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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Beehive: Erasure Codes for Fixing Multiple Failures in Distributed Storage Systems
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Beehive: Erasure Codes for Fixing Multiple Failures in Distributed Storage Systems

机译:Beehive:用于修复分布式存储系统中多个故障的擦除代码

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摘要

In distributed storage systems, erasure codes have been increasingly deployed to tolerate server failures without loss of data. Traditional erasure codes, such as Reed-Solomon codes, suffer from a high volume of network transfer and disk I/O to recover unavailable data at failed storage servers. Typically, unavailable data at different failed storage servers in a distributed storage system are fixed separately. It has been shown that it is possible to reduce the volume of network transfer significantly by reconstructing data from multiple storage servers at the same time. However, there has been no construction of erasure codes to achieve it without imposing strict constraints on system parameters. In this paper, we propose Beehive codes, designed for optimizing the volume of network transfers to fix the data on multiple failed storage servers. Beehive codes can be constructed over a wide range of system parameters at code rate no more than 0.5, while incurring slightly more storage overhead than Reed-Solomon codes. To achieve the optimal storage overhead as Reed-Solomon codes, we further extend vanilla Beehive codes to MDS Beehive codes, which incurs near-optimal volumes of network transfers during reconstruction. We implement both Beehive and MDS Beehive Codes in C++ and evaluate their performance on Amazon EC2. Our evaluation results have clearly shown that the volume of both network transfers and disk I/O can be conserved by a substantial margin.
机译:在分布式存储系统中,擦除代码已越来越多地用于容忍服务器故障而不会丢失数据。传统的擦除代码(例如Reed-Solomon代码)会遭受大量的网络传输和磁盘I / O的困扰,以恢复故障存储服务器上的不可用数据。通常,分布式存储系统中不同故障存储服务器上的不可用数据是单独修复的。已经表明,可以通过同时从多个存储服务器重建数据来显着减少网络传输量。但是,在不对系统参数施加严格限制的情况下,没有擦除码的构造来实现它。在本文中,我们提出了Beehive代码,旨在优化网络传输量以将数据固定在多个故障存储服务器上。蜂巢码可以在不超过0.5的码率下在广泛的系统参数上构建,同时所产生的存储开销比Reed-Solomon码略多。为了实现最佳存储开销(如Reed-Solomon码),我们将香草Beehive码进一步扩展为MDS Beehive码,这在重建期间导致网络传输量接近最佳。我们用C ++实现Beehive和MDS Beehive代码,并评估它们在Amazon EC2上的性能。我们的评估结果清楚地表明,网络传输和磁盘I / O的数量可以节省很多。

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