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Implementing Cooperative Caching in Distributed Streaming Media Server Clusters

机译:在分布式流媒体服务器集群中实现协同缓存

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In distributed streaming media server clusters, by adopting cooperative caching (CC) technique, the free memory of all the servers can be combined to form a bigger, logically integral cooperative cache. It will help raise the hit rate of the cache and reduce disk accesses, resulting in the improvement of the overall throughput of server systems. Traditional CC and streaming buffer replacement algorithms are not quite suitable for streaming server clusters. This paper proposes a new cooperative caching strategy for them, called GLNU (Globally Longest-Not-to-be-Used). It is based on server level cooperation and fully takes the streaming media's continuous playback requirement into consideration. Compared with traditional CC algorithms and cache algorithms for continuous media, this algorithm is more pertinent and suitable to the distributed streaming server cluster systems. Simulation results show that GLNU has better performance than several other traditional cache algorithms in various conditions.
机译:在分布式流媒体服务器集群中,通过采用协作缓存(CC)技术,可以组合所有服务器的自由存储器以形成更大,逻辑上积分的协同缓存。它将有助于提高缓存的命中率并减少磁盘访问,从而提高了服务器系统的整体吞吐量。传统的CC和流缓冲区替换算法不太适合流式服务器集群。本文为他们提出了一种新的合作缓存策略,称为GLNU(全球最长的不使用)。它基于服务器级合作,充分考虑流媒体的持续播放要求。与传统CC算法和缓存算法相比,连续媒体,该算法更相关,适合于分布式流式服务器集群系统。仿真结果表明,GLNU在各种条件下比其他几种传统高速缓存算法更好地表现。

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