Conference Paper
A Suboptimal Network Utility Maximization Approach for Scalable Multimedia Applications.
Sch. of Comput. Sci., IPM, Tehran, Iran
DOI: 10.1109/GLOCOM.2009.5425607 Conference: Proceedings of the Global Communications Conference, 2009. GLOBECOM 2009, Honolulu, Hawaii, USA, 30 November  4 December 2009 Source: IEEE Xplore

Conference Paper: SumProduct Based Optimization for Scalable Video Streams in PeertoPeer Mesh Network
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ABSTRACT: Receiver heterogeneity of a P2P network can be effectively addressed by scalable video streams. Due to the discontinuous nature of scalable video, traditional convexoptimization approach is not applicable. We propose a messagepassing based approach for optimization using the sum product update algorithm. Advantage of this simple but elegant approach over other heuristicbased algorithm is that the optimization algorithm itself is independent of the underlying constraints. The algorithm iteratively updates layer allocation decision based on a given set of codewords. The codewords are binary representation of various network and video constraints. Therefore, any number of constraints can be used to generate a set of codewords without modifying the algorithm. To the best of our knowledge, this is the first work that systematically addresses the scalable video optimization problem. Preliminary simulation with up to 8 layers shows that the sum product update process achieves an average layer delivery of 95% or higher.Computer Communications and Networks (ICCCN), 2011 Proceedings of 20th International Conference on; 09/2011  [Show abstract] [Hide abstract]
ABSTRACT: This paper addresses rate control for transmission of scalable video streams via Network Utility Maximization (NUM) formulation. Due to stringent QoS requirements of video streams and specific characterization of utility experienced by endusers, one has to solve nonconvex and even nonsmooth NUM formulation for such streams, where dual methods often prove incompetent. Convexification plays an important role in this work as it permits the use of existing dual methods to solve an approximate to the NUM problem iteratively and distributively. Hence, to tackle the nonsmoothness and nonconvexity, we aim at reformulating the NUM problem through approximation and transformation of the ideal discretely adaptive utility function for scalable video streams. The reformulated problem is shown to be a D.C. (Difference of Convex) problem. We leveraged Sequential Convex Programming (SCP) approach to replace the nonconvex D.C. problem by a sequence of convex problems that aim to approximate the original D.C. problem. We then solve each convex problem produced by SCP approach using existing dual methods. This procedure is the essence of two distributed iterative rate control algorithms proposed in this paper, for which one can show the convergence to a locally optimal point of the nonconvex D.C. problem and equivalently to a locally optimal point of an approximate to the original nonconvex problem. Our experimental results show that the proposed rate control algorithms converge with tractable convergence behavior.Computing Research Repository  CORR. 02/2011;
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