An Empirical Study of the Coolstreaming+ System
An Empirical Study of the Coolstreaming+ System
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DOI：
10.1109/jsac.2007.071203
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发表时间：
2007-12
影响因子：
16.4
通讯作者：
Bo Li;Susu Xie;G. Y. Keung;Jiangchuan Liu;I. Stoica;Hui Zhang;Xinyan Zhang
中科院分区：
文献类型：
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作者：
Bo Li;Susu Xie;G. Y. Keung;Jiangchuan Liu;I. Stoica;Hui Zhang;Xinyan Zhang
近年来，人们对采用点对点（P2P）技术进行互联网直播视频流产生了浓厚的兴趣。这种发展背后主要有两个原因：消除基础设施支持和P2P系统的自扩展特性。Coolstreaming系统的成功代表了最早的大规模P2P视频流实验之一。从那时起，已经有了几次大规模的商业部署。有了理想的内容，这些系统就有可能超越现有的学术P2P原型的数量级。然而，为了将这种潜力转化为现实，我们需要了解关键的设计权衡和原则，以及这些系统的设计限制。在P2P流媒体系统中有两个主要的设计决策：(i)如何形成覆盖，（ii）如何传递内容。Coolstreaming采用八卦协议构建覆盖层，采用基于群的内容传递协议。虽然这些协议在处理系统动态和随机故障方面提供了出色的灵活性和有效性，但它们对性能和系统可伸缩性的影响仍然鲜为人知。本文将深入了解一个基于Coolstreaming的商业系统，称为Coolstreaming+。我们将探讨其设计选择以及这些选择对流媒体性能的影响。具体来说，通过使用由最近的直播事件生成的内部跟踪，我们研究了系统的工作负载、性能和动态。基于这些痕迹，我们表明(1)流失率是影响系统整体性能的最关键因素，(2)P2P流系统中存在高度倾斜的资源分布，这对资源分配有显著影响。我们进一步讨论了这些观察对系统特性的影响，并提出了处理各种设计挑战的解决方案。特别地，我们提出了解决方案来处理flash人群期间过多的启动时间和高故障率，这是任何流媒体系统需要解决的两个主要挑战。
In recent years, there has been significant interest in adopting the peer-to-peer (P2P) technology for Internet live video streaming. There are primarily two reasons behind this development: the elimination of infrastructure support and the self-scaling property of P2P systems. The success of our system Coolstreaming represented one of the earliest large-scale P2P video streaming experiments. Since then, there have been several large-scale commercial deployments. With desirable content, these systems have the potential to scale orders of magnitude beyond the existing academic P2P prototypes. However, to transform this potential into reality, we need to understand the key design trade-offs and principles, as well as the design limitations of these systems. There are two main design decisions in a P2P streaming system: (i) How to form an overlay, and (ii) How to deliver the content. Coolstreaming adopts a gossiping protocol for overlay construction, and a swarm-based protocol for content delivery. While these protocols provide excellent flexibility and effectiveness in dealing with system dynamics and random failure, their impact on the performance and the system scalability remain less known. This paper takes an inside look at a commercial system based on the Coolstreaming, called Coolstreaming+. We explore its design choices and the impact of these choices on streaming performance. Specifically, by using internal traces generated by recent live broadcast events, we study the workload, performance, and dynamics of the system. Based on these traces, we show that (1) the churn is the most critical factor that affects the overall performance of the system, and (2) there is a highly skew resource distribution in P2P streaming systems, which has significant impact on resource allocation. We further discuss the impact of these observations on the system properties, and present solutions to deal with various design challenges. In particular, we suggest solutions to deal with the excessive start-up time and high failure rates during flash crowd, which are two of the main challenges any streaming system needs to address.