Flashback: A Peer-to-PeerWeb Server for Flash Crowds

Mayur Deshpande, Abhishek Amit, Mason Chang, N. Venkatasubramanian, S. Mehrotra
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引用次数: 23

Abstract

We present Flashback, a ready-to-use system for scalably handling large unexpected traffic spikes on web-sites. Unlike previous systems, our approach does not rely on any intermediate nodes to cache content. Instead, the clients (browsers) create a dynamic, self-scaling peer-to-peer (P2P) Web-server that grows and shrinks according to the load. This approach translates into a challenging problem - a P2P data exchange protocol that can operate in churn rates where more than 90% of peers can leave the overlay in under 10 seconds. This is at least an order of magnitude higher churn rate than previously addressed research. Additionally, our system operates under two strict constraints - users are assured that they upload only as much as they download and second, end-user browsing experience is preserved, i.e., low latency downloads and zero configuration or download of any software. Various innovations were required to meet these challenges. Key among them are (a) A TCP-friendly, UDP protocol (Roulette) for tit-for-tat data exchange under extreme churn, (b) A novel data structure (NOIS) for partial-data management and (c) A distributed hole-punching protocol for automatic NAT traversal. Experimental results show the effectiveness and near optimal scaling of Flashback. For a Web-server (and clients) running on a DSL-like connection, end-user latency increases only one second for every doubling in Web-server load.
闪回:一个点对点网络服务器的闪人群
我们提出Flashback,一个随时可用的系统,可扩展地处理网站上意外的大流量峰值。与以前的系统不同,我们的方法不依赖于任何中间节点来缓存内容。相反,客户机(浏览器)创建一个动态的、自伸缩的点对点(P2P) web服务器,该服务器可以根据负载的大小进行伸缩。这种方法转化为一个具有挑战性的问题——P2P数据交换协议可以在流失率下运行,超过90%的对等点可以在10秒内离开覆盖层。这至少比之前的研究高出一个数量级。此外,我们的系统在两个严格的约束下运行-用户可以放心,他们只上传尽可能多的下载,第二,终端用户的浏览体验得到保留,即低延迟下载和零配置或下载任何软件。需要各种创新来应对这些挑战。其中的关键是(a)一个tcp友好的UDP协议(Roulette),用于在极端混乱下进行对等数据交换,(b)一个用于部分数据管理的新数据结构(NOIS),以及(c)一个用于自动NAT穿越的分布式穿孔协议。实验结果表明了该方法的有效性和接近最优的缩放效果。对于运行在类似dsl的连接上的web服务器(和客户端),web服务器负载每增加一倍,最终用户延迟仅增加一秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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