Improved Particle Swarm Optimization Algorithm for Cloud Computing Scheduling
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Cloud computing resource scheduling is a key and complex scheduling problem in cloud computing, and many factors need to be considered. In order to reduce the time of cloud computing, an Improved Particle Swarm Optimization (IPSO) algorithm is proposed. Based on the linear decreasing inertia weight, the chaotic constant disturbance is added to increase the inertia weight with little probability, so as to get rid of the local search and get the global search. Meanwhile, in order to solve the defect that the two algorithms fall into partial optimization easily, the proposed algorithm combines the optimization strategy of particle swarm optimization and ant colony optimization. The Matlab simulation and the testing of practical examples results show that the improved algorithm can get a more accurate solution under the same condition.

    Reference
    Related
    Cited by
Get Citation

罗云,唐丽晴.云计算调度粒子群改进算法.计算机系统应用,2019,28(7):151-156

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:January 06,2019
  • Revised:February 03,2019
  • Adopted:
  • Online: July 05,2019
  • Published: July 15,2019
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063