Task scheduling optimization in cloud computing based on heuristic Algorithm

被引：139

作者：

机构：

[1] College of Information Sciences and Technology, Donghua University

[2] Department of Computer Science and Engineering, Henan University of Urban Construction

来源：

Guo, L. (kftjh@yahoo.com.cn) | 1600年 / Academy Publisher卷 / 07期

关键词：

Computing cloud; Computing intensive; Data intensive; Particle swarm optimization; Task scheduling;

D O I：

10.4304/jnw.7.3.547-553

中图分类号：

学科分类号：

摘要：

Cloud computing is an emerging technology and it allows users to pay as you need and has the high performance. Cloud computing is a heterogeneous system as well and it holds large amount of application data. In the process of scheduling some intensive data or computing an intensive application, it is acknowledged that optimizing the transferring and processing time is crucial to an application program. In this paper in order to minimize the cost of the processing we formulate a model for task scheduling and propose a particle swarm optimization (PSO) algorithm which is based on small position value rule. By virtue of comparing PSO algorithm with the PSO algorithm embedded in crossover and mutation and in the local research, the experiment results show the PSO algorithm not only converges faster but also runs faster than the other two algorithms in a large scale. The experiment results prove that the PSO algorithm is more suitable to cloud computing. © 2012 ACADEMY PUBLISHER.

引用

页码：547 / 553

页数：6

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