Performance analysis of Gang scheduling in a Grid

Gang scheduling combines time-sharing with space-sharing to ensure a short response time for interactive tasks and high overall system throughput. It has been widely studied in different areas including the Grid. Gang scheduling tries to assign the task belonging to one job to different Grid nodes. During the tasks assignment, there are three targets as follows: (1) to keep the Grid in higher resource utilization, (2) to keep the jobs in a low average waiting time and executing time, and, (3) to keep the system in fairness between jobs. In order to meet these targets, we propose a new model according to the waiting time of the jobs. Then we propose a new scheduling method ZERO–ONE scheduling with multiple targets (ZEROONEMT) to solve the Gang scheduling in the Grid. We have conducted extensive evaluations to compare our method with the existing methods based on a simulation environment and a real log from a Grid. In the experiments, in order to justify our method, different metrics, including adapted first come first served and largest job first served, are selected to test the performance of our methods. Experimental results illustrate that our proposed ZEROONEMT reduces the values in the average waiting time, the average response time, and the standard deviation of waiting time of all the jobs.