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Dynamic information-based scalable hashing on a cluster of web cache servers

机译:Web缓存服务器群集上基于动态信息的可伸缩哈希

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Caching web pages is an important part of web infrastructures. Medium to large-scale infrastructures deploy a cluster of servers to solve the scalability and storage problems inherent in caching. In this paper we present dynamic information-based scalable hashing that evenly hashes client requests to a cluster of cache servers, resulting in performance scalability. Runtime information is used to determine when and how to cache pages. Cached pages are stored and retrieved mutually exclusively to/from all the servers to minimize the use of storage, resulting in storage scalability. We set up an experimental environment consisting of various machines, including client servers, a cluster of 16 cache servers, and a load balancer. We demonstrate through experimental results that dynamic information-based scalable hashing maximizes both performance scalability and storage scalability while the existing approaches do only either one of the two.
机译:缓存网页是Web基础结构的重要组成部分。中型到大型基础架构部署服务器集群以解决缓存固有的可伸缩性和存储问题。在本文中,我们介绍了基于动态信息的可伸缩哈希,该哈希将客户端请求均匀地哈希到缓存服务器集群,从而实现了性能可伸缩性。运行时信息用于确定何时以及如何缓存页面。高速缓存的页面相互存储,并且互斥地向所有服务器/从所有服务器检索,以最大程度地减少存储的使用,从而实现存储可伸缩性。我们建立了一个实验环境,该环境由各种计算机组成,包括客户端服务器,由16个缓存服务器组成的集群和负载平衡器。我们通过实验结果证明,基于动态信息的可伸缩哈希可以最大限度地提高性能可伸缩性和存储可伸缩性,而现有方法只能做到二者之一。

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