Scheduling based resource optimization in networked modeling and simulation

Hai Huang, Lei Tian, Wei Wu, Songlin Sun, Xiaojun Jing
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Abstract

A constantly increasing number of resource demanding applications from various scientific sectors are finding their way towards adopting Grid technologies in order to take advantage of their computational power. The aim of this paper is to demonstrate how tasks of large-scale distributed simulation can be scheduled based on GA in a Grid environment by taking into account load of computing nodes, network bandwidth and communication delay. For this purpose, the connotation of task scheduling formulation, the computation of chromosome fitness, selection, crossover and mutation of GA is expounded. The proposed approach yields very good results for the conducted experiment.
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网络化建模与仿真中基于调度的资源优化
为了利用网格技术的计算能力,来自不同科学部门的资源需求应用程序的数量不断增加。本文的目的是演示如何在网格环境下,在考虑计算节点负载、网络带宽和通信延迟的情况下,基于遗传算法调度大规模分布式仿真任务。为此,阐述了遗传算法任务调度的内涵、染色体适应度的计算、遗传算法的选择、交叉和突变。所提出的方法对所进行的实验产生了很好的结果。
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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