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Approximate Parameters Analysis of Closed Fork-Join Queue Model in Object-Based Storage System

机译:基于对象存储系统中的闭FORK-JOIN队列模型的近似参数分析

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As a new generation of high-performance distributed storage system, object-based storage system is being developed to support high-performance computing environments. In the petabyte-scale object-based storage system, reasonable data distribution and parameters configuration can improve system performance and availability. To make the system performance evaluation work easier, we propose an approximate parameters analysis method to build performance model. We firstly model the whole storage system's architecture based on closed Fork-Join queue model; using our system architecture model, we then deduce an approximately analytical expression with erasure codes and replicas to predict the storage system's mean response time under various workloads simulating the real-world condition. Finally, a large number of comparison experiments validate our approximately analytical expression of system performance, and proved that our analytic method is appropriate to build performance model for object-based storage system.
机译:作为新一代高性能分布式存储系统,正在开发基于对象的存储系统来支持高性能计算环境。在Petabyte级对象的存储系统中,合理的数据分发和参数配置可以提高系统性能和可用性。为了使系统性能评估工作更容易,我们提出了一个近似参数分析方法来构建性能模型。我们首先根据封闭的叉协议队列模型建模整个存储系统的体系结构;使用我们的系统架构模型,我们用擦除代码和副本推断出近似分析表达式,以预测在模拟真实情况下的各种工作负载下的存储系统的平均响应时间。最后,大量的比较实验验证了我们的系统性能的近似分析表达,并证明了我们的分析方法适用于构建基于对象的存储系统性能模型。

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