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Storage-efficient data replica number computation for multi-level priority data in distributed storage systems

机译:分布式存储系统中多级优先级数据的高效存储数据副本数计算

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Distributed storage systems often use replication for improved availability, performance and scalability. In this paper, we consider the case of using file replication to improve the availability of different classes of files, where some classes are more “important” than others and more replicas are created for them to achieve improved availability. The question we attempt to answer is: given a fixed storage budget for storing replicas, what is the number of replicas of each file class to create to maximize the (weighted) overall availability of files? We present our work towards a replica number computation algorithm that takes into account a storage budget, a configurable maximum expected percentage of failed nodes, and weights for different file classes. Simulation results show that our algorithm is able to improve the availability of the prioritized files with higher weights, has a low computation time and can utilize storage space efficiently when total storage space scales to a large size.
机译:分布式存储系统通常使用复制来提高可用性,性能和可伸缩性。在本文中,我们考虑使用文件复制来提高不同类别文件的可用性的情况,其中某些类别比其他类别更“重要”,并且为它们创建了更多副本以提高可用性。我们试图回答的问题是:给定用于存储副本的固定存储预算,为最大程度地提高文件的(加权)总体可用性而创建的每个文件类的副本数量是多少?我们介绍了一种针对副本数计算算法的工作,该算法考虑了存储预算,故障节点的可配置最大期望百分比以及不同文件类的权重。仿真结果表明,我们的算法能够以较高的权重提高优先级文件的可用性,具有较低的计算时间,并且在总存储空间规模较大时可以有效地利用存储空间。

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