首页 | 本学科首页   官方微博 | 高级检索  
     

基于改进布谷鸟搜索算法的云计算任务调度
引用本文:刘竹松,陈洁,田龙.基于改进布谷鸟搜索算法的云计算任务调度[J].广东工业大学学报,2016,33(3):32-36.
作者姓名:刘竹松  陈洁  田龙
作者单位:广东工业大学 计算机学院,广东 广州 510006
基金项目: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)
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  
收稿时间:2016-01-15

Task Scheduling Algorithm Based on Improved Cuckoo Search Algorithm in Cloud Computing Environment
LIU Zhu-Song,CHEN Jie,TIAN Long.Task Scheduling Algorithm Based on Improved Cuckoo Search Algorithm in Cloud Computing Environment[J].Journal of Guangdong University of Technology,2016,33(3):32-36.
Authors:LIU Zhu-Song  CHEN Jie  TIAN Long
Affiliation:School of Computers, Guangdong University of Technology, Guangzhou 510006, China
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.
Keywords:cloud computing  task scheduling  cuckoo search algorithm  Cauchy distribution  
本文献已被 万方数据 等数据库收录!
点击此处可从《广东工业大学学报》浏览原始摘要信息
点击此处可从《广东工业大学学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号