并行Pull-Based LRU:一种新的大规模SCI集群Web缓存请求分配算法

E. Cecchet, Cyril Perrin
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摘要

SIRAC实验室开发了SciFS,一种与Linux操作系统内核紧密集成的分布式共享内存(DSM),它利用了SCI(可扩展相干接口)网络的高性能和远程寻址能力。我们尝试使用SciFS来构建大规模集群web缓存。高效的DSM不仅提供快速和大的数据存储空间,而且还允许设计新的算法来处理用户请求。*我们提出了一个集群web缓存原型与一个新的请求分发算法,称为PPBL (Parallel Pull-Based LRU),特别设计用于DSM系统。与其他分布算法不同,决策分布在所有节点上,从而提供更好的可扩展性。在这篇简短的文章中,我们只介绍了PPBL的原理,但更多的信息可以在我们的网站http://sci-serv.inrialpes.fr上找到。
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Parallel Pull-Based LRU : a New Request Distribution Algorithm for Large Scale SCI Clustered Web Caches
The SIRAC laboratory has developed SciFS, a Distrib- uted Shared Memory (DSM) tightly integrated with the Linux operating system kernel, that exploits the high performance and remote addressing capabilities of SCI (Scalable Coherent Interface) networks. We experiment with using SciFS to build large scale clustered web caches. An efficient DSM does not only provide a fast and large data storage space, but it also allows the design of new algorithms to handle user requests. * We propose a clustered web cache prototype with a new request distribution algorithm, called PPBL (Parallel Pull-Based LRU), especially designed for use with a DSM system. Unlike other distribution algorithms the decision is distributed over all nodes thus providing better scal- ability. In this short paper, we only present PPBL princi- ples but additional information can be found on our web site at http://sci-serv.inrialpes.fr.
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