A framework for efficient evaluation of the fault tolerance of deduplicated storage systems

Eric Rozier, W. Sanders
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引用次数: 13

Abstract

In this paper we present a framework for analyzing the fault tolerance of deduplicated storage systems. We discuss methods for building models of deduplicated storage systems by analyzing empirical data on a file category basis. We provide an algorithm for generating component-based models from this information and a specification of the storage system architecture. Given the complex nature of detailed models of deduplicated storage systems, finding a solution using traditional discrete event simulation or numerical solvers can be difficult. We introduce an algorithm which allows for a more efficient solution by exploiting the underlying structure of dependencies to decompose the model of the storage system. We present a case study of our framework for a real system.We analyze a production deduplicated storage system and propose extensions which improve fault tolerance while maintaining high storage efficiency.
一种有效评估重复数据删除存储系统容错性的框架
本文提出了一个分析重复数据删除存储系统容错性的框架。本文以文件分类为基础,通过对经验数据的分析,讨论了构建重复数据删除存储系统模型的方法。我们提供了从这些信息生成基于组件的模型的算法和存储系统架构的规范。考虑到重复数据删除存储系统详细模型的复杂性,使用传统的离散事件模拟或数值求解方法找到解决方案可能很困难。我们引入了一种算法,通过利用依赖关系的底层结构来分解存储系统的模型,从而实现更有效的解决方案。我们为一个实际系统提供了我们的框架的一个案例研究。本文对一个生产型重复数据删除存储系统进行了分析,提出了在保持高存储效率的同时提高容错能力的扩展方案。
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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