Erasure Codes with Small Overhead Factor and Their Distributed Storage Applications

Hiroaki Kameyama, Yuichi Sato
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引用次数: 13

Abstract

In this paper, we consider a family of XOR-based erasure codes with finite-sized randomly-generated parity check matrices, and report the results of thorough computational search for suitable erasure codes for distributed storage applications. Although the discovered matrices are not "low density" and the resulting codes are only approximately maximum distance separable (MDS) codes, they have performance advantages over other codes, such as LDPC and IRA (irregular repeat-accumulate) codes, in terms of the overhead factor, that is, the average ratio of the total amount of encoded file blocks for restoring lost blocks to the amount of original file blocks. We designed our codes so that the overhead factor becomes small. While typical LDPC codes use matrices that have several thousand rows, our codes use matrices that have only one thousand rows in consideration of practicable operation time and overhead. Because a method for discovering the most suitable matrix from a large number of matrices has not been found, we executed Monte Carlo simulation for a long time in order to discover a suitable matrix with the lowest overhead factor. We have discovered a family of erasure codes with an overhead factor of 1.002 on average, compared to 1.07 for typical LDPC codes when the number of rows is 1000.
小开销因数的擦除码及其分布式存储应用
在本文中,我们考虑了一类基于xor的具有有限大小随机生成奇偶校验矩阵的擦除码,并报告了对适合分布式存储应用的擦除码进行彻底计算搜索的结果。尽管所发现的矩阵不是“低密度”的,所得到的代码也只是近似最大距离可分离(MDS)代码,但就开销因子而言,它们比其他代码(如LDPC和IRA(不规则重复累积)代码)具有性能优势,即用于恢复丢失块的编码文件块总数与原始文件块数量的平均比率。我们设计了代码,使开销系数变小。虽然典型的LDPC代码使用具有几千行的矩阵,但考虑到实际操作时间和开销,我们的代码使用仅具有1000行的矩阵。由于没有找到从大量矩阵中找到最合适矩阵的方法,为了找到开销系数最低的合适矩阵,我们进行了长时间的蒙特卡罗模拟。我们发现一组擦除码的开销系数平均为1.002,而当行数为1000时,典型LDPC码的开销系数为1.07。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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