网格环境下基于文件聚类的复制算法

Hitoshi Sato, S. Matsuoka, Toshio Endo
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引用次数: 27

摘要

网格文件系统中的复制可以显著提高数据密集型应用程序的I/O性能。但是,大多数现有的复制技术都适用于单个文件,这可能会为大量文件带来低效的复制开销。提出了一种基于文件集群的网格文件系统复制算法。我们的算法根据文件之间的同时访问关系对文件进行分组,并将集群文件的副本存储到存储节点中,以满足在给定存储容量限制下期望的对集群文件的大部分未来读访问次数和单个文件的复制次数最小化。在给定网格环境下,5个站点20个节点的实验表明,该算法实现了准确的文件聚类和高效的副本管理;文件集群大小限制为5120 MB,副本存储容量限制为10240 MB的集群策略的效率是不分组相关文件的策略的1.58倍。结果还表明,引入我们的算法所需的开销会显著影响正在运行的应用程序的I/O性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
File Clustering Based Replication Algorithm in a Grid Environment
Replication in grid file systems can significantly improve I/O performance of data-intensive applications. However, most of existing replication techniques apply to individual files, which may introduce inefficient replication overheads for a large number of files. We propose a file clustering based replication algorithm for grid file systems. Our algorithm groups files according to a relationship of simultaneous accesses between files and stores replicas of the clustered files into storage nodes, to satisfy expected most of future read access times to the clustered files and replication times for individual files being minimized under the given storage capacity limitation. Our experiments on a given grid environment, 20 nodes of 5 sites, suggest that the proposed algorithm achieves accurate file clustering and efficient replica management; our clustering policy with the file cluster size limit of 5120 MB and the storage capacity limit for replicas of 10240 MB exhibits 1.58 times efficiency than the policy that never groups related files. The results also indicate that the overheads required for introducing our algorithm significantly affect I/O performance of running applications.
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