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Computer Science ›› 2018, Vol. 45 ›› Issue (6A): 300-303.

• Network & Communication • Previous Articles     Next Articles

Task Scheduling Algorithm Based on DO-GAPSO under Cloud Environment

SUN Min CHEN, Zhong-xiong, LU Wei-rong   

  1. School of Computer & Information Technology,Shanxi University,Taiyuan 030006,China
  • Online:2018-06-20 Published:2018-08-03

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Abstract: In order to find reasonable cloud computing task scheduling scheme,the demand of users can not be satisfied by optimizing scheduling strategy from a single aspect,and there are some weight assignment problems in several aspects to optimize scheduling policy.Focusing on the problems,considering the completion time,cost and service quality,an algorithm of a dynamic target based on particle swarm and genetic algorithm(DO-GAPSO) was proposed,a dynamic linear weighting allocation policy wasintroduced in the fitness of function modeling.Cloud environment simulation experiment was conducted in the CloudSim platform.Under the same condition,discrete particle swarm optimization(DPSO),double fitness genetic algorithm(DFGA) were compared with the proposed algorithm.The experimental results show that the proposed algorithm is better than the other two algorithms in execution efficiency and optimization ability.It is a kind of effective task scheduling algorithm in cloud computing environment.

Key words: Cloud computing, Task scheduling, Inertia weight, Particle swarm optimization, Genetic algorithm

CLC Number: 

  • TP393
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