计算机与现代化 ›› 2016, Vol. 0 ›› Issue (6): 7-11.doi: 10.3969/j.issn.1006-2475.2016.06.002

• 网络与通信 • 上一篇    下一篇

基于混沌人工蜂群的云计算任务调度算法

  

  1. 聊城大学东昌学院,山东聊城252000
  • 收稿日期:2015-12-08 出版日期:2016-06-16 发布日期:2016-06-17
  • 作者简介:姜凯(1986-),男,山东胶州人,聊城大学东昌学院助教,硕士,研究方向:智能优化和云计算。
  • 基金资助:
    山东省教育厅科研计划项目(J13LN75)

Task Scheduling Algorithm in Cloud Computing Based on Chaos Artificial Bee Colony

  1. Dongchang College of Liaocheng University, Liaocheng 252000, China
  • Received:2015-12-08 Online:2016-06-16 Published:2016-06-17

摘要: 任务调度是云计算研究的核心问题之一。为提高云计算资源调度的效率,提出一种基于混沌人工蜂群思想的云计算任务调度算法ICABC。在雇佣蜂阶段、观察蜂阶段和侦察蜂阶段,ICABC算法充分利用混沌思想的遍历性产生新解,使邻域搜索过程具有避免陷入局部极小的能力,并最终获得全局最优解。同时,在观察蜂阶段,引入了基于混沌搜索的锦标赛选择方法,增加了种群的多样性,在一定程度上避免“早熟”现象的产生。最后,在CloudSim仿真平台上进行了实验。实验结果表明,改进后的ICABC算法能够改善算法的收敛速度和精度,是一种有效的云计算调度算法。

关键词: 云计算, 任务调度, 人工蜂群算法, 混沌优化, 混沌人工蜂群算法

Abstract:  Task scheduling is one of the most important problems in cloud computing research. In order to improve the efficiency of cloud computing resource scheduling, a novel algorithm called ICABC based on the chaos artificial bee colony is proposed. In the stages of the employed bees, the onlookers and the scout bees, ICABC makes full use of the ergodicity of chaos to create new solutions, so that the neighborhood search process can avoid falling into local minima, and eventually obtains the global optimal solution. At the same time, a new selection method using the chaos search is introduced, which increases the diversity of the population, and avoids the phenomenon of “premature” to some extent. Finally, experiments are carried out on the CloudSim simulation platform. The results show that the improved ICABC algorithm can improve the convergence speed and precision, and it is an effective task scheduling algorithm in cloud computing.

Key words: cloud computing, task scheduling, artificial bee colony, chaos optimization, chaos artificial bee colony

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