Cooperative caching middleware for cluster-based servers

Francisco Matias Cuenca-Acuna, Thu D. Nguyen
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引用次数: 36

Abstract

Considers the use of cooperative caching to manage the memories of cluster-based servers. Over the last several years, a number of researchers have proposed content-aware servers that implement locality-conscious request distribution to address this memory management problem. During this development, it has become conventional wisdom that cooperative caching cannot match the performance of these servers. Unfortunately, while content-aware servers provide very high performance, their request distribution algorithms are typically bound to specific applications. The advantage of building distributed servers on top of a block-based cooperative caching layer is the generality of such a layer; it can be used as a building block for diverse services, ranging from file systems to web servers. In this paper, we reexamine the question of whether a server built on top of a generic block-based cooperative caching algorithm can perform competitively with content-aware servers. Specifically, we compare the performance of a cooperative caching-based Web server against L2S, a highly optimized locality- and load-conscious server. Our results show that, by modifying the replacement policy of traditional cooperative caching algorithms, we can achieve much of the performance provided by locality-conscious servers. Our modification increases network communication to reduce disk accesses, a reasonable trade-off considering the current trend of relative performance between LANs and disks.
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用于基于集群的服务器的协作缓存中间件
考虑使用协作缓存来管理基于集群的服务器的内存。在过去的几年中,许多研究人员提出了实现位置感知请求分发的内容感知服务器来解决这个内存管理问题。在此开发过程中,协作缓存无法匹配这些服务器的性能已经成为一种共识。不幸的是,虽然内容感知服务器提供了非常高的性能,但它们的请求分发算法通常绑定到特定的应用程序。在基于块的协作缓存层之上构建分布式服务器的优势在于该层的通用性;它可以用作各种服务的构建块,从文件系统到web服务器。在本文中,我们重新审视了建立在通用的基于块的协作缓存算法之上的服务器是否能够与内容感知服务器竞争的问题。具体来说,我们比较了基于协作缓存的Web服务器与L2S的性能,L2S是一种高度优化的位置和负载敏感服务器。我们的研究结果表明,通过修改传统协作缓存算法的替换策略,我们可以实现位置感知服务器提供的大部分性能。我们的修改增加了网络通信以减少磁盘访问,考虑到当前局域网和磁盘之间的相对性能趋势,这是一种合理的权衡。
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