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Hierarchically Clustered P2P Video Streaming: Design, implementation, and evaluation

机译:分层群集的P2P视频流:设计,实施和评估

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摘要

P2P based live streaming has been gaining popularity. The new generation P2P live streaming systems not only attract a large number of viewers, but also support better video quality by streaming the content at higher bit-rate. In this paper, we propose a novel P2P streaming framework, called Hierarchically Clustered P2P Video Streaming, or HCPS, that can support the streaming rate approaching the optimal upper bound while accommodating large viewer population. The scalability comes with the hierarchical overlay architecture by grouping peers into clusters and forming a hierarchy among them. Peers are assigned to appropriate cluster so as to balance the bandwidth resources across clusters and maximize the supportable streaming rate. Furthermore, individual peers perform distributed queue-based scheduling algorithms to determine how to retrieve data chunks from source and neighboring peers, and how to utilize its uplink bandwidth to serve data chunks to other peers. We show that queue-based scheduling algorithms allow to fully utilize peers' uplink bandwidths, and HCPS supports the streaming rate close to the optimum in practical network environment. The prototype of HCPS is implemented and various design issues/tradeoffs are investigated. Experiments over the PlanetLab further demonstrate the effectiveness of HCPS design.
机译:基于P2P的实时流媒体已越来越流行。新一代P2P实时流媒体系统不仅吸引了大量观众,而且通过以更高的比特率流媒体内容来支持更好的视频质量。在本文中,我们提出了一种新颖的P2P流媒体框架,称为“层次集群P2P视频流”或HCPS,它可以在满足大量观众的同时,支持接近最佳上限的流媒体速率。通过将对等方分组到集群中并在集群之间形成层次结构,可伸缩性与分层覆盖体系结构一起提供。将对等方分配给适当的群集,以平衡群集之间的带宽资源并最大化可支持的流传输速率。此外,各个对等方执行基于分布式队列的调度算法,以确定如何从源对等方和相邻对等方检索数据块,以及如何利用其上行链路带宽为其他对等方提供数据块。我们展示了基于队列的调度算法可以充分利用对等方的上行链路带宽,并且HCPS支持的流速率接近实际网络环境中的最佳速率。实施了HCPS的原型,并研究了各种设计问题/折衷方案。通过PlanetLab进行的实验进一步证明了HCPS设计的有效性。

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