Optimizing the Throughput of Data-Driven Peer-to-Peer Streaming Export

@article{optimal_throughput_LP_pull_journal, abstract = {During recent years, the Internet has witnessed a rapid growth in deployment of data-driven (or swarming based) peer-to-peer (P2P) media streaming. In these applications, each node independently selects some other nodes as its neighbors (i.e. gossip-style overlay construction), and exchanges streaming data with the neighbors (i.e. data scheduling). To improve the performance of such protocol, many existing works focus on the gossip-style overlay construction issue. However, few of them concentrate on optimizing the streaming data scheduling to maximize the throughput of a constructed overlay. In this paper, we analytically study the scheduling problem in data-driven streaming system and model it as a classical min-cost network flow problem. We then propose both the global optimal scheduling scheme and distributed heuristic algorithm to optimize the system throughput. Furthermore, we introduce layered video coding into data-driven protocol and extend our algorithm to deal with the end-host heterogeneity. The results of simulation with the real world traces indicate that our distributed algorithm significantly outperforms conventional ad hoc scheduling strategies especially in stringent buffer and bandwidth constraints.}, address = {Los Alamitos, CA, USA}, author = {Zhang, Meng and Xiong, Yongqiang and Zhang, Qian and Sun, Lifeng and Yang, Shiqiang}, citeulike-article-id = {5187595}, citeulike-linkout-0 = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2008.69}, citeulike-linkout-1 = {http://dx.doi.org/10.1109/TPDS.2008.69}, citeulike-linkout-2 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4509427}, day = {02}, doi = {10.1109/TPDS.2008.69}, issn = {1045-9219}, journal = {Parallel and Distributed Systems, IEEE Transactions on}, keywords = {data-driven, overlay, pull, streaming}, month = {May}, number = {1}, pages = {97--110}, posted-at = {2009-07-17 03:16:49}, priority = {2}, publisher = {IEEE Computer Society}, title = {Optimizing the Throughput of Data-Driven Peer-to-Peer Streaming}, url = {http://dx.doi.org/10.1109/TPDS.2008.69}, volume = {20}, year = {2008} }

TY - JOUR ID - optimal_throughput_LP_pull_journal L3 - citeulike-article-id:5187595 N2 - During recent years, the Internet has witnessed a rapid growth in deployment of data-driven (or swarming based) peer-to-peer (P2P) media streaming. In these applications, each node independently selects some other nodes as its neighbors (i.e. gossip-style overlay construction), and exchanges streaming data with the neighbors (i.e. data scheduling). To improve the performance of such protocol, many existing works focus on the gossip-style overlay construction issue. However, few of them concentrate on optimizing the streaming data scheduling to maximize the throughput of a constructed overlay. In this paper, we analytically study the scheduling problem in data-driven streaming system and model it as a classical min-cost network flow problem. We then propose both the global optimal scheduling scheme and distributed heuristic algorithm to optimize the system throughput. Furthermore, we introduce layered video coding into data-driven protocol and extend our algorithm to deal with the end-host heterogeneity. The results of simulation with the real world traces indicate that our distributed algorithm significantly outperforms conventional ad hoc scheduling strategies especially in stringent buffer and bandwidth constraints. IS - 1 JF - Parallel and Distributed Systems, IEEE Transactions on SN - 1045-9219 AD - Los Alamitos, CA, USA EP - 110 TI - Optimizing the Throughput of Data-Driven Peer-to-Peer Streaming PB - IEEE Computer Society VL - 20 SP - 97 KW - data-driven KW - overlay KW - pull KW - streaming AU - Zhang, Meng AU - Xiong, Yongqiang AU - Zhang, Qian AU - Sun, Lifeng AU - Yang, Shiqiang PY - 2008/05/02/ UR - http://dx.doi.org/10.1109/TPDS.2008.69 ER -