• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2013, Vol. 35 ›› Issue (6): 57-64.

• 论文 • 上一篇    下一篇

移动网格关联任务调度研究

鞠宏军1,3,杜丽娟2   

  1. (1.华北科技学院计算机系,北京 101601;2.华北科技学院电信系,北京 101601;
    3.河北省矿井灾害防治重点实验室,河北 廊坊 065201)
  • 收稿日期:2012-08-13 修回日期:2012-11-02 出版日期:2013-06-25 发布日期:2013-06-25
  • 基金资助:

    国家自然科学基金资助项目(61163050);中央高校基本科研业务费专项资助项目(DX1208B)

Research on related tasks scheduling in mobile grid           

JU Hongjun1,3,DU Lijuan2   

  1. (1.Department of Computer,North China Institute of Science and Technology,Beijing 101601;
    2.Department of Electronic Information Engineering,North China Institute of Science and Technology,Beijing 101601;
    3.Hebei Key Laboratory of Mine Disaster Prevention,Langfang 065201,China)
  • Received:2012-08-13 Revised:2012-11-02 Online:2013-06-25 Published:2013-06-25

摘要:

以移动网格为背景,研究关联任务在动态资源环境下的调度问题,既考虑任务之间的依赖关系,还考虑资源动态加入、离开、性能变化等行为。提出子集调度加重调度的动态调度策略。动态子集划分考虑了任务之间的依赖关系,并有利于减少重调度次数。阐述了子集调度目标和约束条件,提出了融合模拟退火思想的粒子群调度算法。重调度进一步提高调度策略对资源动态行为的适应性,阐述了重调度触发条件。给出了移动网格关联任务调度策略的完整流程,并对提出的算法进行了复杂性分析和实验分析。实验结果表明了调度策略和算法的有效性。

关键词: 移动网格, 任务调度, 动态资源, DAG图, 重调度

Abstract:

Taking mobile grid as background, the problem of scheduling related tasks on dynamic resource environment was studied. During scheduling, not only dependencies between tasks, but also resources’ dynamic behavior such as joining, leaving and performance changes are considered. Dynamic scheduling policy was proposed, which includes task subset scheduling and rescheduling. Dynamic partition of subset mainly focuses on dependencies between tasks and helps reduce the number of rescheduling. Subset scheduling objective and constraints were described and particle swarm scheduling algorithm was put forward, which integrates the idea of simulated annealing. Rescheduling further improves the adaptability of scheduling policy to the dynamic behavior of resources. Rescheduling trigger conditions was explained. The complete process of related tasks scheduling in mobile grid was given, as well as complexity analysis and experimental analysis of the proposed algorithm. Experiment results demonstrate the effectiveness of scheduling policy.

Key words: mobile grid;task scheduling;dynamic resources;DAG graph;reschedule