AHSWDG: An Ant Based Heuristic Approach to Scheduling and Workload Distribution in Computational Grids

Abstract

Due to the advent of technologies and large resource intensive applications, a large scale distributed and heterogeneous system like grids have emerged as popular platforms. Grid Computing is a kind of distributed computing that involves the integrated and collaborative use of geographically-dispersed resources. Hence, reliable resource sharing is required to process the huge amount of computational jobs across system. So, effective approaches are required for scheduling the jobs and balance the load distribution among the available resources. In this paper, a heuristic approach using Ant Colony Optimization for balanced workload distribution is proposed. In this, ants represent the submitted jobs while the ant's pheromone trail represents the computational capacity of the grid resources. The computational capacity of the resource is updated whenever the job is allocated to or released from it. In nutshell, the overall objective of the proposed Ant Based Heuristic Approach to scheduling & workload distribution (AHSWDG) is to distribute workload equally among the available resources. This research compares the proposed AHSWDG approach with the Random approach on the basis of finish time of the jobs and the utilization of grid resources in the system.