Joint routing and rate allocation for multiple video streams in ad-hoc wireless networks *

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1 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): Journal of Zhejiang Univerity SCIENCE A ISSN (Print); ISSN (Online) jzu@zju.edu.cn Joint routing and rate allocation for multiple video tream in ad-hoc wirele network * ZHU Xiao-qing 1, SINGH Jatinder Pal, GIROD Bernd 1 ( 1 Information Sytem Laboratory, Stanford Univerity, California 9435, USA) ( Deutche Telekom Laboratorie, Ernt-Reuter-Platz 7, Berlin 1587, Germany) zhuxq@tanford.edu; jatinder.ingh@telekom.de; bgirod@tanford.edu Received Dec. 9, 5; reviion accepted Feb. 18, 6 Abtract: The upport for multiple video tream in an ad-hoc wirele network require appropriate routing and rate allocation meaure acertaining the et of link for tranmitting each tream and the encoding rate of the video to be delivered over the choen link. The routing and rate allocation procedure impact the utained quality of each video tream meaured a the mean quared error (MSE) ditortion at the receiver, and the overall network congetion in term of queuing delay per link. We tudy the trade-off between thee two competing objective in a convex optimization formulation, and dicu both centralized and ditributed olution for joint routing and rate allocation for multiple tream. For each tream, the optimal allocated rate trike a balance between the elfih motive of minimizing video ditortion and the global good of minimizing network congetion, while the route are choen over the leat-congeted link in the network. In addition to detailed analyi, network imulation reult uing n- are preented for tudying the optimal choice of parameter and to confirm the effectivene of the propoed meaure. Key word: Ad-hoc wirele network, Video treaming, Rate allocation, Multi-path routing doi:1.1631/jzu.6.a77 Document code: A CLC number: TN919.8 INTRODUCTION Ad-hoc network are attractive owing to their elf-organizing nature and abence of a fixed infratructure. They are particularly uited for communication in diater-affected area, coordinating military operation, and ening environmental condition. With the growing availability of upporting hardware and decreaing equipment cot, ad-hoc networking baed application are proliferating. Mehe of wirele node are being deployed in citie and houing communitie to upport Internet acce and peer-topeer communication (Ca, 5; Bicket et al., 5). Streaming of multimedia content over uch kind of network i compelling for many application cenario, including vehicular platoon, community mehe, and home entertainment network. Correponding author * Project (No. CCR-35639) partially upported by the National Science Foundation, USA The node in an ad-hoc network communicate in a peer-to-peer fahion and help in relaying data from a ource to the detination. Routing i a challenging tak owing to the dynamic network topology and variation in wirele channel condition. Over the year everal ditributed protocol have been propoed and analyzed for ad-hoc routing. Many of them employ imple metric uch a hop count or end-to-end delay while electing a route between a given ource and a detination. Routing mechanim uing the exitence of multiple path between a ource-detination pair have alo been propoed, and are hown to reult in enhanced performance over ingle-path routing method (Lee and Gerla, ; Marina and Da, 1). Video treaming application additionally impoe high rate requirement and tringent latency contraint on reource-limited ad-hoc network. It i oberved that quality of the received video tream i affected not only by encoder quantization, but alo by elf-inflicted network congetion leading to packet

2 78 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): drop due to late arrival (Zhu et al., 5). An attempt to enhance the ytem performance hould therefore account for both metric in a congetion-ditortion optimized fahion. When multiple tream are preent in an ad-hoc network, the choen rate and route for each tream would alo affect the performance of other. Both rate allocation and routing need to be optimized for all tream in the network, preferably in a decentralized manner. In thi paper, we tudy a convex optimization formulation of the joint routing and rate allocation problem for multiple tream. A centralized olution baed on optimal flow aignment i derived a an upper bound of performance. A ditributed cheme i alo propoed, where the allocated rate at each tream depend on both the ditortion-rate (DR) characteritic of the video and the network congetion increment, which in turn i obtained from a ditributed routing procedure (Zhu and Girod, 5a). We how that the optimal global trade-off between total video ditortion of all tream veru overall network congetion can be tranlated into the local balance between reducing encoded video ditortion veru contraining network congetion at each tream. The ret of the paper i organized a follow. In the next ection, we preent related work on ad-hoc routing protocol and rate allocation for multiple video tream. The network and video model are explained in Section 3, where we alo introduce notation ued throughout the paper, and provide a convex optimization formulation of the problem. Section 4 ummarize previou work on congetion-ditortion optimized routing, which erve a the bai for the joint routing and rate allocation cheme decribed in Section 5. Network imulation reult are dicued in Section 6. RELATED WORK Ad-hoc routing protocol Several ad-hoc routing protocol that have been propoed over the year include proactive tabledriven protocol like Detination-Sequenced Ditance-Vector (DSDV) routing (Perkin and Bhagwat, 1994) and Optimized Link State Routing (OLSR) (Clauen and Jacquet, 3), a well a on-demand protocol like Dynamic Source Routing (DSR) (Johnon and Maltz, 1996) and Ad-hoc On-demand Ditance Vector (AODV) routing (Perkin et al., 3). The former involve the evaluation and torage of the routing table pertaining to the topology at each node. The routing table are periodically updated to counter the topological change aociated with node mobility and wirele channel variation. Thi can reult in ignificant protocol overhead, epecially under high node mobility and dynamic channel condition. The on-demand protocol on the other hand involve dicovery of the route whenever data need to be tranmitted between a ource-detination pair. They typically incur le overhead traffic than the table-driven protocol, and can conequently better adapt to dynamically varying topologie. Comparative tudy of variou routing protocol ha been an active reearch area in the wirele ad-hoc networking community (Royer and Toh, 1999; Lee et al., 1999). The aforementioned routing trategie evaluate the bet equence of node in accordance with criteria like minimum hop or delay, and forward data along a ingle path. de Couto et al.(; 3) pointed out the inadequacy of minimum-hop routing in wirele ad-hoc network, and propoed alternative link metric for evaluating a path. Extenion to multi-path routing have alo been propoed for multi-path AODV (Marina and Da, 1) and for ExOR, an opportunitic multi-hop routing trategy that broadcat data packet to explore multiple path in the network (Biwa and Morri, 5). For video treaming, benefit of multi-path routing over ad-hoc network are demontrated in term of robut packet delivery via path diverity (Mao et al., 3; Wei and Zakhor, 4) and higher utainable rate and quality due to bandwidth aggregation (Setton et al., 4). Unlike mot previou work that conider routing for generic data traffic over ad-hoc network, we take into account pecific characteritic of video treaming in the evaluation of route. Network congetion i incorporated explicitly into the route election metric, to meet the tringent latency requirement for video packet delivery. The rate-ditortion characteritic of each tream i alo conidered in the rate allocation procedure to accommodate multiple tream with variou video content and complexity. Multi-tream rate allocation The problem of rate allocation among multiple traffic tream over a common network ha been well

3 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): tudied. Kelly provided a mathematical formulation of the problem (Kelly, 1997) and invetigated two clae of ditributed rate control algorithm correponding to the primal and dual decompoition of the optimization (Kelly et al., 1998). The application of uch rate allocation algorithm ha been invetigated for elatic traffic over the Internet (La and Anantharam, ) and for video treaming over ad-hoc network with 8.11-like wirele node (Zhu and Girod, 5b). For a more practical etting, a rate allocation algorithm combined with a packet partitioning algorithm ha been propoed to upport video treaming from multiple ender to a ingle receiver over the Internet (Nguyen and Zakhor, 4). The rate are choen to match the available network bandwidth for each tream, and the packet partitioning i deigned to minimize tart up delay. For video treaming over a wirele hop, a rate control cheme ha been hown to efficiently utilize the available wirele link capacity uing multiple TFRC connection (Chen and Zakhor, 4). Our approach target rate allocation in conjunction with route election. The optimization objective function i compried of both video ditortion and network congetion. Thi differ from mot exiting work where routing and rate allocation are performed eparately, without the notion of limiting overall network congetion. PROBLEM FORMULATION In thi ection we explain the wirele network model and a parametric video ditortion-rate (DR) model ued for formulating the joint routing and rate allocation problem. A convex optimization framework i alo preented, together with the notation ued throughout the ret of the paper. Wirele network model Conider an ad-hoc network compried of N node. The collection of link between neighbouring node pair in the network i deignated a: L={(i,j) Node j can hear Node i}. (1) The link capacity from Node i to Node j i denoted a C, and the et of link capacitie can be repreented a: C={C (i,j) L}. () Let F repreent the background traffic from Node i to Node j, already preent before any new video tream i initiated. The et of background traffic over the network i denoted by: F cro ={F (i,j) L}. (3) When a node in the network initiate a video tream tranfer, additional traffic flow are introduced over the link choen by routing. The et of thee flow i expreed a: F={f (i,j) L}. (4) We denote congetion on each link a the average queuing delay normalized by the average packet ize, and congetion over the network a the um of all link delay weighted by the traffic rate on each link. In general, the total congetion X i a function of link capacitie C and exiting flow rate F cro and F. Following the M/M/1 queuing model, the congetion on each link can be expreed a 1/(C F f ), and thu the total congetion become: X = F + f. C F f (5) (, i j) L When the M/M/1 aumption doe not hold, the above expreion can be viewed a an approximation of the average link delay, capturing the non-linear dependency of delay on traffic flow (Kleinrock, 1976). Video ditortion-rate model Denote the et of video tream preented in the network a S. Each tream S i aociated with a mean quared error (MSE) decoding ditortion of D when encoded and treamed at a rate R. The ditortion-rate (DR) characteritic of each tream can be fitted to a parametric model (Stuhlmüller et al., ): θ D ( R ) = D +, ( R R ) (6) where the parameter D, θ and R depend on the coding cheme and the content of the video. They can be etimated from three or more trial encoding uing

4 73 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): non-linear regreion technique. The operational range of encoded video rate i[ Rmin, R max ]. We will how later in Section 5. that, by repreenting the video DR characteritic uing a parametric model, one can derive analytical expreion for ditortion reduction per rate increment: thi facilitate the rate allocation procedure. It hould alo be pointed out that the optimization framework dicued in thi paper i general enough to accommodate any other video ditortion-rate model a long a it i convex. Optimization objective We denote a F={ f ( i, j) L} the traffic flow introduced by the video rate R from Stream, originating from ource node rc() and terminating at detination dt(). Due to the latency contraint of video treaming, increaing the allocated rate R would introduce exceive network congetion, which in turn caue evere degradation of received video quality. On the other hand, decreaing the allocated rate lead to higher video ditortion during encoding. We therefore eek to trike a balance between both objective, and minimize the Lagrangian um of total video ditortion and overall network congetion: D R + λ X C Fcro F (7) S min ( ) (,, ). The optimization i over all R for rate allocation and F for route election for all tream in S. The choice of λ adjut the trade-off between ditortion and congetion. Incorporating the M/M/1 model for calculating congetion Eq.(5) and the video ditortion model Eq.(6), thi i equivalent to: θ F + f min + λ,.t. R R C F f (8a) (, i j) f = f, ( i, j) L, (8b) f < C F, ( i, j) L, (8c) R, n = rc( ), f f = R, n= dt( ),, otherwie. (8d) nr, rn, r:( n, r) L r:( r, n) L R,. min R Rmax S (8e) It can be eaily verified that the objective i convex over the variable f, f, R, where (i,j) L, S. All contraint to thi optimization problem are linear, a given in Eq.(8b)~(8e). In particular, Eq.(8d) tate that for any tream, the net incoming flow for tream equal R for rc() and R for dt(). The net incoming flow of all other node from tream i zero, i.e., there i flow conervation. CONGESTION-OPTIMIZED ROUTING MULTI-PATH Conider a impler pecial cae of the problem formulated in Eq.(8), where only one video tream i involved, and it rate R i fixed. Thi then become the claical problem of minimizing network congetion via optimal flow aignment (Kleinrock, 1976; Berteka and Gallager, 1987). A centralized routing and traffic partitioning algorithm i propoed for video over ad-hoc network, where multiple route are extracted from the optimal flow aignment reult, and the total traffic i dipered over the multiple path in a congetion-optimized manner (Setton et al., 4). Thi centralized cheme, however, require knowledge of global network information uch a capacitie and flow along all the link, which retrict the calability of the network. The computational complexity of the optimization and route extraction from the flow aignment may alo exceed the capabilitie of any ingle node in the network. To counter the problem, a ditributed algorithm for multi-path routing of the video tream i propoed (Zhu and Girod, 5a). The total rate of the video tream R i plit into K mall increment uch that R= K k = 1 R. Then the optimal allocation of increment R k k can be achieved by finding a path P * k that accomplihe the following: where C min, Pk k k = k = 1 R k (, i j) P ( C ) k F (9) F F + f include exiting background traffic F and k 1 rate increment from the preent

5 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): tream. Note that the minimization objective in Eq.(9) correpond to end-to-end accumulated um of C/( C F ), which can be interpreted a congetion enitivity over that link (i.e., amount of increae in congetion per unit increae in rate). Conequently, the optimal path P * k in Eq.(9) can be found via the ditributed Bellman-Ford algorithm (Ford and Fulkeron, 196), by etting the link cot to congetion enitivity. Every node maintain a minimum-cot path from itelf to the ource, exchange thi information with it neighbor, and update to a lower cot path if it dicover one via a neighbor. When the detination node report the choen path for a given rate increment R k to the ender, it can eaily append the correponding accumulated congetion enitivity value to the path information, for later ue in the rate allocation proce a explained in the next ection. The reader i referred to the original paper for further detail of the ditributed routing protocol. JOINT ROUTING AND RATE ALLOCATION For the more generic cenario of multiple ource treaming video in the ad-hoc network, we how in thi ection how route election and rate allocation for each tream can be jointly optimized to trade-off between overall network congetion and total video ditortion of all tream. Centralized olution The optimal rate allocation and flow aignment for the tream in S can be obtained by olving the convex optimization problem in Eq.(8) uing tandard technique, e.g., the interior point method (Neterov and Nemirovky, 1994). Multiple routing path can then be extracted from the optimal flow aignment reult (Setton et al., 4). The complexity of the proce can be limited by retricting the number of extracted path along which a tream i to be routed. Although the centralized olution provide an upper bound of performance in term of congetion-ditortion trade-off, it relie on everal impractical aumption. The algorithm require knowledge of global information pertaining to network topology L, capacity C, background traffic rate F over all link, and video ditortion model parameter R, θ of all tream in S. In practice, the collection of link tate information C and F would incur overhead traffic; the RD model parameter might imply not be available at node other than the ource and detination due to ecurity or privacy concern. Moreover, the complexity of centralized optimization may exceed the computational capability of any wirele node in an ad-hoc network. It i hence deirable to invetigate a ditributed algorithm where rate allocation i performed for each tream eparately and route are dicovered over the network in a decentralized manner. Ditributed cheme We next dicu the framework for a ditributed methodology to allocate rate to a video tream. The Karuh-Kuhn-Tucker (KKT) neceary and ufficient condition for the optimal olution to Eq.(8) tate that the allocated rate to Stream hould either meet the boundary condition exactly, or correpond to zero partial derivative (Boyd and Vandenberghe, 4): dd dr dx + λ =. (1) dr In Eq.(1), dd /dr i derived from the video ditortion model Eq.(6) a dd θ =. d R ( R R ) (11) Hence the ditortion reduction caued by increaing encoding rate by R( k ) i θ D ( k) R,( k) ( R R ). (1) The lope of congetion increment dx/dr, on the other hand, can be expreed a: dx C = d R ( C F f ). (, i j) L: f > (13) If the rate-allocation i performed in ufficiently mall increment R( k ) at each tep k, one can further confine the correponding flow increment f,( k ) to a

6 73 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): ingle path P ( k ) (Zhu and Girod, 5a). The reulting congetion increment X ( k ) can then be approximated a: Note that Eq.(14) i the ame a the optimization criterion in Eq.(9) for routing, and can be accumulated over the choen link of a path. Thi information i then collected at the detination node and fed back to the ource. Given the congetion increment X ( k ) in Eq.(14) and the video ditortion reduction in Eq.(1), the ource node can make the rate allocation deciion by comparing the two quantitie. The allocated rate will be increaed by R( k ) until D( k) > λ X( k), i.e., when the benefit of ditortion reduction i no longer worthwhile the conequential network congetion. Due to the convex nature of both D and X, the initial ditortion reduction i typically ignificant for mall rate increment, wherea increae in network congetion tart out lowly. Therefore, the rate allocation algorithm can continue until it reache the optimal rate that trike a balance between the two trade-off lope. When multiple tream are preent in the network, each of them perform joint routing and rate allocation a decribed above, treating the flow from other video tream a background traffic. Thi procedure need to be carried out periodically at each tream, adapting to the dynamic nature of the underlying wirele channel condition, accommodating newly initiated video tream, and reallocating overall network reource after the termination of a certain video tream. The cheme can be naturally extended to alo handle admiion control. Given a minimum quality and rate requirement for a newly initiated video tream, the ource node can invoke the joint rate allocation and routing procedure for that tream, and admit the new tream if the allocated rate i greater than the minimum requet. C X, (14) ( k) R ( k) (, i j) P ( ) ( k C ) F where cro-traffic F include contribution from other video tream and previouly aigned rate increment: k 1 = + +,( k ) S: k = 1 F F f f. (15) SIMULATION RESULTS Experimental etup Simulation are performed in a network with 15 tationary node randomly placed in a 5 m-by-5 m quare, a illutrated in Fig.1. Node within 5 m of each other are conidered neighbor, and can communicate directly. Link capacitie from Node i to Node j are computed a: C BW = log(1 + γ SINR ), (16) where ignal-to-interference-plu-noie-ratio SINR i calculated auming imultaneou fixed power tranmiion at all node, BW i the double-ided bandwidth for tranmiion, and the coding gain γ <1 indicate the performance gap of a practical channel coder with repect to Shannon informationtheoretical limit (Rappaport, 1996). Y Coordinate (m) X Coordinate (m) Fig.1 Example network with 15 node randomly poitioned in a 5 m-by-5 m quare area. Dahed line indicate the link between two neighboring node. All three video tream are ent from Node 3 to Node 6 Here, the network model aume that the underlying media acce control follow a fixed CDMA procedure, where multiple node can imultaneouly tranmit and receive, and the effect of interference i captured in the calculation of the SINR value. For other network uch a one operating under the IEEE 8.11b protocol, the link capacitie alo depend on

7 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): the traffic rate and contention from adjacent flow. It will be a more challenging tak to determine the link capacity value. Three CIF video equence, Foreman, Mother and Daughter, and Bu are encoded uing the H.64/AVC reference codec ( at 3 fp. A the content of the video equence differ, their repective ditortion-rate characteritic are alo different, a illutrated in Fig.. A dicrete et of available rate i obtained by encoding each video equence at variou quality level. The number of path ued for routing i limited to be 3. PSNR (db) Foreman, model Foreman, data Mother, model Mother, data Bu, model Bu, data Rate (Mbp) Fig. Rate-PSNR performance of Foreman, Mother and Daughter, and Bu CIF equence, all encoded uing H.64/AVC at 3 frame/, with GOP length ofg 15. The experimental data point are fitted with the model curve The olution to the centralized cheme in Section 5.1 i calculated a an upper bound of performance, wherea the ditributed algorithm i executed uing variou rate increment:, 5, 1 and kbp. Network imulation uing n- ( edu/nnam/n/) are alo performed to evaluate the ditributed algorithm in term of received video quality. The background traffic i imulated uing packet with fixed ize of 5 byte and exponentially ditributed arrival interval on each link, with randomly aigned average bit rate of up to 5% of link capacity. For video traffic, the actual encoded packet trace are ued. Packet are dropped if they do not arrive at the receiver by the playout deadline 35 m. Previou-frame concealment i ued in the decoder to recover from dropped video packet. For each experiment, the video equence i looped for more than 5, correponding to 5, 15, and 1 realization for Foreman, Mother and Daughter, and Bu repectively. The calculated average value of all realization are interpreted a the expected performance of the algorithm in a naphot of time for the given network. Single tream In thi ection, we tudy the imple pecial cae where only one video tream i preent in the network. Fig.3 how the allocated rate and correponding video ditortion and network congetion 1, for each of the tream by varying it trade-off choice λ. Smaller value of λ lead to higher allocated rate and encoded video quality, at the expene of greater network congetion. Due to the difference in RD characteritic of the equence, their allocated rate alo differ for the ame given λ. The Mother and Daughter equence with low motion i allocated a lower rate, achieving higher encoded video quality. Wherea the Bu equence i allocated a much higher rate correponding to lower quality, due to it active content and hence the teeper rate-ditortion trade-off curve. It i alo intereting to note that for all three video tream, the reulting rate-congetion trade-off over the network i the ame, a the routing algorithm i congetion-minimized and perform regardle of video content. MSE Congetion (m) 1 15 Foreman Mother Bu Rate (Mbp) Fig.3 Trade-off between network congetion in term of average link delay and video ditortion in MSE reulting from the joint routing and rate allocation cheme, when treaming a ingle video equence over the network Reult from network imulation are hown in Fig.4 for equence Foreman. The decoded video qual- 1 Network congetion i hown here in the ene of average link delay of all packet in the network, which i X (ee Eq.(5)) normalized by the total traffic over all link in the network

8 734 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): ity i plotted againt the allocated rate and network congetion repectively. The encoder quality i alo hown in dahed line for reference. Here it i oberved that the recontructed video quality degrade when the choen λ i too mall, which lead to high allocated rate of the video and conequently exceive network congetion. A the video tream are decoded with a latency contraint, the elf-inflicted network congetion at too high a rate caue a greater percentage of the video packet to arrive too late at the decoder, thu uffering from evere quality drop. Similar phenomena are oberved for the other two equence. PSNR (db) PSNR (db) Encoder Decoder Rate (Mbp) (a) Congetion (m) Encoder Decoder (b) Fig.4 Encoded and received video quality in PSNR veru (a) allocated rate and (b) network congetion in term of average link delay, when treaming the Foreman equence over the network uing joint routing and rate allocation Multiple tream We next evaluate the performance of the propoed optimization meaure with multiple video tream. Note that if the choen route for each tream travel over non-overlapping link, then the network can be decompoed into independent ubet upporting each tream unaffected by other, which reduce to the cenario in the lat ubection. In order to invetigate the interaction among multiple tream, we chooe the ame ource and detination node for all tream o a to have hared link in the choen route. Fig.5 illutrate the initial and final route choen for all three tream during the optimization of the joint routing and rate allocation proce. The correponding rate allocated to each tream i hown in Fig.6 over iteration tep. It can be oberved that the elected route for two of the tream (Mother and Daughter in dahed line and Bu in dotted line) have Y Coordinate (m) Y Coordinate (m) Thi i a conequence of the aumption of fixed link capacitie in our imple wirele network model. In practice, the exitence of traffic over other wirele link may affect the capacity of the current link via increaed interference or contention, the tudy of which i intended for future work 1 X Coordinate (m) (a) X Coordinate (m) (b) Fig.5 (a) Initial and (b) final route election of all three tream: Foreman in olid line, Mother and Daughter in dahed line and Bu in dotted line. Two route for Mother and Daughter and three route for Bu have changed over the iteration. For thi intance, the λ in Eq.(8a) i choen to be.1, and the rate increment i 1 kbp

9 Zhu et al. / J Zhejiang Univ SCIENCE A 6 7(5): Rate (kbp) Foreman Mother Bu Iteration Fig.6 Allocated rate for each tream over the iteration, correponding to the ame etting in Fig.5 changed over the iteration, each re-dipening it own traffic over the network to avoid already congeted link. Change in the route alo affect the congetionincrement information calculated during routing, which in turn lead to change in the rate allocation deciion. In Fig.7 the trade-off between overall network congetion and average video ditortion of all tream i compared among variou cheme. It can be noticed that finer rate increment in the ditributed algorithm yield lightly better reult. When λ i large, implying a heavy penalty for network congetion in the optimization objective, the performance of all the cheme are eentially the ame. A λ decreae and more congetion i allowed in the network, with higher allocated rate, the performance gap between the centralized and ditributed cheme become more pronounced. PSNR (db) Centralized Ditributed, incr= kbp 34 Ditributed, incr=5 kbp Ditributed, incr=1 kbp Ditributed, incr= kbp Congetion (m) Fig.7 Trade-off between overall network congetion in term of average link delay and average video quality of all three video tream in PSNR, uing the propoed ditributed joint routing and rate allocation algorithm. The performance of the centralized olution i alo plotted in olid line for reference CONCLUSION In thi work, a congetion-ditortion optimized framework i invetigated for treaming multiple video in a common wirele ad-hoc network. We propoe a ditributed cheme for joint routing and rate allocation. The allocated rate at each video tream i choen to achieve a common trade-off lope between network congetion increment obtained during the routing procedure, and reduction in video ditortion. When a minimum quality and rate requirement i impoed on each video tream, the cheme can be naturally extended to handle admiion control. A centralized olution for joint flow aignment and rate allocation i alo derived to erve a an upper bound of performance. Simulation reult confirm the effectivene of the cheme in achieving the optimal congetionditortion trade-off for the overall ytem. Compared to the performance bound provided by the centralized olution, variou verion of the ditributed algorithm are hown to incur mall lo of optimality when the network i not congeted. A part of future work, we intend to invetigate joint routing and rate allocation over a more realitic wirele network model, for intance one capturing the CSMA/CA MAC behavior of the widely ued 8.11 device. Simulation comparion againt conventional benchmark cheme uch a min-hop routing or TCP-friendly rate control will alo be conducted for a more comprehenive evaluation of the propoed congetion-ditortion optimized algorithm. Reference Berteka, D., Gallager, R., Data Network. Prentice Hall, New Jerey, USA. Bicket, J., Aguayo, D., Biwa, S., Morri, R., 5. Architecture and Evaluation of an Unplanned 8.11b Meh Network. Proc. ACM 11th Annual International Conference on Mobile Computing and Networking (MOBICOM 5). Cologne, Germany, p Biwa, S., Morri, R., 5. ExOR: Opportunitic Multi-Hop Routing for Wirele Network. Proc. ACM Conference on Communication Architecture, Protocol and Application (SIGCOMM 5). Philadelphia, Pennylvania, USA, p Boyd, S., Vandenberghe, L., 4. Convex Optimization. Cambridge Univerity Pre, United Kingdom. Ca, S., 5. Viva meh vega (meh wirele network). IEEE Spectrum, 4(1): [doi:1.119/mspec.5.

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