擦除编码存储中簇感知的分散修复

Zhirong Shen, J. Shu, Zhijie Huang, Yingxun Fu
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引用次数: 15

摘要

在当今的商品存储系统中,Erasure编码是保证数据可靠性的一种有效的存储手段,但其修复性能受到大量修复业务的严重影响。由于跨集群带宽的稀缺性,集群存储系统的修复变得更加复杂。我们提出了ClusterSR,一种集群感知的分散修复方法。ClusterSR通过仔细选择读取和修复块的集群来最小化跨集群修复流量。它通过调度多个块的修复来进一步平衡跨集群的修复流量。大规模仿真和阿里云ECS实验表明,ClusterSR可以减少6.7-52.7%的跨集群修复流量,提高14.1-68.8%的修复吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ClusterSR: Cluster-Aware Scattered Repair in Erasure-Coded Storage
Erasure coding is a storage-efficient means to guarantee data reliability in today’s commodity storage systems, yet its repair performance is seriously hindered by the substantial repair traffic. Repair in clustered storage systems is even complicated because of the scarcity of the cross-cluster bandwidth. We present ClusterSR, a cluster-aware scattered repair approach. ClusterSR minimizes the cross-cluster repair traffic by carefully choosing the clusters for reading and repairing chunks. It further balances the cross-cluster repair traffic by scheduling the repair of multiple chunks. Large-scale simulation and Alibaba Cloud ECS experiments show that ClusterSR can reduce 6.7-52.7% of the cross-cluster repair traffic and improve 14.1-68.8% of the repair throughput.
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