Cloud-Based Simulation: The State-of-the-Art Computer Simulation Paradigm

Xiaocheng Liu, X. Qiu, Bin Chen, Kedi Huang
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引用次数: 29

Abstract

The cloud computing paradigm attracts increasing amount of Modeling&Simulation (M&S) practitioners to perform their simulations in the cloud. Two issues, namely, the architecture of the Cloud-based Simulation (CSim) and the parallel simulation job scheduling in the CSim, should be addressed ï¬rst to make the CSim practical. This paper reports our recent work on the two issues. The architecture we proposed covers the software involved in the whole process of M&S by providing the Modeling as a Service (MaaS), the Execution as a Service (EaaS) and the Analysis as a Service (AaaS). The architecture also encourages the reuse of available simulation resources with the aid of the Simulation Resource as a Service (SRaaS). For the issue of parallel simulation job scheduling in the CSim, we ï¬rst propose a two-tier processor partition method to organize virtual machines (VMs) for parallel simulation workload consolidation, the two-tier VMs have different CPU priority. We then present four scheduling algorithms under such a partition method to cope with four common situations. Our extensive experiments on well-known traces show that all the four algorithms signiï¬cantly outperform their competitors.
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基于云的仿真:最先进的计算机仿真范式
云计算范式吸引了越来越多的建模与仿真(M&S)从业者在云中执行他们的仿真。两个问题,即基于云的仿真(CSim)的体系结构和并行仿真作业调度在CSim,应该解决ï -以使CSim实用。本文报告了我们最近在这两个问题上的工作。我们提出的体系结构通过提供建模即服务(MaaS)、执行即服务(EaaS)和分析即服务(AaaS),涵盖了M&S整个过程中涉及的软件。该体系结构还鼓励在模拟资源即服务(SRaaS)的帮助下重用可用的模拟资源。针对CSim中的并行仿真作业调度问题,我们ï首先提出了一种两层处理器分区方法来组织虚拟机(vm)进行并行仿真工作负载整合,两层虚拟机具有不同的CPU优先级。在此划分方法下,我们提出了四种调度算法来应对四种常见的情况。我们在众所周知的痕迹上进行的大量实验表明,所有四种算法signiï都明显优于它们的竞争对手。
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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