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

Authors Zhang, Meng
Xiong, Yongqiang
Zhang, Qian
Sun, Lifeng
Yang, Shiqiang
Issue Date 2009
Source IEEE transactions on parallel and distributed systems , v. 20, (1), 2009, JAN, p. 97-110
Summary 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.
ISSN 1045-9219
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Language English
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