UbiCC Journal Volume 2 No 5

UBICC Journal Ubiquitous Computing and Communication Journal 2007 Volume 2 No. 5 . 2007-10-21 . ISSN 1992-8424 UBICC Publishers © 2007 Ubiquitous Computing and Communication Journal Edited by Usman Tariq. Co-Editor Dr. Shafique Ahmad Chaudhry Ubiquitous Computing and Communication Journal Book: 2007 Volume 2 No. 5 Publishing Date: 2007-10-21 Proceedings ISSN 1992-8424 This work is subjected to copyright. All rights are reserved whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illusions, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication of parts thereof is permitted only under the provision of the copyright law 1965, in its current version, and permission of use must always be obtained from UBICC Publishers. Violations are liable to prosecution under the copy right law. UBICC Journal is a part of UBICC Publishers www.ubicc.org © UBICC Journal Printed in South Korea Typesetting: Camera-ready by author, data conversation by UBICC Publishing Services, South Korea UBICC Publishers Message from Editor 2007-10-21 Dr. Shafique Ahmad Chaudhry General Co-Editor Welcome to our volume 2 issue of 2007 for the Ubiquitous Computing and Communication Journal. We hope that you get many chances to expand your knowledge from this issue of UBICC. The Ubiquitous Computing and Communication Journal is a leading resource for computing professionals and students working in the various fields of Information Technology, and for interpreting the impact of information technology on society. We conscientiously attempt to make the journal reach the eyes of those IT professionals who may be interested, thereby helping to bring your contributions to the awareness of many people far beyond your current working environment. We aim to only publish high-quality articles emphasizing innovative concepts, critical frameworks, valuable technologies, ubiquitous computing protocols and applications among other areas. The review process is an important means to reach the goal and that is why we recruit the highest caliber of individuals for reviews. The future success of UBICC will be inescapably linked to the perceived quality of the material that it publishes. This depends significantly on two factors: the first is clearly the scientific quality of the submitted papers. Unfortunately, we are unable to directly control this; however we are able to manage the second factor which is the quality of the reviewing process. High quality peer review is important because reliable information about the ever expanding increasing number of ubiquitous computing and communications topics outside our own field of competence has never been more necessary. It is essential that innovative, interdisciplinary research be reliable as well as useful. For that reason, there is a mounting need for information filtered by a high-quality reviewing process. It is important that our readers increasingly understand what we are engaged in, and see that it is relevant to their work, both as researchers and practitioners. I would make no apology for seeking to make it my uppermost priority to care for and maintain the high quality of peer review for which UBICC is already renowned. Peer review is indeed an arduous task for both the referees and the authors involved – and it is a service that is in essence provided free by scientists. Therefore, I would also strive to bestow esteem on all the reviewers, office staff and editorial board who are really the ones who make the journal what it is. To fill the pages of UBICC, we seek the very best of your research into ubiquitous computing. As submissions are peer-reviewed, I recommend that you allow me a preliminary review of your topic (send to: kj.curran@ulster.ac.uk) before you spend an extensive amount of time on something that may not fit well. For subject matter, please check out our archives for ideas on which areas which have interested our readership in the past. Please do not hesitate however to contact us if you feel that your current research is relevant to our worldwide audience. Finally, UBICC with its broad, high-quality coverage of all areas of relevance to the Ubiquitous computing community from novel user interfaces to philosophical issues related to the design and delivery of content is indeed in a unique position. It should aim to meet head on the challenges presented by the rapidly evolving and changing face of ubiquitous computing and communications and the growing diversity within this comparatively young field. Ultimately I desire that UBICC become the primary journal resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in ubiquitous computing and communications. Table of Contents Papers 33 An efficient block-by-block SVD-based image watermarking scheme Rania Ghazy, Nawal El-fishawy, Mohiy Hadhoud, Moawad Dessouky, Fathi Abd El-Samie ...... 1 34 Extension of UML(open) abstract modeling to develop Web application supporting platform and device independence Manuj Darbari, Bhaskar Karn, Pawan Kumar Bansal, Rajesh Goel . . . . . . . . . . . . . . . . . . . . . . . . . . 10 35 Hand-size variations effect on mobile phone texting satisfaction Vimala Balakrishnan, Paul Heng Ping Yeow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 36 Low crest factor modulation techniques for orthogonal frequency division multiplexing (OFDM) Ashraf Eltholth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 37 Density based topology control for mobile Ad hoc networks Ash Mohammad Abbas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 38 A survey of group merge and split mobility models Wang Furong, Huang Benxiong, Ibrahim Khider . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 39 Mobile Ad Hoc grid architecture using a trace based mobility model Vetriselvi V, Ranjani Parthasarathi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 40 A traffic locality oriented route discovery algorithm for MANETS Julien Montavont, Emil Ivov, Thomas Noel, Karine Guillouard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 41 Analysis of a geo location-based FMIPv6 extension for next generation wireless LANs Julien Montavont, Emil Ivov, Thomas Noel, Karine Guillouard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 42 Fair delay optimization based resource allocation algorithm for video traffic over wireless multimedia system Mohammed R Rizk, Moawad I Dessouky, Sami A El-Dolil, Mohammed Abd-Elnaby . . . . . . . . . . . . 79 43 Solving peak power problems in orthogonal frequency division multiplexing Ashraf A Eltholth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 44 A unified modeling approach using bond graph method and its application for model order reduction and simulation lubna Moin, Vali Uddin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 45 Dynamic admission control And resource reservation for WCDMA Sami A. El-Dolil, Azzam Y. Al-Nahari, Moawad I. Dessouky, Fathi E Abd El-Samie . . . . . . . . . . . . 106 46 Fair queue optimization based resource allocation algorithm for video traffic over wireless multimedia system Mohammed R Rizk, Moawad I Dessouky, Sami A El-Dolil, Mohammed Abd-Elnaby . . . . . . . . . . . . 113 AN EFFICIENT BLOCK-BY-BLOCK SVD-BASED IMAGE WATERMARKING SCHEME R. A. Ghazy #, N. A. El-Fishawy#, M. M. Hadhoud$, M. I. Dessouky# and F. E. Abd El-Samie# # Dept. of Electronics and Elect. Communications., Fac. of Electronic Eng., Menoufia Univ., 32952, Menouf , EGYPT. Dept. of Inform. Tech., Faculty of Computers and Information , Menoufia Univ., 32511, Shebin Elkom , EGYPT. E-mails: eng_rasg@yahoo.com, nelfishawy@hotmail.com, mmhadhoud@yahoo.com and fathi_sayed@yahoo.com ABSTRACT This paper presents a block based digital image watermarking scheme that is dependent on the mathematical technique of singular value decomposition (SVD). Traditional SVD watermarking already exists for watermark embedding on the image as a whole. In the proposed approach, the original image is divided into blocks, and then the watermark is embedded in the singular values (SVs) of each block separately. This segmentation and watermarking process makes the watermark much more robust to the attacks such as noise, compression, cropping. Watermark detection is implemented by extracting the watermark from the SVs of the watermarked blocks. Experiments show that extracting the watermark from one block at least is enough to ensure the existence of the watermark. Keywords: Image Processing, Watermarking, Singular Value Decomposition. 1 INTRODUCTION analog-to-digital conversion, and lossy compression. Fidelity means that the watermark should be neither noticeable to the viewer nor degrading for the quality of the content. Tamperresistance means that the watermark is often required to be resistant to signal processing algorithms. The existence of these properties depends on the application. The watermark can be embedded in the spatial domain or in the transform domain [2]. The SVD mathematical technique provides an elegant way for extracting algebraic features from an image. The main properties of the SVD matrix of an image can be exploited in image watermarking. The SVD matrix of an image has good stability. When a small perturbation is added to an image, large variation of its SVs does not occur [3], [4]. Using this property of the SVD matrix of an image, the watermark can be embedded to this matrix without large variation in the obtained image. Liu et al. have proposed an SVD based watermarking scheme in which the watermark is added to the SVs of the whole image or a apart of it [3]. A single watermark is used in this scheme which may be lost due to attacks. To avoid this disadvantage, we propose an approach in which , the original image is segmented into blocks and the watermark is added to the SVs of each block in a modified manner. The SVs of the modified $ The spreading of digital multimedia nowadays has made copyright protection a necessity. Authentication and information hiding have also become important issues. To achieve these issues, watermarking technology is used. Several researchers have worked in the field of watermarking for its importance [1-11]. The work in this field has led to several watermarking techniques such as correlation-based techniques, frequency domain techniques, DFT based techniques and DWT based techniques [2]. Watermarking means embedding a piece of information into multimedia content, such as video, audio or images in such a way that it is imperceptible to a human observer, but easily detected by a computer or detector [1]. Before the emergence of digital image watermarking, it was difficult to achieve copyright protection, authentication and data hiding but now it is easy to achieve these goals using watermarking techniques. Every watermarking algorithm consists of an embedding algorithm and a detection algorithm. Watermarking has several properties such as robustness, fidelity, and tamper-resistance [1]. The robustness means that the watermark must be robust to transformations that include common signal distortions such as digital-to-analog, UbiCC Journal, Volume 2, Number 5, October 2007 1 watermarked blocks are used to extract the watermark after the attacks. As a result of using several watermarked blocks, several watermarks can be recovered. So if any attack affects the watermarked image, some of the watermarks will survive. This block-by-block method gives robustness against JPEG compression, cropping, blurring, Gaussian noise, resizing and rotation as the results will reveal. The watermark can either be a pseudo-random number, or an image. In this paper the watermark used is an image. This paper is organized as follows: Section 2 briefly explains the SVD-Based watermarking scheme. Section 3 introduces the proposed scheme. Section 4 introduces the experimental results and section 5 gives the concluding remarks. 2 TRADITIONAL SVD-BASED IMAGE WATERMARKING 1. The SVD is performed on the possibly distorted watermarked image (F*w matrix). F*w=U*S*wV*T (5) 2. The matrix that includes the watermark is computed. D*=UwS*wVwT 3. The obtained. possibly corrupted watermark (6) is (7) W*=(D*-S)/k The * refers to the corruption due to attacks. 3 THE PROPOSED WATERMARKING APPROACH 3.1 Watermark Embedding: In this approach the original matrix (F matrix) is divided into blocks and the watermark is embedded to the diagonal matrix (S matrix) of each block giving new matrices. An SVD is performed on each of these new matrices to get the SV matrices of the watermarked image blocks. Then, these SV matrices are used to build the watermarked image blocks. By combining these blocks again into one matrix of the original image dimensions, the watermarked image Fw is built in the spatial domain. The steps of embedding the watermark can be summarized as follows: 1. Divide the original image (F matrix) into nonoverlapping blocks. 2. Perform SVD on each block (Bi matrix) to obtain the SVs (Si matrix) of each block. Where i=1,2,3,…..,N, and N is number of blocks. Bi=UiSiViT 4. (3) (8) 1. The SVD of an image is computed to obtain two orthogonal matrices U and V and a diagonal matrix S [7]. In the approach proposed by Liu et al., the watermark W is added into the matrix S then a new SVD process is performed on the new matrix S+kW to get Uw, Sw and Vw [3]. k is the scale factor that controls the strength of the watermark embedded to the original image. Then the watermarked image Fw is obtained by multiplying the matrices U, Sw, and VT. The steps of watermark embedding are summarized as follows: The SVD is performed on the original image (F matrix). F=USVT (1) 2. The watermark (W matrix) is added to the SVs of the original matrix. D=S+kW (2) The SVD is performed on the new modified matrix (D matrix). D=UwSwVwT 3. Add the watermark image (W matrix) to the S matrix of each block. Di=Si+kW (9) 4. 5. The watermarked image (Fw matrix) is obtained by using the modified matrix (Sw matrix). Fw=USwVT (4) 5. Perform SVD on each Di matrix to obtain the SVs of each (Swi matrix). Di=UwiSwiVwiT (10) To extract the possibly corrupted watermark from the possibly distorted watermarked image, given Uw, S, Vw matrices and the possibly distorted image Fw, , the above steps are reversed as follows: 6. Use the (Swi matrix) of each block to build the watermarked blocks in the spatial domain. UbiCC Journal, Volume 2, Number 5, October 2007 2 Bwi=UiSwiViT (11) watermarked image using the human eye, enforcing the fidelity of this method. Applying some attacks such as Gaussian noise, blurring, cropping, JPEG compression, rotation and resizing on the watermarked images. Figures (3) and (4) show the attacked watermarked images for Liu method and the proposed method, respectively. The major problem encountered with attacks is the process of watermark extraction which is studied in Figs.(5) and (6). The first attack applied is Gaussian noise with zero mean and 0.01 variance. The second attack is blurring using a low pass filter of 3x3 window. The third attack is cropping half of the watermarked image. The fourth attack is JPEG compression. The fifth attack is rotation by 15 degree. The sixth attack is resizing from size 256×256 to 128×128 and then to 256×256. Figure (5) shows the extracted watermark and the correlation coefficient between each extracted watermark and the original watermark for the method of Liu. The results reveal that the value of the correlation coefficient is less than 50% for extracted watermarks under attacks except for the compression attack. Figure (6) shows the extracted watermarks for the proposed algorithm after applying the same attacks we applied on Liu method. The extracted watermark giving the maximum correlation coefficient with the original watermark block is zoomed out in the figure, and the maximum correlation coefficient value is shown. In all cases, there is some blocks with correlation coefficient higher than 50% ensuring the existence of the watermark. Table (1) gives correlation coefficient results after applying Gaussian noise attacks with different values of noise variance. The table gives the highest correlation and number of extracted watermark blocks with correlation coefficients higher than the predetermined threshold for 0.5 and 0.4 thresholds. Similarly, Table (2) gives correlation coefficient results after applying lowpass filtering attacks with filters of different window sizes. Correlation (1) refers to the maximum correlation obtained by the proposed method and correlation (2) refers to the correlation obtained by Liu method. These results reveal the ability of the proposed algorithm to extract watermarks even in the presence of severe attacks. Figure (7) shows the relation between different values of noise variance and the number of successfully extracted blocks using 0.5 and 0.4 thresholds, respectively. Notice that the number 7. Rearrange the watermarked blocks back into one matrix to build the watermarked image in the spatial domain (Fw matrix). 3.2 Watermark Detection: Having Uwi, Vwi, Si, matrices and possibly distorted image F*w, we can follow the steps mentioned below to get the possibly corrupted watermarks. 1. 2. Divide the watermarked image (F*w matrix) into blocks having the same size used in the embedding process. Performs SVD on each watermarked block (B*wi matrix) to obtain the SVs of each one (S*wi matrix). B*wi=Ui*S*wiVi*T 3. (12) Obtains the matrices that contain the watermark using Uwi, Vwi, S*wi, matrices. D*i= UwiS*wi VwiT (13) 4. Extract the possibly corrupted watermark (W* matrix) from the Di matrices. (D*i-Si)/k=W*i (14) 4 EXPERIMENTAL RESULTS In this section several experiments are carried out to compare between the methods of Liu et al. and the proposed approach. The 256x256 cameraman image is used to be watermarked. Figure 1 shows the original image, the watermark, the watermarked image, and the extracted watermark using Liu method. A single watermark is used. Figure 2 shows the original image, the block based watermark, the watermarked image and extracted watermark. The block of extracted watermarks which gives maximum correlation with the original watermark block is magnified in the figure. The correlation coefficients between the original transmitted watermark block and the watermark extracted from each block in the image using the proposed method are indicated in Fig.(2-f) . The size of each block used in our experiments is 16 ×16. Different block sizes can be used but this size is moderate having small complexity. Figure (2-f) indicates that the correlation coefficient is higher than 0.5 for all extracted watermarks. This ensures the ability of the proposed algorithm to extract the watermarks perfectly in the absence of any attacks. Notice also that there is no difference between the original image and the UbiCC Journal, Volume 2, Number 5, October 2007 3 of successive extracted blocks is inversely proportional to the value of the threshold. 5. CONCLUSION This paper presents a visually undetectable, robust watermarking scheme. The proposed algorithm depends on embedding the watermark into the SVs of the original image after dividing it into blocks. The experimental results show that the proposed Block-by-Block SVD-Based method gives fidelity and robustness against Gaussian noise, cropping and JPEG compression. In the future work, the detection system will be extended to more transform domain watermarking approaches such as DWT- SVD and DCT-SVD. 6 REFERENCES [1] M. L. Miller, I. J. Cox, J. M. G. Linnartz and T. Kalker, “A review of watermarking principles and practices”, IEEE International Conference on image processing, 1997. [2] C. Shoemaker, Rudko, “Hidden Bits: A Survey of Techniques for Digital Watermarking” Independent StudyEER-290 Prof Rudko, Spring 2002. [3] R. liu and T. tan, “An SVD-Based Watermarking Scheme for protecting rightful ownership”, IEEE Trans. on multimedia, Vol. 4, no. 1 March 2002. [4] Y. H. Wang, T. N. Tan and Y. Zhu, “Face Verification Based on Singular Value Decomposition and Radial Basis Function Neural Network”, National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences. [5] E. Ganic and A. M. Eskicioglu, “A DFT-BASED Semi-Blind multiple watermarking scheme images”, CUNY Brooklyn College, 2900 Bedford Avenue, Brooklyn, NY 11210, USA. [6] A. H. Tewfik, “Watermarking digital image and video data ”, IEEE Signal processing magazine, September 2000. [7] A. Sverdlov, S. Dexter, A. M. Eskicioglu, “Robust DCT-SVD domain image watermarking for copyright protection: embedding data in all frequencies” [8] F. A. P. Petitcolas, R. J. Anderson and M. G. Kuhn, “Information hiding—A survey”, Proceeding of the IEEE, Vol. 87, No. 7, July 1999. [9] C. Y. Lin, M. Wu, J. A. Bloom, I. J. Cox, M. L. Miller, and Y. M. Lui, “Rotation, Scaling, and Translation Resilient Watermarking for Images”, IEEE Transactions on image processing, Vol.10,No.5,May 2001. [10] J. M. Shieh, D. C. Lou, and M. C. Chang, “A semi-blind watermarking scheme based on singular value decomposition”, computer standards & interface 28 (2006) 428-440. [11] W.Jinwel, L.Guanglle, D.Yuewel, W.Zhiquan, “Correlation detection system of watermarking based on HVS” (a) (b) (c) (d) Extracted watermark given Figure (1) (a) Original image. (b) Watermark. (c) Watermarked image. (d) correlation coefficient=0.8308. UbiCC Journal, Volume 2, Number 5, October 2007 4 (a) (b) (c) (d) (e) (f) Figure (2) (a) Original image. (b) Watermark image. (c) Watermarked image. (d) Extracted watermark images. (e) The extracted watermark which give maximum correlation, after zooming it out. (f) Watermark correlation coefficients (max. correlation=0.9975). 0 Gaussian noise .01 Blurring 3x3 Cropping Resizing 256—128—256 Rotate 15° JPEG compression Figure (3) Attacked watermarked images for Liu method UbiCC Journal, Volume 2, Number 5, October 2007 5 Gaussian noise .01 Blurring 3x3 Cropping Resizing 256—128—256 Rotate 15° JPEG compression Figure (4) Attacked watermarked images for the proposed method Gaussian noise .01 Correlation=0.1271 Blurring 3x3 Correlation=0.0584 Cropping Correlation=0.0090 Resizing 256—128—256 Correlation=0.0921 Rotate 15° Correlation=0.0510 JPEG compression Correlation=0.8202 Figure (5) the extracted watermarks for Liu method after applying attacks UbiCC Journal, Volume 2, Number 5, October 2007 6 Gaussian noise variance = .01 Max. Correlation = 0.5408 Blurring 3x3 Max. Correlation = 0.7072 Cropping Max. Correlation = 0.9975 Resizing 256—128—256 Max. Correlation = 0.5435 7 UbiCC Journal, Volume 2, Number 5, October 2007 7 Rotate 15° Max. Correlation = 0.6537 JPEG compression Max. Correlation = 0.9902 Figure (6) Extracted watermarks for different attacks. Left: the extracted watermark from each block. Right: magnification of the block that achieved maximum correlation with the original watermark. Table (1) Correlation coefficients for noise attacks with different noise variances Variance Correlation1 Corrlation2 No of blocks usingTH=0.5 No of blocks usingTH=0.4 0.001 0.6100 0.3665 13 95 0.005 0.5802 0.1641 8 21 0.01 0.5667 0.1267 4 14 0.05 0.5207 0.0854 1 10 0.1 0.4661 0.0779 0 9 0.5 0.4362 0.0700 0 3 1 0.4377 0.0688 0 2 UbiCC Journal, Volume 2, Number 5, October 2007 8 Table (2) Correlation coefficients lowpass filter attacks with different filter window sizes. Window size Correlation1 Corrlation2 No of blocks using TH=0.5 No of blocks using TH=0.4 3 ×3 0.7072 0.0596 13 16 4 ×4 0.5430 0.0372 2 8 5 ×5 0.6618 0.0261 1 3 6 ×6 0.5736 0.0191 2 2 Figure (7) Noise variance vs. the number of successively extracted watermark Blocks using 0.4 and 0.5 thresholds. UbiCC Journal, Volume 2, Number 5, October 2007 9 EXTENSION OF UML(OPEN) ABSTRACT MODELING TO DEVELOP WEB APPLICATION SUPPORTING PLATFORM AND DEVICE INDEPENDENCE Manuj Darbari, Assistant Professor, Department of Information Technology, BBDNITM, A-649, Indira Nagar, Lucknow,India. manujuma@rediffmail.com Bhaskar Karn, Coordinator, Department of Information Science, B.I.T, Mesra Ranchi,India. Prof.Dr.P.K. Bansal, Principal, Malout Institute of Management and Information Technology(MIMIT),Malout-Punjab.India-152107, Rajesh Goel ,Associate Professor and Head, Electronics and Communication Engineering Department, Ambala college of engineering and applied Research, Post Office- Sambalkha, Ambala Cantt-133101-Haryana. India ABSTRACT Traffic modeling has become a major issue for many cities throughout the world. There are number of simulation tools and websites available which can depict the urban Traffic situations. Our work extends the concept of Traffic Website Design which should be independent of platform as well as device. Keywords: OPEN(Object Process Environment Notation). 1 INTRODUCTION where the abstract platform is defined. In order to design complex abstract platform, we can use UML 20 composite structure to break up a complex design into smaller pieces. Generally for urban traffic modeling we have used state-machine and activity diagrams which encapsulates classifiers to define their behaviour. Since the behaviour of the abstract platform is also described in UML, it may be necessary to continue the explicit and the implicit abstract platform definition approaches. In the next half of the paper we will be concentrating of device independent website design of urban traffic which can provide the information so the common user about traffic conditions on his mobiles, PDA and telephones equipped with speech recognition software's. During late 90's it was general conception that website means it has to be supported by browser of a personnel computer or a laptop. It is very well shown by Ginage and Murugesan in their paper on web engineering[2] that by the help of XML/XDL we can achieve browser loss web providing in basic flexible infrastructure to independently define content and presentation. We will be using UML modeling technique to develop the device independent website. 2 PLATFORM INDEPENDENT WEB MODELING In this paper we will be focusing on a web site design specially designated for urban Traffic commuters as well Traffic Management official. To begin with we are focusing integration of platform independent modeling being UML. The concepts that plain UML prescribes for specifying communication between application parts (Objects and components) imply an abstract platform that is based on request response model and on message passing. In UML 2.0 meta-model, behavioral operations represent the capability of classifier to receive and to respond to requests. Requests are sent when objects exercise signal instances, which are sent asynchronously by other objects when these execute send signal actions and Broad cast signal actions. The specialization of UML[8] for defining abstract platform characteristics can be made more manageable and clearly defined through the use of UML profiles. Profiles are language extensions consisting of metamodel elements[1,3] that specialise elements of a reference model. The specialised elements can be given specific semantic variation points. To further define an abstract platform model, library packages are accommodated in UML 2.0. The abstract platform model library package can be imported by platform Independent Model of the application. Then we will be creating a dependency between the package where platform independence model is defined and the model library package Consider an example of Traffic information website in which a user can enquire about the latest Traffic conditions on a particular route through UbiCC Journal, Volume 2, Number 5, October 2007 10 online query mechanisms with system administration. We can call this abstract platform the Traffic Abstract Platform. In order to define the composition of the Traffic binding object with the application, we use reachable exchange of asynchronous signal exchange with the implicit approach, by defining a UML profile. We can show the relationship between platform independent modeling of the application and the abstract platform. The main of modeling elements used in Figure 1 are class and association. There are certain additional features to enhance the basic conceptual model. System Application 2.2 Discussion of the above model From the above UML model we are able to define the behavioural aspects of components taking part in a web model designing. Secondly the if a designer is following some language then he or she may favour directly some platforms over the other. The UML composite structure proposed in Fig. 2 and Fig. 3. The composite structure of transportation website can be created or destroyed along with components to which they are attached if the port connecting to them is destroyed first. This implies that if we want to model our unbounded number of distinct users may use the component through ports : We can further extend this abstract modeling for Device Independent modeling using XML and UML concepts. 3 DEVICE INDEPENDENT MODELING ABSTRACT Apply Imports Signal Profile Apply Traffic Abstract platform Fig. 1 : Conceptual model of the online Traffic Information 2.1 Transport Abstract Platform It consists of various signals and interface. It consists of a new user <>website and joining the Transport existing user leaving the website. + Signal - Join + Signal - leave Event Control Platform In order to explain this let us extend our example of Urban Traffic Modeling where a normal user sends an SMS from his mobile to get the latest information about city bus plying between a fixed origin-destination. The Device independent model consists of XML compiler that can interpret the language and several runtime components that are configured and deployed on the web server. The components consists of content design how the web application should took like etc. Then comes the implementation stage which is generally dove in My XML language which supports XSL stylesheets which is independents of the device. The deployment part consists of an application logic and web services which are to be extended to various level of users the administrator or used. The final stage consumer of modification in which the necessary changes can be implemented. In this section we an approach to model, implement and compose web services[6] into website with device independence. The framework which we are going to model provides support for the separation of layout, content and application logic in websites and automatically generates web since support for Browser less access to the content and functionality. Consider a detailed device Independent web Model (DIWM) which shows the relationship between various devices and its access to the common transportation server also known as Transportation as transportation Abstract Platform, that supports any query from the user having any device. It applies the features of My XML which provides a framework for loading the content of the website on any device. The Event Abstract Platform decides the type of event which is to be transported and also supports the session management features. <> Message Broadcaster + Signal = Latest Traffic Condition <> User + Signal - Request Fig 2. Transport Abstract Platform Components The interaction point that corresponds to port is of Type Transportation query Port. The query port handles the signals Join and Leave and delegates the handling of signals Message Reg. to the system. Administrator : Fig. 3 shows the internal components of Transport Abstract Platform. Transport Component instances exchange message signals among each other and message broadcaster with interaction. UbiCC Journal, Volume 2, Number 5, October 2007 11 Design Content Layout + Logic + Content Type is <> Implementation My XML + XSL +Static or Dynamic <> <> Deployment + Application logic + Web Services <> Modification + Content/ Layout Change Fig. 3 : Device independent Web Design Components <> Devices + Handheld Devices + Mobiles + Telephone Devices <> Signal Profile + Send 'Apply' <> My XML + SOAP Toolkit + XSL Language support 'Apply' 'Apply' 'Apply' <> 'Import' Event Abstract Platform + Browserless Services + Gross platform support 'Import' 'Apply' <> Transportation Abstract Platform + Signal = True + Signal = False + Signal = Time Out + Auto-answering mode Fig. 4 : Relationship between DIWM and Abstract Platform 3.1 General Description of DIWM components 3.1.1 Devices Devices means any device which has the accessibility of web content it can have windows and Java platform 3.1.2 Signal The signal profile specializes the exchange of asynchronous message sending between the two systems Transport Abstract platforms : It consists of interfaces and signals . It is same as explained in the previous section with an additional feature of 3 UbiCC Journal, Volume 2, Number 5, October 2007 12 autoreply mode about the latest traffic conditions based on origin-destination 3.1.3 Event Abstract Platform It deals with providing a common platform interface with features like browser less content generation and cross platform interface 3.1.4 My XMK Profile It contains SOAP toolkit[7] which is a simple object Access protocol. In this case it is used with combination of HTTP. It provides the framework which supports for the separation of layout, content and application logic in websites and automatically generates web service support for the browser-less access to the content and functionality. My XML language compiler integrates the layout and generates static content embedded in HTML and XML. For every page that is created with MY XM compiler , a corresponding Apache SOAP deployment descriptor in XML is generated service is always of the form SOAP 3.4 Discussion on the above model The abstract model of DIWM is an upcoming concept. We have used the concept of UML for integration and composition of web services and then later on integrating and composing of web services into websites. We have extended the concept of abstract modeling in viewing the web service as functionality that complements the typical functionality provided by a website and focus on the web engineering problem of using web services. 4 CONCLUSION AND EXTENSION connectors in ADLs (Architecture Description Language) can also be implemented in this approach for composite structures both for defining abstract platform from external and internal prospective. The limitation of behavioral aspect of Abstract components cannot be shown in our proposed model which could be the picture extension of the work. The further extension could be moduralisation of abstract platform definitions where the designer should be able to compose an abstract platform from the abstract platform modules developed previously. REFERENCES [1] Lucknow, D.J., Man : Specification and Analysis of System Architecture using RAPID, IEEE Transaction on software engineering, Vol. 21, No. 4, 1995. Lucktiman, D.: An Event Based Architecture Ddefinition language,. IEEE Transaction on software engineering vol. 21, No. 9, 1995. Allen, R : A formal Basis for Architectural Connection, ACM Transaction on software engineering and methodology, Vol 6, No. 3, 1997. C. Abatleir, A model-Driven Architecture Design space modeling, Technical report, Ankara, Turkey, June 2003. J. Warmer, W.Bast, MDA Explained, The model-driven Architecture : practice and Promise, AdditionWesley, 2003. MDG Guide Version 1.0 edited by Jo aquin miller and Jishnu Mukerji. E.D. Willink : UMLX : A graphical language for MDA : In proc. of model driven Architecture : Foundations and applications, pp 13-24, University of Twente, Netherlands, 2003. G. Booch, J, Rumbaugh : The unified modeling language user guide, Addison -Wesley, 1999. [2] [3] [4] [5] In this paper we have fully exploited the concept of EDOC component collaboration architecture in which application part interaction are decomposed into a synchronous messages that are exchanged through various ports. In both the examples (PIM and DIWM) we shown the concept of abstract platform in standard UML, through both implicit and explicit abstract platform defination. Explicit abstract platform definition is comparable to the definition of [6] [7] [8] UbiCC Journal, Volume 2, Number 5, October 2007 13 HAND-SIZE VARIATIONS EFFECT ON MOBILE PHONE TEXTING SATISFACTION Vimala Balakrishnan1, Paul, H.P. Yeow2 Multimedia University, Jln Ayer Keroh Lama, 75450 Melaka, Malaysia vimala.balakrishnan@mmu.edu.my1, hpyeow@mmu.edu.my2 ABSTRACT The effects of hand-size variations and gender on mobile phone users’ texting satisfaction were investigated using structured questionnaire interviews with 110 subjects (18–23 years old). Focus was on text entry factors: speed, learnability, simplicity, navigation and special characters. Gender effect is significant for speed and special characters selection, with females being more satisfied than males. Hand-size effect is significant for speed, special character selections and navigation, with smaller hand-sized subjects being more satisfied than larger handsized subjects. Interaction effect of hand-size x gender was found to be significant for speed and special character selections. Gender, hand-size and hand-size x gender significantly affect subjects’ overall texting satisfaction, with smaller handsized subjects being more satisfied than larger hand-sized subjects, regardless of their gender. It was recommended that an improved or new text entry mechanism would increase texting satisfaction, regardless of their gender and hand-sizes. Results confirm that hand-size variations and gender affect users’ texting satisfaction, with regards to the text entry factors. Keywords: Hand-size; gender; texting satisfaction; text entry factors 1 INTRODUCTION The popularity or success of text messaging with mobile phone users has heightened the interest in text entry research. Some researchers have done comparison studies based on the text entry methods [6, 7, 8, 9, 10] whereas others have tried to introduce new techniques to enter text via mobile phone’s limited interface [11, 12, 13]. Mackenzie et al. explored the text entry rates for several variations of soft keyboards [14]. Literature reviews revealed no studies has been done to find if mobile phone users’ hand-sizes influence their subjective satisfaction in text entry. Does this mean users’ physical hand measurements are not being considered by mobile phone designers or do all the mobile phones cater to users’ satisfactions, regardless of their hand and thumb sizes? This study aims to investigate if different hand-sizes influence mobile phone users’ texting satisfaction with respect to the text entry factors, taking gender into consideration as well. 2 TEXT ENTRY METHOD Text messaging on mobile phones refers to the activity of composing short character based messages (160 characters) and exchanging it between mobile phone subscribers. The first text message is believed to have been sent to a mobile phone in 1992 [1]. Teenagers originally started the textual use of the mobile as a form of cheap and accessible social communication. Today text messaging is the most widely used mobile data service, with 72% of all mobile phone users worldwide at end of 2006, being active users of text messaging service [2]. The European average is nearing 2 text messages sent per day per user, the British send 6, the South Koreans send 10, the Singaporeans send 12 and the Filipinos send 15 [3]. Interestingly a survey conducted by an International IT service company (LogicalCMG) among 1,004 mobile phone users revealed that Malaysians send an average of 17 text messages in a day and spend an average of RM101.50 per month [4]. The Handphone Users Survey 2005 also reported that 84.9% of Malaysian mobile phone users sent at least one SMS per day and 49.6% sent at least five daily, based on a survey among 4,295 mobile phone users [5]. This is an interesting phenomenon to note in view of the limited capability of text entry mechanisms with mobile phones. 2.1 Multitap The multitap is the most common style of text entry using a mobile phone’s keypad that consists of between 12-15 overloaded keys. Text is entered via the keypads with one or two hands using one or two fingers or thumbs. Multiple key presses are made to enter a desired text. When a letter is UbiCC Journal, Volume 2, Number 5, October 2007 14 entered successfully, users can proceed to the next letter if it’s on a different key; else a short waiting period (1–2 seconds) is necessary before the next letter can be entered. Some phones use the “#” key to force to the next letter. For example, to enter “deaf”, users need to type 3–332333 (“–” indicates a time–out), whereas with a next key, users need to type 3#332333 [15]. 2.2 Predictive text entry The predictive text entry method uses linguistic knowledge to predict the intended words of the user. Most mobile phones have licensed the T9 input method which uses a dictionary as the basis for disambiguation. Just like multitap, multiple letters correspond to the same key. However, each key is pressed only once. The phone will predict the word as it is being entered. A next key (e.g. “#”) can be used to cycle through the potential words. The word “deaf” is entered with 3323, however, the first word to be guessed by T9 is “dead”. Users need to press the next key to make the intended selections [15]. 3 DESIGN OF STUDY Text entry factors Speed Learnability Simplicity Texting Satisfaction Special characters Navigation Hand-size Gender Figure 1: Theoretical framework 3.2 Subjects A total of 110 Malaysians were interviewed, consisting of 55 males and 55 females, aged between 18 – 23 years old (mean = 21.5 years, SD = 1.64). The majority of them (84/110) were recruited from a local university and the rest were selected from public places (mall, public library etc.). All the subjects have used SMS before, with an average of 3.8 years of experience and SD = 1.19. All the subjects use their thumbs to compose messages. The majority of the subjects compose messages that are between 75-160 characters in average length (66.4%), followed by 26.4% between 25-74 characters. 80.9% (89/110) of the subjects use multitap for text entry, 11.8% (13/110) use both multitap and predictive text entry interchangeably and only 7.3% (8/110) use predictive text entry. 3.3 Hand-size measurements The mobile phone is normally held in a single hand, gripped by fingers (in most cases with all five fingers) while it sits on the palm. Messages are composed by making key presses using the thumb. Users with large hands and thumbs might find it difficult to hold the small mobile phone and text via the tiny keypads. On the other hand, small handsized users might have to struggle holding a large mobile phone. Moreover, users with short thumbs might find it difficult to reach some of the keys on large phones. In order to determine the effect of hand and thumb sizes on users’ texting satisfaction, four measurements were taken: hand breadth, hand length, thumb length and circumference. Hand breadth was measured at the distal ends of the metacarpal bones (the joints of index finger to the little finger) whereas the length of the hand was measured from the crease of the wrist to the tip of 3.1 Text entry factors The text entry factors used in this study are speed, learnability, simplicity, special characters and navigation. Table 1 shows the description for each of the text entry factors and Fig. 1 shows the theoretical framework. The effect of these factors on texting satisfaction is tested, based on two moderating variables: hand-size and gender. Table 1: Text entry factors Text entry factors Explanations Speed The speed in which a text can be keyed in using multitap or/and predictive text entry system [6 , 7, 8, 10] Learnability The ease in which users can learn the text entry mechanism [6, 7, 16] Simplicity The ease of using the text entry mechanism [16] Special characters The ease in keying in numbers, symbols (punctuations, exclamations, dollar signs etc.)[16] Navigation The ease in which key selections can be made while texting (opening, replying, deleting etc.) [16] UbiCC Journal, Volume 2, Number 5, October 2007 15 the middle finger, with the hand held straight and flat (Fig. 2). The length of the thumb was measured from the second joint of the thumb to the tip of the thumb whereas the circumference was measured at the widest point of the thumb (Fig. 3). All four measurements were taken using measurement tape based on the definitions used by Vasu and Mital [17]. Hand breadth Table 2 shows the summary of hand-sizes statistics based on the genders. It can be noted that generally the males have larger hands and thumbs than females; hence it is also important to determine if gender significantly influence users texting satisfaction. Three hand-size groups (small, medium and large) were defined for each gender based on [18]: for males, <8.8 cm is small, 8.8–9.2 cm is medium and >9.2 cm is large; for females, <7.3 cm is small, 7.3–7.7 cm is medium and >7.7 cm is large. The number of subjects is as follows: for males, 14 small, 18 medium and 25 large; for females, 14 small, 23 medium and 16 large. 3.4 Questionnaire An interview questionnaire was designed based on Sinclair’s guidelines [19]. The questionnaire was developed in English and had two major sections: Section A to obtain the demographic profile of the subjects (gender, hand measurements, hand used to text etc.) whereas Section B is for the subjects to rate their satisfaction/dissatisfaction levels to statements using Likert’s five-point scale, whereby 1 means ‘Strongly dissatisfied’, 2 means ‘Dissatisfied’, 3 means ‘Neutral’, 4 means ‘Satisfied’ and 5 means ‘Strongly Satisfied’. 3.5 Interviews Face-to-face interviews were conducted using the above questionnaire on a one-to-one basis, beginning with the subjects filling in their background information, which includes their age, gender, finger(s) used in composing SMS and so forth. The interviewer then measured the hand-sizes (palm and thumb). Subjects were encouraged to give comments, opinions and suggestions. All verbal comments were recorded by the interviewers. Each interview session lasted for about 30 minutes. Three interviewers participated in these exercise that took almost eight weeks to complete. All interviews involved one interviewer and one subject at the same time. 4 RESULTS Hand Length Figure 2: Hand breadth and length Thumb circumference Thumb length Figure 3: Thumb circumference and length Table 2: Hand-sizes based on genders Measurements (cm) Male (N=55) Mean ± SD (Min–Max) Female (N=55) Mean ± SD (Min– Max) Hand length 18.5 ± 1.2 (16.5 – 23.0) 16.6 ± 1.1 (13.5 – 18.5) Hand breadth 9.8 ± 1.4 (8.0 – 13.0) 7.5 ± 0.4 (6.0 – 8.2) Thumb length 6.4 ± 0.8 (4.8 – 8.2) 5.4 ± 0.7 (4.2 – 8.0) Statistical Package for the Social Sciences (SPSS) software was used to test the statistical significant difference(s) of variables gender, handsize groups and the hand-size x gender interactions against text entry factors. Analysis of variance (ANOVA) and Tukey Post-Hoc analysis were used to analyze the collected data. All results are considered significant at p < 0.05 level. Thumb circumference 4.4 ± 1.9 (1.6 – 7.5) 3.5 ± 1.8 (1.5 – 6.5) Note: Dominant hand measurements only. Independent t-test showed significant differences between genders for all measurements. UbiCC Journal, Volume 2, Number 5, October 2007 16 Table 3: ANOVA test for text entry factors satisfaction, based on gender Table 5: ANOVA test for text entry factors satisfaction, based on hand-size x gender Text Entry Factors F p Text Entry Factors F p Speed 4.638 0.033* Speed 2.796 0.021* Learnability 3.463 0.065 Learnability 1.245 0.294 Simplicity 2.641 0.107 Simplicity 0.991 0.427 Special Characters 8.893 0.004* Special Characters 11.491 <0.001* Navigation 3.187 0.077 Navigation 1.353 0.319 F: F statistic; p: p-value; *: significant at p < 0.05 Table 3 shows that there is a significant effect of gender with respect to users’ satisfaction towards speed and special characters selection. The females were found to be more satisfied (mean = 3.7 and mean = 4.1) than males (mean = 3.3 and mean = 3.5) for speed and special character selections respectively. Table 4: ANOVA test for text entry factors satisfaction, based on hand-size F: F statistic; p: p-value; *: significant at p < 0.05 Table 5 shows that the interaction effect of hand-size x gender was found to be significant for speed and special character selection factors. Texting satisfaction – Special characters (mean) 4.5 Male Female Text Entry Factors F p Speed 3.339 0.039* 4 3.5 Learnability 0.872 0.421 Simplicity 0.596 0.553 Special Characters 15.657 0.001* 3 Navigation 15.149 0.001* F: F statistic; p: p-value; *: significant at p < 0.05 In Table 4, hand-size was found to have significant effect with users’ satisfaction towards speed, special characters selection and navigation. Tukey Post-Hoc analysis revealed that small handsized users are more satisfied with the speed of text entry than large hand-sized users (p = 0.03). They are also more satisfied with the special characters selection and navigation than medium (p = 0.04 and p = 0.001, respectively) and large hand-sized users (p < 0.001 for special characters selection and navigation). Small Medium Hand-size Large Figure 4: Interaction effect of hand-size and gender on special characters UbiCC Journal, Volume 2, Number 5, October 2007 17 4 Male Female Texting satisfaction - speed (mean) 3.8 3.6 Male Female 3.8 3.4 3.2 Texting satisfaction (mean) 3.6 3.4 3.2 3 2.8 3 Small Medium Hand-size Large Small Medium Hand-sizes Large Figure 5: Interaction effect of hand-size and gender on speed Fig. 4 shows a clear gender difference in subjects with medium and large hand-sized users, with the females being more satisfied with the special character selection than males. The difference is not very prominent for subjects with small hand-sizes. This result tallies with the speed of text entry satisfaction (see Fig. 5) too, as the females were found to be more satisfied than males regardless of their hand and thumb sizes. However, the differences are clear for all the hand-size categories. Table 6: ANOVA test for overall text entry satisfaction Figure 6: Interaction effect of hand-size x gender on the overall text entry factor satisfaction Table 6 indicates that the effect of gender, hand-size and the interaction between hand-size x gender are significant for overall users’ satisfaction for text entry factors. As expected, the females (mean = 3.7) were found to be more satisfied with the text entry factors compared to males (mean = 3.3). Tukey post-hoc analysis revealed that small hand-sized users are more satisfied than large handsized users (p = 0.032). As for the interaction effect, Fig. 6 indicates that differences exist between the genders in all the hand-size groups, with the females being more satisfied than males. However, the difference is more prominent between the females with large hand-size and males in the same group. 5 DISCUSSION Variables F p Gender 4.190 0.043* Hand-size 3.518 0.033* Hand-size x gender 2.513 0.034* F: F statistic; p: p-value; *: significant at p < 0.05 5.1 Gender differences According to the p-values in Table 3, females were found to be more satisfied with the text entry speed and special character selections than males. The majority of the males (31/55) feel multitap can be time-consuming, especially when the need to compose messages fast arises. This is especially true for selection of special characters (symbols, punctuations etc.) as additional key presses are required. These may include repetitive presses on the same key or on different keys. This result is consistent with Balakrishnan and Yeow [20] who found that the males are less satisfied with the speed of text entry than females. However, the results are based on a very small sample of 18 subjects. Multitap technique is often criticized for being slow. An experiment using a mobile phone found that experts and novices reached about 8 words per minute (wpm) with multitap [8]. In 2003, the world’s fastest mobile texter typed 29 wpm UbiCC Journal, Volume 2, Number 5, October 2007 18 using multitap technique, which is more than six times slower than the Guinness record of 192 wpm for the desktop QWERTY keyboard [15]. Slow text entry mechanism has also been cited as one of the usability issues of mobile phones by Axup et al. [21]. Eight users who use both the text entry techniques interchangeably prefer to use multitap than predictive text entry as no unnecessary interruptions take place while messaging using the former mechanism. Predictive text entry can be frustrating and slow especially when the words being entered are not recognized by the mobile phone. This is especially true among the youngsters who frequently use abbreviations and dialects in their text. For example, it is a common practice to type “c u” instead of “see you”. Moreover, it is also common for the subjects to text in a language other than English, like Malay or Chinese. Predictive text entry was found to expedite messaging, only when one really knows how to use it. Compared to multitap, predictive text entry was used by novices at 9.1 wpm and experts at 20.4 wpm. However, all these results were based on English-based text only [8]. Another study also identified text entry speed and predictive text entry mechanism as some of the factors affecting SMS users’ satisfaction; however the results are based on 30 subjects only. Moreover, they did not take gender and hand-sizes into consideration [22]. Thirteen of the males mentioned that it is so much simpler to make a phone call instead of struggling with predictive text entry or multitap during an urgency period. Statistics from Table 2 show that females have smaller hands and thumbs than males; hence this could be another reason for their higher level of satisfactions than the males for both speed and selection of special characters. Having smaller hands and thumbs enables them to make multiple key presses and to select special characters with less error and faster. Moreover, females tend to write longer and complex messages that include a lot of emoticons to express their feelings than the males; hence they are more familiar with the mapping of the keys to the appropriate characters and this result in them being more satisfied with the special character selections. Males on the contrary, prefer to write short and simple messages [23]. 5.2 Hand-size differences Smaller hand-sized subjects are more satisfied with the text entry speed, special character selections and navigation than larger hand-sized subjects (Table 4). These can be contributed to the keypad designs as well. Mobile phones with the standard 4 x 3 keypad layout have limited or no space at all in between the keypads. Moreover, the size of the keypads is tiny and this largely causes dissatisfaction to users with larger hands and thumbs. Large hand-sized users find it difficult to make multiple key presses fast and without any or lesser errors to enter both text and special characters. Situation becomes more difficult when there is a need to text in a hurry or while in motion (walking or talking to someone else). 46.3% (19/41) of the large hand-sized users also mentioned that navigation affects their satisfaction as some mobile phone software requires many key presses to navigate through the menus. For example, three Samsung SGHA800 users specifically mentioned that they need to make separate navigations to key in alphabets, numbers and symbols. Multiple navigations sometimes causes frustration and they minimize or do not use special characters at all (“(”, “@” etc.). This statement was concurred by Motorola C261 users, who stated that texting can be cumbersome as it involves many key presses and navigations (e.g. five different key presses and one navigation key to reply an existing message in the inbox). Moreover, they also mentioned that it can be real tedious to locate an intended special character while texting. For example, it takes seven continuous key presses on key-1 to type a “,” symbol, 12 key presses to type “:” and 16 key presses for “(”. These are some of the common symbols used by mobile phone users to express their emotions, e.g. “:(” means sadness. However, having to make so many key presses hinders the users from including these types of emoticons. Moreover, it becomes real frustrating to users with larger hands and thumbs, as making repetitive key presses on the tiny key pads is not an easy task. Problems become worse when they accidentally make erroneous key presses as the whole cycle of pressing the key has to be repeated. Though different mobile phone brands use varying software, most of them still require users to make multiple key presses and navigations for special character selections. Mapping of the appropriate navigational keys to the desired object was also found to be cumbersome by a study conducted among middle-aged users, e.g. locating the key to access the ‘ABC’ (non-predictive) menu that allows a user to change from different character input types, i.e. from numerical to alphabetical is not a straight-forward and clear process. However, this finding is solely based on Samsung T400 model [16]. The problem of tiny mobile phones with tiny keypads further reduces the users’ satisfaction towards text entry, in terms of both speed and accuracy, especially for large hand and thumb sized users. Only two large hand-sized subjects (2/41) use multitap and predictive text entry interchangeably. However, they stated that they only use the latter technique to send short and simple messages. They reasoned that cycling through the possible words can be frustrating as it also means additional key presses and navigations. Moreover, texting in a language other than English becomes almost impossible with predictive text entry. As for the rest UbiCC Journal, Volume 2, Number 5, October 2007 19 of the subjects, using multitap seems to be the more feasible and preferred method compared to predictive text entry. Mobile phone users have to learn to use predictive text entry before being able to use it properly. This factor seems to hinder most of the subjects from adapting or switching to predictive text entry. As one subject stated (statement rephrased in standard English): “My phone has automatic text entry but I have never used it, as I don’t know how to use it!!!”. This is an interesting point to note as large hand and thumb sized mobile phone users seem to prefer the slow multitap than the supposedly faster predictive text entry. An experiment comparing multitap and predictive text entry found similar results, whereby a long training or learning time leads to frustrations among subjects even though predictive text entry is faster [24]. These experiments, however, did not take gender and hand-sizes into consideration. 5.3 Hand-size x gender differences The interaction effect between hand-size x gender was found on text entry speed and special character selections (Table 5). Medium and large hand-sized females are more satisfied with the special character selections compared to males from the same hand-size categories (Fig. 4). They were also found to be more satisfied with the text entry speed than males, regardless of their hand-size (Fig. 5). Females have smaller hands and thumbs compared to the males (see Table 2) and this enables them to make multiple key presses at a faster speed. The majority of the males (44/55) commented that the current multitap mechanism requires too many key presses to be made in order to enter a single character, especially when the intended characters are placed on the same keypad. This problem is further aggravated when some software requires additional navigations for them to make a special character selection. This is due to key overloading whereby a single keypad supports more than one letter in most of the mobile phones today [8, 9, 11, 25]. The subjects also commented that perhaps a new mechanism is needed to make the multiple key presses faster as this seems to be a better solution than increasing the number of keypads. This was agreed by 66.3% (73/110) of the subjects who also stated that an improved text entry mechanism coupled with larger keypads would be the preferred solution, especially for the larger hand and thumb sized mobile phone users. 5.4 Overall text entry satisfaction Finally results in Table 6 shows that gender, hand-size and the interaction effect of hand-size x gender significantly affect users’ texting satisfaction. Interaction effect shows that females are more satisfied with the text entry factors than males, for all the different hand-size categories (Fig. 6). As results shown in Table 3, females were found to be more satisfied than males with regards to text entry speed and special characters selection. Generally it was also found that smaller hand-sized subjects are more satisfied than larger hand-sized subjects (Table 4). Females have smaller hands and thumbs than males, and this enables them to make repetitive key presses on the tiny keypads faster and with lesser errors. The tendency to accidentally press a neighbouring key due to having a large thumb is also reduced or eliminated altogether. On the other hand, the larger hand-sized males have to struggle pressing the keys, especially when the text entry software requires multiple key presses just to select a single letter or character. These factors cause dissatisfaction to these mobile phone users while texting. 6 CONCLUSION The results from structured questionnaire interviews with 110 Malaysian youth on mobile phone text entry satisfaction, based on hand-size variations and gender were presented. Hand-size measurements which include hand breadth, length, thumb length and circumference were measured for this purpose. Focus of this study was mainly on text entry factors: speed, learnability, simplicity, special character and navigation. Females were found to be more satisfied with the speed and special character selections of text entry mechanism (multitap or predictive text entry) than males. Smaller handsized subjects are more satisfied with the text entry speed, special character selections and navigation than subjects with medium and large hands and thumbs. Significant interactions between hand-size x gender were observed for speed and special character selections as well, with the females being more satisfied than males, for all hand-size categories. However, the difference is not prominent between the genders with small handsize for special character selections. Finally, it was found that males are less satisfied with texting than females, regardless of their hand-sizes. This study revealed that hand-size variations and gender do influence texting satisfaction among mobile phone users. Two major factors that were found to significantly affect their satisfaction are speed and special character selections. These factors were prominent among subjects with larger hand and thumb sizes as it becomes cumbersome to repetitively make key presses in order to text or to select special characters (“ : ”, “ @ ” etc.). Subjects also stated their preference to use multitap instead of predictive text entry as the latter involves cycling through possible words to make selections, causing them to be frustrated. An enhanced text entry mechanism, coupled with larger keypads is seen as the preferred solution, especially among the larger hand and thumb-sized users. Mobile phone designers should look into incorporating other UbiCC Journal, Volume 2, Number 5, October 2007 20 possibilities of text entry mechanisms that caters to specific targets, for example users with larger hands and thumbs. 7 REFERENCES [1] GSM Association Press Release. www.gsmworld.com (2000) [2] SMS Feedback. www.smsfeedback.com/facts.htm (2007) [3]http://communitiesdominate.blogs.com/brands/2 007/week19/index.html (2007) [4] M' sians spend average of RM100 a month on SMS. http://startechcentral.com/tech/story.asp?file=/2007/2/1/t echnology/20070131123123&sec=technology (2007) [5] SMS still King. http://startechcentral.com/tech/story.asp?file=/2006/1/31 /technology/13265724&sec=technology (2006) [6] M. Silfverberg, I.S. Mackenzie and P. Korhonen: Predicting Text Entry Speed on Mobile Phones. CHI 2000, 2, pp. 9–16 (2000) [7] G. Buchanan, M. Jones, H. Thimbleby, S. Farrant and M. Pazzani: Improving Mobile Internet Usability. In Web 2001 Conference Hong Kong, ACM Press (2001) [8] C.L. James and K.M. Reischel: Text Input for Mobile Devices: Comparing Model Prediction to Actual Performance. CHI 2001, 3, pp. 365– 371 (2001) [9] A. Cockburn and A. Siresena: Evaluating Mobile Text Entry with the Fastap Keypad. In British Computer Society Conference on Human Computer Interaction, England (2003) [10] D. Wigdor and R. Balakrishnan: A Comparison of Consecutive and Concurrent Input Text Entry Techniques for Mobile Phones. CHI 2004, 6, pp. 81–88 (2004) [11] I.S. Mackenzie: Mobile Text Entry Using Three Keys. In Proceedings of the Second Nordic Conference on Human-Computer Interaction- NordiCHI 2002, pp. 27–34 (2002) [12] D. Wigdor and R. Balakrishnan: TiltText: Using Tilt for Text Input to Mobile Phones. CHI Letters, 5, pp. 81–89 (2003) [13] J. Gong and P. Tarasewich: Alphabetically Constrained Keypad Designs for Text Entry on Mobile Devices. In CHI 2005, PAPERS: Small Devices 1, pp. 211–220 (2005) [14] S. Mackenzie, S.X. Zhang and R.W. Soukoreff: Text entry using soft keyboards. Behaviour & Information Technology, 18, pp. 235–244 (1999) [15] T.E. Starner: Keyboards Redux: Fast mobile text entry. Pervasive Computing (2004) [16] C. Soriano, G.K. Raikundalia and J. Szajman: A Usability Study of Short Message Service on Middle-Aged Users. In Proceedings of OZCHI 2005, Canberra, Australia (2005) [17] M. Vasu and A. Mital: Evaluation of the Validity of Anthropometric Design Assumptions. International Journal of Industrial Ergonomics, Vol. 26 (1), 19-37 (2000) [18] H. You, A. Kumar, R. Young, P. Veluswamy and D.E. Malzahn: An Ergonomic Evaluation of Manual Cleco Plier Designs: Effect of Rubber Grip, Spring Recoil and Worksurface Angle. Applied Ergonomics, Vol. 36, 575-583 (2005) [19]A.M. Sinclair: Subjective Assessment. In Evaluation of Human Work-A Practical Ergonomics Methodology, Wilson, J.R. and Corlett, E.N. (Eds.), pp. 69–100, London:Taylor & Francis (1995) [20] V. Balakrishnan and Paul H. P. Yeow: Texting Satisfaction: does age and gender make a difference?, International Journal of Computer Science and Security, Vol. 1, Issue (1), 85-96 (2007) [21] J. Axup, S. Viller and N. Bidwell: Usability of a Mobile, Group Communication Prototype While Rendezvousing. In CTS’05 International Symposium on Collaborative Technologies and Systems-Special Session on Mobile Collaborative Work (2005) [22] V. Balakrishnan, P.H.P. Yeow and D.C.L. Ngo: An investigation on the Ergonomics Problems of Using Mobile Phones to Send SMS. In: Bust, P.D., and McCabe, P.T. (Eds.), Contemporary Ergonomics 2005, UK (2005) [23] R, Ling: The Socio-linguistic of SMS: An Analysis of SMS Use by a Random Sample of Norwegians. In Mobile Communications: Renegotiation of the Social Sphere , Ling, R. and Pedersen, P. (Eds.), pp. 335 –349, London: Springer (2003) [24] Z. Friedman, S. Mukherji, G.K. Roeum and R. Ruchir: Data Input into Mobile Phones: T9 or Keypad?, Student Online HCI Research Experiments (2001) [25] M. Maragoudakis, N.K. Tselios, N. Fakotakis and N.M. Avouris: Improving SMS Usability Using Bayesian Networks. In Methods and Applications of Artificial Intelligence, Vlahavas, I.P. and Spyropoulos, C.D. (Eds), pp. 179–190, Berlin: Springer-Verlag (2002) UbiCC Journal, Volume 2, Number 5, October 2007 21 Low Crest Factor Modulation Techniques for Orthogonal Frequency Division Multiplexing (OFDM) Ashraf A. Eltholth*, Adel R. Mekhail*, A. Elshirbini*, M. I. Dessouki† and A. I. Abdelfattah †† * † National Telecommunication Institute, Cairo, Egypt Faculty of electronic Engineering, Menouf, Egypt †† Faculty of Engineering, Mansoura, Egypt ABSTRACT OFDM suffer from a high peak-to-average ratio (PAR), caused by the addition of a large number of independently modulated sub-carriers in parallel at the transmitter. When subjected to a non-linear power amplifier, these signals may undergo significant spectral distortion, leading to both in-band and out-of-band interference, and an associated degradation in system performance. In this paper we compare between different modulations techniques in OFDM for the spectral efficiency, BER, and PAR reduction, which reduce the effect of nonlinear amplifier. Simulations of the proposed system models using Matlab are used to compare between three linear modulation families, namely M-QAM, M-PSK and MSK to be used for OFDM. Also we discuss the benefits of using MSK as the lowest crest factor modulation technique to be used for OFDM. Keywords: OFDM, Crest Factor, MSK, HPA, PAPR. the OFDM system. We have compared among several families of modulation techniques. We propose to use a modulation technique with high spectral efficiency and less sensitive to nonlinear channel effects, which is the Minimum Shift Keying (MSK). Sections 2 will describe the statistical properties of the OFDM composite time signal, while in section 3 we will show the performance of OFDM system using the mentioned modulation techniques and in section 4 we will discuss the applicability of power amplifiers to OFDM systems. 2. STATISTICAL PROPERTIES OF OFDM SIGNAL The OFDM transmitted base-band signal may be represented as [3, 4]: 1. INTRODUCTION Besides its lot of advantages, OFDM suffers from some drawbacks that become apparent when used in the real world; a major obstacle is the very high peak to average power ratio (PAR), or equivalently, a large crest factor (CF) [1]. This problem arises because of the nature of the composite time OFDM signal as it is the sum of Nmodulated sub-carriers, and carriers may add-up constructively forming a very high peak. This spurious high amplitude peaks in the composite time signal compared to the average signal power, the instantaneous power of these peaks is high, and consequently, so is the Peak-to-Average power Ratio (PAR). The occurrence of these peaks seriously hampers practical implementations specially the power amplifiers. The impacts of amplifier-induced nonlinear distortions are: the in band waveform distortion, resulting in a signal to noise ratio degradation and the out of band radiation resulting in adjacent channel interference. However, in most practical cases the out of band radiation is the limiting factor, which defines the amplifier back-off requirements [2]. Simply dimensioning the system components to be able to cope with the worst case signal peaks is practically impossible. That is why solutions have been proposed to counter act PAR problem. In this paper we consider the choice of low crest factor modulation techniques to be used in x(t ) = ∑ (a k + jbk ) exp(− j 2πwk t ) k =0 N −1 (1) Where N is the number of sub-carriers, while a k and bk are the real and imaginary components of the complex modulating symbols, respectively. For example, for 16-QAM modulation a k and bk may assume the equi-probable values of {-3, -1, 1, 3}. From the central limit theory it follows that for large values of N (N≥64) both the real and imaginary components of x(t) becomes normally UbiCC Journal, Volume 2, Number 5, October 2007 22 distributed variable having a mean of zero. And thus, the absolute value will have Rayleigh distribution. The crest factor of the discrete time representation x(k) is defined as the ratio of the peak magnitude value and the square root of the average power of this signal. For the OFDM signal as we mentioned it have a zero mean and thus the square root of the average power will be equal to the standard deviation δ. Thus the crest factor can be written as: a. The minimum Euclidean distance amongst phasors, which is characteristics of the noise immunity of the scheme b. The minimum phase rotation amongst constellation points, determining the phase jitter immunity c. The peak to average phasor power, which is a measure of robustness against non-linear distortion introduced by power amplifiers. CF = max( x(k )) E(x ) 2 = max( x(k )) δ (2) Note that, the peak to average power ratio, widely used in literature, is simply the square of the crest factor. Both quantities coincide, if expressed in logarithmic scale (dB). An OFDM system is simulated using Matlab with 512 sub-carriers; We have performed a measure of normality, i.e., wither the composite time signal approaches the normal distribution or not, as a verification of the applicability of central limit theory to OFDM, and we get the following result as shown in figure (1) It can be noticed that the real and imaginary parts of the OFDM signal completely agree with the normal distribution. Normal Probability Plot Fig.(2) Block diagram of OFDM system The Bandwidth efficiency can be increased either by increasing the Number of signal phase levels, or by increasing the Number of signal amplitude levels [6], 1. Increasing the signal amplitude levels has the drawback that the signal envelope is not constant and therefore non-linear amplification may cause spreading of the signal spectrum and increase in BER. 2. Increasing the Number of phase levels will highly increase the BER. 0.999 0.997 0.99 0.98 0.95 0.90 Probability 0.75 0.50 0.25 0.10 0.05 0.02 0.01 0.003 0.001 -0.5 -0.4 -0.3 -0.2 -0.1 0 Data 0.1 0.2 0.3 0.4 Fig.(1) Normal probability plot of OFDM signal 3. OFDM USING DIFFERENT MODULATORS In this section we will simulate an OFDM system as shown in the block diagram in figure (2) using different modulation techniques. We have simulated an OFDM system with different modulation techniques, namely, M-ary PSK, M-ary QAM (with M=4, 8, 16 and 32) and Minimum Shift Keying (MSK). When designing a constellation diagram for a modulation technique, some considerations must be given to [5]: Fig.(3)OFDM Spectrum with different modulation We have noted that for M-PSK, as M increases no effect has been occurred to the dynamic range and the PAR remains nearly the same, while for MQAM, as M increases the dynamic range increase and so the PAR, but both of them agree in the UbiCC Journal, Volume 2, Number 5, October 2007 23 spectral efficiency increase as M increase. This is shown in figure 3. It is also noticeable from figure (3) that the Bandwidth of MSK is nearly the same as that of QPSK, but with lower power. When analyzing the statistical properties of the OFDM composite time signal we deduced the following: As shown in figure (4); The probability density function of the absolute OFDM signal agrees with the Rayleigh distribution for all used modulation techniques. pdf of absolute values of OFDM signal 0.167 16-QAM 0 ranges in [-4δ, 4δ], this can be a good indicator for clipping efficiency. 10 0 10 -2 8-PSK 8-QAM 16-QAM 16-PSK BER 10 -4 10 -6 32-QAM 4,16,32-PSK 1 10 -8 0 2 4 6 8 10 Eb/N0 (dB) 12 14 16 18 0.83 Density Fig.(5-a)BER of OFDM using 8,16 -PSK&QAM 10 0 0.67 0.5 0.33 10 -2 0.167 BER 0 0 0.2 0.4 0.6 0.8 Data 1 1.2 1.4 1.6 10 -4 Fig.(4) PDF of OFDM with different modulation And in agreement with figure (3), as M-increases in M-QAM the dynamic range increases, and in the case of MSK the dynamic range is less than that of QPSK. Table I. Shows PAR, standard deviation δ and the dynamic range of the OFDM signal with the above mentioned modulation techniques TABLE I. PAR AND STD OF OFDM SIGNAL MOD MSK QPSK 8QAM 16QAM 32QAM PAR (dB) 8.3902 8.7001 9.0063 9.2989 10.082 STD (δ) 0.0427 0.0562 0.0965 0.1247 0.1777 Absolute signal range 0.0642 0.0912≡ MSK + 3 dB 0.1470≡ QPSK +4 dB 0.2213≡ 8QAM +3.5 dB 0.2780≡ 16QAM +2 dB 10 -6 32-QAM 32-PSK 64-QAM 10 -8 0 2 4 6 8 10 Eb/N0 (dB) 12 14 16 18 Fig.(5-b) BER of OFDM using 32,64 -PSK&QAM Regarding to the BER performance of the used modulation techniques, it is clear from figure (5-a ) and (5-b) that, for M-PSK and M-QAM, the BER increases ad M increase while for the same M the BER of M-PSK is larger than that of M-QAM for the same Eb/No. 4. THE EFFECT OF POWER AMPLIFIERS Due to the nature of OFDM signal generation, as we mentioned above, signals have large crest factor CF, which set a demand for linearity. PAs are divided into classes according to the biasing used, the most common used amplifier classes are A, B and C. Class A amplifiers are the most linear among all classes, but with the lowest efficiency (50% at maximum). This poor efficiency causes high power consumption, which leads to worming in physical devices, and short battery life for mobile users. To achieve a better efficiency class B or C amplifiers are used but this costs a worse linearity. The high demands on linearity make class B or C unsuitable for OFDM systems. In practical applications of OFDM using QAM modulators, the amplifier is a compromise between class A and B, it is called class AB amplifier. NLA Model used for OFDM system is Rapp’s SSPA with characteristic [7]: It is again in agreement with the above results. It is clear that although the PAR reduction due to the use of MSK instead of QPSK is slightly small, the true gain is the reduction in the dynamic range by 3 dB, which enables us to use a low linearity and high efficiency power amplifiers. In addition a new indicator arises in the table which is the standard deviation δ, it is obvious from the table that MSK has the lowest δ while for M-QAM, as M increase δ increases also, since we can deal with OFDM signal as a narrow band Gaussian noise with a mean of zero and variance of δ2 , then 68% of amplitude values ranges in [-δ,δ] and 99.994% of amplitude values UbiCC Journal, Volume 2, Number 5, October 2007 24 vout = Where vin (1 + ( vin / v sat ) ) 2p 1 2p and hence facilitates the utilization of power efficient class C amplifier [6]. 10 0 QPSK 10 -1 vout and vin are complex i/p & o/p of the 10 -2 HPA , v sat is the output saturation level (we use v sat = 0.2, 0.5, 0.8 and 1) and P is “knee factor” that controls the smoothness of characteristic curve (we use P=2) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 Vsat=0.5 Vsat=0.8 Vsat=0.2 Vsat=1 10 -3 10 -4 QPSK without NLA QPSK with NLA 16-QAM with NLA 16-QAM without NLA 8-QAMwithout NLA 8-QAM with NLA 0 2 4 6 8 10 12 14 16 18 20 10 -5 Figure (7-b) effect of NLA on M-QAM 5. CONCLUSIONS For M-PSK, as M increases no effect has been occurred to the dynamic range and the PAR remains nearly the same, while for M-QAM, as M increases the dynamic range increase and so the PAR, but both of them agree in the spectral efficiency increase as M increase. For M-PSK and M-QAM, the BER increases as M increase while for the same M the BER of M-PSK is larger than that of M-QAM for the same Eb/No. Although the PAR reduction due to the use of MSK instead of QPSK is slightly small, the true gain is the reduction in the dynamic range by 3 dB, which enables us to use a low linearity and high efficiency power amplifiers like class B or C. MSK modulation gives us the lowest Crest Factor when used in OFDM besides its main advantage, that it ignores any fading introduced amplitude fluctuation present in the received signal, and hence facilitates the utilization of power efficient class C amplifier. REFERENCES [1] [2] Hanzo,” Bandwidth efficient wireless multimedia communications”, Proc. of IEEE, Vol.86, No.7, July 1998. J. Akhtman, B.Z. Bobrovsky, L.Hanzo,”Peak-to-average Power Ration reduction for OFDM Modems”, Proc. of VTC’2003, Jeju, Korea, 2003 K. R. Panta, J. Armstrong,” Use of Peak-to- average power reduction technique in HIPERLAN2 and its performance in fading channel”,DSPCS’02, Australia, Jan.2002. Farzaneh Kohandani,” PAR reduction in OFDM/CDMA Systems”, E&CE 612 Project, April 2002. L. Hanzo, W. Webb, T. Keller,“ Single and Multi-carrier Qudrature Amplitude Modulation”, NY, John Wiley sons, LTD, 2000. T. Javornik, G. Kandus, and A.G. Burr, “The performance of N-GMSK signals in non-linear channels”, WMPC'01, Aalborg, September 2001. A. Saul,” Comparison between Recursive Clipping and Active Constellation Extension for Peak Reduction in OFDM Systems”, in Proc. of Int. Symp. on Wireless Personal Multimedia Communications, Vol. 1, Yokusuka, Japan, October 19-22, 2003. © 2003 WPMC Figure (6) NLA input/output characteristic Figure (6) shows the Input output characteristics of the amplifier with the above specified parameters. When applying this amplifier using v sat = 0.1 on the OFDM signal we have noticed the advantage of MSK over QPSK, as shown below in figure (7-a). Also we have applied the amplifier on the OFDM signal using M-QAM with M=4, 8 and 16. Using v sat = 0.2, we noticed that as M increases the distortion due to NLA increases and so the BER as shown in figure (7-b). 10 -1 MSK without NLA MSK with NLA QPSK with NLA QPSK without NLA 10 -2 10 -3 [3] 10 -4 [4] -5 [5] 1 2 3 4 5 6 7 8 9 10 10 Figure (7-a) effect of NLA on MSK & QPSK As regarding to our previous results, it can be noticed that, the MSK modulation gives us the lowest PAR when used in OFDM besides its main advantage, that it ignores any fading introduced amplitude fluctuation present in the received signal, [6] [7] UbiCC Journal, Volume 2, Number 5, October 2007 25 DENSITY BASED TOPOLOGY CONTROL FOR MOBILE AD HOC NETWORKS Ash Mohammad Abbas Department of Computer Engineering Zakir Husain College of Engineering and Technology Aligarh Muslim University Aligarh – 202002, India abbas_iitd2001@yahoo.co.in Bijendra Nath Jain Department of Computer Science and Engineering Indian Institute of Technology Delhi Hauz Khas, New Delhi – 110016, India bnj@cse.iitd.ernet.in ABSTRACT The design of an efficient and effective protocol for topology control in mobile ad hoc networks is a challenging task. In this paper, we present a brief review of protocols reported in the literature and propose a protocol for topology control in mobile ad hoc networks. Our protocol relys on leader election and density based clustering. A problem that may occur in cluster based topology control is usually known as alien-soldier-node problem. We discuss a framework for avoiding aleinsoldier-node problem. Keywords: Ad hoc networks, topology control, leader election, density based clustering, alien-soldier-node problem. 1 INTRODUCTION An ad hoc network is a cooperative engagement of a collection of mobile devices without the required intervention of any centralized access point or an existing infrastructure. Applications of such a network include scenarios where either there is no infrastructure or its use is not permitted e.g. disaster recovery, search and rescue mission, battlefield communication, riot control and law enforcement, convention centers, online classrooms or conferences. In such situations, an ad hoc network may provide cheaper ways to share information. There are many characteristics that are peculiar to an ad hoc network as compared to other wired or wireless networks. The devices used to form an ad hoc network use wireless channel. The devices used have limited transmission range. As a result, the devices need to forward packets of one another towards their ultimate destination. In other words, participating nodes need to double as routers. The transmissions of a wireless device are often received at all nodes within its vicinity, which possibly may cause signal interference at neighboring nodes. The devices are usually powered through batteries. As a result, the depletion of battery power may cause node and associated link failures. The devices often have limited memories, which in turn demand high communication efficiency and small routing overheads. Also, the wireless devices may move about randomly or may adjust their transmission ranges during the communication. This gives rise to a dynamically varying topology of the network. Note that each and every transmission by a device incurs a cost in terms of energy spent by the device. Since energy is a scarce resource in an ad hoc network, therefore, one should try for mechanisms to save energy. In an ad hoc network, energy can be saved, to some extent, by suitably controlling and/or organizing the topology of the network. A mechanism or a protocol that may be used to control the topology of the network is called a topology control protocol. Due to inherent characteristics of an ad hoc network, it is a challenging task to design a protocol that may be used to control the topology of the network in an effective and efficient manner. As mentioned above, topology control is needed in an ad hoc network to conserve energy and maximizing network lifetime while maintaining network connectivity. However, other goals of a topology control protocol may also include optimizing network throughput and fault tolerance. Recently, many researchers have focused on the topology control protocols for ad hoc networks from different perspectives. Generally, an algorithm or a protocol may either be centralized or distributed. An UbiCC Journal, Volume 2, Number 5, October 2007 26 Figure 1: A classification of topology control protocols. algorithm is said to be optimal if it either maximizes the network lifetime or minimizes the energy spent. Centralized algorithms can achieve optimality, but they are suitable for static networks due to their lack of adaptability to changes in topology. In case of an ad hoc network, one does not have the complete information about the topology of the network and the topology may change dynamically. Therefore, one would like to have an algorithm or a protocol that may work with partial information about the topology, and that may adapt to changes in topology. As a result, one would prefer a distributed algorithm as opposed to a centralized algorithm. The rest of the paper is organized as follows. In section 2, we present a brief review of the work carried out by researchers in this field. In section 3, we propose a protocol for topology control in mobile ad hoc networks. Section 4, contains results and discussion. Finally, section 5 is for conclusions. 2 A REVIEW OF PRIOR WORK protocols of MAC layer category, the radios of nodes are turned-off by using in-channel signaling. Note that in case of in-channel signaling the same transmission channel is used for signaling. A demerit of the protocols of this category is relatively longer delays in comparison to the protocols that provide topology control at the network layer. This is due to the fact that the MAC layer protocols have a very small view of the network. In what follows, we present a brief review of the protocols in the second category. 2.2 Routing Level Protocols of routing category have a provision of topology control at the network layer. Protocols of this category can be further divided into subcategories based on the type of information used by an underlying routing algorithm. An underlying algorithm may use information about position, neighbors, direction, or combination of two or more than two types of these information. We call protocols that utilize the information about the positions of participating nodes as spatial protocols. We refer the protocols that are based on the information about neighbors as proximity based protocols and the protocols that use directional information as directional protocols. In addition to that, we call a protocol to be hybrid if a combination of two or more types of information is used in the underlying algorithm. 2.2.1 Spatial Protocols In [3], a protocol that is distributed in nature and that utilizes the position information provided by low power GPS receivers is presented. It tries to build a topology that is proved to minimize the energy required to communicate with a given master node. The master node is assumed to be a control and command station to which all nodes need to communicate. The main idea is that every node broadcasts its position and cost (of its path to master node) to nodes in its neighborhood. Upon receiving this information nodes in the neighborhood update their cost accordingly. Bellman-Ford algorithm is used to find shortest path to the master node, in terms of power as the cost function. Although, the protocol builds a topology that is proved to minimize the energy required to communicate with the given master node, however, the same topology may not work for an all-to-all communication. In other words, the topology built by the protocol might be significantly different from energy optimal topology for the all-to-all communication scheme. The reason is that the nodes that are not direct neighbors need to communicate through the master node, even if there might be a path of less cost if the communications would have not been routed through the master node. Further, for operation of the protocol there should be some Topology control can be provided either at the medium access control (MAC) layer or at the network layer using a routing protocol. Based on that, topology control protocols can be divided into two major categories: (i) MAC level, and (ii) routing level (see Figure 1). In what follows, we briefly review the protocols that provide topology control at the MAC layer. 2.1 MAC Level Topology control of an ad hoc wireless network can be accomplished at the MAC level itself. Generally, the MAC layer protocols follow an approach in which the radios of nodes that are not actively transmitting or receiving packets are turned off. However, when nodes whose radios are turned off need to transmit, a significant time may be consumed to turn on their radios. In other words, the protocols that provide topology control at MAC layer may incur an overhead in terms of turn-on delays. An example of a protocol of this category is SensorMAC (or S-MAC) [2]. In that, the primary issue is that of energy conservation, and the issues of delays and per-node fairness are treated as secondary. As we pointed out, the main idea is to periodically turn off the radios of nodes that are idle for a certain amount of time interval. Generally, in case of the UbiCC Journal, Volume 2, Number 5, October 2007 27 specialized hardware (such as GPS receiver) that provides the position information. As a result, the protocol may not be applied in situations where this type of information is not available. In what follows, we review protocols in the next subcategory. 2.2.2 Proximity Based Protocols As pointed out earlier, we call protocols that utilize information about their neighbors other than that of their positions, as proximity based protocols. One such protocol, called MobileGrid [4], is based on an algorithm that is distributed in nature. The performance of the network is linked with a parameter known as contention index (CI), which each node might estimate in a distributed manner. Therein, the CI is defined in terms of number of neighboring nodes and the transmission range of each node as follows. Let there be n nodes, each with a transmission range r, distributed randomly though uniformly in a region of area A. Then, contention index is given by CI = ρπ r 2 = nπ r 2 / A . In [4], the region with an area A is assumed to be a square with length L. The parameter ρ is called the node density i.e. nodes per unit area. Note that the parameter, CI, is related to the number of nodes within the transmission range (or the interference range, if different) of a node in the network. Specifically, the average number of neighbors of a node is CI - 1. In [4], the impact of CI on the performance of the network is presented from the point of view of network capacity and power efficiency. Therein, it is shown that the impact of node mobility on the network performance is minimal when the value of CI is fairly large. In other words, there would not be a significant effect of node mobility on the performance of the network because number of neighbors of each and every node is large. However, a too large value of CI may result in more congestion. It is argued that the average number of neighbors of a node should be around 3-9 so that the network is fairly connected while there is a tolerable congestion. Note that a node estimates CI using RTS/CTS/ACK messages that it receives from unique node IDs. It is obvious that the number of unique node IDs is the number of neighbors of that node and CI is one more than the number of neighbors. The MobileGrid protocol tries to keep the number of neighbors of every node within a range from a low to high threshold values. When the number of neighbors becomes less than the lower threshold value, the transmission range of nodes is increased, and vice versa. The process of adjustment of transmission range is continued until the number of neighbors fall within a given range. However, neither a characterization of the optimal value of the number of neighbors is provided nor there is any guarantee on the connectivity of the resulting communication graph of the network. Further, in case of MobileGrid, we mentioned earlier that the number of neighbors is determined by overhearing control and data packets at different layers. This type of estimation scheme does not incur an overhead, however, the accuracy of the scheme itself depends upon the flow of control and data packets. A mobile node that is not transmitting any such packets may not be detected by any of its neighbors. In [8], a protocol named k-Neigh is presented. The protocol is distributed, asynchronous, and localized. The k-Neigh protocol maintains the number of neighbors of every node equal to or slightly below a specific value k. Further, the protocol ensures that the resulting communication graph is symmetric. It makes the job of higher protocol fairly simple. It is also shown that, with n nodes in the network, the protocol terminates on every node after exactly flowing 2n messages and within a strictly bounded time. Another positive feature of k-Neigh is that it is based on distance estimation only, which can be implemented at reasonable cost in many realistic scenarios. It has been pointed out that the distance might be estimated based on Received Strength of Signal (RSSI) or Time of Arrival (ToA) of the signal. Therein, a special kind of graph called as k-neighbors graph is defined as follows. Given a parameter k, with 0R/2, then, AI = π