An Enhanced Ant Algorithm for Grid Scheduling Problem

Grid computing is a form of distributed computing that coordinates and shares computation, application, data storage, or network resources across dynamic and geographically dispersed organizations. One primary issue associated with the efficient utilization of heterogeneous resources in a grid is grid scheduling. Grid Scheduling is a critical design issue of grid computing. It is a challenge because the capability and availability of resources vary dynamically. The complexity of scheduling problem increases with the size of the grid and becomes difficult to solve effectively. Hence a new area of research is developed to design optimal methods. It focuses on new heuristic techniques that provide an optimal or near optimal solution for large grids. In this paper, Ant Colony Optimization based grid scheduling algorithm for grid computing is proposed. The proposed scheduler allocates an application to a host from a pool of available hosts and applications by selecting the best match. In the evaluation study a number of intensive experiments with various simulation settings have been conducted. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness with three previously proposed algorithms.