关键词: 计算密集；数据密集；作业调度；平均执行时间

Abstract:

Most of the existing grid job scheduling methods focus on either dataintensive jobs or computingintensive jobs.In the dynamic environment where every job has its deadline,we extend the traditional grid job scheduling methods to propose three new grid job scheduling methods:Eminmin,Ebest and Esufferage.The three methods are validated on the Grid model with clusters that are connected by the high speed network.Simulation results demonstrate that our proposed methods are better than Minmin.The comparison between the three methods and ASJS shows that,Eminmin reduces the waiting time and makespan,Esufferage reduces the waiting time and the makespan greatly with the sacrifice of some jobs,and Ebest gives the same performance in unfinished jobs but has a larger value in waiting time and makespan than ASJS. In general,Eminmin has a better performance than Minmin and ASJS.

Key words: computing-intensive;data-intensive;job scheduling;average makespan