Particle Swarm Optimization Embedded in Variable Neighborhood Search for Task Scheduling in Cloud Computing

Particle Swarm Optimization Embedded in Variable Neighborhood Search for Task Scheduling in Cloud Computing

In cloud computing system,it is a hot and hard issue to find the optimal task scheduling method that makes the processing cost and the running time minimum. In order to deal with the task assignment,a task interaction graph was used to analyze the task scheduling; a modeling for task assignment was...

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Veröffentlicht in:东华大学学报（英文版） 2013, Vol.30 (2), p.145-152
1. Verfasser: 郭力争 王永皎 赵曙光 沈士根 姜长元
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应用程序
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container_title 东华大学学报（英文版）
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creator 郭力争 王永皎 赵曙光 沈士根 姜长元
description In cloud computing system,it is a hot and hard issue to find the optimal task scheduling method that makes the processing cost and the running time minimum. In order to deal with the task assignment,a task interaction graph was used to analyze the task scheduling; a modeling for task assignment was formulated and a particle swarm optimization （PSO）algorithm embedded in the variable neighborhood search （VNS） to optimize the task scheduling was proposed. The experimental results show that the method is more effective than the PSO in processing cost,transferring cost, and running time. When the task is more complex,the effect is much better. So,the algorithm can resolve the task scheduling in cloud computing and it is feasible,valid,and efficient.
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软件开发
title Particle Swarm Optimization Embedded in Variable Neighborhood Search for Task Scheduling in Cloud Computing
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