Job Scheduling in Grids with QoS Satisfaction Using Ant Colony Optimization (ACO)

Grid computing, a next leap in communication technology, a new trend in distributed computing systems, enables utilization of idle resources existing worldwide, to solve data intensive and computational intensive problems. These heterogeneous resources are shared from multiple administrative domains. The problem is divided into independent jobs and the jobs are executed by the resources available in grid. Scheduling these tasks to various resources in a grid is a very important problem and it is NP Complete. Hence we need a good job scheduling strategy to utilize the grids effectively such that overall completion time (makespan) is minimized. In literature, many heuristic scheduling approaches are available that give near optimal solution. In this paper we propose a weighted QoS (Quality of Service) factor enabled ant colony algorithm for scheduling independent jobs on heterogeneous grid resources. The main contribution of our work is to minimize the makespan (overall completion time) with QoS satisfaction and the results are compared with max-min and min-min algorithm.