AZ-Code:一种高效的可用分区级Erasure Code,为云存储系统提供高容错能力

Xin Xie, Chentao Wu, Junqing Gu, Han Qiu, Jie Li, M. Guo, Xubin He, Yuanyuan Dong, Yafei Zhao
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引用次数: 27

摘要

随着现代云存储系统中数据的急剧增长,对数据进行分区并将其存储在不同的可用区(az)中是一种常见的方法。多个可用分区不仅提供高容错性(例如机架级容错性或容灾性),而且还减少了网络延迟。复制和EC (Erasure Codes)是为存储系统提供高可靠性的典型数据冗余方式。与复制方法相比,在具有相同容错能力的情况下,擦除码的成本要低得多。但是,EC在多AZ环境下的恢复成本非常高,特别是数据中心的带宽消耗非常大。为了降低回收成本,LRC是一种广泛使用的EC,但牺牲了存储效率。MSR码是为了降低回收成本和提高存储效率而设计的,但其计算过于复杂。为了解决这个问题,在本文中,我们提出了一种多可用区擦除码(称为AZ-Code),它是一种利用MSR码和LRC码的混合码。AZ-Code使用特定的MSR代码作为本地奇偶校验布局,使用典型的RS代码生成全局奇偶校验。这样,AZ-Code可以保持低的恢复成本和高的可靠性。为了证明AZ-Code的有效性,我们通过数学分析和Hadoop系统中的实验来评估各种擦除代码。结果表明,与传统的擦除编码方法相比,AZ-Code可节省高达78.24%的恢复带宽。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AZ-Code: An Efficient Availability Zone Level Erasure Code to Provide High Fault Tolerance in Cloud Storage Systems
As data in modern cloud storage system grows dramatically, it's a common method to partition data and store them in different Availability Zones (AZs). Multiple AZs not only provide high fault tolerance (e.g., rack level tolerance or disaster tolerance), but also reduce the network latency. Replication and Erasure Codes (EC) are typical data redundancy methods to provide high reliability for storage systems. Compared with the replication approach, erasure codes can achieve much lower monetary cost with the same fault-tolerance capability. However, the recovery cost of EC is extremely high in multiple AZ environment, especially because of its high bandwidth consumption in data centers. LRC is a widely used EC to reduce the recovery cost, but the storage efficiency is sacrificed. MSR code is designed to decrease the recovery cost with high storage efficiency, but its computation is too complex. To address this problem, in this paper, we propose an erasure code for multiple availability zones (called AZ-Code), which is a hybrid code by taking advantages of both MSR code and LRC codes. AZ-Code utilizes a specific MSR code as the local parity layout, and a typical RS code is used to generate the global parities. In this way, AZ-Code can keep low recovery cost with high reliability. To demonstrate the effectiveness of AZ-Code, we evaluate various erasure codes via mathematical analysis and experiments in Hadoop systems. The results show that, compared to the traditional erasure coding methods, AZ-Code saves the recovery bandwidth by up to 78.24%.
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