The Trickle-Down Effect: Web Caching and Server Request Distribution
The Trickle-Down Effect: Web Caching and Server Request Distribution
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DOI：
10.1016/s0140-3664(01)00406-6
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发表时间：
2002-03
期刊：
影响因子：
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通讯作者：
Ronald P. Doyle;J. Chase;S. Gadde;Amin Vahdat
中科院分区：
文献类型：
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作者：
Ronald P. Doyle;J. Chase;S. Gadde;Amin Vahdat
Web代理和内容交付网络(CDN)被广泛用于加速Web内容交付和节省互联网带宽。这些缓存代理对静态内容非常有效，静态内容是所有基于Web的服务的重要组件。本文探讨了无处不在的Web缓存对端到端内容交付体系结构的其他组件(包括Web服务器集群和内部缓存)所看到的请求模式的影响。特别是，Web中的对象流行度分布往往类似于Zipf，但缓存不成比例地吸收对最流行对象的请求，从根本上改变了过滤后的请求流的引用属性。我们称之为涓滴效应。本文使用跟踪驱动的模拟和合成流量模式来说明涓滴效应，并研究其对内容交付体系结构的其他组件的影响，重点是对服务器集群中的请求分发策略的影响。
Web proxies and Content Delivery Networks (CDNs) are widely used to accelerate Web content delivery and to conserve Internet bandwidth. These caching agents are highly effective for static content, which is an important component of all Web-based services. This paper explores the effect of ubiquitous Web caching on the request patterns seen by other components of an end-to-end content delivery architecture, including Web server clusters and interior caches. In particular, object popularity distributions in the Web tend to be Zipf-like, but caches disproportionately absorb requests for the most popular objects, changing the reference properties of the filtered request stream in fundamental ways. We call this the trickle-down effect. This paper uses trace-driven simulation and synthetic traffic patterns to illustrate the trickle-down effect and to investigate its impact on other components of a content delivery architecture, focusing on the implications for request distribution strategies in server clusters.