计算机应用 ›› 2012, Vol. 32 ›› Issue (03): 599-602.DOI: 10.3724/SP.J.1087.2012.00599

• 先进计算 • 上一篇    下一篇

自适应邻域的多目标网格任务调度算法研究

杨明1,2,薛胜军2,陈亮1,刘永生1   

  1. 1.浙江省气象信息网络中心,杭州 310017;
    2.南京信息工程大学 计算机与软件学院,南京 210044
  • 收稿日期:2011-08-24 修回日期:2011-11-18 发布日期:2012-03-01 出版日期:2012-03-01
  • 通讯作者: 杨明
  • 作者简介:杨明(1983-),男,江苏泗阳人,助理工程师,主要研究方向:网格计算、进化算法;薛胜军(1956-),男, 山东青岛人,教授,博士生导师,主要研究方向:人工智能、计算机网络、高性能计算;陈亮(1981-),男,江苏泰兴人,工程师,主要研究方向:高性能计算、计算机网络;刘永生(1981-),男,江苏宿迁人,工程师,主要研究方向:网格计算。

Multi-objective evolutionary algorithm for grid job scheduling based on adaptive neighborhood

YANG Ming1,2, XUE Sheng-jun2, CHEN Liang1, LIU Yong-sheng1   

  1. 1.Zhejiang Meteorological Information Network Center, Hangzhou Zhejiang 310017, China;
    2.College of Computer and Software, Nanjing University of Information Science and Technology, Nanjing Jiangsu 210044, China
  • Received:2011-08-24 Revised:2011-11-18 Online:2012-03-01 Published:2012-03-01
  • Contact: Ming Yang

摘要: 针对网格计算中的多目标网格任务调度问题,提出了一种基于自适应邻域的多目标网格任务调度算法。该算法通过求解多个网格任务调度目标函数的非劣解集,采用自适应邻域的方法来保持网格任务调度多目标解集的分布性,尝试解决网格任务调度中多目标协同优化问题。实验结果证明,该算法能够有效地平衡时间维度和费用维度目标,提高了资源的利用率和任务的执行效率,与Min-min和Max-min算法相比具有较好的性能。

关键词: 网格任务调度算法, 多目标进化算法, 自适应邻域, 任务调度

Abstract: A new adaptive neighborhood Multi-Objective Grid Task Scheduling Algorithm (ANMO-GTSA) was proposed in this paper for the multi-objective job scheduling collaborative optimization problem in grid computing. In the ANMO-GTSA, an adaptive neighborhood method was applied to find the non-inferior set of solutions and maintain the diversity of the multi-objective job scheduling population. The experimental results indicate that the algorithm proposed in this paper can not only balance the multi-objective job scheduling, but also improve the resource utilization and efficiency of task execution. Moreover, the proposed algorithm can achieve better performance on time-dimension and cost-dimension than the traditional Min-min and Max-min algorithms.

Key words: Grid job scheduling algorithm, multi-objective evolutionary algorithm, adaptive neighborhood, job scheduling

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