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Parallelizing Degraded Read for Erasure Coded Cloud Storage Systems Using Collective Communications

机译:使用集体通信对擦除编码云存储系统进行并行降级读取

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摘要

For lower storage costs, storage systems are increasingly transitioning to the use of erasure codes instead of replication. However, the increase in the amount of data to be read and transferred during recovery for an erasure-coded system results in the problem of high degraded read latency. We design a new parallel degraded read method, Collective Reconstruction Read, which aims to overcome the problem of high degraded read latency of erasure coding by utilizing parallel reconstruction. By introducing collective communication operations (e.g. all-to-one reduction and all-to-all reduction) into distributed storage systems, data reading, transferring and decoding are preformed by all of the involved data nodes in parallel rather than the client itself. Therefore, the time complexity of the degraded read operation is reduced from linear time to logarithmic time. We implement Collective Reconstruction Read in HDFSRAID and evaluate it as the block size and stripe size vary. We find that these algorithms can reduce degraded read latency significantly, thereby improving system availability. Specifically, experimental results indicate an approximate 55% to 81% round off drop in degraded read latency.
机译:为了降低存储成本,存储系统越来越多地过渡到使用擦除代码而不是复制。然而,对于擦除编码的系统,在恢复期间要读取和传输的数据量的增加导致高的读取等待时间降低的问题。我们设计了一种新的并行降级读取方法“集体重建读取”,旨在通过利用并行重建来克服擦除编码的高降级读取等待时间的问题。通过在分布式存储系统中引入集体的通信操作(例如全对一还原和全对所有还原),所有相关数据节点并行执行数据读取,传输和解码,而不是客户端本身。因此,降级的读取操作的时间复杂度从线性时间减少到对数时间。我们在HDFSRAID中实现了集体重建读取,并根据块大小和条带大小的变化对其进行评估。我们发现这些算法可以显着减少降级的读取延迟,从而提高系统可用性。具体而言,实验结果表明,降低的读取延迟的舍入下降幅度约为55%至81%。

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