Network Aware Reliability Analysis for Distributed Storage Systems

Amir Epstein, E. K. Kolodner, D. Sotnikov
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引用次数: 6

Abstract

It is hard to measure the reliability of a large distributed storage system, since it is influenced by low probability failure events that occur over time. Nevertheless, it is critical to be able to predict reliability in order to plan, deploy and operate the system. Existing approaches suffer from unrealistic assumptions regarding network bandwidth. This paper introduces a new framework that combines simulation and an analytic model to estimate durability for large distributed cloud storage systems. Our approach is the first that takes into account network bandwidth with a focus on the cumulative effect of simultaneous failures on repair time. Using our framework we evaluate the trade-offs between durability, network and storage costs for the OpenStack Swift object store, comparing various system configurations and resiliency schemes, including replication and erasure coding. In particular, we show that when accounting for the cumulative effect of simultaneous failures, the probability of data loss estimates can vary by two to four orders of magnitude.
分布式存储系统网络感知可靠性分析
随着时间的推移,大型分布式存储系统会受到低概率故障事件的影响,因此很难对其可靠性进行评估。然而,为了规划、部署和操作系统,能够预测可靠性是至关重要的。现有的方法在网络带宽方面存在不切实际的假设。本文介绍了一种结合仿真和分析模型的新框架来评估大型分布式云存储系统的持久性。我们的方法是第一个考虑到网络带宽的方法,重点关注同步故障对修复时间的累积影响。使用我们的框架,我们评估了OpenStack Swift对象存储的持久性、网络和存储成本之间的权衡,比较了各种系统配置和弹性方案,包括复制和擦除编码。特别是,我们表明,当考虑到同时故障的累积效应时,数据丢失估计的概率可以变化2到4个数量级。
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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