广东工业大学学报 ›› 2016, Vol. 33 ›› Issue (03): 32-36.doi: 10.3969/j.issn.1007-7162.2016.03.006

• 综合研究 • 上一篇    下一篇

基于改进布谷鸟搜索算法的云计算任务调度

刘竹松, 陈洁, 田龙   

  1. 广东工业大学 计算机学院,广东 广州 510006
  • 收稿日期:2016-01-15 出版日期:2016-05-19 发布日期:2016-05-19
  • 作者简介:刘竹松(1979-),男,副教授,主要研究方向为云计算、大数据,E-mail:liuzs@gdut.edu.cn
  • 基金资助:

    国家自然科学基金资助项目(61572144);广东省现代信息服务业发展专项资金资助项目(GDEID2011IS022)

Task Scheduling Algorithm Based on Improved Cuckoo Search Algorithm in Cloud Computing Environment

Liu Zhu-song, Chen Jie, Tian Long   

  1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2016-01-15 Online:2016-05-19 Published:2016-05-19

摘要:

针对云计算系统中能否高效地调度子任务的问题,本文提出了一种基于改进布谷鸟搜索算法的任务调度算法.利用柯西分布对陷入局部极值的鸟巢进行扰动,有利于提高布谷鸟搜索算法全局搜索的质量.算法运用整数编码方式,利用改进后的算法求得最优解.使用云仿真平台进行验证,结果证实了所提出算法的有效性.

关键词: 云计算; 任务调度; 布谷鸟搜索算法; 柯西分布

Abstract:

In the view of efficient task scheduling, the researchers propose an improved cuckoo search based on the introduction of the variability of Cauchy operator, which is helpful in improving the global search and speeding up the convergence of algorithm, for addressing the problem of task scheduling and improving the global searching quality of the cuckoo search algorithm. The study uses an improved algorithm of integer encoding structure to get optimal solutions. The experimental results based on CloudSim platform show that the algorithm can significantly improve the effectiveness and efficiency.

Key words: cloud computing; task scheduling; cuckoo search algorithm; Cauchy distribution

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