Efficient Scheduling in Computational Grid with an Improved Ant Colony Algorithm

Grid Computing is a form of distributed computing that involves coordinating and sharing computing, application, network resources across dynamic and geographically dispersed organizations. The primary issue associated with the efficient utilization of heterogeneous resources in a grid is grid scheduling. The main objective of Grid scheduling is to get the best optimal machine to each task, which makes scheduling a complex problem. The complexity of scheduling increases with the size of Grid and becomes difficult to solve effectively. Hence a new area of research, ‘Heuristic approach’ is developed to obtain optimal solution. In this paper, a new Ant Colony Optimization scheduling algorithm is proposed. Experiments are conducted with different data series and conditions. The experimental results reveal that the proposed algorithm produces better results when compared with the existing ant algorithm. The proposed scheduler proves that best suitable resource is allocated to each task with reduced makespan and execution time when compared with the existing algorithm.