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Adding Storage Simulation Capacities to the SimGrid Toolkit: Concepts, Models, and API

机译:向SimGrid工具箱添加存储仿真功能:概念,模型和API

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For each kind of distributed computing infrastructures, i.e., clusters, grids, clouds, data centers, or supercomputers, storage is a essential component to cope with the tremendous increase in scientific data production and the ever-growing need for data analysis and preservation. Understanding the performance of a storage subsystem or dimensioning it properly is an important concern for which simulation can help by allowing for fast, fully repeatable, and configurable experiments for arbitrary hypothetical scenarios. However, most simulation frameworks tailored for the study of distributed systems offer no or little abstractions or models of storage resources. In this paper, we detail the extension of SimGrid, a versatile toolkit for the simulation of large-scale distributed computing systems, with storage simulation capacities. We first define the required abstractions and propose a new API to handle storage components and their contents in SimGrid-based simulators. Then we characterize the performance of the fundamental storage component that are disks and derive models of these resources. Finally we list several concrete use cases of storage simulations in clusters, grids, clouds, and data centers for which the proposed extension would be beneficial.
机译:对于各种分布式计算基础架构,即群集,网格,云,数据中心或超级计算机,存储是应对科学数据生产的巨大增长以及对数据分析和保存的不断增长的需求的必不可少的组成部分。理解存储子系统的性能或适当确定其尺寸是一个重要的考虑因素,对于任意假设的场景,允许进行快速,完全可重复和可配置的实验,可以为仿真提供帮助。但是,为研究分布式系统而量身定制的大多数仿真框架都没有或几乎没有提供存储资源的抽象或模型。在本文中,我们将详细介绍SimGrid的扩展,SimGrid是具有存储仿真功能的,用于大规模分布式计算系统仿真的通用工具包。我们首先定义所需的抽象,并提出一个新的API,以在基于SimGrid的模拟器中处理存储组件及其内容。然后,我们描述基本存储组件(即磁盘)的性能,并推导这些资源的模型。最后,我们列出了集群,网格,云和数据中心中存储模拟的几个具体用例,这些提议的扩展将对其有益。

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