Mobile agent based online bandwidth allocation scheme for multimedia communication

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1 Mobile based online bandwidth allocation scheme for multimedia communication S.S.Manvi and P. Venkataram Electrical Communication Engineering Department, Indian Institute of Science, Bangalore INDIA, Abstract- The allocation of bandwidth for multimedia traffic poses a technical challenge due to bursty and isochronous nature of applications. In this paper, we propose a mobile based approach for bandwidth allocation in multimedia communication. It is based on the the network congestion monitored by the s at the clients. The mobile hosted by the server will allocate bandwidth online to the applications within the requested range at regular intervals. And also, keeps aggregated bandwidth below the link bandwidth of server and clients. The approach reduces the network control traffic used in traditional online bandwidth allocation policies. The scheme is simulated and its performance is evaluated in terms of several parameters, like, bandwidth utilization, application rejection, response time, and s. The simulation results show that the use of s increase flexibility and efficiency in end-to-end bandwidth allocation and operate asynchronously. The flexibility in using this technology is that, the allocation policies can be changed, customized and implemented easily. I. INTRODUCTION Multimedia services such as video-on-demand, videoconferencing, video-telephony, elctronic news and E- commerce impose new QoS (quality of service) requirements such as: bandwidth guarantee (end-to-end and network level), low delay, low delay-jitter and acceptable loss rate without re-transmissions. Most multimedia applications require a minimum bandwidth commitment from network and end-to-end bandwidth guarantee for useful service. A brief introduction to bandwidth management, proposed scheme and mobile s is presented in this section. The remainder of the paper Corresponding author is organized as follows. Proposed scheme for bandwidth allocation is described in section II. Simulation model, its assumptions and the performance parameters are explained in section III. Section IV and V presents results and conclusion. A. Bandwidth resource management Multimedia applications are less loss sensitive and more delay sensitive and also consume most of the bandwidth. Bandwidth should be guaranteed between server and client for correct packet delivery without re-transmissions. This can be achieved by reducing the congestion losses in the network, and end-toend delay for an application. In order to reduce the bandwidth requirements, compression schemes and variable rate decoders are used. These schemes will help the server to control the rate of transmission of multimedia information. Several approaches namely: statistical multiplexing, temporal smoothing, temporal resolution, spatial resolution and multicasting are employed to reduce bandwidth requirements [1]. The bandwidth allocation depends on several factors: desired loss, delays, congestion, buffer levels and flow specifications. Several approaches such as RTCP (Real time control protocol) based allocation, RSVP (resource reservation protocol) based flow reservation, RCBR (renegotiated constant bit rate), explicit rate feedback (for Available bit rate services in ATM networks), variations of max-min rate policy, dynamic search algorithm and based approaches are used for allocation of bandwidth [2-8]. B. Mobile s s are the autonomous programs situated within an environment, which senses it and acts upon it using its knowledge base, and learns so as to act in future. Mandatory properties of the s are: autonomy, reactive, proactive and temporally

2 continuous. The orthogonal properties are: communicative, mobile, learning and believable [9,]. These properties associated with the s, make them different from other programs. Mobile s are the multi systems which possesses the mandatory properties and some or all of the orthogonal properties specified for an. It is an itinerant dispatched from source computer which contains program, data, execution state information, migrates from one host to another host in the heterogeneous network and executes at remote host until they accomplish their task. The mobile code should be platform independent, so that, it can execute at any remote host in the heterogeneous network environment. They communicate and cooperate with other s to achieve its goals. can update its information base while interacting with other s during its travel. Inter- communication can be achieved by message passing, RPC or common knowledge base (black board architecture). There are several good reasons for using mobile s: they reduce network load; overcome latency; encapsulate protocols; execute asynchronously and autonomously; adapt dynamically. Some of the platforms available for mobile s are Aglet work bench, TCL, telescript, Voyager and odyssey. C. Proposed scheme Mobile based approach has been proposed for dynamic bandwidth allocation. This technique assumes that a mobile platform and bandwidth agency comprising mobile s, static s and resource handling information, are available with each of the multimedia server and clients. Mobile platforms have s, server, interpreter and transport mechanism for s (TCP or ). server is responsible for receiving the mobile s and sending it for execution by interpreter. The s can be written in Java, Tcl and perl languages. interpreter depends on the language used. A user application at the client instantiates a bandwidth allocator, which migrates to server and allocates initial bandwidth and provides its desired loss. Network monitoring at the client monitors the losses for an application. Inter- communication is achieved through black board architecture. The server periodically sends a dynamic bandwidth allocator mobile to all its connections, which coordinates with network monitoring to allocate the new bandwidth based on the network congestion level and the desired loss of an application. Once, the returns to server, new bandwidth allocations for each of the applications will be made. The scheduler at the server schedules new allocations. II. PROPOSED MOBILE AGENT BASED SCHEME The scheme considers end-to-end approach for bandwidth allocation based on online packet loss measurements at the clients. Mobile based framework for bandwidth allocation assumes the availability of two components at server and clients: mobile platform (to support, reception and execution) and bandwidth allocation agency. Bandwidth allocation agency comprises of several mobile and static s along with resource handling information. Mobile s are used for initial and online bandwidth allocation. The clients send mobile to server after allocating local bandwidth for an application. The migrated, then allocates to the applications based on surplus bandwidth available on the server link. Initially, applications are allocated minimum bandwidth. Multimedia server sends dynamic bandwidth allocator mobile to all its clients periodically to check monitored losses at the clients for an application and allocate the bandwidth within the requested range. It also tries to keep aggregated bandwidth below the server link bandwidth. Consider N clients, à applications at Ø client, = capacity of server, s link, Ö =capacity of Ö Ø client link, Ò Û Ø = bandwidth of Ø application in Ø client, where i= 1,2,...,N, j= 1,2,...,Ã. The algorithm adjusts the bandwidth online such that, È Æ ½È à ½ Ò Û Ø (1), È Ã ½ Ò Û Ø Ö (2). A. Bandwidth allocation agency Bandwidth allocation agency at the client and server has several mobile and static s and profiles (connection state information). Fig. 1. depicts the details of s used in client and server bandwidth allocation agencies. The server agency comprises of bandwidth profile, application manager, server allocator, dynamic bandwidth allocator mobile, scheduler and server bandwidth profile. The client agency comprises of user, application manager, local allocator, network monitor, bandwidth allocator mobile, bandwidth profile and loss profile. The functions of the s are as follows: user : it provides server requested for connection, maximum bandwidth, minimum bandwidth and desired loss for an application to application manager at client; client application manager : it is responsible for sending bandwidth allocator mobile for initial bandwidth allocation to server

3 for which connection is requested after request is verified by local allocator ; local allocator : It is used to verify aggregate bandwidth to be less than link bandwidth of the client with the aid of bandwidth connection profile at client; network monitor : it monitors the losses for the applications of the client and stores in loss profile, which will be read by mobile of server while allocating bandwidth online; server application manager : it is responsible for sending mobile to all the connected clients for dynamic bandwidth allocation, it interacts with server allocator during initial bandwidth allocation; server allocator : it is used to verify the aggregate bandwidth of all the applications to be less than server link bandwidth; dynamic bandwidth allocator mobile : it picks up maximum, minimum, allocated bandwidth and the desired loss values for applications from the bandwidth profile and goes on a mission to allocate new bandwidth based on the monitored losses stored in loss profile at the client; scheduler : it schedules the bandwidth for the applications at server based on the allocated bandwidth stored in bandwidth profile. Server bandwidth Agency band width profile dbal mobile app manag er Bandwidth agencies at server and clients server allocator schedul er Client bandwidth Agency iba mobile user app manager band local width alloc profile, n/w monitor ed monitor loss profile iba: initial bandwidth allocator, dbal: dynamic bandwidth allocator, Fig 1. Bandwidth allocation agencies. app: application Bandwidth profile at the server maintains database of applications running at the server, maximum and minimum bandwidth, allocated bandwidth, desired loss, connection identifier, client address and surplus bandwidth available at the server. The allocated bandwidth is updated by mobile of server periodically. The client s bandwidth profile consists of database of applications running, source identifier, maximum and minimum bandwidth, allocated bandwidth, desired loss and the surplus bandwidth available at the client. Allocated bandwidth is updated by mobile of server visiting the client. The initial parameters of application are set by mobile of the client at the server bandwidth profile based on surplus bandwidth available at the server. B. Algorithms Initially, the client mobile migrates to server requested for connection and checks bandwidth profile for surplus bandwidth available, if available, allocates the minimum requested bandwidth and sets the parameters of application in bandwidth profile of the server. Once initial allocation is over, dynamic bandwidth allocation is performed by mobile of server as given in the Algorithm. The allocates new bandwidth to an application of the client within its given range based on losses observed at the client. A threshold loss is considered which is used to indicate status of network. If loss observed is above threshold, network is in congested state. Network is said to be loaded, if observed loss is between desired loss and threshold loss. The bandwidth will not be updated during loaded state. Nomenclature: min=minimum, max=maximum, bw=bandwidth, avl=available, alloc=allocated Algorithm: Dynamic allocation 1. Initial allocation by mobile of the clients for accepted applications. 2. mobile from server collects statistics of all connections and addresses from bw profile server. 3. migrate to next client. 4. check(loss profile client) for application. 5. If (observed loss threshold loss) Then new = old alloc bw + 0.5* log(desired loss/observed loss); If new min bw Then new alloc bw = min bw; 6. If (observed loss desired loss ) Then new = old alloc bw + log(desired loss/observed loss); If ( eq. 1 & 2 satisfied and (new max bw)) Then new alloc bw = new; Else new alloc bw = max bw; 7. If ( observed loss between desired loss and thresold loss) Then new alloc bw = old alloc bw;

4 8. If any application left over in client, goto If clients left to visit, goto 3.. return to server and set bw profile server with new allocations. 11. stop. III. SIMULATION MODEL The simulation model considers a single multimedia server and several clients with more than one connection for the server through the sub-net. Sub-net generates losses that are uniformly distributed between the hops of an application as shown in Fig 2. The link capacities are same for all the clients. Cs X mbps server s N = random(1,20) Y = client link capacity, (C1 Cn) loss model (N hops) for an applic ation C1 Y mbps Cn Y mbps clients 1 N X = server link capacity (Cs) Fig 2. Simulation model. The following are the assumptions made in the model: the number of applications are randomly distributed between the clients; minimum bandwidth for an application is uniformly distributed; maximum bandwidth is uniformly distributed between minimum bandwidth and uniformly(u) distributed value, i.e., U(minimum bandwidth, (minimum bandwidth + U(a,b))), where b-a is the range of difference between maximum and minumum bandwidth; desired loss is uniformly distributed and considered in terms of percentage (% of transmitted packets); number of hops for an application from server to client is randomly distributed between minimum and maximum hops; observed or path loss is uniformly distributed among the hops, actual loss is cummulative value of loss seen at hops; time is uniformly distributed; execution time of the is exponentiallly distributed. The performance parameters to be observed in the simulation are bandwidth utilization, percentage of applications rejected, processing time and number of s. IV. RESULTS AND DISCUSSION We have carried out several simulations of the model with different random number seeds. Each experiment results are taken over simulation period of 2000 seconds. The results presented are an average of them. The values considered in the simulation are: X=50 mbps, Y= mbps, execution time=exp(0.1) seconds, time=u(0.8,1.0) seconds, minimum bandwidth(min)=u(1.0, 2.5) mbps, maximum bandwidth=u(min, min + U(1, 3.5)) mbps, number of hops(n)=random(1, 20), desired loss=u(2.0, 3.0) percent, path Èloss for hop=u(0, (.0/N)), total loss for an application= Æ ½ ÓÔÐÓ, update interval = seconds. It is observed from the simulation that the maximum number of applications scheduled for 2, 4, 6, 8 and are, 19, 24, 27 and 27 respectively. The plots given in figures considers the Y-axis for scheduled applications out of the applications requested. Rejection percentage of applications rises steeply with decreasing number of clients and increasing applications as depicted in Fig. 3. This is due to the fact that the has to keep the aggregated bandwidth below the link level at the server and the clients, thus admitting few applications for few clients. Bandwidth utilization increases with increasing number of applications and the clients as depicted in Fig. 4. But, we can observe that the utilization reaches some saturation value for 2 and, since the applications scheduled remains constant, even-though more requests arrive. Utilization goes on increasing in case of 8 and because almost all the requested applications are scheduled. Fig. 6. depicts the response time which shows increase in response with more number of clients. As the clients increase, server can employ more than one, each going to different set of clients and return. This way, response time can be reduced. Applications Rejected(%) Fig 3. Applications rejected(%). Vs. Requseted applications

5 Bandwidth utilization(%) Fig 4. Bandwidth utilization(%). Vs. Requested applications Average response time(sec) Fig 5. Average response time(sec). Vs. Requested applications Number of visits Fig 6. Number of visits. Vs. Requested applications visits to the clients increases with increasing number of clients as depicted in Fig. 6. Visits depends on number of s of. But, with increasing number of applications, visits are reduced over the simulation period. Visit counts are lesser for 8 and for 5 applications as compared to -25 applications, because several clients are not participating. Visits can be reduced using dynamic update intervals rather than fixed intervals. We have also observed that the allocated bandwidth for an application lies between its maximum and minimum, keeping aggregated bandwidth below or equal to link and server bandwidth. V. CONCLUSIONS The possible advent of programmable networks has given rise to mobile technology, which seems to be promising solution for QoS control and network management in multimedia communication. The paper presented importance of bandwidth allocation algorithms and proposed an mobile based scheme. The proposed scheme monitors packet loss for an application at the client to detect congestion in network and allocates bandwidth accordingly. Network delays, buffer levels metrics can also be considered. The s can be dynamically customized based on these metrics which is not possible other than the mobile paradigm. We have shown how the approach can be implemented and also evaluated its performance through simulation. The results obtained are promising and they demonstrate feasibility of bandwidth allocation schemes complemented by mobile and static software s. Mobile s allow high degree of flexibility that is required in heterogeneous networks. However, several overheads are associated with the scheme such as: communication time of s; additional memory space for platform; CPU time for computation of s. Several issues like security, transport mechanisms, portability are still to be resolved, since the technology is still evolving. REFERENCES [1] Marwan Krunz, Bandwidth allocation strategies for transporting variable-bit-rate video traffic, IEEE Commun. Mag, pp , Jan [2] [3] [4] D.B. Hoang, X. Yu, D.Feng, Fair intelligent bandwidth allocation for rate adaptive video traffic, Computer Communications, Vol. 23, pp , Aug [5] kesidis. [6] Errin W. Fulp, Douglas S. Reeves, Online dynamic bandwidth allocation, Proc. of ICNP, pp , [7] Y. Thomas Hou, Bo Li, Shivendra S. Panwar, Henry Tzeng, On network bandwidth allocation policies and feedback control algorithms for packet networks, Computer networks, Vol. 34, pp , Aug [8] S.S. Manvi, P. Venkatram, QoS management by mobile s in multimedia communication, Proc. DEXA, pp , Sep [9] []

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