An Agent Based Approach for End-to-End QoS Guarantees in Multimedia IP networks by ijcsiseditor

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									                                                           (IJCSIS) International Journal of Computer Science and Information Security,
                                                           Vol. 8, No. 4, July 2010




        An Agent Based Approach for End-to-End QoS
            Guarantees in Multimedia IP networks

                   A.Veerabhadra Reddy                                                            Dr. D. Sreenivasa Rao
        Senior Lecturer, Department of ECE                                                     Professor, Department of ECE
       Government Polytechnic for Women, Hindupur                                                  JNTU CE, Hyderabad
             veerabhadrareddyphd@gmail.com                                                        dsraoece@yahoo.co.uk


Abstract— Quality of Service (QoS) guarantees are important, if              multimedia applications such as voice over IP. This is because
the network capacity is insufficient, particularly for real-time             it often requies the fixed bit rate and they are delay sensitive
streaming multimedia applications such as voice over IP.                     and also in networks where the capacity is a limited resource
Differentiated Services or DiffServ are the services of the original         (Eg. Cellular data commumnication). QoS mechanisms are not
internet that prioritizes flows according to their service class and         required in the absence of network congestion [1]. QoS is the
provides much better bandwidth utilization. Predicting the end-              most important implementation consideration within a
to-end behavior and acquiring the method by which individual                 converged network. It is a networking term that specifies a
routers deal with the type of service field is difficult and fairly          guaranteed network data performance level. Practically, QoS
appropriate. Moreover it becomes more difficult if a pakcet                  is a mechanism to ensure that audio and video data pass
crosses two or more DiffServ clouds, before reaching its                     through the network with minimum delay. IP voice or
destination. In this paper, we propose a QoS mapping framework
                                                                             videoconferencing calls will be unreliable, inconsistent, and
to achieve scalability and end-to-end accuracy in QoS, using a
Policy Agent (PA) in every DiffServ domain. This agent performs
                                                                             often unsatisfactory, if network QoS is poor [2].
admission control decisions depending on a policy database. It
configures the ingress and egress routers to perform traffic                 C. Two solutions for Quality of Service guarantees
policing and conditioning jobs. Moreover, it constructs the                  (i) Differentiated services (DiffServ)
shortest path between a source and destination satisfying the QoS                Differentiated Services or DiffServ are the services of the
constraints Bandwidth and Delay. By simulation results, we show              original internet which maintains stateless property.
that our proposed approach attains high throughput with                      Differentiated Services is a computer networking architecture
reduced packet loss when compared with the normal DiffServ                   which specifies a scalable,simple, and coarse-grained
architecture.
                                                                             mechanism for classifying, managing network traffic and
    Keywords-Quality of Service (QoS); Policy Agent (PA);
                                                                             providing QoS guarantees on modern IP networks [1]. The
DiffServ domain; QoS Route Selection; Packet loss, Throughput.               basic of this architecture is to provide network resources
                                                                             between the traffic aggregates. DiffServ prioritizes flows
                                                                             according to their service class and provides much better
                          I. INTRODUCTION                                    bandwidth utilization [3]
A. IP Networks                                                               (ii) Integrated services
    A computer network made of devices that support the                           Services that require stateful architecture of the internet are
Internet Protocol is an IP network [1]. In Internet Protocol                 known as Integrated Services or IntServ [1]. This architecture
Suite, IP is the primary protocol in Internet Layer which has                specifies the elements to guarantee QoS on the networks and it
the task of delivering the packets from source to destination                is the basis of the reservation of network resources between
mainly based on their address.                                               the individual flows [3]. The main idea of the service is the
                                                                             resource reservation and admission control. [4]. Deterministic
B. Quality of Service (QoS) in IP                                            bandwidth and end-to-end delays to the individual flows can
                                                                             be offered by the IntServ. Moreover, it depends upon the
     When compared with the achieved service quality, the                    admission control by placing strict resource reservations
traffic engineering term quality of service (QoS) will refer to              which guarantees the worst case situation [3]. The following
the resource reservation control mechanisms in both the fields               are the categories of services in this architecture:
of computer networking and other packet-switched
telecommunication networks.The abiltiy of the QoS is to                         o     Guaranteed Services
provide different priorties to different applications, users or                 o     Controlled-load Service
data flows or guaranteeing a certain level of performance to a
data flow. For example, it guarantees required bit rate, delay,                  Guaranteed Services: It is estimated as the strongest
jitter, packet dropping probability and/or bit error rate. Quality           allowable service in the environment of the internet so far. It
of Service (QoS) guarantees are important, if the network                    has the ability to provide per flow bandwidth and delay
capacity is insufficient, particularly for real-time streaming



                                                                       188                                http://sites.google.com/site/ijcsis/
                                                                                                          ISSN 1947-5500
                                                        (IJCSIS) International Journal of Computer Science and Information Security,
                                                        Vol. 8, No. 4, July 2010



guarantees and it can assure that the packets will arrive within         dimensioned to carry the same traffic. The traffic management
a selected delivery time [1].                                            is used to prevent the collapse during the peaks.
    Controlled-load Service: It allows the services poorly. It               Measuring the peak load is not possible. Since the TCP
supports the applications which are highly sensitive to                  protocol requests more bandwidth as the loss rate decreases, it
congested networks such as real time applications and these              is not possible to measure the links to avoid end-to-end loss
applications must tolerate small amounts of loss and delay. If           altogether, when sending a large file. On the other hand,
an application uses this service, the performance will not be            increasing the capacity of one link causes loss on a different
affected even when the network load is increased. The traffic            link.
will be provided with service similar to normal traffic in a
network under light condition [1].                                           By dropping the packets which are expended in carrying
                                                                         these packets until now through the network, the resources
                                                                         will be wasted. The bandwidth consumption at the congestion
D. Problems or Challenges of QoS                                         point and in the network is caused by retransmitting this traffic
    Many things can happen to packets as they travel from                in many cases. The packets must be discarded as close to the
origin to destination, resulting in the following problems as            edge of the network as possible, while Diffserv is often
seen from the point of view of the sender and receiver:                  implemented throughout a network to minimize this waste.
   When the packets travel from the source to destination, it                The problem with IntServ is that many states must be
experiences the following problems as seen from the point of             stored in each router. It is difficult to keep the path of all the
view fo the sender and the receiver.                                     reservations because it works on the small scale. Thus the
   Dropped Packets: The routers may fail to deliver (drop)               architrecture is not much familiar [1].
some packets when they arrive, if the buffers of the dropped                In this paper, we propose a QoS mapping framework to
packets are already full. Dependng on the state of the network,          achieve scalability and end-to-end accuracy in QoS, using a
some of the packets or none or all the packets might be                  Policy Agent (PA) in every DiffServ domain. This agent
dropped. Thus it is not possible to forecast the packets.                performs admission control decisions depending on a policy
    Delay: For a packet it may take a long time to reach its             database.
destination, because it gets held up in long queues, or takes a
indirect route to avoid congestion. Excessive delay can render                                   II. RELATED WORK
an application such as VoIP or online gaming unusable, in                    Kazi Khaled Al-Zahid et al [5], have presented a strategy
some cases.                                                              for ETE QoS management in IP networks based on the use of
     Jitter: Packets may reach the destination with different            programmable software agents. They have proposed a QoS-
delays from the source. A packet’s delay varies with its                 based routing architecture to serve multi-constrain ETE high
position in the queues of the routers along the path between             priority applications. According to their proposal, the users
source and destination.This position can vary and thus it                can be electronically specify their QoS requirement from the
cannot be predicted. This variation in delay is known as jitter          host application based on their preference. Although, their
[1].                                                                     proposed system has some performance limitations, but as a
                                                                         whole it is flexible, because the routing functionality is
    Out-of-order Delivery: When a group of packets are                   completely done by the agents which works as complements
routed, then different packets may take different route. Each of         with the existing technology.
the packets results in different delay because the order of the
packets are changed from the source to the destination. Special              Sergio Gonzalez-Valenzuala et al [6] have investigated an
additional protocols are required to rearrange the out-of-order          improvement by developing algorithms for determining the
packets.                                                                 optimal multipoint-to-point (mp2p) routes through the use of
                                                                         mobile software agents. They have presented an mp2p routing
    Error: When packets are transmitted along a route, it may            scheme using a mobile intelligent agent system, called
be misdirected or combined together or corrupted. The                    WAVES. The agents work in a highly distributed and parallel
receiver have to detect this and the request the sender to               manner, cooperating to determine optimal routes in an mp2p
resend packets [1].                                                      connection scenario. This work aims at closing the gap
                                                                         between the theoretical routing research based on mobile
E. Problems in Differentiated and Integrated Services                    agents, and practical routing requirements for real world
    Predicting the end-to-end behavior and acquiring the                 networks that are likely to be deployed during the forthcoming
method by which individual routers deal with the type of                 years.
service field is difficult and fairly appropriate. Moreover it               Yao-Nan Lien et al [7] have stated briefly an approach for
becomes more difficult if a pakcet crosses two or more                   the problem of QoS budget allocation which is deliberated in
DiffServ clouds, before reaching its destination.                        optimization for increasing resource usage efficiency. The
    Simple over-provisioning is an inefficient solution for the          end-to-end QoS controller in QoS coordination layer has the
internet traffic which is highly bursty. If the network is               capability of global resource planning. It suggests that an end-
dimensioned to carry all traffic with traffic management, it             to-end QoS controller will plan all resource provisions
will cost an order of magnitude more than a network                      according to the traffic demands, and all the resource




                                                                   189                               http://sites.google.com/site/ijcsis/
                                                                                                     ISSN 1947-5500
                                                          (IJCSIS) International Journal of Computer Science and Information Security,
                                                          Vol. 8, No. 4, July 2010



allocation policy will be in accord with the planning. Their                              B p = MIN{Bl | l ∈ P}                                 (1)
framework with simulation study demonstrates that it can
indeed substantially increase the total number of network                                 Dp =   ∑Dl + ∑Dn                                      (2)
paths under constraints of end-to-end QoS requirements.                                          l∈P       n∈P
    Daniel Schlosser et al [8] have proposed a simple interface                             Cp =   ∑Cl + ∑Cn                                    (3)
as an abstraction of a network service based on the service                                        l∈P     n∈P
oriented architecture approach. The approach considers QoS
as the network functionality the user is mainly interested in                 Where, P is the path from source s to the destination d .
and includes charging. They have shown how QoS guarantees
for several parts of one connection can be consolidated into a             B p is the bandwidth of the path P
QoS description for the complete service. Moreover, they have              D p is the delay of the path P
discussed options to measure the QoS and presented
measurements exposing the quality of an available active                   C p is the cost of the path P
measurement tool, Cisco IP SLA.                                                The problem is to find a path between s to d , such that it
    Lynda Zitoune et al [9] have presented a reactive control              would satisfy all QoS constraints from source to destination.
policy which adapts the source bit rate to the reserved                    The above constraints can be categorized in two groups: link
resources in order to ensure performance guarantees for                    constraints and path constraints. Path constrains again consist
multimedia applications. Their proposed method called                      of two classes: additive and multiplicative. Serving application
flatness based trajectory tracking deals with drastic traffic flow         that requires both of these constraints simultaneously is yet an
rate changes and limits the traffic in order to respect the time           unsolved problem.
constraints. They have showed the contribution of the reactive
control and the dynamic regulation using purely control                                IV. PROPOSED AGENT BASED APPROACH
theoretic approaches which stabilize the network and avoid
undesirable oscillations for the transmission of such critical             A. Design Overview
flows. By their work they have presented a performance                         In this work, we propose a QoS mapping framework for
analysis for such rate control mechanism, and illustrate its               both user and administrative policy, qualitative and
feasibility through its implementation on MPLS-TE control                  quantitative QoS constraints over the internet’s DiffServ
plane of SSFnet/Glass simulator.                                           domain. We consider the Policy Agent (PA) that depends on
    Rick Whitner et al [10] have examined the issue of                     the local state information to satisfy the end user and do not
matching active measurements to the network’s QoS                          consider any central mechanisms such as bandwidth broker or
configuration when monitoring a QoS-enabled IP network.                    adaptive bandwidth scheme. Thus in our approach, according
Initially, they have illustrated the issue using common active             to the service and the requirement of the end user, multi
measurement techniques. Then, they have examined                           constraint MQoS is used for QoS mapping requested in
approaches to matching active measurements to the network’s                different degrees by user applications.
QoS configuration. Finally, they presented their experiences in                By assigning each packet with an appropriate QoS level,
prototyping one approach.                                                  the QoS control takes place. In order to manage traffic
                                                                           according to the traffic conditioning agreement specified in the
                      III. NETWORK MODEL                                   service level agreement (SLA), the application layer is
    We assume that a communication network can be modeled                  responsible for producing the MQoS and sending it to the
using a graph G = (V , E ) where V is the set of nodes which               ingress of a DiffServ domain. The PA dynamically configured
                                                                           the necessary interface based on the requested traffic’s source
could be routers, servers or switches and E represents the set             and destination information. Thus the traffic which is marked
of edges or links of the network. For any consecutive nodes a,             as the high priority will get the opportunity while the BE
b, the link l ab can be expressed for different parameters as:             traffic is considered as low priority. The process is repeated
                                                                           for each node along the destination, if the PA satisfies the
 H l = H ab                                                                requested MQoS. Otherwise, a negative notification is sent to
Cl = C ab                                                                  the source that current network is unable to meet the requested
 Dl = Dab                                                                  QoS constraints.
 Bl = Bab                                                                  B. QoS Moniroting by the PA
    Where H l , is the hops, Cl is the cost, Dl is the delay and
 Bl is the bandwidth of the link l , where the link l ∈ E is                                 TABLE I. QOS RESOURCE MATRIX
directly connected by a ∈ V and b ∈ V . These parameters may                  N            Bandwidth                   Delay             Cost
occur in either nodes or edges. And these have either positive
or non-negative impact over the communication network. QoS                    N0              e00                       e01              E02
for different parameter can be expressed using the following                  N1              e10                       e11              E12
relation.                                                                     N2              e20                       e22              E23




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                                                                                                         ISSN 1947-5500
                                                         (IJCSIS) International Journal of Computer Science and Information Security,
                                                         Vol. 8, No. 4, July 2010



                                                                          such as bandwidth, delay, cost, etc. Thus, the important
    The QoS monitoring at each node involves checking                     parameter is checked first by the PA.
whether there are sufficient resources for meeting the MQoS.
This is performed by the QoS Mapping Engine (QME) of the                  Algorithm
PA at the routers or switches. The QME contains a 2-D                         Our algorithm takes a sub-optimal path search approach
resource matrix shown in Table I that maps different network              for the selected QoS constraints. The required input parameter
resource parameters with its neighbor routers entity. In Table            is the MQoS which includes the source ( s ), destination ( d )
I, N denotes the current visiting node that meets all the                 and multiple QoS criterion. In this algorithm, { N } denotes the
requested constraints of host application and N0, N1, N2 are the          set of nodes that are involved in the path P( s, d ) , while V is
attached neighbors of N. eij (where i is the router entity and            the total number of nodes in entire network.
 j is the constraint) in the resource matrix denotes the value of         1. MQoS is applied from s to the next hop router through the
constraints with the attached interface. The main advantage of            primary shortest path on the routing table.
using PA in admission control is to find a path with the                  2. If PAi accept the request then
requested QoS constraints.
                                                                                The RV is updated to {N}, where RV is the route vector.
   The objective of the PA at any node i , is to check the                      PA stores the partial route and no new QoS provisioning
consistency of the following relations to optimize the                          is accepted for the resources.
requested MQoS.                                                               End if
                                                                          3. If MQoS reaches the d, then
      MIN ( Bli −1 ) ≥ Bcons , where li −1 ∈ P                (1)                positive feedback is sent to the source in the reverse
      i −1
                                                                                unicast path.
                                                              (2)            End if
      ∑ Dl ≤ Dcons
        s                                                                 4. If the QoS monitoring fails, then
      i −1                                                                       PAi sends the negative feedback to the last router that
      ∑ Cl ≤ Ccons                                            (3)
                                                                                 accepts the request.
       s                                                                     End if
    During the path selection, if PAi accepts the request                 5. When an infeasible link is encountered, PA searches for
                                                                          alternate paths for that can support the requested QoS
from PAi −1 , then PAi prohibits the RE (router entity) to accept
                                                                          constraints.
any new resource request from others until the current request
expires. If PAi fails to qualify any one of the inequalities              6. PA then bypasses the MQoS through the alternate path.
shown above, a reject reply is send to PAi −1 so that PAi −1              7. The PA can trace back when it faces infeasible link that
can trigger the routing algorithm to find the next alternate path         fails to satisfy the requested QoS constraints.
to the destination.                                                       8. The algorithm runs repeatedly until it finds any path to
    From the above description, it is easy to understand that             destination if there is any. MQoS can be send with current
PA can support as many as QoS constraints as the application              accumulated value of the constraints from the stored value at
requires. Addition of a new constraint is just to include it in           any time when it is looking for alternate paths.
the resource matrix at each node so the QME can take care off                 To find the route using MQoS properly, it requires a set of
the incoming MQoS request for new constraint.                             standards which should be implemented in the PA. Low
                                                                          priority traffic that travels in the same route may experience
C. QoS Route Selection                                                    delay due to the high precedence of QoS traffic. If PA wants
    The following assumptions are made in order to attain                 to satisfy the requested QoS constraints, it adjusts the router to
optimal performance:                                                      handle high priority traffic. Another advantage of this
                                                                          approach is, PA can dynamically tune only those sub
   1. The existing link state protocol such as Open Shortest              interfaces where high priority traffic actually flows and others
Path Protocol is used to obtain the topology information.                 IP interface can be remain untouched. When a session is
   2. A hop by hop parameter optimization is considered to                closed PA can readjust the router’s state for usual operation
reach the final destination rather than considering the whole             according to RE’s need. Moreover PA can send advance
path.                                                                     warning message to other same priority or low priority streams
                                                                          to inform them to choose either different path or slow down
    3. The PA and the corresponding routing entity are closely            their transmission to avoid congestion and loss of transmission
integrated in such a way that if there any changes in the                 quality.
routing entity, then PA is informed to make necessary changes
in the QoS resource matrix.
                                                                                               V. SIMULATION RESULTS
    If the routing decisions are made in each router with local
information by the PA, then it is referred as hop by hop
routing. In our algorithm, we maintain a topological order



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A. Simulation Model and Parameters
                                                                                                                                  Rate Vs Packet Loss2
    In this section, we examine the performance of our agent
based QoS mapping approach with an extensive simulation                                                                300000
study based upon the ns-2 network simulator [11]. We                                                                   250000




                                                                                                        Packet Loss2
compare our results with the normal DiffServ architecture.                                                             200000
The topology used in our experiments is depicted in Figure 1.                                                                                                          Agent
                                                                                                                       150000
As we can see from the figure, we have five senders and five                                                                                                           Normal
                                                                                                                       100000
receivers connected by a ingress router E1 and egress router
                                                                                                                        50000
E2 through a core router.
                                                                                                                            0
                                                                                                                                  5     10          15   20
                                                                                                                                             Rate


                                                                                                                         Figure 3. Rate Vs Packet Loss at Receiver 2


                                                                                                                                  Rate Vs Packet Loss3


                                                                                                                       300000
                                                                                                                       250000




                                                                                                        Packet Los3
                                                                                                                       200000
                                 Figure 1. Simulation Topology                                                                                                         Agent
                                                                                                                       150000
                                                                                                                                                                       Normal
                                                                                                                       100000
B. Performance Metrics                                                                                                  50000
    In our experiments, we vary the bottleneck bandwidth,                                                                   0
traffic flow and traffic rate. We measure the following metrics:                                                                  5     10          15   20
                                                                                                                                             Rate
    •    Packet Loss
    •    Throughput in terms of packets                                                                                  Figure 4. Rate Vs Packet Loss at Receiver 3
    •    Throughput in Mb/s
                                                                                                                                  Rate Vs Packet Loss4
   The results are described in the next section.
                                                                                                                       250000
C. Results
                                                                                                                       200000
                                                                                                        Packet Loss4




A. Effect of Varying Rate
                                                                                                                       150000                                          Agent
    In our first experiment, we vary the rate as 5Mb, 10Mb,
15Mb and 20Mb in order to calculate the packet loss,                                                                   100000                                          Normal
throughput (packets received) and throughput (Mbps). The                                                               50000
results for the individual receivers are given.                                                                             0
1. Packet Loss                                                                                                                    5     10          15   20
                                                                                                                                             Rate
                                    Rate Vs Packet Loss1


                        350000                                                                                           Figure 5. Rate Vs Packet Loss at Receiver 4
                        300000
         Packet Loss1




                        250000
                                                                                                                                  Rate Vs Packet Loss5
                        200000                                          Agent
                        150000                                          Normal
                        100000                                                                                         250000
                         50000                                                                                         200000
                                                                                                        Packet Loss5




                             0
                                   5      10       15   20                                                             150000                                          Agent

                                            Rate                                                                       100000                                          Normal
                                                                                                                        50000

                          Figure 2. Rate Vs Packet Loss at Receiver 1                                                       0
                                                                                                                                  5     10          15   20
                                                                                                                                             Rate


                                                                                                                         Figure 6. Rate Vs Packet Loss at Receiver 5




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    Figure 2 to 6 shows the packet loss at the receivers 1 to 5
                                                                                                                                              Rate Vs Throughput (pkts)4
respectively. From the figure, we can see that the packet loss
is high in the Normal scheme when compared with our Agent
                                                                                                                                 80000
based scheme when varying the rates.




                                                                                                            Throughput (pkts)4
                                                                                                                                 60000
2. Throughput (Packets)
                                                                                                                                                                                    Agent
                                                                                                                                 40000
                                     Rate Vs Throughput (pkts)1                                                                                                                     Normal
                                                                                                                                 20000
                             60000
        Throughput (pkts)1




                                                                                                                                      0
                             50000
                                                                                                                                               5     10          15   20
                             40000
                                                                            Agent                                                                         Rate
                             30000
                                                                            Normal
                             20000
                             10000                                                                                                Figure 10. Rate Vs Throughput at Receiver 4
                                 0
                                      5      10          15   20
                                                                                                                                              Rate Vs Throughput (pkts)5
                                                  Rate
                                                                                                                                 80000




                                                                                                            Throughput (pkts)5
                               Figure 7. Rate Vs Throughput at Receiver 1                                                        60000
                                                                                                                                                                                    Agent
                                                                                                                                 40000
                                     Rate Vs Throughput (pkts)2                                                                                                                     Normal
                                                                                                                                 20000
                             80000
                                                                                                                                      0
        Throughput (pkts)2




                             60000                                                                                                             5     10          15   20
                                                                            Agent                                                                         Rate
                             40000
                                                                            Normal
                             20000
                                                                                                                                  Figure 11. Rate Vs Throughput at Receiver 5
                                 0
                                      5      10          15   20                                       Figure 7 to 11 gives the Throughput in packets for the
                                                                                                    receivers 1 to 5 by varying the rates. It shows that the
                                                  Rate
                                                                                                    Throughput is more in the case of Agent based scheme when
                                                                                                    compared with Normal scheme
                               Figure 8. Rate Vs Throughput at Receiver 2
                                                                                                    3. Throughput (Mbps)
                                     Rate Vs Throughput (pkts)3                                                                           Rate Vs Throughput(Mbps)1

                             80000                                                                                               14
                                                                                                            Throughput(Mbps)1
        Throughput (pkts)3




                                                                                                                                 12
                             60000                                                                                               10
                                                                            Agent                                                 8                                                 Agent
                             40000                                                                                                6                                                 Normal
                                                                            Normal
                                                                                                                                  4
                             20000                                                                                                2
                                                                                                                                  0
                                 0
                                                                                                                                          5        10          15     20
                                      5      10          15   20
                                                                                                                                                        Rate
                                                  Rate


                                                                                                                                  Figure 12. Rate Vs Throughput at Receiver 1
                               Figure 9. Rate Vs Throughput at Receiver 3




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                                                                                              Figure 12 to 16 gives the Throughput in Mbps for the
                         Rate Vs Throughput(Mbps)2                                         receivers 1 to 5 for varying the rates. It shows that the
                                                                                           Throughput is more in the case of Agent based scheme when
                    12                                                                     compared with Normal scheme.
Throughput(Mbps)2

                    10
                     8                                                                     B. Effect of Varying Simulation Time
                                                                   Agent                       In our second experiment, we vary the time as 2, 4,6,..10
                     6
                                                                   Normal                  seconds in order to calculate the packet loss, throughput
                     4
                     2
                                                                                           (packets received) and throughput (Mbps). The results for the
                     0
                                                                                           individual receivers are given.
                          5       10          15   20                                      1. Packet Loss
                                       Rate
                                                                                                                              Tim e Vs Packet Loss1

                     Figure 13. Rate Vs Throughput at Receiver 2                                                  25000
                                                                                                                  20000




                                                                                                   Packet Loss1
                         Rate Vs Throughput(Mbps)3                                                                15000                                           Agent
                                                                                                                  10000                                           Normal
                    12
Throughput(Mbps)3




                                                                                                                   5000
                    10
                                                                                                                      0
                     8
                                                                   Agent                                                  0     2   4    6     8   10
                     6
                                                                   Normal                                                            Tim e
                     4
                     2
                     0                                                                                             Figure 17. Time Vs Packet Loss at Receiver 1
                          5       10          15   20
                                       Rate
                                                                                                                              Tim e Vs Packet Loss2


                     Figure 14. Rate Vs Throughput at Receiver 3                                                  20000
                                                                                                   Packet Loss2




                                                                                                                  15000
                         Rate Vs Throughput(Mbps)4                                                                                                                Agent
                                                                                                                  10000
                                                                                                                                                                  Normal
                    10                                                                                             5000
Throughput(Mbps)4




                     8
                                                                                                                      0
                     6                                             Agent                                                  0     2   4    6     8   10
                     4                                             Normal                                                            Tim e
                     2
                     0                                                                                             Figure 18. Time Vs Packet Loss at Receiver 2
                          5       10          15   20
                                       Rate
                                                                                                                              Tim e Vs Packet Loss3

                     Figure 15. Rate Vs Throughput at Receiver 4                                                  20000
                                                                                                   Packet Loss3




                                                                                                                  15000
                         Rate Vs Throughput(Mbps)5                                                                                                                Agent
                                                                                                                  10000
                                                                                                                                                                  Normal
                    10                                                                                            5000
Throughput(Mbps)5




                    8
                                                                                                                      0
                    6                                              Agent                                                  0     2   4     6    8   10
                    4                                              Normal                                                            Tim e
                    2
                    0
                                                                                                                   Figure 19. Time Vs Packet Loss at Receiver 3
                          5       10          15   20
                                       Rate


                     Figure 16. Rate Vs Throughput at Receiver 5




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                                                                                                                                    ISSN 1947-5500
                                                                                     (IJCSIS) International Journal of Computer Science and Information Security,
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                                        Tim e Vs Packet Loss4                                                                           Tim e Vs Throughput(pkts)2


                            20000                                                                                               14000




                                                                                                            Throughput(pkts)2
                                                                                                                                12000
        Packet Loss4


                            15000                                                                                               10000
                                                                                                                                 8000                                          Agent
                                                                            Agent
                            10000                                                                                                6000                                          Normal
                                                                            Normal                                               4000
                             5000                                                                                                2000
                                                                                                                                    0
                                0                                                                                                       0    2    4    6    8   10
                                    0     2   4    6    8   10
                                                                                                                                                  Tim e
                                               Tim e

                                                                                                                                 Figure 23. Time Vs Throughput at Receiver 2
                             Figure 20. Time Vs Packet Loss at Receiver 4

                                                                                                                                        Tim e Vs Throughput(pkts)3
                                        Tim e Vs Packet Loss5
                                                                                                                                14000




                                                                                                            Throughput(pkts)3
                            15000                                                                                               12000
                                                                                                                                10000
                                                                                                                                                                               Agent
        Packet Loss5




                                                                                                                                 8000
                            10000                                                                                                6000                                          Normal
                                                                            Agent
                                                                                                                                 4000
                                                                            Normal                                               2000
                            5000
                                                                                                                                    0
                                                                                                                                        0    2    4    6    8   10
                                0
                                                                                                                                                  Tim e
                                    0     2   4    6    8   10
                                               Tim e
                                                                                                                                 Figure 24. Time Vs Throughput at Receiver 3

                             Figure 21. Time Vs Packet Loss at Receiver 5
                                                                                                                                        Tim e Vs Throughput(pkts)4
   Figure 17 to 21 show the packet loss for the receivers 1 to
5. From the figures, we observe that the loss is high in the                                                                    14000
                                                                                                            Throughput(pkts)4




Normal scheme when compared with our Agent based scheme                                                                         12000
                                                                                                                                10000
when varying the time.                                                                                                           8000                                          Agent

2. Throughput in Packets                                                                                                         6000                                          Normal
                                                                                                                                 4000
                                    Tim e Vs Throughput(pkts)1                                                                   2000
                                                                                                                                    0
                                                                                                                                        0    2    4    6    8   10
                            14000
        Throughput(pkts)1




                            12000                                                                                                                 Tim e
                            10000
                             8000                                           Agent                                                Figure 25. Time Vs Throughput at Receiver 4
                             6000                                           Normal
                             4000
                             2000                                                                                                       Tim e Vs Throughput(pkts)5
                                0
                                    0     2   4    6    8   10                                                                  14000
                                                                                                            Throughput(pkts)5




                                                                                                                                12000
                                               Tim e
                                                                                                                                10000
                                                                                                                                 8000                                          Agent
                                                                                                                                 6000                                          Normal
                             Figure 22. Time Vs Throughput at Receiver 1
                                                                                                                                 4000
                                                                                                                                 2000
                                                                                                                                    0
                                                                                                                                        0    2    4    6    8   10
                                                                                                                                                  Tim e


                                                                                                                                 Figure 26. Time Vs Throughput at Receiver 5




                                                                                              195                                                http://sites.google.com/site/ijcsis/
                                                                                                                                                 ISSN 1947-5500
                                                                                    (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                    Vol. 8, No. 4, July 2010



   Figure 22 to 26 give the Throughput in packets for the
receivers 1 to 5 by varying the time. It shows that the                                                                               Time Vs Throughput(Mbps)4
Throughput is more in the case of Agent based scheme when
compared with Normal scheme                                                                                                      3




                                                                                                            Throughput(Mbps)4
                                                                                                                                2.5
3. Throughput (Mbps)                                                                                                             2
                                                                                                                                                                             Agent
                                                                                                                                1.5
                                        Time Vs Throughput(Mbps)1                                                                                                            Normal
                                                                                                                                 1
                                                                                                                                0.5
                            5
        Throughput(Mbps)1




                                                                                                                                 0
                            4                                                                                                         0   2     4    6    8    10
                            3                                              Agent                                                                Tim e
                            2                                              Normal
                            1                                                                                                     Figure 30. Time Vs Throughput Receiver 4
                            0
                                    0       2       4      6    8   10                                                                Time Vs Throughput(Mbps)5
                                                    Tim e
                                                                                                                                2.5




                                                                                                            Throughput(Mbps)5
                                Figure 27. Time Vs Throughput Receiver 1                                                         2
                                                                                                                                1.5                                          Agent
                                                                                                                                 1                                           Normal
                                        Time Vs Throughput(Mbps)2
                                                                                                                                0.5

                            2.5                                                                                                  0
        Throughput(Mbps)2




                                                                                                                                      0   2     4    6    8    10
                                2
                                                                                                                                                Tim e
                            1.5                                            Agent
                                1                                          Normal
                                                                                                                                  Figure 31. Time Vs Throughput Receiver 5
                            0.5
                                0                                                                     Figure 27 to 31 gives the Throughput in Mbps for the
                                        0       2   4       6   8   10                             receivers 1 to 5 by varying the time. It shows that the
                                                        Tim e                                      Throughput is more in the case of Agent based scheme when
                                                                                                   compared with Normal scheme.

                                Figure 28. Time Vs Throughput Receiver 2
                                                                                                                                              VI. CONCLUSION
                                                                                                       In this paper, we propose a QoS mapping framework to
                                        Time Vs Throughput(Mbps)3                                  achieve scalability and end-to-end accuracy in QoS, using a
                                                                                                   Policy Agent (PA) in every DiffServ domain. This agent
                            2.5                                                                    performs admission control decisions depending on a policy
        Throughput(Mbps)3




                                2
                                                                                                   database. It configures the ingress and egress routers to
                                                                                                   perform traffic policing and conditioning jobs. The QoS
                            1.5                                            Agent                   monitoring at each node involves checking whether there are
                                1                                          Normal                  sufficient resources for meeting the Multiple QoS constraints
                            0.5
                                                                                                   (MQoS). This is performed by the QoS Mapping Engine
                                                                                                   (QME) of the PA at the routers or switches. Moreover, it
                                0                                                                  constructs the shortest path between a source and destination
                                        0       2   4       6   8   10                             satisfying the QoS constraints Bandwidth and Delay. During
                                                        Tim e                                      the path selection, if PA at node i accepts the request from its
                                                                                                   previous node, then PA prohibits the router entity to accept
                                                                                                   any new resource request from others until the current request
                                Figure 29. Time Vs Throughput Receiver 3                           expires. If PA fails to qualify any one of the inequalities, a
                                                                                                   reject reply is send to the PA at previous node so that it can
                                                                                                   trigger the routing algorithm to find the next alternate path to
                                                                                                   the destination. By simulation results, we have shown that our
                                                                                                   proposed approach attains high throughput with reduced
                                                                                                   packet loss when compared with the normal DiffServ
                                                                                                   architecture.




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                                                                                                                                                ISSN 1947-5500
                                                                   (IJCSIS) International Journal of Computer Science and Information Security,
                                                                   Vol. 8, No. 4, July 2010



                                REFERENCES                                            Science & Technology, member of JNTU forum for Science & Society and
                                                                                      Coordinator for campus networking at JNTU CE,
[1]  http://en.wikipedia.org/wiki
[2]  E. Brent Kelly, “Quality of Service in Internet Protocol (IP) Networks”,
     Infocomm – 2002.
[3] S. Terrasa, S. Saez, J. Vila and E. Hernandez, “Comparing the utilization
     bounds of IntServ and DiffServ”, supported by the “HET-NETs – 2004.
[4] R.Braden, D.Clark and S.Shenker, “Integrated Services in the Internet
     Architecture: an Overview”, RFC Editor, July 1994.
[5] Kazi Khaled Al-Zahid and Mitsuji Matsumoto, “Software Agent (SA) to
     guarantee QoS for multi constrain applications in all-IP networks”,
     Second International Conference on Mobile Computing and Ubiquitous
     Networking, April 2005.
[6] Sergio Gonzalez-Valenzuela, Victor C. M. Leung and Son T. Vuong,
     “Multipoint-to-Point Routing With QoS Guarantees Using Mobile
     Agents”, Mobile Agents for Telecommunication Applications,
     SpringerLink, January 2001, DOI: 10.1007/3-540-4651-6.
[7] Yao-Nan Lien, Hsing Luh and Chien-Tung Chen, “End-to-end QoS with
     Budget-Based Management”, Proc. of the 2003 First International
     Working Conference on Performance Modeling and Evaluation of
     Heterogeneous Networks, July 2003.
[8] Daniel Schlosser and Tobias Hobfeld, “Service Oriented Network
     Framework Enabling Global QoS and Network Virtualization”, 20th
     ITC Specialist Seminar, 18.-20. May 2009.
[9] Lynda Zitoune, Amel Hamdi, Hugues Mounier and Veronique Veque,
     “Dynamic Resource Management Approach In QoS-Aware IP Networks
     Using Flatness Based Trajectory Tracking Control”, IEEE, IET
     International Symposium On Communication Systems, Networks And
     Digital Signal Processing, 2009.
[10] Rick Whitner, Graham Pollock and Casey Cook, “On Active
     Measurements in QoS-Enabled IP Networks”, In PAM'02, Fort Collins
     CO, Mar. 2002.
[11] Network Simulator: www.isi.edu/nsnam/ns



                     A.Veerabhadra Reddy completed his B.Tech in
                     Electronics and Communication Engineering from
                     Bapatla college of Engineering In 1988.He worked as a
                     production Engineer in Unitron ltd. Faridabad for one
                     year and from June 1989 to June 1990 worked as Asst.
                     professor in ECE at KITS, Ramtek. Then he has been
                     serving to department of Technical Education A.P,
                     Hyderabad from 1990. He completed his M.Tech (ECE)
                     from JNTU, Kakinada in 2005. Now he is holding the
post of Senior lecturer in ECE at Govt. polytechnic for women, Hindupur and
additional charge to Govt. Polytechnic, Dharmavaram as an Offier on Special
Duty. He was the visiting faculty to RGM Engineering College, Alfa College
of Engineering, and Sri Ramakrishna post graduate college, Nandyal, A.P and
taught various subjects in Computer Science and Electronics. He worked for 5
years as Assistant project officer in Community polytechnic scheme of
MHRD, Govt. of India attached to polytechnics. He has been persuing his
Ph.D under the guidance of Dr. D.Sreenivasa Rao, Professor, JNTU.


                   Dr.D.Srinivasa Rao has 20 years of teaching experience.
                   He worked at CBIT as Lecturer in ECE Department for 6
                   years during 1988 – 1994. He worked at ECE
                   Department of JNTU, Aanantapur in various capacities
                   for 11 years during 1994-2005. Presently he is working
                   as Professor in ECE Department of JNTU CE,
                   Hyderabad. His research interest are in the area of
                   communications and computer network s Presently 12
                   research students are working under his guidance. He has
                   22 publications in various National, International
Conferences and Journals. He has attended more than 10 Short Term Courses,
Summer Schools, and Workshops, conducted by various organizations. He has
organized workshops and refresher courses. He has chaired sessions at various
national conferences. He is advisory committee member for GNIT,
Hyderabad. He is also governing body member for Syed Hashim College of




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                                                                                                                   ISSN 1947-5500

								
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