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An Efficient I/O-Redirection-Based Reconstruction Scheme for Erasure-Coded Storage Clusters

机译:擦除编码存储集群的一种高效的基于I / O重定向的重构方案

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This paper addresses an problem encountered in on-line reconstruction of erasure-coded storage clusters, where user I/Os compete with reconstruction I/Os for both disk and network bandwidth. We propose a redirection scheme called ‘’ to minimize the I/O interference among user and reconstruction requests. RAM-RS redirects user read/writes targeted at failed nodes to an RS-coded RAM region, which is formed by pre-allocated main memory in surviving nodes in the RS-coding manner. The RS-coded RAM region quickly serves all user read/write misses; therefore, a rebuilding node can devote its disk and network bandwidths to the node reconstruction. The RAM region substantially reduces the amount of data rebuilt by the rebuilding node, because (1) missed writes are buffered in the RAM region and (2) missed reads are satisfied by using surviving nodes to failed blocks. We build two Markov models to estimate the reliability of the RAM-RS system. Modeling results demonstrate that the MTTDL of RS-coded RAM region in a storage cluster is larger than that of the same cluster comprised of surviving nodes. We implement both RAM-RS and the traditional schemes in an erasure-coded storage cluster, on which real-world I/O traces are replayed. Experimental results show that compared with the scheme running on a 9-node storage cluster, RAM-RS improves system performance in terms of both user response time and reconstruction time by a factor of 1.78 and 1.20, respectively.
机译:本文解决了在擦除编码存储集群的联机重建中遇到的问题,其中用户I / O与重建I / O在磁盘和网络带宽上竞争。我们提出了一种称为“”的重定向方案,以最大程度减少用户请求和重建请求之间的I / O干扰。 RAM-RS将针对故障节点的用户读/写重定向到RS编码的RAM区域,该区域由在生存节点中以RS编码方式预分配的主存储器形成。 RS编码的RAM区域可快速为所有用户读/写未命中服务。因此,重建节点可以将其磁盘和网络带宽专用于节点重建。 RAM区域显着减少了由重建节点重建的数据量,因为(1)丢失的写入被缓存在RAM区域中,并且(2)通过使用幸存的节点来处理失败的块,可以满足丢失的读取。我们建立了两个马尔可夫模型来估计RAM-RS系统的可靠性。建模结果表明,存储集群中RS编码RAM区域的MTTDL大于由尚存节点组成的同一集群的MTTDL。我们在擦除编码的存储集群中实现RAM-RS和传统方案,在该集群上重播实际的I / O跟踪。实验结果表明,与在9节点存储群集上运行的方案相比,RAM-RS在用户响应时间和重建时间方面分别提高了1.78和1.20倍。

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