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。
Taking mobile grid as background, the problem of scheduling related tasks on dynamic re- source environment was studied. During scheduling, not only dependencies between tasks, but also re- sources 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 par- tition of subset mainly focuses on dependencies between tasks and helps reduce the number of re-schedu- ling. 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 demon- strate the effectiveness of scheduling policy.
出处
《计算机工程与科学》
CSCD
北大核心
2013年第6期57-64,共8页
Computer Engineering & Science
基金
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)
关键词
移动网格
任务调度
动态资源
DAG图
重调度
mobile grid
task scheduling
dynamic resources
DAG graph
re-schedule
