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首页> 外文会议>IEEE Pacific Rim International Symposium on Dependable Computing >MEC: Network Optimized Multi-stage Erasure Coding for Scalable Storage Systems
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MEC: Network Optimized Multi-stage Erasure Coding for Scalable Storage Systems

机译：MEC：可扩展存储系统的网络优化多级擦除编码

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摘要

In scalable storage systems, there are two kinds of methods for data redundancy: mirroring and parity. Each has its pros and cons. Mirroring creates a large amount of redundancy data, resulting in less usable space. Write performance degrades proportionally to the redundancy level due to an increase in communication. Parity-based methods partition data into multiple pieces, add parity information, and distribute the pieces of data and parity information. Parity-based methods are not often used with memory class media that are faster than the network, because distributing the data across servers results in low read performance. This research aims to establish an efficient data protection method that can be applied to fast, memory class media. We propose a new parity-based method called Multi-stage Erasure Coding (MEC), which creates two different erasure codes: one at the data transmission source server, and the other at the destination server. We show that our method reduces the space required to achieve redundancy while achieving high performance by making the amount of write communication independent of the redundancy level. We built a prototype program using MEC on a commodity cluster server. We show that compared with conventional parity-based methods with redundancy level 2, read I/O throughput is over one order of magnitude higher thanks to local reads and that write I/O throughput is almost the same due to network bottleneck.
机译：在可伸缩存储系统中，有两种数据冗余方法：镜像和奇偶校验。每个都有其优点和缺点。镜像会创建大量的冗余数据，从而减少可用空间。由于通信的增加，写入性能与冗余级别成比例地降低。基于奇偶校验的方法将数据划分为多个部分，添加奇偶校验信息，然后分发数据和奇偶校验信息。基于奇偶校验的方法通常不用于速度比网络快的内存类介质，因为在服务器之间分配数据会导致较低的读取性能。这项研究旨在建立一种可应用于快速的存储类媒体的有效数据保护方法。我们提出了一种新的基于奇偶校验的方法，称为多阶段擦除编码（MEC），该方法会创建两种不同的擦除代码：一种在数据传输源服务器上，另一种在目标服务器上。我们表明，通过使写入通信量与冗余级别无关，我们的方法减少了在实现高性能的同时实现冗余所需的空间。我们在商品集群服务器上使用MEC构建了一个原型程序。我们显示，与具有冗余级别2的常规基于奇偶校验的方法相比，由于本地读取，读取I / O吞吐量要高出一个数量级，而由于网络瓶颈，写入I / O吞吐量几乎相同。

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