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  • 标题:Research for the Task Scheduling Algorithm Optimization based on Hybrid PSO and ACO for Cloud Computing
  • 本地全文:下载
  • 作者:JieHui JU ; WeiZheng BAO ; ZhongYou WANG
  • 期刊名称:International Journal of Grid and Distributed Computing
  • 印刷版ISSN:2005-4262
  • 出版年度:2014
  • 卷号:7
  • 期号:5
  • 页码:87-96
  • DOI:10.14257/ijgdc.2014.7.5.08
  • 出版社:SERSC
  • 摘要:In cloud computing environment, there are a large number of users which lead to huge amount of tasks to be processed by system. In order to make the system complete the service requests efficiently, how to schedule the tasks becomes the focus of cloud computing Research. A task scheduling algorithm based on PSO and ACO for cloud computing is presented in this paper. First, the algorithm uses particle swarm optimization algorithm to get the initial solution quickly, and then according to this scheduling result the initial pheromone distribution of ant colony algorithm is generated. Finally, the ant colony algorithm is used to get the optimal solution of task scheduling. The experiment simulated on CloudSim platform shows that the algorithm has good effect in real-time performance and optimization capability. It is an effective task scheduling algorithm.
  • 关键词:Cloud Computing; Task Scheduling; Particle Swarm Optimization (PSO); Ant ; Colony Optimization (ACO)
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