Sat, 19 Jul 2008 04:36:33 BST CiteULike: p2pstreaming's optimization http://www.citeulike.org/user/p2pstreaming/tag/optimization CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/p2pstreaming/article/2795182 <i>Circuits and Systems for Video Technology, IEEE Transactions on, Vol. 18, No. 1. (2008), pp. 140-144.</i><br /><br />A rate-distortion (R-D) optimization rate control (RC) algorithm with adaptive initialization is presented for H.264. First, a linear distortion-quantization (D-Q) model is introduced and thus a close-form solution is developed to derive optimal quantization parameters (Q_p)for encoding each macroblock. Then we exploit to determine the initial Q_p efficiently and adaptively according to the content of video sequences. The experimental results demonstrate that the proposed algorithm can achieve better R-D performance than that of other two RC algorithms including the algorithm JVT-G012 which is the current recommended RC scheme implemented in the H.264 reference software JM9.5. Rate-Distortion Optimization of Rate Control for H.264 With Adaptive Initial Quantization Parameter Determination Hanli Wang Sam Kwong doi:10.1109/TCSVT.2007.913757 Circuits and Systems for Video Technology, IEEE Transactions on, Vol. 18, No. 1. (2008), pp. 140-144. 2008-05-13T14:35:48-00:00 2008 Circuits and Systems for Video Technology, IEEE Transactions on 18 1 140 144 control distortion h264 optimization quantization rate http://www.citeulike.org/user/p2pstreaming/article/2755265 <i>Multimedia, IEEE Transactions on, Vol. 8, No. 2. (2006), pp. 390-404.</i><br /><br />This paper addresses the problem of streaming packetized media over a lossy packet network in a rate-distortion optimized way. We show that although the data units in a media presentation generally depend on each other according to a directed acyclic graph, the problem of rate-distortion optimized streaming of an entire presentation can be reduced to the problem of error-cost optimized transmission of an isolated data unit. We show how to solve the latter problem in a variety of scenarios, including the important common scenario of sender-driven streaming with feedback over a best-effort network, which we couch in the framework of Markov decision processes. We derive a fast practical algorithm for nearly optimal streaming in this scenario, and we derive a general purpose iterative descent algorithm for locally optimal streaming in arbitrary scenarios. Experimental results show that systems based on our algorithms have steady-state gains of 2-6 dB or more over systems that are not rate-distortion optimized. Furthermore, our systems essentially achieve the best possible performance: the operational distortion-rate function of the source at the capacity of the packet erasure channel. Rate-distortion optimized streaming of packetized media PA Chou Zhourong Miao doi:10.1109/TMM.2005.864313 Multimedia, IEEE Transactions on, Vol. 8, No. 2. (2006), pp. 390-404. 2008-05-05T05:43:21-00:00 2006 Multimedia, IEEE Transactions on 8 2 390 404 distortion optimization http://www.citeulike.org/user/p2pstreaming/article/2755122 <i>Image Processing, 2006 IEEE International Conference on (2006), pp. 721-724.</i><br /><br />In live peer-to-peer streaming, a video stream is transmitted to a large population of viewers, through the use of the uplink bandwidth of participating peers. This approach overcomes the cost of large-scale deployment of such services. An essential problem of this type of system is to limit the incurred congestion. In particular, overwhelming the uplink of some peers would create a large increase in the latency of the system and make this application less compelling. In this work we focus on limiting the congestion in a peer-to-peer network where multiple multicast trees are used to distribute video to a large set of receivers. We present the idea of congestion-distortion optimized streaming which aims at maximizing decoded video quality while limiting network congestion. We describe how this type of media scheduling maintains high video quality even for low latencies, and extend its usage to the peer-to-peer scenario. Experiments over a simulated network of 300 peers illustrate the benefits of the suggested approach Congestion-Distortion Optimized Peer-to-Peer Video Streaming E Setton Jeonghun Noh B Girod doi:10.1109/ICIP.2006.312442 Image Processing, 2006 IEEE International Conference on (2006), pp. 721-724. 2008-05-05T04:31:51-00:00 2006 Image Processing, 2006 IEEE International Conference on 721 724 distortion optimization peer-to-peer http://www.citeulike.org/user/p2pstreaming/article/383455 <i>Real-Time Technology and Applications Symposium, 1999. Proceedings of the Fifth IEEE (1999), pp. 276-286.</i><br /><br />We present a QoS management framework that enables us to quantitatively measure QoS, and to analytically plan and allocate resources. In this model, end users' quality preferences are considered when system resources are apportional across multiple applications such that the net utility that accrues to the end-users is maximized. We previously worked with continuous QoS dimensions, and assumed that the utility gained by improvements along a QoS dimension were always representable by concave functions. In this paper we relax both assumptions. One, we support discrete QoS operating points. Two, we make no assumptions about the concavity of the utility functions. Using these as the basis, we tackle the problem of maximizing system utility by allocating a single finite resource to satisfy the QoS requirements of multiple applications along multiple QoS dimensions. We present two near-optimal algorithms to solve this problem. The first yields an allocation within a known bounded distance from the optimal solution, and the second yields an allocation whose distance from the optimal solution can be explicitly controlled by the QoS manager, We compare the run-times of these near-optimal algorithms and their solution quality relative to the optimal allocation, which in turn is computed using dynamic programming. These detailed evaluations provide practical insight into which of these algorithms can be used online in real-time systems On quality of service optimization with discrete QoS options Chen Lee J Lehoezky R Rajkumar D Siewiorek Real-Time Technology and Applications Symposium, 1999. Proceedings of the Fifth IEEE (1999), pp. 276-286. 2005-11-08T07:28:16-00:00 1999 Real-Time Technology and Applications Symposium, 1999. Proceedings of the Fifth IEEE 276 286 discrete of optimization quality service http://www.citeulike.org/user/p2pstreaming/article/695313 <i>Multimedia Systems, Vol. 10, No. 5. (2005), pp. 413-421.</i> Optimizing transmission time of scalable coded images in peer-to-peer networks Xiao Su Rod Fatoohi Tao Wang doi:10.1007/s00530-005-0170-y Multimedia Systems, Vol. 10, No. 5. (2005), pp. 413-421. 2006-06-13T23:09:39-00:00 2005 Multimedia Systems 10 5 413 421 optimization peer-to-peer scalable http://www.citeulike.org/user/p2pstreaming/article/670709 <i>Euromicro Conference on Real-Time Systems (2003), pp. 83-92.</i><br /><br />This paper presents a time-aware admission control and resource allocation scheme in the context of a future generation mobile network. The quality levels (and their respective utility) of the different connections are specified using discrete resource-utility (R-U) functions. The scheme uses these R-U functions for allocating and reallocating bandwidth to connections, aiming to maximize the accumulated utility of the system. However, different applications react differently to resource reallocations Therefore at each allocation timepoint we take into account the following factors: the age of the connection, a drop (disconnection) penalty and the sensitiveness to reallocation frequency. Finally, we show the superior performance of our approach compared to a recent adaptive bandwidth allocation scheme. Time-aware utility-based QoS optimization C Curescu S Nadjm-Tehrani Euromicro Conference on Real-Time Systems (2003), pp. 83-92. 2006-05-25T23:25:29-00:00 2003 Euromicro Conference on Real-Time Systems 83 92 optimization qos time utility http://www.citeulike.org/user/p2pstreaming/article/334075 <i>IEEE/ACM Trans. on Networking, Vol. 8, No. 5. (October 2000), pp. 667-678.</i> A Game Theoretic Framework for Bandwidth Allocation and Pricing in Broadband Networks H Yaiche RR Mazumdar C Rosenberg IEEE/ACM Trans. on Networking, Vol. 8, No. 5. (October 2000), pp. 667-678. 2005-09-28T16:28:00-00:00 2000 IEEE/ACM Trans. on Networking 8 5 667 678 allocation game optimization pricing resource theory http://www.citeulike.org/user/p2pstreaming/article/334065 <i>(2003)</i> Can Shortest-path Routing and TCP Maximize Utility J Wang L Li S Low J Doyle (2003) 2005-09-28T16:27:59-00:00 2003 optimization routing http://www.citeulike.org/user/p2pstreaming/article/334002 <i>(June 2002), pp. 23-27.</i> Downlink Resource Allocation and Pricing for Wireless Networks P Marbach R Berry (June 2002), pp. 23-27. 2005-09-28T16:27:47-00:00 2002 23 27 allocation optimization resource wireless http://www.citeulike.org/user/p2pstreaming/article/333987 <i>IEEE/ACM Trans. on Networking, Vol. 10, No. 2. (2002)</i> Utility-based rate control in the Internet for elastic traffic RJ La V Anantharam IEEE/ACM Trans. on Networking, Vol. 10, No. 2. (2002) 2005-09-28T16:27:43-00:00 2002 IEEE/ACM Trans. on Networking {10} {2} congestion control nonlinear optimization programming http://www.citeulike.org/user/p2pstreaming/article/333978 <i>Journal of the Operational Research Society, Vol. 49 (1998)</i> Rate Control in Communication Networks: Shadow prices, Proportional Fairness and Stability FP Kelly AK Maulloo DKH Tan Journal of the Operational Research Society, Vol. 49 (1998) 2005-09-28T16:27:42-00:00 1998 Journal of the Operational Research Society {49} congestion control nonlinear optimization pricing programming http://www.citeulike.org/user/p2pstreaming/article/333977 <i>European Trans. on Telecommunications, Vol. 8 (1997)</i> Charging and Rate Control for Elastic Traffic FP Kelly European Trans. on Telecommunications, Vol. 8 (1997) 2005-09-28T16:27:42-00:00 1997 European Trans. on Telecommunications {8} congestion control nonlinear optimization pricing programming http://www.citeulike.org/user/p2pstreaming/article/333973 <i>(2001)</i> Optimization Based Rate Control for Multirate Multicast Sessions K Kar S Sarkar L Tassiulas (2001) 2005-09-28T16:27:42-00:00 2001 allocation multicast nonlinear optimization programming resource http://www.citeulike.org/user/p2pstreaming/article/333972 <i>(2001)</i> A Simple Rate Control Algorithm for Maximizing Total User Utility K Kar S Sarkar L Tassiulas (2001) 2005-09-28T16:27:42-00:00 2001 congestion control nonlinear optimization programming http://www.citeulike.org/user/p2pstreaming/article/333971 <i>(2001)</i> A Low-Overhead Rate Control Algorithms for Maximizing Aggregate Receiver Utility for Multirate Multicast Sessions K Kar S Sarkar L Tassiulas (2001) 2005-09-28T16:27:42-00:00 2001 congestion control multicast nonlinear optimization programming http://www.citeulike.org/user/p2pstreaming/article/333968 <i>(June 2002), pp. 477-486.</i> QoS and Fairness Constrained Convex Optimization of Resource Allocation for Wireless Cellular and Ad Hoc Networks D Julian M Chiang D O'Neill S Boyd (June 2002), pp. 477-486. 2005-09-28T16:27:42-00:00 2002 477 486 ad allocation hoc network optimization resource http://www.citeulike.org/user/p2pstreaming/article/333933 <i>IEEE Transactions on Automatic Control, Vol. 34, No. 9. (1989)</i> Control and Optimization Methods in Communication Network Problems A Ephremides S Verdu IEEE Transactions on Automatic Control, Vol. 34, No. 9. (1989) 2005-09-28T16:27:35-00:00 1989 IEEE Transactions on Automatic Control 34 9 communication control network optimization http://www.citeulike.org/user/p2pstreaming/article/333894 <i>(1989)</i> Parallel and Distributed Computation D Bertsekas J Tsitsiklis (1989) 2005-09-28T16:27:21-00:00 1989 Prentice-Hall optimization http://www.citeulike.org/user/p2pstreaming/article/333893 <i>(1999)</i> Nonlinear Programming D Bertsekas (1999) 2005-09-28T16:27:21-00:00 1999 Athena Scientific nonlinear optimization programming