期刊名称：International Journal of Computational Intelligence Techniques
印刷版ISSN：0976-0466
电子版ISSN：0976-0474
出版年度：2010
期号：567
页码：27-31
出版社：Bioinfo Publications
摘要：During recent years, the Internet has witnessed a rapid growth in deployment of datadriven (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 mincost 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.
