云计算中基于改进的布谷鸟算法的资源调度
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


Resource Scheduling Based on Improved Cuckoo Algorithm in Cloud Computing
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 增强出版
  • |
  • 文章评论
    摘要:

    云计算的资源调度一直以来都是研究的重点,引入布谷鸟算法来解决资源分配问题,首先描述云计算资源模型,其次针对该算法存在局部收敛速度快,容易造成局部最优值的问题,采用三个方面来改进,其一采用变长因子进行调整,减小探索求解质量之间的差别;其二使用差分变异策略更新鸟窝位置;其三使用基于Coelho的混沌全局搜素和局部搜索避免了Levy的随意扰动.通过测试函数说明表明本文算法的性能优于基本布谷鸟算法, Cloudsim仿真平台说明本文的算法在消耗时间,成本和用户满意度方面具有明显的优势.

    Abstract:

    Resource scheduling in cloud computing has always been the focus of research, thus the cuckoo algorithm is introduced in this paper to solve the problem of resource allocation. The resource model of cloud computing is described at first. Then, aiming at the problem that this algorithm is easy to cause local optimal value with fast local convergence speed, this model is improved from the following three aspects. Firstly, the variable-length factor is adopted to make the adjustment and reduce difference between the quality of solutions. Secondly, differential mutation strategy is used to update the bird nest's location. Thirdly, chaotic global search and local search are used based on Coelho to avoid the random disturbance of Levy. It is shown through the test functions that the algorithm proposed in this paper has superior performance than the basic cuckoo algorithm, and the Cloudsim simulation platform shows that algorithm in this paper has obvious advantages in the consumption of time, costs and users' satisfaction.

    参考文献
    相似文献
    引证文献
引用本文

陈海涛.云计算中基于改进的布谷鸟算法的资源调度.计算机系统应用,2016,25(1):114-120

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2015-04-13
  • 最后修改日期:2015-06-08
  • 录用日期:
  • 在线发布日期: 2016-01-15
  • 出版日期:
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京海淀区中关村南四街4号 中科院软件园区 7号楼305房间,邮政编码:100190
电话:010-62661041 传真: Email:csa (a) iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号