• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (08): 1423-1429.

• 论文 •     Next Articles

Three grid job scheduling methods heuristics
for data-intensive and computing-intensive jobs            

HAO Yongsheng 1,LU Junwen2,LIU Guanfeng3,WEN Na4   

  1. (1.Network Center,Nanjing University of Information Science & Technology,Nanjing 210044;2.Xiamen University of Technology,Xiamen 361024;
    3.Soochow Advanced Data Analytics Lab,Soochow University,Suzhou 215006;
    4.College of Atmospherics Science,Nanjing University of Information Science & Technology,Nanjing 210044,China)
  • Received:2013-03-20 Revised:2013-05-20 Online:2014-08-25 Published:2014-08-25

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