计算机与现代化 ›› 2013, Vol. 1 ›› Issue (9): 78-81,1.doi: 10.3969/j.issn.1006-2475.2013.09.019

• 软件工程 • 上一篇    下一篇

基于改进粒子群算法的云计算任务调度策略

马 亮1,2,李 晓1   

  1. 1.中国科学院新疆理化技术研究所,新疆 乌鲁木齐 830011;2.中国科学院大学,北京 100049
  • 收稿日期:2013-03-15 修回日期:1900-01-01 出版日期:2013-09-17 发布日期:2013-09-17

Cloud Computing Task Scheduling Strategy Based on Improved Particle Swarm Algorithm

MA Liang1,2, LI Xiao1   

  1. 1. Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Sciences, Urumqi 830011, China;2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2013-03-15 Revised:1900-01-01 Online:2013-09-17 Published:2013-09-17

摘要: 如何进行合理高效的任务调度是云计算研究的重要问题。针对云计算任务调度和负载均衡问题,本文在对云计算环境及其任务的详细量化分析的基础上,结合实际问题对粒子群调度算法进行变异和修改,着重从任务完成时间和负载均衡两方面对云计算中的任务调度进行优化。实验表明,该算法具有较好的性能,不仅使得任务完成时间高效,并且有效地兼顾了负载均衡,取得了一定的效果。

关键词: 云计算, 任务调度, 粒子群算法, 负载均衡

Abstract: Task scheduling is an important issue for cloud computing research. Based on detailedly quantitative analysis of the environment and task of cloud computing, this article proposes an improved particle swarm scheduling algorithm, focuses on task completion time and load balancing to optimize task scheduling in cloud computing. The experiments show that the algorithm is of better performance, not only makes the task completion time efficient, but also effectively considers load balancing, achieves a certain effect.

Key words: cloud computing, task scheduling, particle swarm algorithm, load balancing

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