paper, the
directional antennas are used. Directional antennas allow a         multi-beam adaptive array (MBAA) system is used [1]. It is
transmitting node to focus its antenna in a particular              capable of forming multiple beams for simultaneous
direction. Similarly, a receiving node can focus its antenna        transmissions or receptions of different data messages.
in a particular direction, which leads to increased sensitivity     The rest of the paper is organized as follows. In Sec. II,
in that direction and significantly reducing multi-path             resource allocation in wireless networks through utility
effects and cochannel interference (CCI). This allows               functions are proposed and proved to be optimal under
directional antennas to accomplish two objectives: (1) Power        certain conditions while In Sec. III, resource allocation in
saving: a smaller amount of power can be used to cover the          wireless networks through directional antennas Finally, the
                                                                    paper is concluded in Sec. IV.
34                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010


                                                                  2.1.1 Problem Statement and Definitions
2. Resource Allocation In Wireless Networks                       Suppose that there are n users served by a base station. Let
   Through Utility Functions                                      rtotal denote the total amount of radio resource available at
                                                                  the base station, and r i, the amount of resource to be
                                                                  allocated to user i. Users with the same kind of traffic may
In [4], a utility-based power control scheme with respect to      not feel the same way by given the same amount of resource
channel quality is proposed. In that scheme, users with           because the wireless channel quality for each user may not
higher SIR values have higher utilities, and thus are more        be identical. Let denote the channel quality 2 of user i, 0 ≤
likely to transmit packets. Therefore, the wireless medium            ≤ 1, and i = 1, 2, · · ·n. The smaller the value of the
can be better utilized and the transmission power can be          worse the channel quality. Given an amount of resource r i
conserved, which can adapt to channel conditions and              and channel quality qi, the amount of resource actually
guarantee the minimum utility requested by each user. In          beneficial to user i is given by θ i = · qi . Let T (i) denote the
[8-9], the authors design a utility-based fair allocation         type of traffic of user i. The utility function of user I is
scheme to ensure the same utility value for each user.            expressed by                         where        (.) is the utility
However, letting users with different traffic demands to          function of traffic T (i) and Ui(.) is the utility function for
achieve an identical level of satisfaction may not be an          the type of traffic described by UT(i)(.) but taking into
efficient way of using wireless resource. Worse, traffic          account the channel quality of user i. The marginal utility
which is difficult to be satisfied tends to consume most of
the system resource leading to another kind of unfairness. In     function of Ui(.) is                                    and that of


                                                                                                            and ∀ ≥ 0. An
[5], a utility-based scheduler together with a Forward Error            (.) is         (.). Our objective is to maximize
Correction (FEC) and an ARQ scheme is proposed. That                          subject to
work gives lagging users more resource and thus results in a      optimal allocation for n users with total available resource
similar performance level (i.e., fixed utility value) for each         is defined as follows. Note that the optimal allocation
user. The work in [13-14] targets at multi-hop wireless           may not be unique in the system.
networks Utility functions have also been widely used in
Internet pricing and congestion control [6]. The typical
approach is to set a price to radio resource and to allocate
tokens to users. The objective is then to maximize the
“social welfare” through a bidding process. These kinds of
bidding schemes, while useful for Internet pricing and
congestion control, may not be practical for wireless
networks. In wireless environments, the types of traffic, the
number of users, and channel conditions are all time-
                                                                  Figure 1. The utility functions of two types of traffic
varying. It would-be very expensive to implement a wireless
                                                                      • Definition 2.1: A resource allocation R+ = {r 1 ,r 2
bidding process because the users would have to keep
                                                                       ,∙∙∙,r n } for n users is an optimal allocation if for all
exchanging control messages for real-time bidding, and the
                                                                       feasible allocations Ra= {r ’1,r ’2 ,∙∙∙,r ’n},U(R+ ) ≥
control protocols of the wireless system would also have to
                                                                       U(Ra ),where       U(R+ ) =                      and U(Ra )=
be modified to accommodate this process. Finally, the
complexity and efficiency of wireless bidding have not been                          .
analyzed. It is hard to estimate the time elapsed to achieve          • Definition 2.2: R = {r 1, r 2 ,∙∙∙, r n } is a full allocation
the Nash equilibrium. We consider two common types of                  if
traffic: hard QoS and best effort traffic, and propose three
allocation algorithms1 for these two types of traffic, namely,    2.1.2 HQ Allocation for Hard QoS Traffic
1) the HQ allocation for hard-QoS traffic, 2) the elastic         Suppose that there are n users in the queue, all with hard
allocation for best effort traffic, and 3) the mixed allocation   QoS traffic. Let               denote the residual resource in the
for the co-existence of both types of traffic. These three        system. The resource allocation algorithm designed for users
allocation schemes are all polynomial time solutions and          whose utility functions are all unit-step functions is referred
proved to be optimal under certain conditions, and in any         to as the HQ allocation and the output is denoted by RHQ =
case, the difference between the total utilities obtained by      {r 1, r 2 ,∙∙∙, r n }. Given the total available resource in the
our solutions and the optimal utility are bounded. The            system               , the channel quality and utility function
performance of the proposed schemes is validated via                      (.) for all users i, RHQ can be obtained as follows.
simulations. The results show that optimal wireless resource      1) Initialize ← 0, i = 1, 2, · · · , n;          ←
allocation depends on the traffic demand, total available
                                                                  2) Sort all users i in the queue in descending order of
resource, and wireless channel quality, rather than solely
dependent on channel quality or traffic type as assumed in        .
most existing work.                                               3) Repeat Steps (4) and (5) until the queue becomes empty.
                                                                  4) Pop out user i who is now at the head of the queue.
2.1 Resource Allocation Using Hard Qos, Best, And                 5) If         >        , then    =      , ;         =           −
Mixed Traffic In Wireless Network Through Utility
Based Functions                                                     .
                                                                       (IJCNS) International Journal of Computer and Network Security, 35
                                                                                                                  Vol. 2, No. 3, March 2010

The utility function for user i with hard QoS traffic is                   4) If the queue is not empty, then pop out the QoS user i at
described by                                     where                     the head of the queue; else go to Step (8).
is a unit-step function, is the channel quality of this user,              5) For the popped user i: if         ≥   ,   then   =      ;else
Mi is the kind of QoS traffic,    is the preferred amount of
                                                                             = 0; go to Step (4).
resource to be allocated.
                                                                           6) Δ =         −                 .
                                                                           7) If (Δ > 0), then         =     − ; go to Step (4); else
                                                                           = 0; go to Step (8);
                                                                           8) If    ( ) < (0), then =              ( ));else = 0.
                                                                           The allocation rule of this mixed allocation is to: 1) allocate
                                                                           resource to the first k QoS users at the sorted queue, and 2)
                                                                           then allocate the residual bandwidth (i.e.,       −        ) to
                                                                           all best effort users based on the elastic allocation. The
                                                                           value of k is determined based on the requirement that there
                                                                           is sufficient resource for this QoS user and the utility gain
Figure 2. Allocation ordering of k users in the HQ                         ΔUk is positive (i.e.,    − > 0) .
allocation.
                                                                           2.2 Resource Allocation Using Directional Antennas
2.1.3 . Elastic Allocation for Best Effort Traffic                         Medium Access Protocols (MAC) protocols for directional
We next consider the best effort traffic. The resource                     antenna systems can be classified into two categories: on
allocation algorithm for users with concave utility functions              demand and scheduled. In the on-demand scheme nodes
        is referred to as the elastic allocation and the output is         must exchange short signals to establish a communication
denoted by                  = {r 1, r 2 ,∙∙∙, r n }. Given the total       session.
available resource              , the channel quality qi and
marginal utility function              for each user i,            can
be obtained as follows.
1) For each user i, derive               , the inverted function of
      .
2) Derive             , by summing up                , over all users i,
i.e,          =             .
3) Find          , the inverted function of             .
4) Find        , which is equal to               ).
5) For all , i = 1, 2, · · · , n,if                 < (0), then =
            ; else = 0.
                                                                           Figure 3. An example of mixed allocation
The allocation rule of this scheme is to 1) derive the
aggregated utility function from the inverse functions of all              Data message transmission is done using the
users, 2) calculate the allocated marginal utility from the                omnidirectional mode, and reception is done using the
aggregated utility function, and 3) determine                 for each     directional mode. Directional antennas are used to transmit
user.                                                                      request-to-send (RTS) and receive clear-to-send (CTS)
                                                                           signals while the receiver antenna remains in the
2.1.4 Mixture of Hard QoS and Best Effort Traffic                          omnidirectional mode during this exchange. In [13],
Finally, we consider the co-existence of QoS and best effort               communicating pairs are set up using the multi-beam
traffic in the system, which is referred to as mixed                       forming ability of directional antennas. through cashing of
allocation and the output of which is denoted by               = {r 1 ,    the angle of arrival (AoA), Takai [14] avoided the use of the
r 2 , ∙∙∙ , r n }.                                                         omnidirectional mode, which is only used when the AoA
Let            denote the amount of residual resource to be given to       information is not available.
best effort traffic, and ΔUi, the utility gain by allocating
resource to QoS user i. Other notations remain the same as
in the HQ and the elastic allocations. Given the total
available resource              , the channel quality            and
marginal utility function              for each user i,      can be
obtained as follows.
1) Initialize ri ← 0, i = 1, 2, · · · , n ; and     ←        .             Figure 4 . (a) Transmission pattern of an omnidirectional
2) Sort all QoS users i in descending order of                   , and     antenna. (b) Transmission pattern of a directional antenna.
store them in the queue.
                                                                           2.2.1 Directional Antenna System Assumptions And
3) For each best effort user j, derive        from                 ;
                                                                           Definitions
Find          by summing up            over all users j;                   In this paper, it is assumed that each node in the network is
Find       , the inverted function of        .                             equipped with an MBAA-antenna system. Each antenna is
                                                                           capable of transmitting or receiving using any one of k
36                                                           (IJCNS) International Journal of Computer and Network Security,
                                                                                                        Vol. 2, No. 3, March 2010

beams which can be directed towards the node with which          directional antenna systems. Each node keeps track of the
communication is desired. In order for node x to transmit to     slot status information of its 1-hop and 2-hop neighbors.
a node y, node x directs one of its k antennas to transmit in    This is necessary in order to allocate slots in a way that does
the direction of node y, and node y in turn directs one of its   not violate the slot allocation conditions imposed by the
k antennas to receive from the direction of node x.              nature of the wireless medium and to take the hidden and
Radio signals transmitted by omnidirectional antennas            exposed terminal problems into consideration.
propagate equally in all directions. On the other hand,
directional antennas install multiple antenna elements so        2.2.3 Slot Allocation Conditions For Directional
that individual omnidirectional RF radiations from these         Antennas
antenna elements interfere with each other in a constructive     A time slot t is considered free to be allocated to send data
or destructive manner.                                           from a node x to a node y if the following conditions are
                                                                 true:
                                                                 1) Slot t is not scheduled to receive in node x or scheduled to
                                                                 send in node y, by any of the antennas of either node (i.e.
                                                                 antennas of x must not be scheduled to receive and antennas
                                                                 of y must not be scheduled to transmit, in slot t).
                                                                 2) Slot t is not scheduled for receiving in any node z, that is
                                                                 a 1-hop neighbor of x, from node x where y and z are not in
                                                                 the same angular direction with respect to x (i.e.       ∩
Figure 5. Transmission pattern of an MBAA antenna                ≠ ).
system with k=4 beams. Each of the k beams can be oriented       3) Slot t is not scheduled for receiving in node y from any
in a different desired direction. The figure shows: (a) Beams    node z, that is a 1-hop neighbor of x, where x and z are in
in transmission mode. (b) Beams in reception mode.               the same angular direction with respect to y (i.e.     ∩      ≠
                                                                   ).
This causes the signal strength to increase in one or multiple   4) Slot t is not scheduled for communication (receiving or
directions. The increase of the signal strength in a desired     transmitting) between two nodes z and w, that are 1-hop
direction and the lack of it in other directions are modeled     neighbors of x, where w and y are in the same angular
as a lobe. The angle of the directions, relative to the center   direction with respect to z (i.e.    ∩      ≠ ), and x and z
of the antenna pattern, where the radiated power drops to        are in the same angular direction with respect to w (i.e.
one-half the maximum value of the lobe is defined as the         ∩       ≠ ).
antenna beamwidth, denoted by β [9]. With the                    In Figure6, which illustrates allocation rule 2, node x cannot
advancement of silicon and DSP technologies, DSP modules         transmit to node y using slot t, because it is already using
in directional antenna systems can form several antenna          slot t to transmit to node z, which is in the same angular
patterns in different desired directions (for transmission or    direction as node y. In Figure7, which illustrates allocation
reception) simultaneously.        Figure 4(a) shows the          rule 3, node x cannot allocate slot t for sending to node y
transmission patterns of an omnidirectional antenna. Figure      because slot t is already scheduled for sending from node z,
4(b) shows the transmission pattern of a directional antenna     that is a 1-hop neighbor of x, and       ∩      ≠ . In Figure
.In this paper, it is assumed that an MBAA antenna system        9, which illustrates allocation rule 4, slot t cannot be
is capable of detecting the precise angular position of a        allocated to send from x to y because it is already scheduled
single source for locating and tracking neighbor nodes.          for communication between two nodes z and w, that are 1-
Figure 5 shows a node equipped with an MBAA antenna              hop neighbors of x, where        ∩      ≠ and        ∩    ≠
array with k=4 beams. Each of the k beams is able to be          . When a node S wants to send data to a node D, with a
oriented in a different desired direction. Figure 5(a) shows     bandwidth requirement of b slots, it initiates the QoS path
the antenna array in the transmission mode, and Figure 5(b)      discovery process
shows the antenna array in the reception mode.

2.2.2 Protocols For Directional Antennas
The networking environment that is assumed in this paper is
TDMA where a single channel is used to communicate                Figure 6. Illustration of allocation rule 2.
between nodes. The TDMA frame is composed of a control
phase and a data phase [17]. Each node in the network has a
designated control time slot, which it uses to transmit its
control information. However, the different nodes in the         Figure 7. Illustration of allocation rule 3.
network must compete for the use of the data time slots in
the data phase of the frame. In this section, the slot
allocation rules for the TDMA directional antenna
environment are presented. The hidden and exposed
terminal problems make each node’s allocation of slots           Figure 8. Illustration of allocation rule 4.
dependent on its 1-hop and 2-hop neighbor’s current use of
                                                                 2.2.4 The Qos Path Reservation Algorithm
that slot. The model used in this protocol is similar to that
used in [11] and [12], but includes modifications to support
                                                                  (IJCNS) International Journal of Computer and Network Security, 37
                                                                                                             Vol. 2, No. 3, March 2010

 Node S determines if enough slots are available to send              the schemes proposed in [18-19] are the examples of the
from itself to at least one of its 1-hop neighbors. If that is        ”fairness” scheme (i.e., α = − 1), and the GR+ scheme in [9]
the case, it broadcasts a QREQ(S, D, id, b, x, PATH, NH) to           is an example of the ”throughput” scheme. Fig. 8(a)
all of its neighbors. The message contains the following              compares the proposed HQ allocation with different
fields:                                                               allocation schemes, and Fig. 9(b) compares the proposed
• S, D and id: IDs of the source, destination and the session.        elastic allocation with different allocation schemes. Note
The (S,D, id) triple is therefore unique for every QREQ               that the axis of       in Fig. 9(b) is in the logarithmic scale.
message and is used to prevent looping.                               Theresults show that the ”throughput-first” scheme has a
• b: Number of slots required.                                        higher total utility when          is small, but the ”fixed”
• x: The node ID of the host forwarding this message.                 allocation one is closer to the proposed scheme as
• PATH: A list of the form ((                                 ). It         increases. Finally, when          becomes very large, the
contains the accumulated list of hosts and time slots, which          ”fairness-first” scheme can achieve the highest utility. In
have been allocated by this QREQ message so far?           is the     order to verify, and analyze the performance of the
ith host in the path, and is the list of slots used by           to   directional antennas (protocols presented in paper),
send to        . Each of the elements of       contains the slot      simulation      experiments     were      conducted.    Several
number that would be used, along with the corresponding               performance measures were computed as the traffic rate
the set of angular groups,             , which represents the         (messages/second) is varied. The measured parameters are
direction in which the sending antenna of host i must be              the overall percentage of packets received successfully, the
pointed, during that slot, to send data to host i + 1.                average number of requests per successful acquisition of
• NH: A list of the form ((                             ). It         QoS path , The average number of requests per session, and
contains the next hop information. If node x is forwarding            the average QoS path acquisition time
this QREQ message, then NH contains a list of the next hop
host candidates. The couple              is the ID of the host,
which can be a next hop in the path, along with a list of the
slots, which can be used to send data from x to            is a
list of the slots to be used to send from host i to host i+1
along with the angular group for each slot.       has the same
format as in PATH.

3. Performance Analysis
                                                                                                    (a)

In this paper we have gone through two methods of resource
allocation i.e resource allocation through utility functions
and the other using directional antennas. Now since both
methods are for resource allocation it is necessary to
analyze the performance of both the above given methods,
analyzing them leads to the comparison of the the resource
allocation method . In this section, we conduct simulations
to evaluate the performance of our allocation algorithms.                                           (b)
firstly analyzing resource allocation in wireless network             Figure 9. Utility comparison with different resource
through utility function. So we consider QoS traffic, best            allocation schemes a)Qos traffic b)best effort traffic
effort traffic, and the con-existence of both. The simulation
parameters are described as follows. For QoS traffic, the              Simulation results clearly demonstrate the increased
utility function is a unit-step function with        = 10 and UM      efficiency and performance of the network as the number of
= 1, i.e., UQoS(r) = fu(r − 10); for best effort traffic, UBE(r) =    directional antennas increases. As was indicated earlier, this
1 − er/10. The value of qi is randomly generated by a uniform         increased performance is due to the considerable increase in
distribution over [0, 1]. We then measure the distributions           spatial reuse and the ability for each node to simultaneously
of and θ i under different values of           .                      send or receive data in different directions. This functionally
In Fig. 9, different resource allocation schemes are                  increases the effective number data slots by a multiple of the
compared with the proposed allocation schemes. The                    number of antennas (or directions) used. This effect
comparison is based on the scheme proposed in [10], which             significantly improves performance. As the data shows, the
allocates radio resource proportionally based on factor               increase in performance, or speed-up factor, when the
Depending on the setting of the value α, the system can be            number of antenna is increased by a factor of 2 (i.e. doubled
tuned to work with different performance metrics. The curve           from 1 to 2, and then from 2 to 4) is significant (speed up
denoted ”throughput” is for α = 1, which gives more                   factor > 1).As expected, however, it still below a theoretical
resources to the users in better channel conditions, thereby          speed-up factor of 2. For the first set of experiments for
leading to a larger system throughput. The curve denoted              example, the data shows that that ratio of the overall
”fairness” is for α = − 1, giving all users an identical value        average percentage (average for all data traffic rates) of
of θi = · qi. The curve denoted ”fixed” is for α = 0, which           successful packets of the two-antenna case to the one-
provides the same amount of resource to all users. Note that          antenna case is 1.61, which is > 1 and < 2. The ratio for the
38                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010

four-antenna case to the two antenna case is 1.84, which is       paths due to the extended range of directional antennas
also > 1 and < 2, and the ratio for the four-antenna case to      using the same total transmission power compared to the
the one-antenna case is 2.95 which are < 4. This is to be         omnidirectional case. In turn this results in reduced end-to-
expected from the theory of parallel and distributed systems      end delay. The simulation results clearly show a significant
because the actual speed-up factor is always below the ratio      gain in performance with an increase in the number of
of the number of parallel units, or antennas.                     successfully received packets, as well as a decrease in the
                                                                  QoS path acquisition time. However, as expected, this gain
                                                                  in performance is still below the theoretical speed-up factor.
4. Conclusion                                                     In the future, we intend to improve this protocol through the
                                                                  employment of additional optimization techniques. T
                                                                  his leads us to conclude that existing channel-dependent-
In this paper, we study about two basic method of allocating      only resource schemes and schedulers cannot provide
resources in wireless networks the first one Data message         optimal allocation in wireless networks. So In addition, we
length:100MB was utility-based maximization for resource          intend to perform more simulations in order to further study,
allocation in infrastructure-based wireless networks.             analyze and improve the performance of the protocol under
                                                                  different network environments including different mobility
                                                                  rates, and traffic conditions.

                                                                  References
                                                                  [1] D.Angelini and M. Zorzi, “On the throughput and
                                                                       fairness      performance of heterogeneous downlink
                                                                       packet traffic in a locally centralized CDMA/TDD
                                                                       system,” in Proc. IEEE VTC-Fall 2002.
                              (a)                                 [2] Furuskar et al., “Performance of WCDMA high speed
                                                                       Packet data,” in Proc. IEEE VTC 2002-Spring.
                                                                  [3] Y. Cao, V. O. K. Li, and Z. Cao, “Scheduling delay-
                                                                       sensitive and besteffort traffic in wireless networks,”
                                                                       in Proc. IEEE ICC 2003.
                                                                  [4] M. Xiao, N. B. Shroff, and E. K. P. Chong, “A utility-
                                                                       based power control scheme in wireless cellular
                                                                       systems,” IEEE/ACM Trans. Netw., vol. 11, no. 2,
                                                                       2003.
                              (b)                                 [5] X. Gao, T. Nandagopal, and V. Bharghavan,
               Figure 10. Simulation results.                          “Achieving application level fairness through utility-
                                                                       based wireless fair scheduling,” in Proc. IEEE
  In this we develop some essential theorems for utility-              Globecom 2001.
based resource management. Then, three polynomial time            [6] F. P. Kelly, “Charging and rate control for elastic
resource allocation algorithms are proposed for two types of           traffic,” European Trans. Telecommun., Jan. 1997.
utility functions. We prove that, in any case, the difference     [7] V. A. Siris, B. Briscoe, and D. Songhurst, “Economic
between the total utilities obtained by our proposed                   models for resource control in wireless networks,” in
solutions and the optimal utility is bounded, and under                Proc. IEEE PIMRC 2002, Lisbon, Portugal, Sept. 2002.
certain conditions, all these three schemes can achieve the       [8] L. Chen, S. H. Low, and J. C. Doyle, “Joint congestion
maximum total utility (i.e., optimal). From the simulation             control and media access control design for wireless ad
results, we find that different types of traffic require               hoc networks,” in Proc. IEEE Infocom, Miami, FL,
different kinds of schemes to achieve optimal allocation. In           March 2005.
addition, when         is small, the system tends to allocate     [9] L. Bao and J. J. Garcia-Luna-Aceves. Transmission
more resources to the users in better channel conditions, i.e.,        scheduling in ad hoc networks with directional
”throughput-oriented;” however, when         is abundant, the          antennas. Proc. of the 8th annual international
system becomes ”fairness-oriented,” meaning that even with             conference on mobile computing and networking, pages
the same traffic, the preference tendency between                      48–58, September 2002.
throughput and fairness can still differ. The second one was      [10] Q. Dai and J. Wu. Construction of power efficient
a protocol for TDMA-based bandwidth reservation for QoS                routing tree for adhoc wireless networks using
routing in MANETs using directional antennas The protocol              directional antenna. Distributed Computing Systems
takes advantage of the significant increase in spacial reuse           Workshops. Proceedings. 24th International
provided by the directional antenna environment, which                 Conference on, pages 718–722, March 2004.
drastically increases the efficiency of communication in          [11]       Jawhar and J. Wu. A race-free bandwidth
MANETs. This is due to the reduction in signal                         reservation     protocol for QoS routing in mobile ad
interference, and the amount of power necessary to establish           hoc networks. Proc. of the 37th Annual Hawaii
and maintain communication sessions. Additionally, this                International Conference on System Sciences
protocol provides for a relatively smaller hop count for QoS           (HICSS’04), IEEE Computer Society, 9, January 2004.
                                                                  (IJCNS) International Journal of Computer and Network Security, 39
                                                                                                             Vol. 2, No. 3, March 2010

[12] W.-H. Liao, Y.-C. Tseng, and K.-P. Shih. A TDMA-                  Algorithms, Compiler Design books for the technical students of
     based bandwidth reservation protocol for QoS routing              graduation and postgraduation.He has published various research
     in a wireless mobile ad hoc network. Communications,              papers in National and International journals. He has also
     ICC 2002. IEEE International Conference on,                       attended one faculty development program organized by Oracle
                                                                       Mumbai on Introduction to Oracle 9i SQL and DBA
     5:3186–3190, 2002.
                                                                       Fundamental.
[13] S.; You J.; Hiromoto R.E.; Nasipuri, A.; Ye. A MAC
     protocol for mobile ad hoc networks using directional                             Vidushi Gupta received her    B.tech (C.S)
     antennas. Wireless Communications and Networking                                  degree from Uttar Pradesh Technical
     Conference, 2000. WCNC. 2000 IEEE, 3(23-28):1214–                                 University, Lucknow.She is also pursuing
     1219, September 2000.                                                             M.tech from Karnataka University, She is
[14] M. Takai, J. Martin, and R. Bagrodia. Directional                                 working as Lecturer ( CS/IT department) in
     virtual carrier sensing for directional antennas in                               SRMSWCET, and Bareilly She has also
     mobile ad hoc networks. In Proc. ACM International                attended one faculty development program based on the
                                                                       “Research Methodologies”.
     Symposium on Mobile Ad Hoc Networking and
     Computing (MOBIHOC), Lausanne, Switzerland, June
     2002.
[15] J. Ward and R.T.Jr. Compton. High throughput slotted
     aloha packet radio networks with adaptive arrays.
     Communications, IEEE Transactions on, 41(3):460–
     470, March 1993.
[16] J. Zander. Slotted aloha multihop packet radio networks
     with directional antennas. Electronics Letters,
     26(25):2098–2100, December 1990.
[17] C. R. Lin and J.-S. Liu. QoS routing in ad hoc wireless
     networks. IEEE Journal on selected areas in
     communications, 17(8):1426–1438, August 1999.
[18] Jawhar and J. Wu. Qos support in TDMA-based mobile
     ad hoc networks. The Journal of Computer Science and
     Technology (JCST), Springer, 20(6):797–810,
     November 2005.
[19] Jawhar and J. Wu. Race-free resource allocation for
     QoS support in wireless networks. Ad Hoc and Sensor
     Wireless Networks: An International Journal, 1(3):179–
     206, May 2005

Authors Profile
                   Dr. Yahpal Singh is a Reader and HOD (CS)
                   in BIET, Jhansi (U.P.). He obtained Ph.D.
                   degree    in     Computer      Science from
                   Bundelkhand University, Jhansi. He has
                   experience of teaching in various courses at
                   undergraduate and postgraduate level since
                   1999. His areas of interest are Computer
                   Network, OOPS, DBMS. He has authored
 many popular books of Computer Science for graduate and
 postgraduate level. He has attended many national and
 international repute seminars and conferences. He has also
 authored many research papers of international repute.

                     Manish Varshney received his M.Sc (C.S)
                    degree from Dr. B.R.A. University, Agra,
                    M.Tech. (IT) from Allahabad University and
                    Pursuing PhD in Computer Science. He is
                    working as a HOD (CS/IT) in SRMSWCET
                    Bareilly. He has been teaching various
                    subjects of computer science for more than
                    half a decade. He is known for his skills at
 bringing advanced computer topics down to the novice's level. He
 has experience of industry as well as teaching various courses. He
 has authored various popular books such as Data Structure,
 Database Management System, Design and Implementation of
40                                                               (IJCNS) International Journal of Computer and Network Security,
                                                                                                            Vol. 2, No. 3, March 2010


   Comparative Analysis of Wireless MAC Protocol
  for Collision Detection and Collision Avoidance in
               Mobile Ad Hoc Networks
                                              D.Sivaganesan1, Dr.R.Venkatesan2
                                          1
                                         Department of Computer Science and Engineering,
                                 Karpagam College of Engineering, Coimbatore-32, TamilNadu, India.
                                                     dsg_pol@rediffmail.com
                                                2
                                                  Department of Information Technology.
                                        PSG College of Technology, Coimbatore, TamilNadu, India.


                                                                     collision detection requires a node to transmit and listen at
Abstract:    Packet collisions at the Medium Access Control
(MAC) layer in distributed wireless networks use a combination       the same time for terminating a possible collision. Although
of carrier sensing and collision avoidance. When the collision       CSMA/CD have been proven to be very successful in wired
avoidance strategy fails, such schemes cannot detect collisions      LANs, it cannot be directly employed in wireless networks
and corrupted data frames are still transmitted in their entirety,   because of two problems [21]. The first is the hidden
thereby wasting the channel bandwidth and significantly              terminal problem [3]. Two mutually hidden terminals are
reducing the network throughput. To address this problem, this       two nodes that cannot sense each other (due to the distance
paper compares the wireless MAC protocol CSMA, MACA and
                                                                     or obstacles between them) but can still interfere with each
IEEE802.11 capable of collision detection and collision
avoidance. The performance of the MAC protocol has been              other at a receiver. With hidden terminals, carrier sense
investigated using extensive analysis and simulations. Our           alone cannot effectively avoid collisions. The other problem
results shows that as compared with CSMA, MACA MAC                   for CSMA/ CD in wireless networks is that, in the same
protocols, the protocol IEEE802.11 has significant performance       wireless channel, the outgoing signal can easily overwhelm
gains in terms of node throughput and reduce the network             the incoming signal due to high signal attenuation in
collisions.
                                                                     wireless channels. This problem makes it difficult for a
  Keywords: MAC, collision detection, collision avoidance,           sender to directly detect collisions in a wireless channel.
CSMA, CSMA/CD, MACA.                                                 Some existing MAC protocols [5],[6],[7],[8] depend on in-
                                                                     band control frames for exploring the possible future
1. Introduction                                                      channel condition for a data frame and also for reserving the
Distributed Medium Access Control (MAC) protocols such               medium for the data frame. However, when the collision
as the IEEE 802.11 Distributed Coordination function                 avoidance strategy fails, a corrupted data frame is still fully
(DCF) are widely used in computer networks to allow users            transmitted. Another category of protocols [3],[9],[10]uses
to statistically share a common channel for their data               one or more out-of-hand control channels to avoid
transmissions. In wireless networks, a critical drawback of          collisions, These protocols are more effective in dealing
distributed MAC protocols is the inability of nodes to detect        with hidden terminals and thus, reduce the probability of
collisions while they are transmitting. As a result,                 collisions in a network. However, they are incapable of
bandwidth is wasted in transmitting corrupted packets, and           detecting collisions either, and if the collision prevention
the achieved throughput degrades. This situation is                  strategies of these protocols fail, then the collided data
exacerbated as the number of nodes in the network                    frames are still transmitted in their entirety.
increases, since, now, the rate of collisions increases. To
address this issue, this paper presents MAC protocol capable         2. Carrier Sensing and Collision Avoidance
of detecting collisions in wireless networks which                   The most widely used mechanism to avoid collisions in the
outperforms existing MAC protocols. The Aloha protocol               contention-based MAC is probably ‘‘carrier sensing” [11].
[1] was the first MAC protocol proposed for packet radio             Which is used in both wired and wireless networks? The
networks. With pure Aloha, a node sends out a packet                 drawbacks associated with this mechanism that motivates
immediately upon its arrival at the MAC sub layer and a              the development of a scheme with collision detection. With
collided packet is retransmitted with a probability P                carrier sensing, a node listens before it transmits. If the
immediately or after each packet transmission time. Carrier          medium is busy, then the node defers its transmission. After
Sense Multiple Access with Collision Detection                       the medium has been sensed idle for a specified amount of
(CSMA/CD) [2] employs two mechanisms to enhance the                  time, the node usually takes a random back off before
medium utilization in aired local area networks                      transmitting its frame. The random back off is for avoiding
(LANs):“carrier sense” and “collision detection.” Carrier            collisions with other nodes that are also contending for the
sense requires a node to listen before transmitting and              medium. Besides the “physical” carrier sensing technique
                                                               (IJCNS) International Journal of Computer and Network Security, 41
                                                                                                          Vol. 2, No. 3, March 2010

introduced above, the IEEE 802.11 DCF and MACA                     3. Spectrum Reuse                 and       the     Capture
(Multiple Access Collision Avoidance) also employs a                  Phenomenon
technique called “virtual” carrier sensing. The virtual
carrier sense technique relies on in-band control frames to        The radio spectrum needs to be spatially reused in multihop
deal with hidden terminals. Before sending a data frame in         wireless network for improving network through-put. Better
to the idle medium after proper deferrals and back offs, a         spectrum reuse allows more transmissions to go on
source sends out a Request to Send (RTS) frame to contact          simultaneously in the network without collisions. A
the receiver and reserve the medium a round the source, If         phenomenon closely related to spectrum reuse is “capture”
the receiver receives the RTS frame and its channel is             which implies that, when two frames collide at a receiver in
determined to be clear, the receiver sends out a Clear to          a wireless network, one of the frames may still be correctly
Send (CTS) frame to respond to the sender and reserve the          decoded if the received power of the frame is higher than
medium too. The data transmission then begins if the               that of the other by a threshold. However, as we now show
handshake and medium reservation process succeeds.                 the capture effect is not sufficient to eliminate collisions and
Several situations may cause difficulties to the virtual carrier   collision detection is required to prevent bandwidth wastage
sensing technique. One of them is the ‘chained’ hidden             on corrupted frames. To illustrate the possibility of
terminal phenomenon. Basically, in a data transaction in the       collisions in the presence of capture effect, two scenarios are
MAC layer, the CTS frame sent by a receiver to suppress the        shown in Figure. 2a and 2b (the nodes are in a line for easy
hidden terminals of the initiating sender may be lost at the       demonstration). In the case, nodes A and D are the initiating
receiver’s neighbors due to the receiver’s own hidden              senders, whereas nodes B and C are their receivers,
terminals. In such a case, some hidden terminals of the            respectively. In the second case, nodes B and C are the
initiating sender may not be suppressed. An example is             senders and nodes A and D are their receivers, respectively.
shown in Figure 1, where node A is the initiating sender           In these two cases, assuming same transmission power
and node B is the receiver, The CTS frame generated by             levels and ambient noise, captures for the data frames may
node B is corrupted at node C (a hidden terminal of node A)        easily happen at receivers because the senders are much
by the signals of node D, which is a hidden terminal of node       closer to their receivers than the interference sources.
B. Node mobility may also limit the effectiveness of the           However, for combating high link error rates,
virtual carrier sensing technique with a small probability.        acknowledgments for data frames are widely used in the
With virtual carrier sensing, only nodes that have receive         MAC sub layer of wireless networks. Therefore, interference
the medium reservation message know when to defer.                 may come not only from the initiating senders, but also from
Therefore, when a node newly moves into a neighborhood             their receivers. In both cases shown in Figure. 2b, the two
and misses the preceding reservation information, it               senders have to finish their transmissions almost at the same
becomes an unsuppressed hidden terminal to an ongoing              time for all the data and acknowledgment frames to be
data transaction, another phenomenon that may impact               received without collisions. For example, in case A shown
virtual carrier sensing is that the interference range of a        in Figure. 2a, if node A finishes its data transmission earlier
node can larger than its data transmission range[12].              than node D, then node B will send its acknowledgment
Therefore, even if a node is out of the range of another node      frame to node A while node C is still receiving the data
for successfully receiving its CTS frame, the node may still       frame from node D. A collision may therefore easily occur at
interfere with the other node’s data reception. A more             node C. Similarly, if node D finishes is transmission earlier,
effective way to suppress hidden terminals is to use an out-       then node B may easily have a collision. The same thing is
of-band control channel. With a single data channel, control       true for case B. The corrupted frame, however, be an
information cannot be delivered when the data frame is in          acknowledgment instead of a data frame. In reality, two
transmission. With an additional control channel, however,         nodes may not finish their transmissions the same time,
control signals can always be present whenever necessary,          since their frames may have different sizes and their
which improves the ability of hidden terminal suppression.         transmissions may begin at different times. Thus, collision
                                                                   detection is important in these cases to terminate the
                                                                   colliding transmissions.




            Figure 1. Hidden Terminal Problem

                                                                              Figure 2 a. Exposed Terminal Problem
42                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010

                                                                  Once the node has finished transmitting the frame header in
                                                                  the data channel, it expects the intended receiver node B to
Case A                                                            have received the information and reply with a CTS pulse in
                                                                  the control channel. The CTS pulse is transmitted by node B
     A                                           B                during a pause in the pulses being sent by node A in the
                                                                  control channel. If a node A does not obtain the expected
                                                                  CTS pulse in the following pause period after the frame
                                                                  header is transmitted then node A aborts its transmission in
                                                                  both channels If node A obtains the expected CTS pulse.
     C                                           D                Then it keeps transmitting. Node A, however may still abort
Case B                                                            its transmissions after obtaining the expected CTS pulse if it
                                                                  detects a pulse of another node in one of its pulse pauses
                                                                  after, which indicates a colliding situation. If the node
         C                                     D                  aborts its transmissions due to the lack of the expected CTS
                                                                  pulse or the detection of a pulse of another node, then it
                                                                  doubles its contention window and then returns to monitor
                                                                  the control channel. After node A fully transmits the packet,
                                                                  it expects an acknowledgment from the receiver. If the node
     A                                         B
                                                                  does not obtain the expected acknowledgment, then it
                                                                  doubles its contention window and starts to monitor the
             Figure 2 b. Collision involving capture              control channel again to look for a retransmission
                                                                  opportunity. The whole process repeats until either node A
4. The MAC Protocol IEEE 802.11                                   obtains an acknowledgment for the packet or the retry limit
                                                                  is reached. The node discards the packet in the latter case
  3.6    IEEE 802.11-Carrier Sensing and Collision                and resets its contention window to the minimum size in
         Avoidance                                                both cases. The above description is for the case of a unicast
The MAC protocol in this paper assumes that each node has         packet. In the case of a broadcast packet, the proposed
the ability to simultaneously transmit on two channels, the       protocol uses the basic CSMA protocol as in the IEEE
control and data channels, with two antennas and, their           802.11 DCF. Figure 3. Shows the RTS / CTS dialogue.
associated communication circuitry. The control channel
has a much smaller bandwidth as compared to the data
channel and is used for transmitting medium reservation
related signals, whereas the data channel is for transmitting
the data and acknowledgments. Instead of relying on bit-
based frames, the control channel employs pulses to deliver
control information. The pulses in the control channel are
single-frequency waves with random length pauses. In the
proposed protocol, pulses only appear in the control channel
and the control channel only carries pulses. When a node is
an active sender or receiver in the data channel, it monitors
the control channel all times, except when it itself is
transmitting in the control channel. If a node is transmitting
in the data channel but detects a pulse in the control
channel, then it aborts its transmissions. To describe the
operation of the protocol, we consider what happens when
the MAC sub layer at a node say node A, receives a packet
to transmit to node B. Before node A can transmit, it first
listens to the control channel to make sure that it is idle. If
the control channel is found idle for a period of time longer
than the maximum pause duration of a pulse, then node A
starts a random back off timer whose value is drawn from
the node’s contention window. If the node detects no pulse
before its back off timer expires, then it proceeds to transmit
the packet upon the expiration of its back off timer.
Otherwise, the node cancels It’s back off timer and keeps
monitoring the control channel. As soon as the back off
timer of node A expires, it starts to transmit pulses in the
control channel a long with the packet in the data channel.
                                                              (IJCNS) International Journal of Computer and Network Security, 43
                                                                                                         Vol. 2, No. 3, March 2010

                                                                  therefore terminate their transmissions, and the collision is
                                                                  resolved automatically. If only one of the two receivers can
                                                                  correctly read the frame header, then the sender of the other
                                                                  receiver will, in general, abort its transmissions due to the
                                                                  lack of a legitimate CTS pulse. The collision on is therefore
                                                                  also resolved in such a case. If both receivers can correctly
                                                                  read the frame headers, then each will send back a CTS
                                                                  pulse with the length specified in the MAC headers of their
                                                                  respectively received data frames. If the two initiating
                                                                  senders do not d raw the same CTS length, then the sender
                                                                  that draws the shorter one may not receive a legitimate CTS
                                                                  pulse and thus abort its transmissions. If both senders
                                                                  receive legitimate CTS pulses, then one sender will usually
                                                                  still need to abort its transmissions (since their
                                                                  acknowledgment frames may be interfered with or ca use
                                                                  interference). The collision detection mechanism starts to
                                                                  work in such a case. With pauses of random lengths, lie
                                                                  pulses of the two senders will desynchronize each other over
                                                                  time. A collision is therefore resolved. The above
                                                                  description of collision detection is not restricted to two
                                                                  transmitting nodes that are neighbors. Therefore, two nodes
                                                                  that are hidden terminals to each other still detect each other
                                                                  if they transmit at the same time.

                                                                  5. Results
                                                                  The comparison of MAC protocols CSMA, MACA and
                                                                  IEEE 802.11 has been simulated using Network Simulator
                                                                  Glomosim 2.03. In our simulation each node always has
                                                                  packets to send, and the destination of each packet is
                                                                  randomly drawn among the neighbors of the node. The
     Figure 3. RTS / CTS dialogue IEEE 802.11 MAC                 results for three wireless MAC protocols in terms of
                     HANDSHAKE                                    collision rate and throughput. Figure 3 a, 3 b. Shows the
                                                                  collision rate and throughput simulation graph for CSMA.
   3.7 Collision Avoidance and Detection                          Figure 4 a, 4 b. Shows the collision rate and throughput
This section further explains how the proposed MAC                simulation graph for MACA. Figure 5 a, 5 b. Shows the
protocol achieves collision avoidance and collision               collision rate and throughput simulation graph for IEEE
detection. As in the CSMA case, the protocol considers it a       802.11.The      protocol  IEEE802.11     has    significant
potential colliding situation when a transmitting node            performance gains in terms of node throughput and reduce
detects another transmitting node. For collision avoidance,       the network collisions.
the proposed protocol uses handshake and medium
reservation procedures like those used by traditional wireless
MAC protocols. The difference is that, in the proposed
protocol, these procedures are moved to the control channel
where CTS pulses are used for handshaking and the pulse
relay is used for medium reservation. When the collision
mechanism comes into play and this is the essential
difference between the proposed protocol and other wireless
MAC protocols. To understand how the proposed protocol
resolves collisions, we consider the case where two
neighboring nodes cause collisions. If two neighboring
nodes draw the same back off delays at a contention point
for medium access, then they start to transmit signals in the
data and control channels almost at the same time. If both
receivers of the two senders cannot correctly read the frame
headers due to the resulting collision (that is, the address or
another field in the header does not have a legitimate value),
then neither will send back a CTS pulse. Both senders will                  Figure 3 a. CSMA – Nodes Vs Collision
44                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                         Vol. 2, No. 3, March 2010




     Figure 3 b. CSMA – Nodes Vs Throughput               Figure 5 a. IEEE 802.11 – Nodes Vs Collision




      Figure 4 a. MACA – Nodes Vs Collision


                                                       Figure 5 b. IEEE 802.11 – Nodes Vs Throughput




                                                 6. Conclusion
                                                 From the simulation result, we conclude that, a better
                                                 behavior is obtained when using CSMA instead of MACA
                                                 because of the RTS / CTS messages. The use of RTS packets
                                                 whenever a source has a data packet to send without first
                                                 sensing the channel, results in an increase in packet
                                                 collisions and hence decreased throughput. The collision
                                                 avoidance mechanism incorporated into IEEE 802.11 for the
                                                 transmission of RTS packets aids in the reduction of the
                                                 number      of collision    improves    the     throughput.
                                                 Consequently, more data packets reach their destination. We
                                                 conclude that, the MAC protocol IEEE802.11 has
     Figure 4 b. MACA – Nodes Vs Throughput      significant performance gains in terms of node throughput
                                                 and reduces the network collisions in Mobile Ad Hoc
                                                 Networks.
                                                         (IJCNS) International Journal of Computer and Network Security, 45
                                                                                                    Vol. 2, No. 3, March 2010

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       Computer Comm.(SIGCOMM ‘94), Aug. 1994.                      Wireless Packet Networks,” Proc. IEEE INFOCOM.
[4]     Z.J. Haas and J. Deng, “Dual Busy Tone Multiple             Apr. 2001.
        Access (DBTMA)-A Multiple Access Control             [19]   P.Jacquet, P.Minet, P.Muhlethaler, and N. Rivierre,
        Scheme for Ad Hoc Networks,” IEEE Trans. Comm.,             ‘‘Priority and Collision Detection with Active
        vol. 50, pp. 975-985, June 2002.                            Signaling — The Channel Access Mechanism of
[5]    CL. Fullmer and J.J. Garcia-Luna-Aceves, “Solutions          HIPERLAN,’’ Wireless Personal Comm., vol. 4, pp.
       to Hidden Terminal Problems in Wireless Networks,”           11-25, Jan. 1997.
       Proc. ACM Ann. Conf Applications, Technologies,       [20]   Y.Thy and K. Chua, “A Capacity Analysis for the
       Architectures, and Protocols for Computer Comm.              IEEE 802.11 MAC Protocol, Wireless Networks,
       (SIGCOMM ‘97), Sept. 1997.                                   vol.7, no.2, pp.159-171, Mar, 2001.
[6]    C.L. Fullmer and J.J. Garcia-Luna-Aceves, “Floor      [21]   T. Rappaport, Wireless Communication: Principles
       Acquisition Multiple Access (FAMA) for Packet—               and Practice .PHI, 1999.
       Radio Networks,” Proc. ACM Ann, Conf
       Applications, Technologies, Architectures, and
       Protocols for Computer Comm.(SIGCOMM ‘95),            Authors Profile
       Sept. 1995.
[7]    F.A, Tobagi and L. Kleinrock, “Packet Switching in                   D.Sivaganesan received his BE degree in
       Radio Channels: Part I—The Hidden Terminal                           Computer Science Engineering in 1999,
       Problem in Carrier Sense Multiple Access and the                     M.Tech degree in Information Technology in
       Busy Tone Solution,” IEEE Trans. Comm.,vol. 23,                      2004.He is currently working as an Assistant
       pp. 1417-1433, 1975.                                                 Professor in the Department of CSE,
[8]    IEEE 802.11 Wireless Local Area Networks,                            Karpagam       College    of    Engineering,
       http://grouper.ieee.org/ groups/802/ 11/, 1999.                      Coimbatore.He is currently pursuing Ph.D.
[9]    C. Wu and V.O.K. Li, “Receiver-Initiated Busy-Tone    His research interest includes Mobile Computing, Mobile
       Multiple Access in Packet Radio Networks,” Proc.      Agents, Web Programming, Object Computing, Simulation
       ACM Ann. Conf Applications, Technologies,             and Microprocessors Based Systems. He has published 10
       Architectures, and Protocols for Computer Comm.       technical papers in International, National Conferences and
       (SIGCOMM ‘87), Aug. 1987.                             Journals.
[10]   Z.J. Haas and J. Deng, “Dual Busy Tone Multiple
        Access (DBTMA)-A Multiple Access Control                              Dr.R.Venkatesan received his PhD
        Scheme for Ad Hoc Networks,” IEEE Trans. Comm.,                       degree in Computer Science and
        vol. 50, pp. 975-985, June 2002.                                      Engineering. He is currently working as
[11]    L. Kleinrock and F.A. Tohagi, “Packet Switching in                    Professor and Head, Department of
        Radio Channels: Part I-Carrier Sense Multiple-                        Information Technology, PSG College of
        Access Modes and Their Throughput-Delay                               Technology, Coimbatore. His research
        Characteristics,” IEEE Trans. Comm., vol. 23, pp.                     interest   includes   Simulation    and
        1400-1416, 1975.                                     Modeling, Software Engineering, Software, Algorithm
[12]    K. Xu, M. Gerla, and S. Bae, “How Effective Is the   Design,   Database      Technology,   Software    Project
        IEEE 802.11 RTS/CTS Handshake in Ad Hoc              Management, Software Process Management. He has
        Networks?” Proc. IEEE Global Telecom, Conf.          published 25 technical papers in International, National
        (GLOBECOM ‘02), Nov. 2002.                           Conferences and Journals.
[13]    V. Kanodia, C. Li, A. Sabharwal, B. Sadeghi, and
        E.Knightly, “Distributed Multi-Hop Scheduling and
        Medium Access with Delay and Throughput
        Constraints,” Proc.ACM MobiCom, July 2001.
[14]    M.Barry, A.T.Campbell, A.Veres, “Distributed
        Control Algorithms for Service Differentiation in
        Wireless Packet Networks,” Proc. IEEE INFOCOM.
        Apr. 2001.
46                                                                     (IJCNS) International Journal of Computer and Network Security,
                                                                                                                  Vol. 2, No. 3, March 2010


Data Encryption technique using Location based key
    dependent Permutation and circular rotation
                                      Prasad Reddy. P.V.G.D*, K.R.Sudha2 , S.Krishna Rao3


                  *   Department of Computer Science and Systems Engineering, Andhra University, Visakhapatnam, India,
                                                      prasadreddy.vizag@gmail.com
                               2
                               Department of Electrical Engineering, Andhra University, Visakhapatnam, India,
                                                           arsudhaa@gmail.com
              3
              Department of Computer Science and Systems Engineering, Sir.C.R.Reddy College of Engineering, Eluru,
                                                  krishna_sala@yahoo.com


                                                                          transfer of credit card information, financial details and
Abstract: Wireless delivers data through public channels                  other important documents.
to unspecified clients in mobile distributed systems. In                  The basic goal of most cryptographic system is to transmit
such scenario, a need for Secure Communication arises.                    some data, termed the plaintext, in such a way that it cannot
Secure communication is possible through encryption of                    be decoded by unauthorized agents[5][6][7][8][9]. This is
data. A lot of encryption techniques have evolved over                    done by using a cryptographic key and algorithm to convert
time. However, most of the data encryption techniques are                 the plaintext into encrypted data or cipher text. Only
location-independent. Data encrypted with such                            authorized agents should be able to convert the cipher text
techniques can be decrypted anywhere. The encryption                      back to the plaintext.
technology cannot restrict the location of data decryption.               GPS-based encryption (or geo-encryption) is an innovative
GPS-based encryption (or geo-encryption) is an innovative                 technique that uses GPS-technology to encode location
technique that uses GPS-technology to encode location                     information into the encryption keys to provide location
information into the encryption keys to provide location                  based security[12][13]. GPS-based encryption adds another
based security. In this paper a new technique for Data                    layer of security on top of existing encryption methods by
encryption method using Location based key dependent                      restricting the decryption of a message to a particular
permutation and circular rotation is proposed for mobile                  location. It can be used with both fixed and mobile.
information system.                                                       The terms location-based encryption or geo-encryption are
                                                                          used to refer to any method of encryption in which the
Keywords: Location                 dependent,   circular   rotation,      encrypted information, called cipher text, can be decrypted
Permutation, GPS                                                          only at a specified location. If, someone attempts to decrypt
                                                                          the data at another location, the decryption process fails and
1.    Introduction                                                        reveals no details about the original plaintext information.
                                                                          The device performing the decryption determines its
The dominant trend in telecommunications in recent years                  location using some type of location sensor such as a GPS
is towards mobile communication. The next generation                      receiver. Location-based encryption can be used to ensure
network will extend today’s voice-only mobile networks to                 that data cannot be decrypted outside a particular facility -
multi-service networks, able to carry data and video services             for example, the headquarters of a government agency or
alongside the traditional voice services. Wireless                        corporation or an individual's office or home. Alternatively,
communication is the fastest growing segment of                           it may be used to confine access to a broad geographic
communication industry. Wireless became a commercial                      region. Time as well as space constraints can be placed on
success in early 1980’s with the introduction of cellular                 the decryption location.
                                                                          Adding security to transmissions uses location-based
systems. Today wireless has become a critical business tool
                                                                          encryption to limit the area inside which the intended
and a part of everyday life in most developed countries.
                                                                          recipient can decrypt messages. The latitude/longitude
Applications of wireless range from common appliances that
                                                                          coordinate of node B is used as the key for the data
are used everyday, such as cordless phones, pagers, to high               encryption in LDEA. When the target coordinate is
frequency applications such as cellular phones. The                       determined, using GPS receiver, for data encryption, the
widespread deployment of cellular phones based on the                     ciphertext can only be decrypted at the expected location. A
frequency reuse principle has clearly indicated the need for              toleration distance(TD) is designed to overcome the
mobility and convenience. The concept of mobility in                      inaccuracy and inconsistent problem of GPS receiver. The
application is not only limited to voice transfer over the                sender can also determine the TD and the receiver can
wireless media, but also data transfer in the form of text ,              decrypt the ciphertext within the range of TD. Denning’s
alpha numeric characters and images which include the                     model is effective when the sender of a message knows the
                                                               (IJCNS) International Journal of Computer and Network Security, 47
                                                                                                          Vol. 2, No. 3, March 2010

recipient’s location L and the time that the recipient will be            of the cipher text denoted by X consisting of the
there, and can be applied especially effectively in situations            binary bits of the form x11 x12 x13 ……xn 21…..xn28
where the recipient remains stationary in a well-known                  As the numbers in the first stage of the cipher text are
location.                                                               between 0 to 256 we have bits in every number. Here we
The mobile client transmits a target latitude/longitude                 have 8n 2 binary bits . Thus we divide the string of 8n 2
coordinate and an LDEA key is obtained for data encryption              binary bits into 8 substrings each having n 2 binary bits.
to information server. The client can only decrypt the                  1. The next stage of the cipher we transpose the
ciphertext when the coordinate acquired form GPS receiver                   matrix X consisting of 7 substrings and we
matches with the target coordinate. For improved security, a                interchange the first bit of the substring with k1th
random key (R-key) is incorporated in addition to the LDEA                  bit of the entire string. Similarly the second bit
key. In the present paper the objective is to modify the                    with k2th bit of the entire string. This process is
cipher by introducing the concept of key dependent circular                 continued for all the bits in X to get the final cipher
rotation. In this the bits are rotated depending upon the R-                text.
key after whitening with the LDEA key using the Exclusive               2. The next stage of the cipher we transpose the
– OR operation.                                                             matrix X consisting of 7 substrings. The bits in X
2.     Random     number              generator         using               are rotated left di times where di = ki mod n 2. In the
       quadruple vector                                                     decryption process the bits are rotated di bits right.
For the generation of the random numbers a quadruple
vector is used[7][10]. The quadruple vector T is generated                    3.1 Algorithm
for 44 values i.e for 0-255 ASCII values.
                                                                              Algorithm for Encryption:
T=[0 0 0 0 0 0 0 0 1 1 ……………… 0 0 0 0 1 1 1 1 2
                                                                        {
2……………………..                 0 1 2 3 0 1 2 3 0 1
                                                                        1.    read n,K,P,r
……………………..3]
                                                                        2.    For i=1 to n
The recurrence matrix[1][2][3] [4]
                                                                                       {
    0 1 0 
                                                                        3.    p=convert(P);
A = 1 1 0 
                                                                      4.    X=p LDEA key
    0 0 1 
                                                                      5.    C1=Permute(X)
is used to generate the random sequence for the 0-255                   6.    C=Lrotate(C1)
ASCII characters by multiplying r=[A] *[T]                and                          }
considering the values to mod 4. The random sequence                    7.    Write(C)
generated using the formula [40 41 42]*r is generated.[10]              }
                                                                              Algorithm for Decryption:
3.     Development of the cipher                                        {
                                                                        1.     read LDEA-key,R-key,n,C
Consider a plain text represented by P which is represented             2.    for i=1 to n
in the form P=[Pij] where i=1to n and j=1 to n ---1                                     {
Let the key matrix be defined by                                        3.    C1=Rrotate(C)
K=[Kij] where i=1 to n and j=1 to n          ---2                       4.    X=permute(C1)
Let the cipher text be denoted by C=[ Cij] where i=1to n and            5.    p= X LDEA key
j=1 to n corresponding to the plain text (1)                            6.    P=convert(p)
For the sake of convenience the matrices P,K and C are                                  }
represented as                                                          7.    write P;
P=[p1 p2 ……pn2]                                                         }
K=[k1 k2 ……kn2]
C=[c1 c2 ……cn2 ]                                                   4.        Illustration of the cipher
Where in the components are taken row wise from the
corresponding matrices.                                            Encryption :
The process of encryption and decryption are shown
  1. The components of p are first converted into their            The distance between every pair of points in the universe is
        corresponding binary bits in the form                      negligible by virtue of communication facilities. Let us
     p11 p12 p13 p14 p15 p16 p17 p18, p21 ……pn2 1…..pn28           reach each point in the sky. This is the wish of scientists.
     where p11 p12 .... are the corresponding binary bits
     corresponding to p1 p2…..                                     ASCII equivalent
     As the numbers in the plain text are between 0 to 256
     we have bits in every number. Here we have 8n 2 binary        P=[ 84 104 101 32 100 105 115 116 97 110
     bits . Thus we divide the string of 8n 2 binary bits into 8   99 101 32 98 101 116 119 101 101 110 32
     substrings each having n 2 binary bits.                       101 118 101 114 121 32 112 97 105 114 32
  2. The plain text P is whitened by using the Exclusive –         111 102 32 112 111 105 110 116 115 32 105
        or operation with the LDEA key to get the first stage      110 32 116 104 101 32 117 110 105 118 101
                                                                   114 115 101 32 105 115 32 110 101 103 108
48                                                       (IJCNS) International Journal of Computer and Network Security,
                                                                                                    Vol. 2, No. 3, March 2010

105 103    105 98 108 101 32 98 121 32 118                   32 102     97 99 105 108 105 116 105 101 115
105 114    116 117   101 32 111 102 32 99 111                46 76     101 116 32 117 115 32 114 101 97
109 109    117 110 105 99 97 116 105 111 110                 99 104    32 101 97 99 104 32 112 111 105
32 102     97 99 105 108 105 116 105 101 115                 110 116    32 105 110 32 116 104 101 32 115
46 76     101 116 32 117 115 32 114 101 97                   107 121    46 84 104 105 115 32 105 115 32
99 104    32 101 97 99 104 32 112 111 105                    116 104    101 32 119 105 115 104 32 111 102
110 116     32 105 110 32 116 104 101 32 115                 32 115    99 105 101 110 116 105 115 116 115
107 121     46 84 104 105 115 32 105 115 32                  46]
116 104    101 32 119 105 115 104 32 111 102
32 115    99 105 101 110 116 105 115 116 115                 The distance between every pair of points in the universe is
46]                                                          negligible by virtue of communication facilities. Let us
                                                             reach each point in the sky. This is the wish of scientists.
LDEA- key
r1=[ 0 0 1 0 0 0 1 1 ];                                      5.     Cryptanalysis
r2= [1 0 0 1 1 1 1 1 ];
r3= [1 1 1 1 1 1 1 1];                                       If the latitude and longitude coordinate is simply used as the
                                                             key for data encryption; the strength is not strong enough.
X=P xor LDEA key                                             That is the reason why a random key is incorporated into
Permuting with R-key and Rotating right di times where di    LDEA algorithm.
= ki mod 16 and transposing                                  Let us consider the cryptanalysis of the cipher. In this cipher
C=[34 88 14 9 32 120 38 3 101 125 86                         the length of the key is 8n2 binary bits. Hence the key space
87 53 89 95 85 99 94 110 13 58 120 55                        is 28n2 . Due to this fact the cipher cannot be broken by
43 39 104 86 30 33 25 122 69 49 89 111                       Brute force attack.
69 102 124 22 27 121 111 119 102 127 30                      The Cipher cannot be broken with known plain text attack
91 61 99 31 74 77 60 104 55 50 39 105                        as there is no direct relation between the plain text and the
86 94 37 25 122 85 49 89 79 69 100 124                       cipher text even if the longitude and latitude details are
22 19 39 104 118 30 35 25 122 77 107 93                      known.
78 109 52 122 55 19 109 110 118 54 59                        It is noted that the key dependent permutation plays an
27 91 109 123 87 79 109 92 126 53 51 124                     important role in displacing the binary bits at various stages
109 55 114 119 31 75 93 103 92 78 29                         of iteration, and this induces enormous strength to the
48 121 55 67 113 109 119 70                119 28 91         cipher.
29 65 76 76 4 48 48 19 3 61 105 119
118 103 31 90 93 81 13 73 68 116 36 19                                 Avalanche Effect
18 61 105 119 118 103 31 90 93 117 93                        With change in LDEA key from 2334719 to 2334718 the
79 85 116 125 23 83 101 110 118 22 59                        cipher text   would change to
25 91 109]                                                    G=[34 88 14 9 32 120 38 3 37 121 86
Cipher text C =                                              87 37 89 94 85 99 94 110 13 58 120 55
 "Xx& e}VW5Y_Uc^n:x7+'hV-! zE1YoEf|             yowf -[=c   43 103 108 86 30 49 25 123 69 49 89 111
JM<h72'iV^% zU1YOEd|         'hv-# zMk]Nm4z7 mnv6;           69 102 124 22 27 57 107 119 102 111 30
  [m{WOm\~53|m7rwK]                                          90 61 99 31 74 77 60 104 55 50 103 109
g\N 0y7CqmwFw [ ALL 00  =iwvgZ] Q                          86 94 53 25 123 85 49 89 79 69 100 124
IDt$     =iwvgZ] u]OUt} Senv ; [m                            22 19 103 108 118 30                 51 25 123 77 107
Decryption:                                                  93 78 109 52 122 55 19 45 106 118 54
cipher text C=                                               43 27 90 109 123 87 79 109 92 126 53 51
"Xx& e}VW5Y_Uc^n:x7+'hV-! zE1YoEf|             yowf -[=c    60 105 55 114 103 31 74 93 103 92 78 29
JM<h72'iV^% zU1YOEd|         'hv-# zMk]Nm4z7 mnv6;           48 121 55 67 49 105 119 70 103 28 90
  [m{WOm\~53|m7rwK]                                          29 65 76 76         4 48 48 19 3 125 109 119
g\N 0y7CqmwFw [ ALL 00  =iwvgZ] Q                          118 119 31 91 93 81 13 73 68 116 36 19
IDt$     =iwvgZ] u]OUt} Senv ; [m                            18 125 109 119 118 119 31 91 93 117 93 79
After key dependent permuting and circular rotation the      85 116 125 23 83 37 106 118 22                 43 25
ASCII equivalent is                                          90 109]
                                                             The change in the cipher text is 44 bits
P=[ 84 104 101 32 100 105 115 116 97 110
99 101 32 98 101 116 119 101 101 110 32                      6.     Conclusions
101 118 101 114 121 32 112 97 105 114 32
111 102 32 112 111 105 110 116 115 32 105
                                                             In this chapter a cipher is developed using the LDEA key
110 32 116 104 101 32 117 110 105 118 101
                                                             dependent permutation and circular rotation as the primary
114 115 101 32 105 115 32 110 101 103 108
                                                             concept. The cryptanalysis is discussed which indicates that
105 103 105 98 108 101 32 98 121 32 118
                                                             the cipher is strong and cannot be broken by any
105 114 116 117   101 32 111 102 32 99 111
109 109 117 110 105 99 97 116 105 111 110
                                                            (IJCNS) International Journal of Computer and Network Security, 49
                                                                                                       Vol. 2, No. 3, March 2010

cryptanalytic attack since this includes transposition of the   Authors Profile
binary bits of the plain text at every stage.
                                                                                Dr Prasad Reddy P V G D, is a Professor of
7.     Acknowledgements                                                         Computer Engineering with Andhra University,
                                                                                Visakhapatnam, INDIA. He works in the areas of
This work was supported by grants from the All India                            enterprise/distributed technologies, XML based
Council for Technical Education (AICTE) project under                           object models. He is specialized in scalable web
RPS Scheme under file No. F.No.8023/BOR/RID/RPS-                                applications as an enterprise architect. With over
114/2008-09.                                                                    20 Years of experience in filed of IT and teaching,
                                                                                Dr Prasad Reddy has developed a number of
References                                                      products, and completed several industry projects. He is a regular
                                                                speaker in many conferences and contributes technical articles to
[1]   K.R.Sudha, A.Chandra Sekhar and Prasad                    international Journals and Magazines with research areas of
     Reddy.P.V.G.D “Cryptography protection of digital          interest in Software Engineering, Image Processing, Data
     signals using some Recurrence relations” IJCSNS            Engineering , Communications & Bio informatics
     International Journal of Computer Science and
     Network Security, VOL.7 No.5, May 2007 pp 203-207
                                                                                 K.R.Sudha received her B.E. degree in
[2] A.P. Stakhov, ”The ‘‘golden’’ matrices and a new kind                        Electrical Engineering from GITAM, Andhra
     of cryptography”, Chaos, Soltions and Fractals 32 (                         University 1991.She did her M.E in Power
     (2007) pp1138–1146                                                          Systems 1994. She was awarded her Doctorate
[3] A.P. Stakhov. “The golden section and modern harmony                         in Electrical Engineering in 2006 by Andhra
     mathematics. Applications of Fibonacci numbers,”                            University. During 1994-2006, she worked with
     7,Kluwer Academic Publishers; (1998). pp393–99.                             GITAM Engineering College and presently she
[4] A.P. Stakhov. “The golden section in the measurement        is working as     Professor in the department of Electrical
     theory”. Compute Math Appl; 17(1989):pp613–638.            Engineering, Andhra University, Visakhapatnam, India.
[5] Whitfield Diffie And Martin E. Hellman, New
     Directions in Cryptography” IEEE Transactions on
     Information Theory, Vol. -22, No. 6, November 1976
                                                                                      S.Krishna Rao received his M Tech degree in
     ,pp 644-654
                                                                                      Computer Science and Systems Engineering
[6] Whitfield Diffie and Martin E. Hellman “Privacy and                               from Andhra University in 2000.He is
     Authentication: An Introduction     to Cryptography”                             presently working as Associate Professor in the
     PROCEEDINGS OF THE IEEE, VOL. 67, NO. 3,                                         Department of Computer Science and
     MARCH 1979,pp397-427                                                             Engineering in Sir.C.R.Reddy College of
 [7] A. V. N. Krishna, S. N. N. Pandit, A. Vinaya Babu “A       Engineering, Eluru.
     generalized scheme for data encryption technique
     using a randomized matrix key” Journal of Discrete
     Mathematical Sciences & Cryptography Vol. 10
     (2007), No. 1, pp. 73–81
[8] C. E. SHANNON Communication Theory of Secrecy
     Systems The material in this paper appeared in a
     confidential report “A Mathematical Theory of
     Cryptography” dated Sept.1, 1946, which has now
     been declassified.
 [9] E. Shannon, A Mathematical Theory of
     Communication, Bell System Technical Journal 27
     (1948) 379–423, 623–656.
[10] A. Chandra Sekhar , ,K.R.Sudha and Prasad
     Reddy.P.V.G.D “Data Encryption Technique Using
     Random Number Generator” Granular Computing,
     2007. GRC 2007. IEEE International Conference, on
     2-4 Nov. 2007 Page(s):576 – 576
[11] V. Tolety, Load Reduction in Ad Hoc Networks using
     Mobile Servers. Master’s thesis, Colorado School of
     Mines, 1999.
[12]L. Scott, D. Denning, Geo-encryption: Using GPS to
     Enhance Data Security, GPS World, April 1 2003.
[13] Geo-encryption protocol for mobile networks A. Al-
     Fuqaha, O. Al-Ibrahim / Computer Communications
     30 (2007) 2510–25
50                                                              (IJCNS) International Journal of Computer and Network Security,
                                                                                                           Vol. 2, No. 3, March 2010


 Implementation of Watermarking for a Blind Image
        using Wavelet Tree Quantization
                                     S.M.Ramesh1, Dr.A.Shanmugam2 , B.Gomathy3
                                                1
                                              Senior Lecturer, Dept.of ECE,
                                Bannari Amman Institute of Technology, Erode- 638401, India
                                                    smrameshme@yahoo.co.in
                                                    2
                                                        Professor, Dept.of ECE,
                                Bannari Amman Institute of Technology, Erode-638401, India
                                                         dras_bit@yahoo.com
                                                    3
                                                 Lecturer, Dept.of CSE,
                                Bannari Amman Institute of Technology, Erode- 638401, India
                                                        gomramesh@gmail.com


                                                                    mid-frequency to ensure the transparency and robustness of
Abstract:      This paper proposes implementation of
watermarking for a blind image using wavelet tree quantization      the watermarked image. For suggested inserting the
for copyright protection. In such a quantization scheme, there      watermark into the perceptually significant portion of the
exists a large significant difference while embedding a             whole DCT transformed image, wherein a predetermined
watermark bit 1 and a watermark bit 0; it then does not require     range of low frequency components excludes the DC
any original image or watermark during the watermark                component.
extraction. As a result, the watermarked images look lossless in    This watermarking scheme has been shown to be robust
comparison with the original ones, and the proposed method can
effectively resist common image processing attacks; especially
                                                                    against common attacks such as compression, filtering, and
for JPEG compression and low-pass filtering. Moreover, by           cropping. The proposed a watermarking method, in
designing an adaptive threshold value in the extraction process,    accordance with the multi-threshold wavelet coding
our method is more robust for resisting common attacks such as      (MTWC), the successive subband quantization (SSQ) is
median filtering, average filtering, and Gaussian noise.            adopted to search for the significant coefficients. The
Experimental results show that the watermarked image looks          watermark is added by quantizing the significant coefficient
visually identical to the original, and the watermark can be
                                                                    in the significant band by using different weights. The
effectively extracted even after either an unintentional image
processing or intentional image attacks.                            proposed a watermarking method based on the qualified
                                                                    significant wavelet tree (QSWT). The QSWT is derived
  Keywords - Wavelet tree quantization, JPEG compression,           from the embedded zerotree wavelet algorithm (EZW). The
Low-pass filtering, Discrete Wavelet Transform.
                                                                    watermark is embedded in each of the two subbands of the
                                                                    wavelet tree. Several watermarking methods used two sets of
1. Introduction
                                                                    coefficients, one to represent the watermark bit 0, and the
The Internet has popularized tremendously fast in our life in       other to represent the watermark bit 1. According to the
the last decade. Due to the digitalization of documents,            embedded watermark bit, only a set of coefficients are
images, music, videos, etc, people can access and propagate         quantized each time. The proposed a blind watermarking
them easily via the network. The watermarking technique             approach called differential energy watermarking. A set of
has been widely applied to digital contents for copyright           several 8×8 DCT blocks are composed and divided into two
protection, image authentication, proof of ownership, etc.          parts to embed a watermark bit. The high frequency DCT
This technique embeds information so that it is not easily          coefficients in the JPEG/MPEG stream are selectively
perceptible; that is, the viewer cannot see any information         discarded to produce energy differences in the two parts of
embedded in the contents. The issue here is the detection of        the same set.
the existence of watermarks in the digital contents to prove          The wavelet coefficients of the host image are grouped
ownership. The spatial and spectral domains are two                 into wavelet trees, and each watermark bit is embedded
common methods for watermarking. In the spatial domain,             using two trees. One of the two trees is quantized with
the watermark is embedded in the selected areas on the              respect to a quantization index, and both trees exhibit a
texture of the host image. In the spectral domain, since the        large statistical difference between the quantized tree and
spread spectrum communication is robust against many                the unquantized tree; the difference can later be used for
types of interference and jamming, the host image is                watermark extraction. EL [10] improved SHW [11] method
transformed to the frequency domain using methods such as           by adding the Human Visual System (HVS) to effectively
Discrete Cosine Transform (DCT) or Discrete Wavelet                 resist geometric attack. BKL [9] improved SHW [11]
Transform (DWT); then the watermark is embedded in the              method by using four trees to represent two watermark bits
                                                            (IJCNS) International Journal of Computer and Network Security, 51
                                                                                                       Vol. 2, No. 3, March 2010

to improve visual quality. One of the four trees is quantized   difference is greater than the adaptive threshold value;
according to the binary value of the two embedded               otherwise, a watermark bit 0 is extracted. Experimental
watermark bits. But these methods [9-11] cannot effectively     results show that the proposed method is very efficient for
resist the attacks of low-pass filtering for JPEG               resisting various kinds of attacks.
compression. In this paper, propose a blind watermarking
method based on wavelet tree quantization.                      2. Watermarking by Quantization of Wavelet
                                                                   Trees

                                                                   2.1 Wavelet Trees
                                                                  A host image of size n by n is transformed into wavelet
                                                                coefficients using the 4-level discrete wavelet transform
                                                                (DWT).With 4-level decomposition and have 13 frequency
                                                                bands as shown in Fig. 1. The parent-child relationship can
                                                                be connected between these sub nodes to form a wavelet
                                                                tree. If the root consists of more than one node, then an
                                                                image will have many wavelet trees after the DWT. In this
                                                                case, we have 3 sub bands LH4, HL4, and HH4 as roots, and
                                                                the total wavelet trees are 3×(n/24×n/24) after an image of
                                                                size n by n is transformed by a 4-level wavelet transform. A
                                                                higher resolution level (such as level 3 in Fig.1) has more
                                                                significant coefficients than a lower resolution level (such as
                                                                level 2 in Fig.1). As we can see, when n = 512, there are 85
      Figure 1. The watermark embedding procedure.
                                                                coefficients for a wavelet tree constructed from a node in
                                                                LH4 to LH1 following the parent-child relationship. For
  A watermarking technique is denoted as blind if the
                                                                avoiding attacks such as low pass filters, in our proposed
original image is not needed for extraction. In previous
                                                                method we only need the largest two coefficients; these two
research, the watermark embedded in the significant
                                                                coefficients are selected from one coefficient of LH4 and
coefficients was found to be robust. The common issue is the
                                                                four coefficients of the same orientation in the same spatial
use of blind detection to find out whether the extracting
                                                                location in LH3 as shown in Fig. 2.
order is the same as the embedding order. Hence, propose a
watermarking method which embeds a watermark bit in the
                                                                 2.2 The Preprocess
maximum wavelet coefficient of a wavelet tree. The
                                                                  With a four-level DWT and have 13 frequency bands as
proposed method is different from others, which use two
                                                                shown in Fig.1. A higher level subband is more significant
trees or two blocks to embed a watermark bit. We embed the
                                                                than a lower subband. Using the LL4 subband as a root is
watermark by scaling the magnitude of the significant
                                                                not suitable for embedding a watermark, since it is a low
difference between the two largest wavelet coefficients in a
                                                                frequency band that contains important information about
wavelet tree to improve the robustness of the watermarking
                                                                an image and easily causes image distortions. Embedding a
                                                                watermark in the HH4 subband is also not suitable, since the
                                                                subband can easily be eliminated, for example by a lossy
                                                                compression. The LH4 subband is more significant than the
                                                                HL4 subband, hence the LH4 subband has a higher priority
                                                                than the HL4 subband in the selection. A binary watermark
                                                                image W comprised of size Nw (≤ S = n/24×n/24) bits is
                                                                embedded. We represent each watermark bit as 1 or 0, and
                                                                use a 90 pseudorandom function with another seed to shuffle
                                                                Nw bits. According to the watermark bits embedded later, we
                                                                select Nw non-overlapping wavelet trees and compute the
                                                                global average significant difference of the total number of
                                                                the Nw wavelet trees using Eq.(1).

      Figure 2. The watermark extraction procedure.                        1   Nw
                                                                  ε = { ------ ∑ (maxi – seci)}                       (1)
  The trees are so quantized that they exhibit a sufficiently            Nw i = 1
large enough energy difference between a watermark bit 1
and a watermark bit 0, which is then used for watermark            Where ε is the global average significant difference in all
extraction. During extraction, an adaptive threshold value is   Nw wavelet trees; {⋅} is the floor function; maxi is the local
designed. A watermark bit 1 is extracted if the significant     maximum wavelet coefficient of the ith wavelet tree; seci is
52                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010

the local second maximum wavelet coefficient of the ith           Otherwise, the embed a watermark bit 0 according to Eq. (7)
wavelet tree, 1≤ i ≤ Nw. If the embedded watermark bit is 1,      as follows:
the local maximum coefficient is not quantized under                 if (seci < 0 ), than maxinew = 0, secinew = 0;
Maximum (ε ,T) Δi ≥ ε and is quantized under Δi <
Maximum (ε ,T) . If the embedded watermark bit is 0, the             otherwise maxinew = seci                     (7)
local maximum coefficient is quantized by setting the local
maximum coefficient = local second maximum coefficient.           Where secinew denotes the new second maximum coefficient
                                                                  in the ith wavelet tree after embedding the watermark bit 0.
                                                                  When embedding a watermark bit 1, the maximum local
 2.3 Watermark Embedding
  Let maxi and seci be the local maximum wavelet                  significant coefficient is quantized and added by an
                                                                  incremental β if Δi < Maximum (ε, T); otherwise (i.e., Δi ≥
coefficient and the local second maximum wavelet
                                                                  Maximum (ε, T)), it is kept the same as before. The reason
coefficient in a wavelet tree; the difference between both of
                                                                  for not quantizing the maximum local significant coefficient
them is named as the local significant difference. The select
                                                                  is that we won’t increase the distortion of the image. Some
a threshold value β as an increment for quantization. The         images having small ε imply that their significant difference
larger the β is, the better robustness but the worse distortion   is not obvious. We need an extra parameter T to improve the
of the watermarked image will be. Each time at embed a            robustness. The larger the T is, the higher probability the
watermark bit and quantize the maximum coefficient in a           maxi is quantized to a larger value; but, in the meanwhile,
wavelet tree.                                                     the more distortion of the image will be as well. For
                                                                  example, let ε =12 and Δi = 13. Suppose T is set to be less
     if (maxi < 0), then maxi = 0                    (2)          than ε, such as T =11, maxi will not be quantized as Δi >ε
                                                                  =12. On the other hand, if T is set to be larger than ε, such
      Δi = maxi − seci,                              (3)          as T =14, maxi will be quantized and increased by β as Δi
                                                                  <T=14. On the contrary, when embedding a watermark bit
   Where Δi denotes the significant difference between the        0, the value of maxi is quantized by decreasing to the local
maximum coefficient and the second maximum coefficient            second maximum seci and hence the new Δi will be equal to
in the ith wavelet tree of Nw. Because some maximum               0. Based on this strategy, there exists a large 91 energy
coefficients in a wavelet tree may be a negative value, and a     difference between embedding watermark bit 1 and
positive value has higher robustness than a negative value        watermark bit 0.
under attacks, it will result in Δi more significant if we
modify the maximum coefficient from a negative value to a         3. Design of Watermark Decoder
positive value. When the Δi is more significant, it will be
more accurate at extracting watermark. To achieve the new         3.1 The Decoder Design
maximum coefficient be positive and to decrease the                 In the proposed method, neither an original image nor an
                                                                  original watermark image is required for the extraction
distortion of watermarked image due to quantization, the
                                                                  process. During the embedding process, embed a watermark
new maximum coefficient is set to a smallest positive value
                                                                  bit 1 by adding an energy β (or β × γ ) to the local maximum
zero here.
                                                                  wavelet coefficient in the wavelet tree, and embed a
   When embed a watermark bit 1, the maxi is quantized by         watermark bit 0 by setting maxi = seci Hence, if the
                                                                  wavelet tree was embedded a watermark bit 0, the local
  maxinew = maxi ,if (Δi ≥ Maximum (ε, T))             (4)        significant difference between the largest two coefficients
                                                                  will be close to zero; otherwise, if the wavelet tree was
  maxinew = maxi + β, if (Δi < Maximum (ε ,T)                     embedded a watermark bit 1, the local significant difference
             and maxi is root)                         (5)        between the largest two coefficients will be greater than β.
                                                                     In order to extract watermark bits correctly and the value
  maxinew = maxi + β × γ , if (Δi < Maximum(ε ,T)                 of y by Eq. (8).
            and maxi is root)                     (6)
                                                                            1      Nw × α
  Where maxinew denotes the new maximum coefficient in               y = --------- ∑ ϕ j                 ------ (8)
the ith wavelet tree after embedding the watermark bit. The              Nw × α j = 1
maxi located at lower resolution level (child node) is less
robust than those located at higher resolution levels (root          Where φ = {max1 - sec1 ,max2 - sec2 ,…..,maxi - seci }, for
node). The reason has been stated in Section II-B.                i=1,2,…,N; the sorted φ is denoted as ϕ (φ) = { ϕ1,ϕ 2 ...ϕ
According to the band sensitivity, the coefficients quantized     Nw }, ϕ1 < ϕ 2 < .... < ϕ Nw ; α is the scale parameter, 0 <
at different resolution level are given different weights. The    α ≤ 1; α is crucial to y and is used to determine how many
quantized coefficient at the lower resolution level is given a    percentages of the significant difference in φ can be used for
heavier weight than that at the higher resolution level.          the average. Hence, α marks the minimal y value for
Hence, if the maxi does not locate at the highest resolution      extracting the watermark. The larger α is, the larger the y
level, we will quantize the maxi by adding γ times of β           will be. Suppose all embedded watermark bits are 1 in the
energy, here γ is a scale parameter and we set γ =1.5.            watermark. This means that the difference between the
                                                               (IJCNS) International Journal of Computer and Network Security, 53
                                                                                                          Vol. 2, No. 3, March 2010

maximum wavelet coefficients and the second maximum                  The peak signal-to-noise ratio (PSNR) to evaluate the
wavelet coefficients for any embedded wavelet tree is greater      quality between the attacked image and the original image.
than β. The value of α should be set as small as possible to       After extracting the watermark, the normalized correlation
avoid extraction errors (see Eq. (9),(10)); the reason for this    coefficient (NC) is computed using the original watermark
is that it can exclude those big significant differences of the    and extracted watermark to judge the existence of the
embedded wavelet trees in Eq. (8). On the other hand, if all       watermark. The value of the NC coefficient is defined as
embedded watermark bits are 0 in the watermark, the value          follows:
of α must be set as large as possible. Therefore, α is sensitive
to the content of the watermark.                                             1     w h -1 w w -1
                                                                   NC = ----------- ∑     ∑ w (i, j) × w ' (i, j)          (11)
3.2 Watermark Extraction                                                wh ×ww i = 0 j = 0
  Following Eqs. (8),(9) and (10), it would be easy to extract
the watermark. If the local significant difference is greater         Where wh and ww are the height and width of the
than or equal to y, where 0 < y ≤ β, then the embedded             watermark. w (i, j) and w' (i, j) are the values of the
watermark bit could be 1; otherwise, the embedded                  coordinate (i, j) in the original watermark and the extracted
watermark bit could be 0. The watermark bit can be                 watermark, respectively. Here w (i, j) is set to 1 if it is a
extracted based on Eq. (9) and (10) as follows:                    watermark bit 1; otherwise, it is set to -1. w' (i, j) is set in
                                                                   the same way. So the value of w(i, j) × w' (i, j) is either -1 or
  watermark bit = 1, if (maxi - seci ) > y        (9)              1.

  watermark bit = 0, otherwise                   (10)                Table 1: Normalized Correlation Coefficients (NC) after
                                                                     Attacks by JPEG Compression with the Quality Factors
                                                                       (QF) 10, 20, 30, 40, 50, 60, 70, 80, 90, AND 100.

                                                                                             Normalized
                                                                        Quality Factors      Correlation         Extracted
                                                                             (QF)            Coefficients        Watermark
                                                                                                (NC)

                                                                               10                0.33

                                                                               20                0.65               E

                                                                               30                0.78               ES

                                                                               40                0.82               E A
                                                    ESHA
                   (a)                               (b)                       50                0.89               ES

Figure 3. (a) The original image of Lena of size 512×512.                      60                0.96               ESH
          (b) The original binary watermark of size 32×16.
                                                                               70                 1                 ESHA

                                                                               80                 1                 ESHA

                                                                               90                 1                 ESHA

                                                                              100                 1                 ESHA

                                                                     The Lena (512×512 pixels, 8 bits/pixel) obtained from
                                                                   attacking the Stir mark benchmark and Photo Impact 11
                                                                   software tools to simulate common image attacks. While
                                                                   there is no attack, for the sake of brevity only the Lena
                                                                   image and the binary watermark are shown in Fig. 3. Fig. 4
                                                 ESHA              shows the watermarked image and the extracted result. Pre-
                   (a)                             (b)             determine the scale parameter T at 10, β =7, γ =1.5, and α
                                                                   =0.7. In the following, consider both geometric and
Figure 4. (a) Watermarked Lena with PSNR = 41.88dB                 nongeometric attacks. Nongeometric attacks include JPEG
           (b) The extracted watermark with NC = 1                 compression, low pass filtering, histogram equalization, and
                                                                   sharpening. From Table 1, the proposed method can
                                                                   correctly extract the watermark while the quality factors are
4. Experimental Results
                                                                   greater than 70 and it becomes worse if the quality factor is
54                                                             (IJCNS) International Journal of Computer and Network Security,
                                                                                                          Vol. 2, No. 3, March 2010

decreased. The less the quality factor is, the more vague the        In this paper, propose a wavelet-tree-based blind
extracted watermark is.                                            watermarking method by quantizing the maximum wavelet
                                                                   coefficient in a wavelet tree. Embed a watermark bit by
                                                                   quantizing the maximum wavelet coefficient in a wavelet
                                                                   tree. The trees are so quantized that they exhibit a
4.1 Experiment Analysis                                            sufficiently large enough energy difference between a
   Compare the proposed method with BKL [9], EL [10],              watermark bit 0 and a watermark bit 1, which difference,
and SHW [11] using the Lena image. The watermark                   denoted as significant difference, is then useful for later
consists of 256 bit 1and 256 bit 0. The results are shown in       watermark extraction. During extraction, an adaptive
Table 2. From Table 2, the PSNR of the proposed method is          threshold value is designed. The magnitude of the
better than those of [11]. In this method, it is not so good for   significant difference in a wavelet tree is compared to the
the rotation attacks with degree greater than ± 0.70; but it is    adaptive threshold value. Furthermore, regarding each
far better than the listed methods; especially for low pass        wavelet tree embedded with a watermark bit, we not only
filtering attacks for JPEG compression.                            can embed more bits in an image but can extract the
                                                                   watermark without any need of the original image and
     Table 2: Comparison of the Proposed Method and the            watermark. Moreover by designing an adaptive threshold
                Methods in [9], 10] and [11].                      value in the extraction process. In addition to the copyright
                                                                   protection, the proposed method can also be applied to data
                                                                   hiding and image authentication.
Attacks /    SHW         EL        BKL       Proposed
  NC        PSNR =     PSNR=      PSNR=      Method
            38.2dB     40.6dB     41.54dB    PSNR =
                                                                   References
                                             41.88dB
                                                                   [1] D. P. Mukherjee, S. Maitra, and S. T. Acton, "Spatial
 JEPG         NA        0.15        0.17       0.33                    domain digital watermarking of multimedia objects for
 (QF =                                                                 buyer authentication," IEEE Trans. Multimedia, vol. 6,
  10)                                                                  pp. 1-15, Feb. 2004.
                                                                   [2] N. Nikolaidis and I. Pitas, "Robust image watermarking
 JEPG         NA        0.34        0.61       0.65                     in the spatial domain," Signal Processing, vol. 66, pp.
 (QF =                                                                  385-403, 1998.
  20)
                                                                   [3] A. K. Mahmood and A. Selin,"Spatially adaptive
                                                                        wavelet thresholding for image
 JEPG        0.15       0.52        0.79       0.78
 (QF =                                                                  watermarking,"presented at Proc.IEEE ICME, Toronto,
  30)                                                                   2006 of Conference.
                                                                   [4] J. R. Hernandez, M. Amado, and F. Perez- Gonzalez,
 JEPG        0.23       0.52        0.83       0.82                     "DCT- omain watermarking techniques for still images:
 (QF =                                                                  detector performance analysis and a new structure,"
  40)                                                                   IEEE Trans.Image Processing, vol. 9, pp.55- 68, Jan.
                                                                        2000.
 JEPG        0.28       0.52        0.89       0.89                [5] L. Sin-Joo and J. Sung-Hwan, "A survey of
 (QF =
                                                                        watermarking techniques applied to multimedia," in
  50)
                                                                        Proc. IEEE ISIE 2001, pp. 272-277
 JEPG        0.46       0.59        0.94       0.96                [6] V. M. Potdar, S. Han, and E. Chang,"A survey of digital
 (QF =                                                                  image watermarking techniques,"presented at Proc.
  60)                                                                   IEEE INDIN 2005 of Conference.
                                                                    [7] H. J. Wang, P. C. Su, and C. C. J. Kuo, "Wavelet-based
 JEPG        0.57       0.63        0.97        1                       digital image watermarking," Optics Express,vol.3, pp.
 (QF =                                                                   491- 496, Dec. 1998.
  70)                                                              [8] M. Hsieh, D. Tseng, and Y. Huang, "Hiding digital
                                                                        watermarks using multiresolution wavelet transform,"
 JEPG        0.89       0.71        0.99        1                       IEEE Trans. Ind. Electron., vol. 48, pp. 875-882, Oct.
 (QF =
                                                                        2001.
  80)
                                                                    [9] B. K. Lien and W. H. Lin,"A watermarking method
 JEPG          1        0.78         1          1                        based on maximum distance wavelet tree
 (QF =                                                                   quantization," presented at 19th Conf. Computer
  90)                                                                    Vision, Graphics and Image Processing, 2006 of
                                                                         Conference.
 JEPG          1        0.88         1          1                  [10] E. Li, H. Liang, and X. Niu,"An integer wavelet based
 (QF =                                                                   multiple logo-watermarking scheme," presented at
  100)                                                                   Proc. IEEE WCICA, 2006 of Conference.
                                                                   [11] S. H. Wang and Y. P. Lin, "Wavelet tree quantization
5. Conclusion                                                             for copyright protection watermarking," IEEE Trans.
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     Image Processing, vol. 13, pp. 154-165, Feb. 2004.                Guide Award” five times from Tamil Nadu state Government. He
[12] G. C. Langelaar and R. L. Lagendijk, "Optimal                     is also the recipient of “Best Outstanding Fellow Corporate
     differential energy watermarking of DCT encoded                   Member Award” by Institution of Engineers (IE),India -2004 and
     images and video,"IEEE Trans. Image Processing,                   “Jewel of India” Award by International Institute of Education and
                                                                       Management, New Delhi–2004 and “Bharatiya Vidya Bhavan
     vol. 10, pp. 148-158, Jan.2001.
                                                                       National Award for Best Engineering College Principal 2005” by
                                                                       Indian Society for Technical Education (ISTE). “Education
 [13] F. A. P. Petitcolas, Weakness of existing watermark              Excellence Award” by All India Business& Community
      Scheme               1997[online]            Available:          Foundation, New Delhi.
       http://www.petitcolas.net/fabien/watermarking/stirma
       rk/index.html.
[14] PhotoImpact 11 software, http://www.ulead.com,
      Ulead system, Inc.


Authors Profile

                           S.M.Ramesh received the B.E degree
                           in Electronics and Communication
                           Engineering from National Institute of
                           Technology
                            (Formerly     Regional    Engineering
                           College),    Trichy,    Bharathidhasan
                           University, India in the year 2001 and
                           the M.E, degree in Applied Electronics
                           from RVS College of Engineering and
                           Technology,        Dindugal,     Anna
University, India in the year 2004. From 2004 to 2005, he served
as a Lecturer in the Department of Electronics and Communication
Engineering, Maharaja Engineering College, Coimbatore, India.
From 2005 to 2006, he served as a Lecturer in the Department of
Electronics and Communication Engineering, Nandha Engineering
College, Erode, India. Since June 2006, he served as Senior
Lecturer, in the Department of Electronics and Communication
Engineering, Bannari Amman Institute of Technology,
Sathyamangalam, and Erode, India. He is currently pursuing the
Ph.D. degree in Anna University, Chennai-India, working closely
with Prof. Dr.A.Shanmugam and Prof Dr.R.Harikumar.


                            Dr.A.Shanmugam received the B.E,
                            degree       in      Electronics    and
                            Communication Engineering from PSG
                            College of Technology., Coimbatore,
                            Madras University, India in the year
                            1972 and the M.E, degree in Applied
                            Electronics      from      College    of
                            Engineering, Guindy, Chennai, Madras
                            University, India in the year 1978 and
                            received the Ph.D. in Computer
                            Networks from PSG College of
Technology., Coimbatore, Bharathiyar University, India in the year
1994.From 1972 to 1976, he served as a Testing Engineer at Test
and Development Center, Chennai, India. From 1978 to 1979, he
served as a Lecturer in the Department of Electrical Engineering,
Annamalai University, India. From 1979 to 2002, he served
different level as a Lecturer, Asst.Professor, Professor and Head in
the Department of Electronics and Communication Engineering of
PSG College of Technology, Coimbatore, India. Since April
2004.He assumed charge as the Principal, Bannari Amman
Institute of Technology, Sathyamangalam, Erode, India.

  He works in field of Optical Networks, broad band computer
networks and wireless networks, Signal processing specializing
particularly in inverse problems, sparse representations, and over-
complete transforms.Dr.A.Shanmugam received “Best Project
56                                                                (IJCNS) International Journal of Computer and Network Security,
                                                                                                             Vol. 2, No. 3, March 2010


       A Hierarchical Genetic Algorithm for Topology
       Optimization and Traffic Management in ATM
       Networks Utilizing Bandwidth and Throughput
                                    Alaa Sheta1, Malik Braik2 and Mohammad Salamah3
                                         1
                                             Taif University, Information Systems Department,
                                             College of Computers and Information Systems,
                                                            Taif, Saudi Arabia
                                                           asheta66@gmail.com
                                2
                                 Al-Balqa’ Applied University, Information Technology Department,
                             Prince Abdullah Bin Ghazi Faculty of Science and Information Technology,
                                                           Salt, Jordan
                                                        malik@bau.edu.jo
                                         3
                                             National Education Center for Robotics (NECR),
                                                       King Hussein Foundation,
                                                            Amman, Jordan
                                                        m.omar82@gmail.com

                                                                      increasingly used in telecommunications systems for high
Abstract: The Asynchronous Transfer Mode (ATM) network is
expected to become a backbone network for high speed digital          speed multimedia services [2], [3].
multimedia services in distributed environments. This paper           Recently, control flow and management are core concepts of
explores an optimization based hierarchical approach using            the optimal structure of ATM networks; hence, flow control
Genetic Algorithms (GAs) for installing an ATM network with           and management have drawn much attention by the
optimal structure and traffic flow. A Hierarchical Genetic            researchers in telecommunication field. In addition to that
Algorithm (HGA) is used to solve such an optimization problem.        the nodes in the ATM network design must be linked in an
HGA approach can improve the performance of conventional
GA, though it consumes more computation time. Thus, HGA
                                                                      economical way to handle expected traffic and capacity
approach is capable of reducing the overall delay while               constraints [1], [4]. As the models for the design of ATM
increasing the bits transmitted over the network. This will           networks are quite complex, and one of the limiting factors
definitely improve the network performance and meets the              is the requirement of expensive exchange based equipments,
requirements in multimedia service environments. The                  therefore, Genetic Algorithms (GAs) were used to solve such
preliminary results indicate that HGA based ATM network               problems of traffic assignment and topological design of
design can be very efficacious.
                                                                      local area networks [5], [6], flow optimization in survivable
     Keywords: Genetic Algorithms, ATM Network, Flow                  ATM networks [7], and flow assignment in ATM networks
Management.                                                           [8]–[10]. However, many programming models have been
                                                                      developed which deals with telecommunication network
                                                                      planning [11]. In this context, Evolutionary Algorithms
1. Introduction                                                       (EAs) have been frequently applied to telecommunication
There is a rapidly demand for telecommunication networks              services in the last years [9], [12].
to function efficaciously despite obstacles such as disabling          This paper handles an optimal ATM network structure (i.e.
portions of the network, limiting the links capacities, high          topology and link capacities) using Hierarchical Genetic
cabling costs, and so on [1]. Thus, networks must constantly          Algorithms (HGA) [13], [14]. The objectives of the network
able to maintain an acceptable level of performance. Despite          planning are: designing the network structure to carry out
this need, the problem of dynamic redesign of functioning             the estimated traffic, and minimizing the cost of network
networks still received a little attention. Today, with the           [15],[16]. Consequently, we are dealing with flow
intensifying role of using the Internet and networking                assignment and links capacities as complex optimization
technologies, there have been immense advances in using               problems using GAs in two levels, the first GA level deals
the telecommunications services in the present information            with selection the optimal network structure, and the second
society. Asynchronous Transfer Mode (ATM) is one of the               GA level reduces the overall delay while maintain the
most promising networking technologies. ATM was rated to              throughput, this cycle will continues until terminated by
reduce the complexity of the network and improve the                  some condition.
flexibility of traffic performance which has good ability for         The remainder of the paper is organized as follows. In
transmitting many kinds of information, and carry traffic             Section 2 we explain the details of GA levels; each
over all kinds of networks. Furthermore, ATM has been                 alternative level of HGA is described extensively. The case
                                                                (IJCNS) International Journal of Computer and Network Security, 57
                                                                                                           Vol. 2, No. 3, March 2010

study and the schematic diagram of the ATM network are               2.2 GA Level 2
discussed in section 3. In Section 4 we provide an extensive       GA is optimized to find the best value of (fi) such that the
and comprehensive formulation of the use of HGA for                overall delay is minimized. The computed network delay is
solving the ATM design problem. In section 5 we present            then returned to GA Level 1 to be considered as the new
our preliminary results for the ATM network case study.            fittest value. The fitness criterion, in this level, is considered
Finally, in section 6 we offer several concluding remarks and      as the mean time delay. The mean delay is computed as in
address the challenges ahead in the future enhancements.           Equation 3.

2. Hierarchical GA                                                           1 N            fi          N
                                                                       T =      ∑                , θ = ∑ fi                    (3)
The ATM design problem was considered as a parameter                         θ i =1 C
                                                                                        i   − fi      i =1
estimation problem. GAs has been used in a hierarchical
approach to optimize the ATM network. The proposed novel
                                                                   where θ is the total traffic over the network, N is the number
HGA optimization problem is shown in Figure 1. There are           of links. This idea was presented in [16].
two levels were performed to produce an optimal ATM
network design. The two levels are evolved in parallel. The
                                                                   3. Case Study: ATM Network
fitness score of the individuals in each level depends on the
performance of the chromosomes in both levels.                     There are two sets of customers to be considered while
                                                                   planning the ATM network design:
                                                                   1) the user who uses the services through the network. The
                                                                       network should meet the user’s needs in terms of quality
                                                                       of service. The flow assignment and the capacities links
                                                                       are the two main entities affecting the cost of the ATM
                                                                       network. The maximum flow assignment must be tested,
                                                                       and the network should maintain a high capacity.
                                                                    2) the company which will be building the ATM network
                                                                       and maintaining it. The network operation should be as
                                                                       cost effective as possible for both installation and
                                                                       maintenance. Minimizing the total cost is mainly an
                                                                       important matter of selecting the best design of ATM
                                                                       network.
                                                                   The schematic diagram for the ATM under study with all
                                                                   specified links and capacities is shown in Figure 2.

          Figure 1. Hierarchical GAs in two levels

   2.1 GA Level 1
GA is used to install a new network with a set of network
links which satisfies the constraints demand criterion and
has a minimum delay over the network. In this level, a new
network structure is evolved which has all nodes of the
original network and a subset of its links. The network
configuration must be implemented subject to the constraints
defined in Equations 1 and 2.
                                                                               Figure 2. The ATM Network Topology
    f ≤ C × 95%                                (1)
     i   i
                                                                   This ATM network was presented in [17], [18]. The network
Thus, the maximum flow value (fi) for link (i) in Equation 1       has 7 nodes with 14 links. The links and capacities for each
is restricted not to exceed 95% of the capacity (Ci).              node are presented in Table 1.
                      n                                            Each network link is characterized by a set of attributes;
Throughput ≥ 0.5 ×   ∑      C
                             i
                                                (2)                these attributes for a given link (i) form the flow (fi ) and the
                     i =1                                          capacity (Ci ). (fi ) is defined as the effective quantity of
The throughput of the network is allowed not to be less than       information transported by link (i). The capacity (Ci ) is
half the sum of all capacities. We must realize that the           defined as the measure of the maximal quantity of
boundary range of the genes values is based on the link ID of      information that can be transmitted by link (i).
the ATM experiments and the gene redundancy must be
eliminated. A gene duplicate leads to a link duplicate, which
leads to the increase of the network delay.
58                                                              (IJCNS) International Journal of Computer and Network Security,
                                                                                                           Vol. 2, No. 3, March 2010

           Table 1: ATM network capacity of each link              selection method is the fitness assignment. Each individual
                                                                   in the selection pool receives a reproduction probability
     Links                                                         depending on its objective value. This fitness is used for the
                Start Node      End Node     Link Capacity
      ID                                                           selection step afterwards. Stochastic uniform selection
      1             1               4             150              mechanism is considered in this work.
      2             1               6             150              Reproduction: This step increases the number of good
                                                                   chromosomes in the next generation. This scheme
      3             1               3             225
                                                                   determines how the new individuals will be assimilated into
      4             1               2             225
                                                                   the population. Many number of reproduction operators were
      5             2               3             150              presented in the literature [3], [7].
      6             2               6             150              Crossover: This procedure exchanges genes between the
      7             2               5             150              parents. Two chromosomes are randomly selected from the
      8             3               4             150              population as parent chromosomes. Two new chromosomes
                                                                   with the genes from both the parent chromosomes are
      9             3               5             150
                                                                   obtained. A scattered function for the crossover is considered
      10            4               6             150
                                                                   in this work.
      11            6               5             150              Mutation: This step is used to have a new chromosome
      12            5               7             150              which differs from the chromosomes in the population. A
      13            6               7             150              chromosome is randomly selected as the mutated
      14            4               7             150              chromosome. In this paper, the mutation type is Gaussian
                                                                   function with Scale equal 1 and Shrink equal 1.
                                                                   Fitness Evaluation: The fitness function is computed by
4. Problem Formulation
                                                                   using the mean time delay as given in Equation 3. This
The optimization problem of the ATM network is                     fitness is based on a given objective function on level 2
implemented in a hierarchical manner. Two levels of GAs            which is the minimum time delay over the evolved network
are used.                                                          in level 1. Each chromosome in the population is assigned a
• GAs Level 1 is used to select the best network topology          specific value associated with the gene arrangement in order
    and forward it to GA Level 2. The ATM network should           to select the best individuals. Finally, the effectiveness of the
    be effectively connected such that at least half the           proposed algorithm was tested based on the GA utilization.
    network bandwidth is busy.                                     The GA utilization criterion can be computed as given in
• GAs level 2 computes the minimum delay over the                  Equation 4.
    network. In GAs level 2 we determine the (fi) parameters                           f
    for each network link (i).                                         Utilization =    i                            (4)
HGA requires number of steps for the problem formulation                               C
                                                                                         i
as shown below:                                                    Improving GA utilization in all cases will increase the flow
Encoding Mechanism: This step is used to encode the                assignment of the links for the ATM network. HGA requires
variables of the optimization problem in terms of genes. In        number of tuning parameters in accordance with GA
this work, a table was created for all pairs of links              optimization. We run GA using various population sizes in
combination. The links in the table correspond to the virtual      the two levels of HGA. The corresponding results of the
paths included between pair of nodes. In the proposed              network topology for the various population sizes are shown
algorithm each link is identified by an ID number which is         in Figures 3, 4, 5, 6, 7, 8, 9, 10 and 11.
in accordance to the row number in the table. The proposed
GAs will have 14 genes. Each gene corresponds to a link
and each link has an identified (Ci).
Initialization: This step uses the encoding method to create
a random initial population by randomly generating a
suitable number of chromosomes. In this paper, the
chromosome length equals to the number of links in the
original network.
Number of Populations: Various population sizes were used
while running GA in each level.
Selection Mechanism: Selection schemes helps in
determining the convergence properties of GAs. A selection          Figure 3. Network Topology evolved by Pop. Size L1 = 10
scheme in GAs is known as the process which favorably                                and Pop. Size L2 = 25
selects better individuals in the current population for the
mating pool [19], [20]. The selection method determines
how individuals are chosen for mating. The first step in the
                                                          (IJCNS) International Journal of Computer and Network Security, 59
                                                                                                     Vol. 2, No. 3, March 2010




                                                              Figure 8. Network Topology evolved by Pop. Size L1 = 30
Figure 4. Network Topology evolved by Pop. Size L1 = 10             and Pop. Size L2 = 75. Delay time = 10.7585
      and Pop. Size L2 = 50. Delay time = 11.0223




                                                              Figure 9. Network Topology evolved by Pop. Size L1 = 50
                                                                   and Pop. Size L2 = 25. Delay time = 10.76630
Figure 5. Network Topology evolved by Pop. Size L1 = 10
     and Pop. Size L2 = 75. Delay time = 10.76282




                                                              Figure 10. Network Topology evolved by Pop. Size L1 = 50
                                                                    and Pop. Size L2 = 50. Delay time = 10.7643


Figure 6. Network Topology evolved by Pop. Size L1 = 30
      and Pop. Size L2 = 25. Delay time = 10.8009




                                                              Figure 11. Network Topology evolved by Pop. Size L1 = 30
Figure 7. Network Topology evolved by Pop. Size L1 = 30                        and Pop. Size L2 = 75
      and Pop. Size L2 = 50. Delay time = 10.7581
60                                                                (IJCNS) International Journal of Computer and Network Security,
                                                                                                             Vol. 2, No. 3, March 2010

The HGA related parameters used in the experiments were              was presented to show the performance of the proposed
determined as shown in Table 2.                                      HGA algorithm. Figure 12 shows the convergence process of
                                                                     GAs with various population sizes for both level 1 and level
     Table 2: Parameters evolved for GA-based experiments            2.

  Operator                     Type

  Creation function            random initial with uniform
                               distribution

  Initial range                lower bound is 1 and upper bound
                               is 95% of line capacity

  Selection mechanism          Stochastic uniform

  Crossover type               Scattered function
                               Gaussian function with
  Mutation type                Scale = 1 and Shrink = 1

  Maximum generations          50


5. Experimental Results
From the developed results, the proposed HGA was able to
provide number of ATM network with various topologies.
Having a closer look to each developed structure, we can               Figure 12. The convergence process of GAs with various
find that all evolved network have seven links except one                                 population sizes
network which has 8 links (see Figure 4). This network has
the maximum delay which is expected since the number of              The algorithm converges to the optimal solution at ”high”
links increased. The evolved network were able to achieve            speed and finds a good solution in less than 20 generations
the required criteria which is specified by the designer (i.e.       of running. Moreover, the algorithm reached a solution with
increasing the network throughput to at least 50% of the             the lowest (i.e. optimal) delay in most cases. In some cases,
network capacity and manage the traffic to be with                   the algorithm finds the optimal solution very quickly;
minimum delay). The developed network could be unreliable            however, there are some cases where longer convergence
in some sense because the reduced number of links may                times are observed in order to obtain the optimal solution.
cause a problem if failure occurs in a link. This could be
another objective to investigate in the future. Of course the        6. Conclusions and Future Work
best reliable network will be the fully connected network.           A Hierarchical Genetic Algorithms (HGA) based
This will be, of course, a very expensive network to                 optimization mechanism for Asynchronous Transfer Mode
implement. The computed delay times for various population           (ATM) network has been formulated. Minimizing the total
sizes of the GA in levels 1 and 2 are shown in Table 3.              cost is mainly the purpose of the proposed approach,
                                                                     subsequently; the work addresses the maximum allowable
                                                                     flow assignment in each link while simultaneously keeping
     Table 3: Delay time for various Pop. sizes of GA levels         the overall delay within the minimum acceptable range. It
                                                                     can be inferred from the results obtained that ATM network
       Description    GAs level 1     GAs level 2   Delay time       design using HGA produces good network plans in terms of
       Pop. Size          10              25        10.81690         network throughput and GA utilization. Also, it allows more
       Pop. Size          10              50        11.02230         flexibility in the traffic management, and less complexity of
       Pop. Size          10              75        10.76282         the planning task. It is suggested to improve the current
                                                                     work by adding new issues related to dynamic capacity
       Pop. Size          30              25        10.80090
                                                                     allocation within the network. Additionally, improvement
       Pop. Size          30              50        10.75810
                                                                     can be achieved if using Parallel Genetic Algorithms
       Pop. Size          30              75        10.75850         (PGAs). This way the computation time can be reduced to a
       Pop. Size          50              25        10.76630         reasonable computational effort.
       Pop. Size          50              50        10.76430
       Pop. Size          50              75        10.76006         References
                                                                     [1] L. Painton and J. Campbell, “Genetic algorithms in
It was found that the minimum delay was achieved with                    optimization of system reliability,” IEEE Transactions
population size 30 for GA level 1 and 50 for GA level 2. In              on Reliability, vol. 44, pp. 172–178, 1995.
general, as a common practice, the convergence of the GA
                                                               (IJCNS) International Journal of Computer and Network Security, 61
                                                                                                          Vol. 2, No. 3, March 2010

[2] D. Raychaudhuri and D. Wilson, “ATM–based                          networks: Genetic algorithm and tabu search
     transport architecture for multiservices wireless                 approach,” International Journal of Computer Science,
     personal communication networks,” IEEE Journal On                 vol. 1, no. 3, 2006.
     Selected Areas In Communications, vol. 12, no. 8, pp.        [18] R. Susmi, A. M. Sherry, and B. V. Reddy, “ATM
     1401–1413, 1994.                                                  network planning: A genetic algorithm approach,”
[3] H. El-Madbouly, “Design and bandwidth allocation of                Journal of Theoretical and Applied Information
     embedded ATM networks using genetic algorithm,” In                Technology, vol. 1, pp. 74–79, 2007.
     Proceedings of World Academy of Science,                     [19] D. Thierens and D. E. Goldberg, “Convergence models
     Engineering and Technology, vol. 8, pp. 249–252,                  of genetic algorithm selection schemes,” In PPSN III:
     2005.                                                             Proceedings of the International Conference on
[4] D. W. Coit and A. E. Smith, “Reliability optimization              Evolutionary Computation. The Third Conference on
     of series-parallel systems using genetic algorithm,”              Parallel Problem Solving from Nature. London, UK:
     IEEE Transactions on Reliability, vol. 45, pp. 254–260,           Springer-Verlag, pp. 119– 129, 1994.
     1996.                                                        [20] B. L. Miller and D. E. Goldberg, “Genetic algorithms,
[5] Alaa Sheta, Mohammad Salamah and Malik Braik,”                     selection schemes, and the varying effects of noise,”
     Topology Optimization and Traffic Management in                   Evolutionary Computation. vol. 4, no. 2, pp. 113–131,
     Telecommunication Network Using Hierarchical                      1996.
     Genetic Algorithms”, In the Proceedings of
     ICICIS2009, Ain Shams Univ., Cairo, Egypt, pp. 143-          Authors Profile
     148, March, 2009.
[6] E. lbaum and M. Sidi, “Topological design of local-
     area networks using genetic algorithms,” In                                         Alaa Sheta received his B.E., M.Sc.
     IEEE/ACM Transactions on Networking, vol. 4, pp.
                                                                                         degrees in Electronics and Communication
     766–778, 1996.
[7] K. Walkowiak, “Genetic algorithms for backup virtual                                 Engineering from Faculty of Engineering,
     path routing in survivable ATM networks,” In                                        Cairo University in 1988 and          1994,
     Proceedings of MOSIS 99, vol. 2, pp. 123–130, 1999.
                                                                                         respectively. A. Sheta received his Ph.D.
[8] A. Kasprzak and K. Walkowiak, “Algorithms for flow
     assignment ATM virtual private networks,” In                                        degree    from   the    Computer     Science
     Proceedings Of First Polish-German Teletraffic               Department, School of Information Technology and Engineering,
     Symposium PGTS 2000, vol. 2, pp. 24–26, 2000.
[9] E. Alba, “Parallel evolutionary algorithms in                 George Mason University, Fairfax, VA, USA. His published work
     telecommunications: Two case studies,” In Proceedings        exceeds 70 publications between book chapters, journal papers,
     of the CACIC02, Buenos Aires, Argentina, 2002.               conferences and invited talks. His research interests include
[10] L. He and N. Mort, “Hybrid genetic algorithms for
     telecommunications network back-up routing,” BT              Evolutionary Computation, Computer Networks, Image Processing,
     Technology Journal, vol. 18, no. 4, pp. 42–50, 2000.         Software Reliability and Software Cost Estimation. Currently, Dr.
[11] L. Xian, “Network capacity allocation for traffic with
                                                                  Sheta is a Professor with the College of Computers and Information
     time priorities,” Journal of International Network
     Management, vol. 13, pp. 411–417, 2003.                      Systems and the Director of the Vision and Robotics Laboratory at
[12] C. Rose and R. Yates, “Genetic algorithms and call           Taif University, Taif, Saudi Arabia. He is on leave from the
     admission      to     telecommunications     networks,”
                                                                  Electronics Research Institute (ERI), Giza, Egypt.
     Computers and Operations Research, vol. 23, pp. 9–6,
     1996.
[13] L. Davis and Coombs, Optimizing networks link sizes                                 Malik Braik received his B.Sc. degree in
     with genetic algorithms. Modeling and Simulation
     Methodology, Knowledge System’s Paradigms,                                          Electrical Engineering from Faculty of
     Amsterdam, The Netherland: Elsevier, 1989.                                          Engineering, Jordan University of Science
[14] S. Pierre and H. H. Hoang, “An artificial intelligence                              and Technology in 2000. Five years later,
     approach for improving computer communication
     network design,” Journal Of Operational Research                                    M. Braik received his M.Sc in Computer
     Society, vol. 41, no. 5, pp. 405–418, 1990.                                         Science from Department of Information
[15] M. Gerla, J. A. S. Monteiro, and R. Pazos, “Topology
                                                                  Technology, Al-Balqa Applied University, Jordan in 2005. His
     design and bandwidth allocation in ATM nets,” IEEE.
     JSAC, vol. 7, no. 8, pp. 1253–1262, 1989.                    research interests focus on Evolutionary Computation, Image
[16] A. Sheta, M. Salamah, H. Turabieh, and H. Heyasat,           Processing, Data Security and Computer Networks. Currently,
     “Selection of appropriate traffic of a computer network
                                                                  Braik is working with the Department of Information Technology,
     with fixed topology using GAs,” International Journal
     of Computer Science, IAENG, vol. 34, no. 1, 2007.            Prince Abdullah Bin Ghazi Faculty of Science and Information
[17] S. Routray, A. Sherry, and B. Reddy, “Bandwidth              Technology, Al-Balqa Applied University, Al-Salt, Jordan.
     optimization through dynamic routing in ATM
62                                                                 (IJCNS) International Journal of Computer and Network Security,
                                                                                                              Vol. 2, No. 3, March 2010



                     Mohammad Salameh received his B.E.
                     degree in Computer Science from Faculty of
                     King Abdullah II School for Information
                     Technology (KASIT), University Of Jordan
                     in 2005, and in 2009 Mohammad received
                     his M.Sc. degree in Computer Science from
Faculty of Graduate Studies and Scientific Research, Al-Balqa`
Applied University in 2009. Mohammad Salameh is a joiner
researcher; his research interest fields are Robotics Design and
Programming, Evolutionary Computation, Computer Networks,
Image Processing. Mohammad is a Robotics Trainer and
Programmer in the National Education Center for Robotics
(NECR), King Hussein Foundation, Amman, Jordan.
                                                                     (IJCNS) International Journal of Computer and Network Security, 63
                                                                                                                Vol. 2, No. 3, March 2010




 Capacity Enhancement of 3G Cellular System using
  Switched Beam Smart Antenna with Windowed
                  Beam former
                            Prof. T. B. Lavate1, Prof. V. K. Kokate2 , Prof. Dr A. M. Sapkal 3
                                1
                                    Department of E & T/C, College of Engineering Pune, Maharashtra, India,
                                              Lavate.tb@rediffmail.com, tukaram.lavate@gmail.com
                   2
                       Department of E & T/C,Indira College of Engineering & Management, Pune, Maharashtra, India,
                                                         vkkokateetc@gmail.com
                               3
                                   Department of E & T/C, College of Engineering Pune-5, Maharashtra, India,
                                                           ams.extc@coep.ac.in

Abstract: The 3G cellular networks are being designed to                CDMA all subscribers use same frequency & this creates
provide high bit rate services, multimedia traffic, in addition to      inter-cell & intra-cell co-channel interference. Thus the
voice calls within the limited bandwidth available. The suitable        actual performance of CDMA system is still interference
solution to the bandwidth limitation is the smart antenna. The
                                                                        limited and is affected by adverse channel conditions created
smart antennas at the base station of cellular system have the
interference rejection or signal to interference plus noise             by multipath propagation. It is obvious that the capacity of
improvement capability and in turn to improve the capacity of           CDMA based wireless communication system can be
cellular system. The smart antennas can generally be classified         improved by different interference reduction techniques &
as either switched beam or adaptive array smart antenna.                that can be achieved by using smart antennas such as
However switched beam smart antenna is cheaper to implement             switched beam smart antenna (SBSA) or adaptive array
in many applications and hence investigated here much in                smart antenna . In this paper section 2. describes switched
detail.
                                                                        beam smart antenna used to improve the capacity of
      Switched beam smart antenna (SBSA) creates a group of
                                                                        CDMA cellular system.
overlapping beams that together result in omni directional
coverage. SBSA has the interference rejection capability
depending on side lobe level. The simplest way to reduce the side
lobe level and improve the SINR of SBSA is to use non adaptive
                                                                        2. Switched Beam Smart Antenna and its
windowed beam forming functions. In this paper performance of              Array Pattern
linear SBSA has been investigated using MATLAB for various
windowed beam forming functions such as Hamming, Gaussian                    2.1 Concept of SBSA
and Kaiser-Bessel functions. It has been observed that the              Depending upon the various aspects of smart antenna
Kaiser-Bessel weights provide one of which lowest array side
                                                                        technology they are categorized as switched beam smart
lobe levels still maintaining nearly the same beam width as
uniform weights and consequently Kaiser-Bessel function can             antenna and adaptive array smart antenna. Here we
widely be used with SBSA to improve the capacity of 3G cellular         investigate switched beam smart antenna in detail. The
system.                                                                 switched beam smart antenna (SBSA) has multiple fixed
                                                                        beams in different directions & this can be accomplished
  Keywords: SBSA, DS/CDMA, Windowed Beam forming                        using feed network referred to as beam former & most
                                                                        commonly used beam former is Butler matrix. In terms of
1. Introduction                                                         radiation patterns switched beam is an extension of cellular
Nowadays the wireless operators are faced with increasing               sectorization method of splitting a typical cell. That is
capacity demands for both voice & data services. To achieve             switched beam antenna increases the capacity of cellular
this, multiple access techniques such as TDMA & CDMA                    system by creating micro sectors and each micro sector
can be employed. For instance in TDMA based wireless                    contains a pre-determined fixed beam pattern with greatest
communication system (2G systems) the frequency reuse                   sensitivity located in the centre of the beam & less sensitivity
factor is normally greater than 6. That is these systems                elsewhere. The receiver selects the beam that provides
employ the frequency reuse concept which increases their                greatest signal enhancement & interference reduction.
capacity to some extent. But this frequency reuse concept               Actually SBSA enhances receive signals & switch from one
creates the co-channel interference. In CDMA systems the                beam to another as the desired user moves throughout the
frequency reuse factor is 1 which enables it to offer higher            sector. An N beam switched beam antenna generally
capacities & the capacity improvement by CDMA                           provides an N-fold antenna gain and some diversity gain by
technology may be as high as 13 times that of TDMA. But in              combining the received signal from different beams as
64                                                                      (IJCNS) International Journal of Computer and Network Security,
                                                                                                                   Vol. 2, No. 3, March 2010

shown in Fig.1.                                                            as shown in Fig. 2. It is obvious that N element SBSA forms
                                                                           N spatial channels whose input signal is given by

              Beam-1
                                                                           S = [S1 S2 S3 ------- SN ]
                                                                           (3)

        Beam-2           B                                                 where Si = √Pi*[1 e-jφi e-j2φi e-j3φi ……. e-j (N-1)φi ] is the
                         e                                                 ith user signal φi=2πd/λ*sinΦ i ; Φi is the ith user angle of
                         a
                         m                                                 arrival signal with power Pi. Taking into account an
                                                  Signal output            equation (1) and equation (3) the output of SBSA is
     Interference        f               Beam
     Signal              o               Select
                         r                                                 Y=AHS                                       =          [Y1                 Y2               Y3          ----------YN]
                         m
       Beam-3            e                                                 (4)
                         r


        Beam-4                                                             If all users are located exactly as өi = Φi; the vector Yi=[0, 0,
                                                                           0, 0, √Pi, 0, 0, --- 0]. But if өi ≠ Φi; , we have to evaluate
           Desired signal Direction                                        the maximum element of each vector to detect active users.

                                                                                                                0
            Figure 1. Switched beam smart antenna.
                                                                                                                -5

However these switched beam smart antennas have non                                                            -10
uniform gain with respect to AOA due to scalloping & they


                                                                                 Norm aliz ed power gain(dB)
                                                                                                               -15
can also have a problem with locking into the wrong beam
                                                                                                               -20
due to multi path fading or interference and provide limited
interference suppression since they can't suppress the                                                         -25

interference if it is in the same beam as the desired signal.                                                  -30
Hence switched beam smart antenna solutions work best in                                                       -35
minimal to moderate co-channel interference scenario.
                                                                                                               -40
Further they are often much less complex and are easier to
retro-fit to existing wireless technologies.                                                                   -45

                                                                                                               -50
     2.2 Signal model and array pattern of SBSA                                                                  -60        -40         -20             0         20          40        60
                                                                                                                                                       AOA
The SBSA creates a number of two way spatial channels on
a single conventional channel in frequency, time or code.                     Figure 2. SBSA Array pattern for number of antenna
Each of these spatial channels has the interference rejection                                      elements N = 8.
capabilities of the array depending on side lobe level (γ).The             It is apparent from Fig.2 that the array factor of SBSA has
steering matrix for N element SBSA is given by                             side lobe level γ= -16 dB. The presence of side lobes means
A= [a1 a2 a3 ------- aN ]                                         (1)      the array radiates in untended directions or the side lobes
                                                                           can receive the same signal from multiple angles which may
                                                                           cause fading in communication systems. These harmful side
where ai = [1 e-jΨi e-j2Ψi     e-j3Ψi ……. e-j (N-1)Ψi ] is the             lobes of SBSA can be suppressed by windowing the array
steering vector; Ψi=2πd/λ*sinөi ; өi is the ith reference                  elements also called as array weighting and is discussed in
angle, d is the spacing between the antenna elements. The                  section 3.
matrix A forms the special filters with orthogonal properties
aiH ak =N, if i=k; and aiH ak =0, if i≠k.                                  3. WINDOWED BEAM FORMERS FOR SBSA
   In practice the SBSA creates several simultaneous fixed
beams through the use of equation (1) and Butlar Matrix
                                                                                                                                              y
theory. With Butlar Matrix for SBSA of N elements the
array factor can be given as
             sin[Nπd/λ (sinө - sinөℓ)]
AF(ө) =                                                            (2)
                                                                                                                                                  Ѳ
                Nπd/λ (sinө - sinөℓ)                                                                                 wN/2    w2         w1            w1     w2        wN/2
                                                                                                                                                                                   x
                                                                                                                                                                  d
where sinөℓ = ℓλ/Nd; ℓ= ±1/2, ±3/2, ------- ± (N-1)/2. If
the element spacing is d = λ/2 the beams of SBSA are evenly
distributed over the span of 1800 and using MATLAB 7.0                     Figure 3. N Element linear antenna array with
equation (2) for N=8 is simulated and simulation results are                         weights.
                                                                 (IJCNS) International Journal of Computer and Network Security, 65
                                                                                                            Vol. 2, No. 3, March 2010

The array factor of N element uniform linear array is given
by
                                                                                         0
            sin[NΨ/2]
                                                                                                                                       Hamming window
AF(ө) =                                                     (5)
                                                                                                                                       Boxcar window
            N (sinΨ/2)
                                                                                        -10

where Ψ= kdsinө + β, β is the phase shift from element to
element. But such uniform linear array also called Boxcar                               -20
window, exhibits side lobe levels of about γ = -16 db. The
array side lobes can be suppressed by weighting or




                                                                            |A F |d B
windowing the array elements as shown in Figure 3. The                                  -30
array factor of such N linear element windowed array is
given by
                                                                                        -40

           N/2
 AFn (ө) = Σ wncos((2n-1/2)kdsinө)
                                                                                        -50
(6)
           n=1
To determine the weights wn there are number of useful
                                                                                        -60
window functions that can provide weights for each element                                -90     -60         -30       0        30          60         90
in array viz. Hamming, Gaussian, Kaiser-Bessel functions                                                                θ
etc. By carefully controlling the side lobes in windowed
                                                                    Figure 4. Array factor with Hamming weights for N=8
SBSA arrays,        most interference can be reduced to
insignificant level. But side lobe suppression is achieved at
the expense of main lobe beam width. These windowed non                   3.1.2     Gaussian weight function: The Gaussian
adaptive beam formers have advantages as:                           weights are found by Gaussian function to be

•  Cheaper to implement than adaptive beam forming,                 w (n+1)= exp((-0.5(α (n-N/2)/N/2) 2)
•  No main lobe distortions due to interference,                    (8)
•  Any level of side lobe suppression is possible with correct                where n=0,1,…,N                                      α≥2
   choice of windows.
The disadvantages of windowed beam former are:                      The Gaussian array weights can be determined using the
• Distribution and power of interference affects its                gaussian(N) command in        MATLAB. The normalized
   performance,                                                     gaussian array weights for N=8 and α=2.5 are
• Increase in main lobe beam width (∆).
                                                                     w1=1, w2=0.6766, w3=0.3098 and w4=0.0960.
     3.1 Window weight functions for SBSA
The useful window functions for SBSA are investigated               The Gaussian weighted array factor is plotted in Fig..5
below:
                                                                                        0
                                                                                                                                 Gaussian window
     3.1.1 Hamming weight function :           The Hamming
                                                                                                                                 Bxcar window
weights are chosen by                                                                 -10


w(n+1)=0.54 -0.46 cos[2πn/(N-1)]                       (7)
                                                                                      -20
             where n = 0, 1, 2, ……. ,N-1.
The hamming array weights can be found using the
                                                                          |A F |d B




                                                                                      -30
hamming(N) command in MATLAB. Array pattern for N=8
elements with normalized Hamming weights for linear array
                                                                                      -40
is plotted in Fig. 4. It is apparent that Hamming weights
provide side lobe suppression γ = -39 db at the expense of
large increase in beam width ∆=2.                                                     -50


    Table 1: Hamming normalized weights for array N=8
                                                                                      -60
                                                                                        -90     -60     -30         0       30        60           90
                                                                                                                    θ

      Weight types      w1     w2         w3        w4              Figure 5. Array factor with Gaussion weights for N=8
                                                                    It is clear that Gaussian weighted array pattern provides side
                                                                    lobe suppression γ = -48dB with increase in main lobe beam
       Hamming           1    0.673     0.2653    0.0838
                                                                    width ∆=1.85
66                                                                                         (IJCNS) International Journal of Computer and Network Security,
                                                                                                                                      Vol. 2, No. 3, March 2010

        3.1.3 Kaiser-Bessel weight function: The Kaiser                                       lobe beam width (∆=1.2) compared to Hamming and
Bessel weights are determined by                                                              Gaussian weight functions & hence Kaiser Bessel weight
                                                                                              functions are chosen to suppress the side lobes in switched
                                                                                              beam smart antenna. (SBSA)
                           I0
w (n) =
(9)                                                                                           4.                    Performance analysis of Kaiser-Bessel
                                         I0
                                                                                                                    windowed SBSA and simulation results
                                                                                              We consider the DS/CDMA system model in which the data
                                      where         n= 0,…..,N/2, α>1                         is modulated using BPSK format. The pulse and PN code
                                                                                              amplitudes are all independently and identically distributed
The Kaiser-Bessel normalized weights for N=8 are found                                        random variables. We assume that the PN code length
using the Kaiser(N,α) command in MATLAB .                                                     M=128 & the power of each mobile station is perfectly
                                                                                              controlled by the same base station BS which employs
Table 2: Kaiser-Bessel normalized weights for array                                           switched beam smart antenna.
       N=8
                                                                                              As shown in [2] the bit error rate (BER) for DS-CDMA,
                   Weight types                w1         w2         w3          w4           1200 sectorized systems is given by
                   Kaiser-Bessel               1      0.8136        0.5136     0.210

The Kaiser-Bessel weighted array factor is plotted in Fig 6                                   Pe = Q                                                                          (10)
using MATLAB; in which γ = -33 db and ∆=1.2.
                                                                                              where Eb(1)/N0 is SINR for user of interest #1, Eb(k)/N0 is the
                  0
                                                                      Kaiser-Bessel
                                                                                              same for interfering users.
                                                                      Boxcar window           We extended equation (10) to switched beam smart antenna
                 -10
                                                                                              as

                 -20
                                                                                               Pe= Q                                                                          (11)
     |A F |d B




                 -30

                                                                                              where k1 is the number of interfering users with same PN
                 -40                                                                          code like user #1 affected side lobe, k2 is the number of
                                                                                              interfering users affected main lobe & k3 is like k2 but
                                                                                              affected side lobes.
                 -50

                                                                                                                     0
                                                                                                                    10
                 -60                                                                                                                                 120 deg. sect. Antenna
                   -90          -60      -30          0        30         60          90                                                             Boxcar SBSA
                                                      θ                                                              -2                              Kaiser-Bessel SBSA
                                                                                                                    10
Figure 6. Array factor with Kaiser-Bessel weights N=8

                                                                                                                     -4
  Table 3: Important parameters of windowed beams for                                                               10
                                                                                                   Bit Error Rate




               N=8 element linear array
       Window            Beam width        γ
                                                                                                                     -6
                         (∆)             (db)                                                                       10
       Boxcar              1.0          -16
                       Hamming                        2.0              -38                                           -8
                                                                                                                    10

                       Gaussian                      1.85              -48
                       (α = 2.5)
                                                                                                                     -10
                       Kaiser-Bessel                  1.2              -33                                          10
                                                                                                                           0   2   4   6         8      10        12          14
                       (α = 3.0)                                                                                                        Eb/No dB


                                                                                              Figure 7. The BER performance for DS/CDMA and
Table3. shows that Kaiser-Bessel function provides side lobe                                  switched beam smart antenna for 100 users and N=8
suppression γ = -33dB but with minimum increase in main
                                                                   (IJCNS) International Journal of Computer and Network Security, 67
                                                                                                              Vol. 2, No. 3, March 2010

 For Boxcar (non windowed) SBSA the side lobe level (as               [5]   Md. Bhakar, Vani R. M., P. V. Hunagund, “Smart
shown in fig.2) γ = -16 db. While as Kaiser-Bessel weights                  Antennas Systems: Concepts of Beam steered Array
shown in Table 2 can be selected for SBSA so that its side                  Configurations”, Proceedings of IEEE International
lobe level (as shown in fig.6) can be reduced to γ= -33db.                  symposium on microwaves 2008, Banglore section
Using MATLAB 7.0 equation (10) and equation (11) with                 [6]   David    Cabrera,    Joel   Rodriuez,Adviser:Victor
γ= -16 db. & γ= -33db are simulated.                                        V.Zaharov, “ Switched Beam Smart Antenna BER
                                                                            Performance analysis for 3G CDMA Cellular
That is using equation (10) & (11) the simulation results are               Communication”, Polytechnic University of Puerto
presented in Fig 7. where BER as a function of Eb/N0 and                    Rico.
number of active users = 100 in the service area is plotted.
Fig. 7 presents BER of DS/CDMA system with conventional               Authors Profile
1200 sectored antenna, no windowed SBSA (N=8, γ= -16dB)
& Kaiser Bessel windowed SBSA (N=8, γ = -33dB). As
follows from Fig. 7 for the fixing level of BER, e.g. for 3G                         T.B. Lavate received ME (Microwave)
communication system acceptable BER is        Pe =10-4 , by                          degree in E&T/C in 2002 from Pune
the application of SBSA the number of active users in                                University. He is pursuing his Ph.D. in
conventional CDMA system can be increased up to 1.12                                 College of Engineering, Pune-5 affiliated to
times for no windowed SBSA antenna and up to 1.4 times                               pune university. He has published nine
with Kaiser- Bessel windowed SBSA antenna. i.e Kaiser-                               papers on wireless communication & smart
Bessel windowed SBSA antenna can increase the number of               antenna. He is member of IETE & ISTE.
active users in 3G system significantly without losing of
performance quality.
                                                                                    V. K. Kokate graduated in E & T/C from
                                                                                    University of Pune in 1973 and received his
5. Conclusion                                                                       Masters in E & T/C (Spl: Microwave) from
In this paper the performance analysis of windowed SBSA is                          the University of Pune..
investigated. The relation of BER for DS/CDMA is extended             Presently he is working as H.O.D. of E&TC Engineering
for the case of application of SBSA at base station. As a             Department of Indira College of Engineering, , Pune. having
                                                                      over 35 years experience in teaching and administrative. His
result shows, the application of Kaiser-Bessel windowed
                                                                      fields of interests are Radar, Microwaves, Antennas and
SBSA improves the BER which in turn increases the active
                                                                      EMI & C. He is a Fellow Member of IETE and Member
users in conventional CDMA system significantly & hence
                                                                      of ISTE/IEEE.
SBSA is still an attractive solution to increase the capacity of      In his credit, he has about twenty papers published in
existing 3G cellular wireless communication system.                   International/National repute Conferences/ Journals.

References                                                                            A.M.Sapkal graduated in E&TC from
                                                                                      University of Pune in 1987 and received
[1] L.C.Godara,“Application of antenna arrays to mobile                               his Masters in E & TC (Spl: Microwave)
    communications II: Beamforming & direction of                                     from the University of Pune in 1992 and
    arrival conciderations”, Preceedings of IEEE,volume                               obtained his Ph.D in 2008. Presently he is
    85,issue 8,August 1997, pages 1195-1245.                          working as Professor in Dept. of E &TC Engineering of
[2] T. S. Rappaport,“ Smart antennas for wireless                     College of Engineering, Pune. Having, over 20 years
    communications,” Prentice Hall, India 2005.                       experience in teaching, his fields of interests are power
[3] Frank Gross ,“ Smart antennas for wireless                        electronics, microwaves, and image processing. He is a
    communication,” McGraw-Hill, New York 2005                        member of ISTE, IETE & IEEE.
[4] J. C. Liberti, T. S. Rappaport, “Smart antennas for               In his credit, he has about twenty five papers published in
    wireless communications: IS-95 and Third Generation               National / International repute Conferences/Journals.
    CDMA Applicatons”, Prentice Hall PTR, New Jersey
    1999..
68                                                               (IJCNS) International Journal of Computer and Network Security,
                                                                                                            Vol. 2, No. 3, March 2010


          DDOM: The Dynamic Data Oriented Model for
                 Image Using Binary Tree
          A.Shahrzad Khashandarag1*, A.Mousavi2, R.Aliabadian3, D. Kheirandish4 and A.Ranjide Rezai5
                              1
                               Young Researchers Club of Tabriz, Islamic Azad University Tabriz Branch,
                                                             Tabriz-Iran
                                                      1
                                                        a.shahrzad@iaut.ac.ir
            2                                  3                         4                                 5
                alireza.mousavi499@gmail.com       ramin.ali@gmail.com       kheyrandish@iaupmogan.ac.ir       aranboy@gmail.com


                                                                     GIF (Graphics Interchange Format) is an 8-bit-per-pixel
     Abstract: This paper presents a dynamic data oriented
model (DDOM) of image. The ability of model is very fast image       bitmap image format that was introduced by CompuServe in
processing against Data oriented Model that Habibizad and            1987 and has since come into widespread usage on the
cooperators proposed in [8]. In our approach, the Sobel              World Wide Web due to its wide support and portability.
algorithm is used for edge detection of image and histogram
thresholding is used for clustering of image and binary tree is      The format uses a palette of up to 256 distinct colors from
used for anatomy of model. Each node of this tree represents the     the 24-bit RGB color space. GIF images are compressed
feature of image or sub image. By using the presented model in       using the LZW lossless data compression technique to
this paper, tasks as measuring similarity ratio, segmentation,       reduce the file size without degrading the visual quality
clustering … can be done with high desired precision and             [10].
corresponding speed [8].
   Keywords: Data oriented modeling; Image Segmentation;             In computing, JPEG (pronounced JAY-peg) is a commonly
histogram thresholding; Binary Tree.                                 used standard method of compression for photographic
                                                                     images. The name JPEG stands for Joint Photographic
1. Introduction                                                      Experts Group, the name of the committee who created the
Recently many researchers have been studied on data                  standard. The group was organized in 1986, issuing a
structures for image processing tasks. In [1-7] has been             standard in 1992, which was approved in 1994 as ISO
explained the data structures of images. The main idea of            10918-1. The compression method is usually lossy
this paper is to present an optimized and dynamic data               compression, meaning that some visual quality is lost in the
oriented model of image. Dynamic Data Oriented Modeling              process, although there are variations on the standard base
(DDOM) is an approach which models concepts by using                 line JPEG, which are lossless. There is also an interlaced
the data structure. We have introduced dynamic data                  "progressive" format, in which data is compressed in
oriented modeling of image for fast image processing. The            multiple passes of progressively higher detail. This is ideal
Conventional methods use the color of the pixels to model            for large images that will be displayed whilst downloading
the image and try to reduce the size of image (Compression)          over a slow connection, allowing a reasonable preview
[8]. Previous image models are:                                      before all the data has been retrieved [11].

      •   BMP                                                        DOM (Data Oriented Model) proposed by Habibizad and
      •   JPEG                                                       cooperators. This model is design for tasks that are very fast.
                                                                     In the related works section, this model will be explained.
      •   GIF
      •   DOM
                                                                     2. Related Works
.BMP or .DIB (device-independent bitmap) is a bitmapped              In this paper we want to optimize the model of DOM which
graphics format used internally by the Microsoft Windows             the Habibizad and cooperators proposed in [8]. Habibizad
and OS/2 graphics subsystem (GDI), and used commonly as              and cooperators in [8] proposed:
a simple graphics file format on those platforms. This
format is in two parts, Part one, is the data, which indicate
whole image features including width, height, color palette              2.1 Data Oriented Modeling
etc. The second part consists a block of bytes that describes        Habibizad and cooperators suppose that Fig1 is the image
the image, pixel by pixel. Pixels are stored starting in the         for data oriented modeling. Fig. 2 shows ADBT of Fig. 1.
bottom left corner going from left to right and then row by          ADBT is Average-Difference-Binary-Tree-of-Image which
row from the bottom to the top. Each pixel is described              is stored in an array. This ADBT has three levels, numbered
using one or more bytes [9].                                         as 0, 1 and 2. The features of pixels are stored in the leaves.
                                                                     Features of F are obtained by combining features of A and
                                                                     C. In the same way, features of G are obtained from B and
                                                            (IJCNS) International Journal of Computer and Network Security, 69
                                                                                                       Vol. 2, No. 3, March 2010

D. finally features of the entire image, E, are obtained by     Fig. 6 shows segmented of Fig. 5. This segmented image is
combining features of F and G. By putting F and G together,     created with histogram thresholding. Fig. 7 shows the
we can achieve smooth of original image as is shown in Fig.     reverse N for image processing in this model. Fig. 8 shows
3 [8].                                                          ADBT of Fig. 6. This ADBT has three levels, numbered as
                                                                0, 1 and 2. The features of regions are stored in the leaves.
Fig. 4 shows the array, which stores the ADBT of Fig. 2.        Features of L0 are obtained by combining features of R0 and
                                                                R1. In the same way, features of L1 are obtained from R2
                                                                and R3. Finally features of the entire image, L2, are
                                                                obtained by combining features of L0 and L1. By putting L0
                                                                and L1 together, we can achieve smooth of original image
                                                                as is shown in Fig. 9. Fig. 10 shows the ADBT of Fig. 6 that
                                  1
                 Figure 1. an   I 2 Image [8].                  has been stored in an array.

                                                                In Fig.8 A and B and D have the similar intensity.


                                                                     3.2   Edge detection with Sobel Algorithm
                                                                Edges characterize boundaries and are therefore a problem
                                                                of fundamental importance in image processing. Edges in
                                                                imag-

                                       1
            Figure 2. ADBT of an      I2   image [8].




           Figure 3. Smoothed of original image [8].
                                                                                Figure 6. a segmented image.




        Figure 4. ADBT of Fig. 2 stored in an array [8].

For ease of understanding, mentioned steps are described
top to down; but for enhancing speed of making ADBT, it
will be created down to top [8]. After that leaves will be
initialized by values of produced vector. Therefore, count of
leaves is equal to count of pixels of image. Each leaf is
corresponded to a pixel of original image and its A and D
are same as the pixel’s color. For each non-leaf node, A is
equal to average of its children’s A and D is equal to
difference of its children’s A [8].
                                                                        Figure 7. the reverse N for image processing.

3. Our Works

    3.1      Dynamic Data Oriented Modeling
This paper presents a dynamic data oriented model
(DDOM) of image. To illustrate the concept, Fig. 5 shows a
3 3 images, which have nine pixels, labeled A, B, C, D, E, F,
G, H and I respectively.


                                                                                   Figure 8. ADBT of Fig.8




                                                                             Figure 9. Smoothed of original image
                 Figure 5. An instance Image
70                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010




         Figure 10. ADBT of Fig. 8 stored in an array

-es are areas with strong intensity contrasts – a jump in
intensity from one pixel to the next. Edge detecting an
image significantly reduces the amount of data and filters
out useless information, while preserving the important
structural properties in an image. There are many ways to
perform edge detection. However, the majority of different
methods may be grouped into two categories, gradient and
Laplacian. The gradient method detects the edges by looking
for the maximum and minimum in the first derivative of the
image. The Laplacian method searches for zero crossings in
the second derivative of the image to find edges [12].

The Sobel operator performs a 2-D spatial gradient
measurement on an image. The Sobel operator is shown in
Fig. 11.
                                                                         Figure 12. Edge detection with Sobel algorithm
Note: G is Gradient and f is Image.
                                                                      4.3    Image Segmentation Algorithm
                                                                 According to the S. Arora and cooperator’s results in article
                                                                 [13], segmentation algorithm is:

                                                                 Following steps describe the proposed algorithm for image
                                                                 segmentation:

                                                                      1. Repeat step 2–6,               times; where n is the
                 Figure 11. Sobel Operator.                               number of thresholds.
                                                                      2. Range R = [a, b]; initially a = 0 and b = 255.
                                                        (1)           3. Find mean and standard deviation            of all the
                                                        (2)               pixels in R.
                                                                      4. Sub-ranges’ boundaries and are calculated as
                                                                                         and                                  ;
                                                                          where and are free parameters.
                                                                      5. Pixels with intensity values in the interval [       ]
                                                        (3)
                                                                          and [      ] are assigned threshold values equal to
                                                        (4)               the respective weighted means of their values.
                                                                      6. a = T1 + 1 ; b = T2 − 1 .
                                                                      7. Finally, repeat step         5    with               and
                                                                          with            .
                                                        (5)
                                                                 In Fig13 shown the result of image segmentation algorithm.
                                                        (6)      Also in Fig14 the result of histogram Lena is shown.

In Fig. 12 Shown the result of Sobel algorithm:
                                                                 4. Conclusion
                                                                 In this paper, a dynamic data oriented model for image is
                                                                 introduced which models image as a binary tree. Each node
                                                                 of this tree represents the feature of image or sub image. By
                                                                 using the presented model in this paper, tasks as measuring
                                                                 similarity ratio, segmentation, clustering … can be done
                                                                 with high desired precision and corresponding speed.
                                                                  (IJCNS) International Journal of Computer and Network Security, 71
                                                                                                             Vol. 2, No. 3, March 2010

                                                                          segmentation through a fast statistical recursive
                                                                          algorithm", pattern recognition letters 29 (2008) 119-
                                                                          125, published by Elsevier.

                                                                     Authors Profile
                                                                                        Asghar Shahrzad Khashandarag received the
                                                                                        B.S. degree in computer engineering from the
                                                                                        Payame Noor University Bonab Branch, Iran, in
                                                                                        2008, and the M.S. degree in computer
                                                                                        engineering from the Islamic Azad University
                                                                                        Tabriz Branch, Iran, in 2009, respectively.
                                                                     From 2008, he works as a researcher with the Young Researchers
                                                                     Club of Tabriz. He has published more than 10 papers in various
                                                                     journals and conference proceeding. His research interests include
 Figure 13. Results: Lena (a) Lena gray, (b) histogram, (c) 2        image processing, signal processing, wireless sensor network.
  level thresholding, (d) 4 level, (e) 6 level and (f) 8 level.
                                                                                      Alireza Mousavi received his B.Sc. in computer
                                                                                      engineering, software Engineering, from
                                                                                      Allameh     Mohaddes      Nouri     University,
                                                                                      Mazandaran, Iran, in 2008, and the M.S. degree
                                                                                      in computer engineering from the Islamic Azad
                                                                                      University Tabriz Branch, Iran, in 2010,
                                                                     respectively. His research interests include image processing,
                                                                     Residue Number systems, wireless sensor network.



                  Figure 14. Result of Histogram                                       Ramin Aliabadian received the B.Sc. degree in
                                                                                       computer engineering from the Shomal
                                                                                       University, Amole, Iran, in 2008, and the M.S.
                                                                                       degree in computer engineering from the Islamic
                                                                                       Azad University Arak Branch, Iran, in 2010,
References                                                                             respectively. His research interests include
[1] Zhiyong Wang, Dagan Feng, and Zheru Chi, “Region-                image processing, computer architecture, computer networks.
       Based Binary Tree Representation For Image
       Classification”, IEEE International Conference on
       Neural Networks & Signal Processing, Nanjing,
       China, 2003.
[2]    Xiaolin Wu, “Image Coding by Adaptive Tree-
       Structured Segmentation”, IEEE Transactions on                                  Davar Kheirandish Taleshmekaeil received
       Information Theory, VOL. 38, NO. 6, 1992.                                       the B.Sc. degree in Computer Hardware
[3]    G.S.Seetharaman, B.Zavidovique, “Image Processing in                            engineering from the Allameh Mohaddes Nouri
       a Tree of Peano Coded Images”, Computer Architecture                            University, Mazandaran, Iran, in 2008, and the
       for Machine Perception, 1997.CAMP’97. Proceeding                                M.S. degree in computer engineering from
       Fourth IEEE International Workshop on.
[4]    M. Kunt, M. Benard, and R. Leonardi, “Recent results                            the Islamic Azad University Tabriz Branch,
       in highcompression image coding”, IEEE Transaction            Tabriz, Iran, in 2010, respectively. His research interests include
       Circuits Syst., vol. CAS- 34, no. 11, pp. 1306-1336,          image processing, computer architecture, computer networks.
       Nov 1987.
[5]    R. Leonardi and M Kunt, “Adaptive split-and-merge for
       image analysis and coding”, Proc. SPIE, vol. 594, 1985.
[6]    G. J. Sullivan and R. L. Baker, “Efficient quadtree
       coding of images and video”, in ICASSP Proc., May                               Ali Ranjide Rezai received the B.Sc. degree in
       1991, pp. 2661-2664.                                                            computer engineering from the Shomal
[7]    J. Vaisey and A. Gersho, “Image compression with                                University Amole, Iran, in 2008, and the M.S.
       variable block size segmentation”, IEEE Trans. Signal
       Processing, vol. SP-40, pp.2040- 2060, Aug. 1992.                               degree in computer engineering from the
[8]    A. Habibizad Navin, A. Sadighi, M. Naghian                                      Islamic Azad University Tabriz Branch, Iran, in
       Fesharaki, M. Mirnia, M. Teshnelab, and R. Keshmiri,                            2010, respectively. His research interests
       "Data Oriented Model of image : as a framework for            include image processing, computer architecture.
       image processing", World Academy of Science,
       Engineering and Technology 34 2007
[9]    http://en.wikipedia.org/wiki/Windows_bitmap
[10]   http://en.wikipedia.org/wiki/GIF
[11]   http://en.wikipedia.org/wiki/JPEG
[12]   http://www.pages.drexel.edu/~weg22/edge.html
[13]   S. Arora, J. Acharya , A. Verma, Prasanta K.
       Panigrahi, " Multilevel thresholding for image
72                                                              (IJCNS) International Journal of Computer and Network Security,
                                                                                                           Vol. 2, No. 3, March 2010




       Comprehensive Analysis and Enhancement of
       Steganographic Strategies for Multimedia Data
                Hiding and Authentication
                               Ali Javed, Asim Shahzad, Romana shahzadi, Fahad Khan

                                     Faculty of Telecommunication and Information Engineering
                                     University of Engineering and Technology Taxila Pakistan
                      ali.javed@uettaxila.edu.pk, asim.shahzad@uettaxila.edu.pk, fahad.khan@uettaxila.edu.pk


Abstract: This research paper focuses on the analysis and           wish to plan an escape from jail.
enhancement of steganographic strategies for multimedia data
hiding authentication. Based on an authentication game
between an image and its authorized receiver, and an opponent,
security of authentication watermarking is measured by the
opponent's inability to launch a successful attack. In this work,
we consider two stages of data hiding mechanism: Hiding the
data in an image along with conditional security and detecting
the hidden data. First we detect whether there exists a hidden
message within the image and then applying the conditional
security mechanism, we extract that hidden message. We
propose a novel security enhancement strategy that results in
efficient and secure LSB-based embedding and verification
phenomenon. Both theoretical analysis and experimental results
are presented. They show that using our approach, protection is                    Figure 1. Stenography Process
achieved without significant increase in image size and color
distortion, and without sacrificing the image or video quality.     However, the prison warden, Ward, can monitor any
                                                                    communication between Alice and Bob, and if he detects any
Keywords: Steganography, LSB, Stego image, Stego key,               hint of “unusual" communications, he throws them both in
payload, Watermarking, Covert Communication                         solitary confinement. Alice and Bob must then transmit their
                                                                    secret plans so that nothing in their communication seems
1. Introduction                                                     unusual" to Ward. There have been many proposed solutions
                                                                    to this problem, ranging from rudimentary schemes using
The word steganography literally means covered writing as           invisible ink to a protocol which is provably secure assuming
derived from Greek. It includes a vast array of methods of          that one-way functions exist.
secret communications that conceal the very existence of the
message. Among these methods are invisible inks, microdots,
character arrangement (other than the cryptographic methods
of permutation and substitution), digital signatures, covert
Channels and spread-spectrum                communications.
Steganography is the art of concealing the existence of
information within seemingly inoffensive carriers.
Steganography can be viewed as parallel to cryptography.
Both have been used throughout recorded history as means to
protect information. At times these two technologies seem to
converge while the objectives of the two differ.
Cryptographic techniques "scramble" messages so if
intercepted, the messages cannot be understood.
Steganography, in an essence, "camouflages" a message to
hide its existence and make it seem "invisible" thus
concealing the fact that a message is being sent altogether.                 Figure 2. General Model of Steganography
An encrypted message may draw suspicion while invisible
messages will not [1]. Steganography refers to the problem of       2. Literature Survey
sending messages hidden in “innocent looking"
communications over a public channel so that an adversary           2.1 Steganography Techniques
eavesdropping on the channel cannot even detect the presence
                                                                    2.1.1 Physical steganography
of the hidden messages. Simmons gave the most popular
                                                                    Steganography has been widely used including recent
formulation of the problem: two prisoners, Alice and Bob[2],
                                                                    historical times and the present day. Possible permutations
                                                                 (IJCNS) International Journal of Computer and Network Security, 73
                                                                                                            Vol. 2, No. 3, March 2010

are endless and known examples include                               • Chaffing and winnowing.
•Hidden messages within wax tablets: in ancient Greece,              • Mimic functions convert one file to have the statistical
people wrote messages on the wood, and then covered it with          profile of another. This can thwart statistical methods that
wax upon which an innocent covering message was written.             help brute-force attacks identify the right solution in a
• Hidden messages on messenger's body: also in ancient               ciphertext-only attack.
Greece. Herodotus tells the story of a message tattooed on a         • Concealed messages in tampered executable files,
slave's shaved head, hidden by the growth of his hair, and           exploiting redundancy in the i386 instruction set.
exposed by shaving his head again. The message allegedly             • Pictures embedded in video material (optionally played at
carried a warning to Greece about Persian invasion plans.            slower or faster speed).
This method has obvious drawbacks such as delayed                    • Injecting imperceptible delays to packets sent over the
transmission while waiting for the slave's hair to grow, and         network from the keyboard. Delays in key presses in some
its one-off use since additional messages requires additional        applications (telnet or remote desktop software) can mean a
slaves. In WWII, the French Resistance sent some messages            delay in packets, and the delays in the packets can be used to
written on the backs of couriers using invisible ink.                encode data.
• Hidden messages on paper written in secret inks, under             •Content-Aware Steganography hides information in the
other messages or on the blank parts of other messages.              semantics a human user assigns to a datagram. These systems
• Messages written in morse code on knitting yarn and then           offer security against a non-human adversary/warden.
knitted into a piece of clothing worn by a courier.                  •Blog-Steganography. Messages are fractionalized and the
• Messages written on the back of postage stamps.                    (encrypted) pieces are added as comments of orphaned web-
                                                                     logs (or pin boards on social network platforms). In this case
2.1.2 Digital steganography
                                                                     the selection of blogs is the symmetric key that sender and
Modern steganography entered the world in 1985 with the advent
                                                                     recipient are using; the carrier of the hidden message is the
of the personal computer applied to classical steganography
problems. Development following that was slow, but has since
                                                                     whole blogosphere.
taken off, going by the number of 'stego' programs available: Over
                                                                     2.2 Types of Steganography
725 digital steganography applications have been identified by the
Steganography Analysis and Research Center.                          Pure Steganography
                                                                     Pure steganography is where you only need to know the
                                                                     technique to be able to read off the message.
                                                                     Private Steganography
                                                                     Private Steganography requires you to know a password as
                                                                     well as the technique.
                                                                     Public steganography
                                                                     Public steganography is like public key cryptography - you
                                                                     have a public and private key and knowledge of the
                                                                     technique. A standard library for pure steganography isn't so
                                                                     smart - because it would allow people to simply try the
                                                                     techniques.

                                                                     2.3 Image Steganography
                   Figure 3. Cover Image
                                                                     Steganography is the art of hiding the fact that
Here a cover Image of a tree is shown in fig. 3. By removing
                                                                     communication is taking place, by hiding information in
all but the last 2 bits of each color component, an almost
                                                                     other information. Many different carrier file formats can be
completely black image results. Making the resulting image
                                                                     used, but digital images are the most popular because of their
85 times brighter results in the image below.
                                                                     frequency on the Internet.
                                                                     For hiding secret information in images, there exist a large
                                                                     variety of steganographic techniques some are more complex
                                                                     than others and all of them have respective strong and weak
                                                                     points.
                                                                     As stated earlier, images are the most popular cover objects
                                                                     used for steganography. In the domain of digital images many
                                                                     different image file formats exist, most of them for specific
                                                                     applications. For these different image file formats, different
                                                                     steganographic algorithms exist.

                                                                     2.4 Image Compression
                    Figure 4. Stego Image                            When working with larger images of greater bit depth, the
                                                                     images tend to become too large to transmit over a standard
Digital steganography techniques include:                            Internet connection. In order to display an image in a
• Concealing messages within the lowest bits of noisy images         reasonable amount of time, techniques must be incorporated
or sound files.                                                      to reduce the image’s file size. These techniques make use of
• Concealing data within encrypted data. The data to be              mathematical formulas to analyze and condense image data,
concealed is first encrypted before being used to overwrite          resulting in smaller file sizes. This process is called
part of a much larger block of encrypted data.
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compression. In images there are two types of compression,
Lossy and Lossless. Both methods save storage space, but the
procedures that they implement differ. Lossy compression
creates smaller files by discarding excess image data from the
original image. It removes details that are too small for the
human eye to differentiate, resulting in close approximations
of the original image, although not an exact duplicate. An
example of an image format that uses this compression
technique is JPEG (Joint Photographic Experts Group).
Lossless compression, on the other hand, never removes any
information from the original image, but instead represents
data in mathematical formulas. The original image’s integrity
is maintained and the decompressed image output is bit-by-
bit identical to the original image input. The most popular
image formats that use lossless compression is GIF
(Graphical Interchange Format) and 8-bit BMP (a Microsoft                        Figure 5. Main Flow Diagram
Windows bitmap file).
                                                                 3.2 Text in Image Flow Diagram
2.5 Video Steganography
Since a video can be viewed as a sequence of still images,
video steganography can be viewed simply as an extension of
image steganography. The internet and the World Wide Web
have revolutionaries the way in which digital data is
distributed. The widespread and easy access to multimedia
content has motivated development of technologies for digital
steganography or data hiding, with emphasis on access
control, authentication, and copyright protection.
Steganography deals with information hiding, as opposed to
encryption. Much of the recent work in data hiding is about
copyright protection of multimedia data. This is also referred
to as digital watermarking. Digital watermarking for
copyright protection typically requires very few bits, of the
order of 1% or less of the host data size. These watermarks
could be alpha-numeric characters, or could be multimedia
data as well.
One of the main objectives of this watermarking is to be able
to identify the rightful owners by authenticating the
watermarks. As such, it is desirable that the methods of
embedding and extracting digital watermarks are resistant to
typical signal processing operations, such as compression,
and intentional attacks to remove the watermarks.
While transparent or visible watermarks are acceptable in
many cases, hidden data for control or secure communication
need to be perceptually invisible. The signature message data
is the data that we would like to embed or conceal. The
source data is used to hide the signature data; we often refer
to the source as the host data. After embedding a signature in
to a host, we get the watermarked or embedded data. The
recovered data, also referred to as the reconstructed data, is
the signature that is extracted from the embedded data. [11]
                                                                             Figure 7. Text in Image flow Diagram
3. Proposed Methodology                                          3.3 Image in Image Flow diagram
3.1 Proposed Main Flow Diagram
The proposed methodology in this work is to embed the stego
message into image and video using LSB Technique.
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                                                                                              Vol. 2, No. 3, March 2010

                                                      3.5 LSB Technique
                                                      The most widely used technique to hide data is the usage of
                                                      the LSB- Least Significant Bit technique. Least Significant
                                                      Bit insertion method is a simple approach to embed
                                                      information in a cover file [11]. The LSB is the lowest order
                                                      bit in a binary value. This is an important concept in
                                                      computer data storage and programming that applies to the
                                                      order in which data are organized, stored or transmitted [12].
                                                      Usually, three bits from each pixel can be stored to hide an
                                                      image in the LSBs of each byte of a 24-bit image.
                                                      Consequently, LSB requires that only half of the bits in an
                                                      image be changed when data can be hidden in least and
                                                      second least significant bits and yet the resulting stego-image
                                                      which will be displayed is indistinguishable to the cover
                                                      image to the human visual system [11].
                                                      When using a 24-bit image, a bit of each of the red, green
                                                      and blue color components can be used, since they are each
                                                      represented by a byte. In other words, one can store 3 bits in
                                                      each pixel.
                                                      An 800 × 600 pixel image, can thus store a total amount of
                                                      1,440,000 bits or 180,000 bytes of embedded data [13]. For
                                                      example a grid for 3 pixels of a 24-bit image can be as
                                                      follows:
                                                      (00101101 00011100 11011100)
         Figure 7. Image in Image flow Diagram        (10100110 11000100 00001100)
                                                      (11010010 10101101 01100011)
3.4 Text in Video Flow Diagram                        When the number 200, which binary representation is
                                                      11001000, is embedded into the least significant bits of this
                                                      part of the image, the resulting grid is as follows:

                                                      (00101101 00011101 11011100)
                                                      (10100110 11000101 00001100)
                                                      (11010010 10101100 01100011)

                                                      Although the number was embedded into the first 8 bytes of
                                                      the grid, only the 3 underlined bits needed to be changed
                                                      according to the embedded message. On average, only half of
                                                      the bits in an image will need to be modified to hide a secret
                                                      message using the maximum cover size [13]. Since there are
                                                      256 possible intensities of each primary color, changing the
                                                      LSB of a pixel results in small changes in the intensity of the
                                                      colors. These changes cannot be perceived by the human eye -
                                                      thus the message is successfully hidden. With a well-chosen
                                                      image, one can even hide the message in the least as well as
                                                      second to least significant bit and still not see the difference.
                                                      In the above example, consecutive bytes of the image data –
                                                      from the first byte to the end of the message – are used to
                                                      embed the information. This approach is very easy to detect
                                                      [14]. A slightly more secure system is for the sender and
                                                      receiver to share a secret key that specifies only certain pixels
                                                      to be changed. Should an adversary suspect that LSB
                                                      steganography has been used, he has no way of knowing
                                                      which pixels to target without the secret key [15].
                                                      In its simplest form, LSB makes use of BMP images, since
                                                      they use lossless compression. Unfortunately to be able to
                                                      hide a secret message inside a BMP file, one would require a
                                                      very large cover image.


            Figure 8. Text in Video Flow Diagram      3.6 Implementation of LSB Technique
                                                      To illustrate implementation of LSB technique, consider the
                                                      following image of parrots showing true colors Palette of the
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                                                                                                         Vol. 2, No. 3, March 2010

Image                                                             resulting difference between the new from the original color
                                                                  value is called the embedding error. Since there are only
                                                                  three LSB’s for each pixel, the total number of bits that can
                                                                  be hidden is only three times the total number of pixels
                                                                  having the dimensions 768x512.

                                                                  4. Simulation and Results
                                                                  Following images were taken and processed by the
                                                                  application of Digital Steganography and the results are as
                                                                  following:

                                                                  4.1 Procedure for Text in Image hiding
         Figure 9. Parrot (True Color Palette Image)              The procedure is started with opening the image in which
This image is composed of red, green, and blue color              you want to hide the data and then enter the stego message in
channels. The pixel at the top-left corner of the picture has     the specified space. The image is shown in fig.11and the
the values 122, 119, and 92 for its red, green, and blue color    stego message is shown in the text box.
components respectively. In binary, these values may be
written as:

01111010 01110111 01011100




                                                                                     Figure 11. Open Image

                                                                  The stego message is then merged into the original image as
                                                                  shown in fig. 12.




  Figure 10. Red, Green and Blue color channels of Parrot
                          Image

To hide the character “a” in the image, the LSB (the
rightmost bit) of each of the three 8-bit color values above
will be replaced with the bits that form the binary equivalent
of the character “a” (i.e., 01100001). This replacement
operation is generally called embedding. After embedding,
the color value would now change to:
01111010 1110111 01011101
Since there are only three values, only three of the eight bits                      Figure 12. Merge Text
of the character “a” can fit on this pixel. Therefore the         The stego message is detected on the receiving end as shown
succeeding pixels of this image will also be used. In the three   in fig. 13.
color values shown above, only the last value actually
changed as a result of LSB encoding, which means almost
nothing has changed in the appearance of the image.
Nevertheless, even in case wherein all LSB’s are changed;
most images would still retain their original appearance
because of the fact that the LSB’s represent a very minute
portion (roughly 1/255 or 0.39%) of the whole image. The
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                                                                                                         Vol. 2, No. 3, March 2010

                                                                  mountain on the left is the original image in which the stego
                                                                  image will be embedded.




                      Figure 13. Detect
                                                                                     Figure 16. Open Images
The stego message is finally extracted as shown in the text
box in fig. 14                                                    For merging the stego image in the original image user has to
                                                                  enter the password and then the stego image embeds into the
                                                                  original image.




                     Figure 14. Extract

The difference between the original image and the image                              Figure 17. Merge Image
after insertion of stego message is shown in fig. 15. The two
images look exactly the same which is why image                   On the receiving end the stego image can be recovered by
steganography is so important and useful in hiding data or        entering the password as shown in fig. 18.
sending secret messages




                                                                                   Figure 18. Enter Password

                 Figure 15. View Difference                       The stego image is finally extracted after entering the
                                                                  password as shown in fig. 19

4.2 Procedure for Image in Image stenography
In this phase the stego message is also image. The image of a
cat in fig. 16 is a stego image in this case and the image of a
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                                                                                                       Vol. 2, No. 3, March 2010




                 Figure 19. Extract Image

The difference between the original image and the image                            Figure 22. View Frames
after insertion of stego message is shown in fig. 20. The two
images look exactly the same.                                   The stego text is added to be embedded in the video as shown
                                                                in fig. 23




                Figure 20. View Difference

4.3 Procedure for Text in Video stenography
                                                                                     Figure 23. Add Text
In this phase the stego message is embedded in the video, as
you can see in fig. 21 the video is added to enter the stego    The stego text is detected as shown in fig. 24
message.




                                                                                    Figure 24. Detect text
                   Figure 21. Add Video
The frames can be viewed in the fig. 22                         Finally the stego data is extracted on the receiving end as
                                                                shown in fig. 25
                                                                  (IJCNS) International Journal of Computer and Network Security, 79
                                                                                                             Vol. 2, No. 3, March 2010

                                                                      [11] N. F. Johnson, S. Jajodia, “Exploring Steganography: Seeing
                                                                           the Unseen,” IEEE Computer, February 1998, pp.26-34.
                                                                      [12] Julie K. Petersen, The Telecommunications Illustrated
                                                                           Dictionary, CRC Press, 2002, ISBN: 084931173X.
                                                                      [13] Krenn, R., “Steganography and Steganalysis”.
                                                                      [14] Wang, H & Wang, S, “Cyber warfare: Steganography vs.
                                                                           Steganalysis”, Communications of the ACM, 47:10, October
                                                                           2004
                                                                      [15] Anderson, R.J. & Petitcolas, F.A.P., “On the limits of
                                                                           steganography”, IEEE Journal of selected Areas in
                                                                           Communications, May 1998
                                                                      [16] E. Kawaguchi and R. O. Eason :"Principle and applications of
                                                                           BPCS-Steganography", Proceedings of SPIE: Multimedia
                                                                           Systems and Applications, Vol.3528, pp.464-463, 1998.


                       Figure 25. Extract
                                                                      Author Profile
5. Conclusion
                                                                                           Engr. Ali Javed is serving as a Lecturer in
Thus we conclude that steganographic techniques can be                                     Software Engineering Department at
used for a number of purposes along with the covert                                        University of Engineering & Technology
communication or deniable data storage, Confidential                                       Taxila, Pakistan since September, 2007.
communication, Protection of data alteration, Secret data                                  He has received his MS degree in Computer
storing, Media Database systems, Copyright Protection,                                     Engineering from the University of
Feature Tagging and perhaps most importantly digital                                       Engineering & Technology Taxila, Pakistan
watermarking. A digital watermark is invisible to the eye,            in January, 2010. He has received B.Sc. degree in       Software
undetectable without the appropriate secret key, but contains         Engineering from University of Engineering & Technology Taxila,
                                                                      Pakistan, in September, 2007. His areas of interest are Digital
small ownership identification. A much wider field of
                                                                      Image Processing, Computer vision, Video Summarization,
steganography is digital Steganography allows copyright
                                                                      Machine Learning, Software Design and Software testing.
owners to incorporate into their work identifying information
invisible to human eye, yet protecting against the dangers of
copyright infringement.

References

[1] Neil F. Johnson, Zoran Duric, Sushil Jajodia, Information
     Hiding: Steganography and Watermarking - Attacks and
     Countermeasures Kluwer Academic Press, Norwrll, MA,
     New York, The Hague, London, 2000.
[2] G. Simmons, \The prisoners problem and the subliminal
     channel," CRYPTO, pp. 51{67, 1983.
[3] C. Kurak, J. McHugh, "A Cautionary Note On Image
     Downgrading," IEEE Eighth Annual Computer Security
     Applications Conference, 1992. pp. 153-159.
[4] Tuomas Aura, "Invisible Communication," EET 1995,.
[5] Warren Zevon, Lawyers, Guns, and Money. Music track
     released in the albums Excitable Boy, 1978; Stand in the Fire,
     1981; A Quiet Normal Life, 1986; Learning to Flinch, 1993.
[6] David Kahn, The Codebreakers, The Macmillan Company.
     New York, NY 1967. [Kurak92] C. Kurak, J. McHugh, "A
     Cautionary Note On Image Downgrading," IEEE Eighth
     Annual Computer Security Applications Conference, 1992.
     pp. 153-159.
[7] Herbert S. Zim, Codes and Secret Writing, William Marrow
     and Company. New York, NY, 1948.
[8] Anderson, R.J. & Petitcolas, F.A.P., “On the limits of
     steganography”, IEEE Journal of selected Areasin
     Communications, May 1998
[9] Owens, M., “A discussion of covert channels and
     steganography”, SANS Institute, 2002
[10] Johnson, N.F. & Jajodia, S., “Steganalysis of Images Created
     Using Current Steganography Software”, Proceedings of the
     2nd Information Hiding Workshop, April 1998
80                                                                   (IJCNS) International Journal of Computer and Network Security,
                                                                                                                Vol. 2, No. 3, March 2010


           Modeling and Simulation of Synchronous Buck
           Converter for PMG in Low Power Applications
                                   R. Bharanikumar1, A. Nirmal Kumar2 and K.T. Maheswari3.
1, 2, 3,
           Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Anna University, Tamil Nadu, India
                                                                         .
                                       E-mail: bharanikumar.rbk@rgmail.com, maheswarikt@gmail.com


Abstract: This paper focuses on the design and development of            3. Small Wind Turbine in Battery Charging
synchronous buck converter in low power generation system.
The buck topology suffers from low efficiency at light loads due
                                                                         Application
to dissipation that does not scale with load current. In this paper
                                                                             The performance limitations of permanent magnet wind
we present a method for improving efficiency in buck converter
                                                                         turbine generators in battery-charging applications are
by reducing gate drive losses. Results of PSIM simulation are
presented.                                                               caused by the poor match of the rotor, generator and load
                                                                         characteristics over most of the operating wind speed range.
  Keywords: Buck Converter, Synchronous Rectification, PMG,              Even the small amount of energy (1kWh) that these batteries
Wind turbine.                                                            store can sufficiently improve the quality of life for such
                                                                         areas, giving people access to electrical lighting, TV/radio,
1. Introduction                                                          and other household conveniences. We placed an optimizing
   Small wind turbines offer a promising alternative for                 direct current DC/DC voltage converter between the rectifier
many remote electrical uses where there is a good wind                   and batteries. We can control the current output of the
resource. The goal of this work is to characterize small wind            synchronous buck converter, which allows us to control the
turbines, wind-diesel hybrid system components and wind-                 power going to the batteries. Battery-charging systems are
hybrid systems and to develop new off-grid applications for              very important in developing countries where rural families
small wind turbines in order to expand the international                 cannot afford a solar-battery home system or other
market for these systems. Projects fall into two                         electricity options. The technical aspects of charging
classifications: applications development and testing.                   numerous 28-V batteries with a small permanent magnet
Testing includes both small turbines and wind-hybrid                     alternator wind turbine suggest that a special battery-
systems. Although the projects that fall under applications              charging station needs to be developed. The major
development and testing are varied, they all focus on the                advantage of a centralized battery-charging station is that it
remote power market and all include small wind turbines as               can bring electric service to a very low-income segment of
the power source.                                                        the population. This performance improvement comes at
                                                                         higher system capital cost; however, the cost per charged
2. Block Diagram                                                         battery of the system with the individual charge controllers
                                                                         is lower because of better performance characteristics.
   A block diagram consists of a rectifier stage , a buck
converter and controller. Many small wind turbine
generators consist of a variable-speed rotor driving a                   4. Permanent Magnet Generator
permanent-magnet synchronous generator. The principal
                                                                            Permanent magnet alternators are the most powerful
application of such wind turbines is battery charging, in
                                                                         and cost-effective solution for building a wind generator.
which the generator is connected through a rectifier to a
                                                                         Their low-rpm performance is excellent, and at high
battery bank. The        wind turbine electrical interface is
                                                                         speeds they can really crank out the current due to their
essentially the same whether the turbine is part of a remote
                                                                         efficiency. They provide an optimal solution for varying-
power supply for                     tele communications, a
                                                                         speed wind turbines, of gearless or single stage gear
stand-alone residential power system or a hybrid village
                                                                         configuration. [5] The evolution of the control design of
power system.
                                                                         PM drives begins with the cost reduction of permanent
                                                                         magnet material and follows the progress of control
                                                                         theory of AC electric machinery. The main difference
                                                                         between PM drives and their earlier developed counter
                                                                         parts lies in the removal of the excitation field circuitry
                                                                         with troublesome brushes and its replacement with
                                                                         permanent magnets. But the application PM disables
                                                                         classical field weakening control, because the magnets
                                                                         produce constant magnetic field intensity. With the cost
                                                                         reduction of rare permanent magnet materials PM
                                                                         machines became very popular in industry due to their

                                                                                         •    Simple structure
                         Figure 1. Block Diagram
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                                                                                                        Vol. 2, No. 3, March 2010

               •   High efficiency                               explained below. The first state corresponds to the case
               •   Robustness                                    when the switch is ON. In this state, the current through the
               •   High torque to size ratio.                    inductor rises, as the source voltage would be greater than
                                                                 the output voltage, whereas the capacitor current may be in
  4.1 Types of Permanent Magnet Generators                       either direction, depending on the inductor current and the
                                                                 load current. When the inductor current rises, the energy
   Modern permanent magnet generators need no separate           stored in it increases. During this state, the inductor
excitation system. They can be gearless or with gearbox and      acquires energy. When the switch is closed the diode is in
are fully controlled with variable speed and reactive power      the off state. In Figure 2 the capacitor is getting charge.
supply. They provide the highest power quality and                  The second state relates to the condition when the switch
efficiency for the end user. They offer three different          is OFF and the diode is ON. In this state, the inductor
concepts of permanent magnet generator technology.               current freewheels through the diode and the inductor
                                                                 supplies energy to the RC network at the output. The energy
     4.1.1. Low Speed Robust Gearless System                     stored in the inductor falls in this state. In this state, the
   In a direct drive application the turbine and the generator   inductor discharges its energy and the capacitor current may
are integrated to form compact and structurally integrated       be in either direction, depending on the inductor current and
unit. The design gives free access to all parts for easy         the load current.
installation and maintenance. The simple and robust low
speed rotor design with no separate excitation or cooling
system results in minimum wear, reduced maintenance
requirements, lower life cycle costs, and a long lifetime.

    4.1.2. Medium Speed Compact and Economical Unit
    This is a very compact slow speed system with the
turbine main bearing and the permanent magnet generator
                                                                           Figure 3. Second Stage of Basic Circuit
integrated to a single-stage gearbox giving high efficiency
with low maintenance needs. It emphasizes the same simple           When the switch is open, the inductor discharges its
and robust low speed rotor design with no separate               energy. When it has discharged all its energy, its current
excitation or cooling system, resulting in less wear, reduced    falls to zero and tends to reverse, but the diode blocks
maintenance requirements, lower life cycle costs, and a long     conduction in the reverse direction. In the third state, both
lifetime.                                                        the diode and the switch are OFF. During this state, the
                                                                 capacitor discharges its energy and the inductor is at rest,
    4.1.3. High Speed Small Power Pack                           with no energy stored in it. The inductor does not acquire
                                                                 energy or discharge energy in this state.
  The system is mechanically similar to the doubly fed type
with even smaller space requirements. Extremely high
power with a small size and typical speed range is from
1000 to 2000 rpm for a 6 or 8 pole generator.

  The following are the key specifications evolved for PMG
  PMG                      AC 3φ, 4-pole machine
  Rated Speed             500 RPM - 3000 RPM                                  Figure 4. Third Stage of Basic Circuit
  Output Power            1.0 - 1.5 kW
  Output voltage           65V                                      Here it is assumed that the source voltage remains
                                                                 constant with no ripple, and the frequency of operation is
                                                                 kept fixed with a fixed duty cycle. When both the input
5. Buck Converter                                                voltage and the output voltage are constant, the current
  Output current           20A
                                                                 through the inductor rises linearly when the switch is ON
                                                                 and it falls linearly when the switch is OFF. Under this
                                                                 condition, the current through the capacitor also varies
                                                                 linearly when it is getting charged or discharged.

                                                                 6. Synchronous Buck Converter
                                                                    The synchronous-rectified buck converter uses current-
                                                                 mode control to regulate the output voltage. This control
                                                                 mode allows the converter to respond to changes in line
      Figure 2. Basic Circuit of Buck Converter                  voltage without delay. Also, you can reduce the output
                                                                 inductance to increase the converter's response to dynamic-
                                                                 load conditions.
  The operation of the buck converter is explained first.
This circuit can operate in any of the three states as
82                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010

   Although these features would appear to favor current-         MOSFETs. Under light loads, the control block usually
mode control in applications that require a fast dynamic          turns the lower MOSFET off to emulate a diode.
response, this control method has some disadvantages. For            Synchronous rectification with discrete MOSFETs causes
example, it tends to be sensitive to noise in the control loop.   variable switching delays because of the variations in gate
Also, current-mode control method requires two feedback           charge and threshold voltage from one MOSFET to another.
loops: a current inner loop and a voltage outer loop, thus        Standard control circuits compensate for these variations by
complicating the design. Finally, the controller uses a           delaying the turn-on drive of the lower MOSFET until after
current-sensing resistor in series with the output inductor.      the gate voltage of the upper MOSFET falls below a
This current-sensing resistance typically dissipates as much      threshold. This delay creates a dead time in which neither
power as do the MOSFETs, further reducing the current-            MOSFET conducts. The dead time eliminates the possibility
mode converter's efficiency. Voltage-mode control is              of a destructive shoot-through condition in which both
attractive for low-voltage buck converters because, it            MOSFETs conduct simultaneously. Standard designs use
involves a single control loop, exhibits good noise immunity      the same method to delay the turn-on of the upper device. A
and allows a wide range for the PWM duty-cycle ratio. Also,       typical design delays discrete MOSFET conduction with a
voltage-mode converters do not require a resistor for sensing     60-nsec dead time and limits converter switching frequency
current. However, the transfer function of standard voltage-      to 300 kHz.
mode buck converters that use Schottky diodes changes from
no load to full load, making it difficult to achieve fast           6.1 Conventional Vs Synchronous Buck Converter
response to large dynamic loads. The voltage drop of a
MOSFET is much less than that of a Schottky diode,                   The comparison of efficiency between a synchronous
which                                                             rectifier with a parallel Schottky diode and that of a
improves the efficiency of buck converters using                  Schottky diode alone is shown in Figure 6.
synchronous rectification. Synchronous rectification
increases the efficiency of a buck converter by replacing the
Schottky diode with a low-side NMOSFET. The resultant
voltage drop across the MOSFET is smaller than the
forward voltage drop of the Schottky diode. A more
comprehensive comparison includes the switching losses for
both the MOSFET and the Schottky diode. However, at
typical operating frequencies and voltages, a buck
regulator's switching losses are usually small in comparison
with the conduction losses. The low-side MOSFET conducts
current in its third quadrant during the off times of the high-
side MOSFET. This synchronous switch operates in the
                                                                                    Figure 6. Efficiency Graph
third quadrant, because the current flows from the source to
the drain, which results in a negative bias across the switch.
A positive voltage at the gate of the device still enhances the   7. Test Results
channel.                                                            7.1Generator Testing Details


                                                                    7.1.1. G ENERATOR SPEED VS GENERATOR OUTPUT
                                                                    VOLTAGE

                                                                     The table shows various readings of generator speed and
                                                                  their corresponding output voltages. It can be seen from the
                                                                  table the generator output voltage of 51.1 volts is obtained
                                                                  for the maximum speed of 1900 rpm.

                                                                              Table 1: Speed and generator voltage
            Figure 5. Synchronous Buck Converter                                Generator speed        Generator o/p
   As Figure 5 shows, conventional synchronous-rectified                           in rpm               voltage
buck converters partition the PWM-control and                                                            in Volts
synchronous-drive functions into a single IC that drives                              900                  19.2
discrete MOSFETs. The control and driver circuits                                     1200                 26.33
synchronize the timing of both MOSFETs with the                                       1350                 29.41
switching frequency. The upper MOSFET conducts to                                     1700                  46.2
transfer energy from the input, and the lower MOSFET                                  1900                  51.1
conducts to circulate inductor current. The synchronous
PWM control block regulates the output voltage by
                                                                    The following graph has been drawn for the generator
modulating the conduction intervals of the upper and lower
                                                                  speed versus generator output voltage. Generator speed is
                                                            (IJCNS) International Journal of Computer and Network Security, 83
                                                                                                       Vol. 2, No. 3, March 2010

taken in x axis and generator output voltage is taken in y-                                             1200                    4.10
axis.                                                                                                   1350                    4.62
                                                                                                        1700                    5.81
                                                                                                        1900                    6.50

                                                                  The following graph has been drawn for the generator
                                                                speed versus wind velocity. Generator speed is taken in x
                                                                axis and wind velocity is taken in y axis.




                                                                        Generator Speed in
                                                                                             2000
   Figure 7. Generator Speed Vs Generator Output Voltage
                                                                                             1500




                                                                               rpm
    7.1.2. Generator Output Voltage Vs Wind Velocity                                         1000


   The table shows various readings of wind velocity and                                      500

their corresponding output voltages. It can be seen from the
                                                                                               0
table the generator output voltage of 51.1 volts is obtained                                        0            2       4      6      8
for the maximum wind velocity of 6.5 m/s.
                                                                                                               Wind Velocity in m /s

                                                                        Figure 9. Generator Speed Vs Wind Velocity
             Table 2: Voltage with wind velocity
             Generator output       Wind velocity
             voltage in volts         in m/s
                                                                8. Simulation Results
                    19.2                3.07
                   26.33                4.10               Electronic circuit design requires accurate methods for evaluating
                   29.41                4.62                    circuit performance. Because of enormous complexity of
                    46.2                5.81                    modern integrated circuits, computer aided circuit analysis
                                                                is essential and can provide information about circuit
                    51.1                6.50
                                                                performance that is almost impossible to obtain with
                                                                laboratory prototype measurements. PSIM is a general-
  The following graph has been drawn for the wind velocity purpose circuit program that simulates electronic circuits.
versus generator output voltage. Wind velocity is taken in x- PSIM can perform various analyses of electronic circuits:
axis and in y axis generator output voltage is taken. The the operating points of transistors, a time domain response,
generated voltage is maximum when the wind velocity is a small signal frequency response, and so, on. Simulation
between 6 and 12 m/s.                                           work was done for all the circuits and results are attached.


                                                                  8.1Simulated Circuit Diagram




      Figure 8. Generator Output voltage Vs Wind Velocity

    7.1.3. Generator Speed Vs Wind Velocity

   The table shows various readings of generator speed and
their corresponding wind velocity. It can be seen from the
table the wind velocity of 6.5 m/s is obtained for the
maximum speed of 1900 rpm.

          Table 3: Speed with wind velocity
            Generator speed in      Wind velocity in
                 rpm                    m/s
                   900                   3.07
84                                                            (IJCNS) International Journal of Computer and Network Security,
                                                                                                         Vol. 2, No. 3, March 2010

             Figure 10. Simulated Circuit Diagram                    of IEEE Power Electronics Conference. pp. 787-791,
                                                                     2006.
                                                                 [6]    A.B. Raju, K.Chatterjee and B.G. Fernandes, “A
   The figure shows the simulated circuit diagram. The               Simple Power Point Tracker for Grid connected
Synchronous buck converter operate in current program                Variable Speed Wind Energy Conversion System with
mode control .The unit is a PI controlled device that controls       reduced Switch Count Power Converters”,       IEEE
the power level at which the converter operates. The unit is         conference on Power Electronic specillists,2003. pp
primarily designed to operate from the three-phase                   456-462.
alternating current output of the wind turbine. The
following graph shows the PSIM simulation results for the
output voltage from the synchronous buck converter.              Authors Profile

                                                                                          Bharanikumar.R was born in Tamilnadu,
                                                                                          India, on May 30, 1977. He received the
                                                                                          B.E degree in Electrical and Electronics
                                                                                          Engineering from Bharathiar University, in
                                                                                          1998. He received his M.E Power
                                                                                          Electronics and Drives from College of
                                                                                          Engineering Guindy Anna University in
                                                                                          2002. He has 9 yrs of teaching experience.
                                                                                          Currently he is working as Asst. Professor
                                                                                          in EEE department, Bannari Amman
                                                                 Institute of Technology, Sathyamangalam, TamilNadu, India
     Figure 11. Output result of Synchronous buck converter      Currently he is doing research in the field of power converter for
                                                                 special machines; vector controlled based synchronous machine
                                                                 drives, converters for wind energy conversion systems.
9. Conclusion
   Synchronous rectification is possible with all commonly                               A.Nirmal Kumar was born in the year
used converter topologies. It is achieved by simply adding a                             1951. He completed his PG and UG in
                                                                                         Electrical Engineering from Kerala and
MOSFET in parallel with the free-wheeling diode. As a
                                                                                         Calicut University respectively. He
result of this addition, the efficiency will improve                                     completed PhD in Power Electronics in the
significantly. A simple to operate and robust wind-electric                              year 1992 from P.S.G. College of
battery-charging station has been developed and tested.                                  Technology,       Coimbatore           under
Future work for the applications development and testing                                 Bharathiar University. He was with
team will include continued testing of commercial or near                                N.S.S. College of Engineering for nearly
commercial products for the remote electrification market.       28 years in various posts            before       joining    Bannari
                                                                 Amman Institute of Technology, Sathyamangalam, TamilNadu,
                                                                 India in the year 2004. He is a recipient of Institution of Engineers
                                                                 Gold Medal in the year 1989. His current research areas include
References                                                       Power converters for Wind Energy Conversion System and
                                                                 Controller for Induction motor drives.
[1] Monica Chinchilla, Santiago Arnaltes, Juan Carlos
    Burgos, “Control of Permanent-Magnet Generators
    Applied to Variable-Speed Wind-Energy Systems                               Maheswari .K.T was born in Tamilnadu
    connected to the Grid”, IEEE Transactions on Energy                         India, on Dec 20, 1980. She received her B.E
    Conversion, vol. 21, no. 1, pp.130-135, , March 2006.                       Degree in Electrical and Electronics
[2] F. Z. Peng, “Z-Source inverter,” IEEE Trans. Ind                            Engineering     from     Erode    Sengunthar
                                                                                Engineering College, Erode, Bharathiyar
    Applicat.,vol. 39, pp.504–510, Mar./Apr. 2003.
                                                                                University. Currently she is pursuing M.E in
[3] F. Z. Peng, M. Shen, and Z. Qian, “Maximum boost                            Power Electronics and Drives at Bannari
    control of the z- source inverter,” IEEE Transaction on                     Amman Institute of Technology, affiliated to
    Power Electronics. vol.20, no.4, pp833-838 July2005.     Anna University. Her field of interest    includes PMG and
[4] Shigeo Morimoto, Hideaki Nakayama, Masayuki Sanada, Power converters.
    Yoji Takeda, “Sensorless Output Maximization Control
     For Variable-Speed Wind Generation System using
    IPMSG” , IEEE Transactions on Industrial Applications
    2003, pp.1464-1471
[5] Tomonobu Senjyu, Sathoshi Tamaki , Naomitusu
    Urasaki, Katsumi Uezato Toshihisa Funabashi, Hideki
    Fujita “Wind Velocity and             PositionSensorless
    Operation for PMSG Wing Generator”, Proceedings

				
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