基于信道人气的PPLive测量研究

Ruixuan Li, Guoqiang Gao, Weijun Xiao, Zhiyong Xu
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引用次数: 7

摘要

近年来,点对点(P2P)流媒体系统经历了巨大的发展,成为互联网上最大的带宽消耗者之一。PPLive是该类别中最受欢迎的应用程序之一,为数百万注册用户提供数百个直播电视频道和数百万个其他视频剪辑。与标准的文件共享系统相比,流媒体服务具有更严格的时间限制和更高的网络带宽要求。评估和分析现有的应用程序,研究这些系统的优缺点,对未来的发展至关重要。在本文中,我们对PPLive进行了全面的测量研究。直播电视和视频点播(VoD)频道都会被评估。我们在客户端记录运行时的网络流量,并根据这些通道的受欢迎程度对其特征进行比较和分析。对于这两个类别,我们认为,一般来说,如果在特定通道中存在足够的并发对等点,PPLive将提供令人满意的性能。我们还观察到,VoD频道在数据传输、工作负载分配和信号流量开销方面优于直播电视类别的同行。然而,电视直播频道比视频点播频道表现出更好的同伴协调。总体而言,我们的研究结果表明,尽管PPLive可以为热门频道提供出色的观看体验,但要完全支持不热门频道仍然存在挑战。迫切需要新的设计和算法,特别是对于不受欢迎的电视直播频道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measurement Study on PPLive Based on Channel Popularity
In recent years, Peer-to-Peer (P2P) streaming systems experienced tremendous growth and became one of the largest bandwidth consumer on Internet. PPLive, one of the most popular applications in this category, is serving millions of registered users with hundreds of Live TV channels and millions of other video clips. Compared to the standard file sharing systems, the streaming service shows unique characteristics with more stringent time constraints and requires much higher network bandwidth. It is extremely important to evaluate and analyze existing applications, investigate the merits and weaknesses in these systems for the future development. In this paper, we conduct a comprehensive measurement study on PPLive. Both Live TV and Video-on-Demand (VoD) channels are evaluated. We record run-time network traffic on the client side, compare and analyze the characteristics of these channels based on their popularity. For both categories, we perceive that, in general, PPLive delivers satisfactory performance if enough concurrent peers are present in a particular channel. We also observe that VoD channels perform better than their counterparts in Live TV category in terms of data transmission, workload distribution, and signal traffic overhead. However, Live TV channels show better peer coordinations than VoD channels. Overall, our results reveal that although PPLive can provide excellent viewing experiences for popular channels, there are still challenges to fully support unpopular channels. New designs and algorithms are in urgent need, especially for unpopular Live TV channels.
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