作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2013, Vol. 39 ›› Issue (3): 218-222. doi: 10.3969/j.issn.1000-3428.2013.03.043

• 人工智能及识别技术 • 上一篇    下一篇

基于PSO改进算法的气象数据网格任务调度

李 飞,张 琨,牛京武,王 浩   

  1. (成都信息工程学院网络工程学院,成都 610225)
  • 收稿日期:2012-04-23 出版日期:2013-03-15 发布日期:2013-03-13
  • 作者简介:李 飞(1966-),男,教授,主研方向:网格计算,云计算;张 琨、牛京武、王 浩,硕士研究生
  • 基金资助:
    四川省科技支撑计划基金资助项目(2011GZ0195)

Meteorological Data Grid Task Schedule Based on PSO Improved Algorithm

LI Fei, ZHANG Kun, NIU Jing-wu, WANG Hao   

  1. (College of Network Engineering, Chengdu University of Information Technology, Chengdu 610225, China)
  • Received:2012-04-23 Online:2013-03-15 Published:2013-03-13

摘要: 为提高在有限带宽下气象观测中心海量数据的任务调度和数据传输效率,提出一种基于粒子群优化(PSO)改进算法的气象数据网格任务调度算法。给出副本域的概念,将PSO算法与副本域相结合,设计任务调度模型和符合气象数据网格环境的目标函数。仿真结果表明,该算法完成调度的时间小于遗传算法和穷尽搜索算法,收敛速度快于离散型PSO算法,且更加稳定。

关键词: 数据网格, 粒子群优化算法, 任务调度, 副本域, 气象数据

Abstract: In order to improve the efficiency of task schedule and data transmission about the massive data of weather bureau under limited bandwidth, this paper proposes a meteorological data grid task schedule algorithm based on Particle Swarm Optimization(PSO) improved algorithm. It gives the conception of Replica Domain(RD), makes combination of PSO algorithm, and designs task schedule model and the objective functions which conform to the meteorological data grid environment. Simulation results show that the finishing scheduling time of this algorithm is less than Genetic Algorithm(GA) and end search algorithm, its convergence speed is faster than Discrete Particle Swarm Optimization(DPSO) algorithm, and is more stable.

Key words: data grid, Particle Swarm Optimization(PSO) algorithm, task schedule, Replica Domain(RD), meteorological data

中图分类号: