Scheduling in Computational Grid Using Improved Ant Colony Optimization Algorithm

Abstract

Grid Computing is the combination of computer resources from multiple administrative domains applied to achieve a goal, it is used to solve scientific, technical or business problem that requires a great number of processing cycles and needs large amounts of data. Grid computing is now being used in many applications that are beyond distribution and sharing resources. One primary issue associated with the efficient utilization of heterogeneous resources in a grid is grid scheduling. The distributed resources are useful only if the grid resources are scheduled. Grid scheduling involves mapping of tasks to resources which are available in grid environment. The main objective of the scheduling is to get the best optimal machine to each task, which makes scheduling a complex problem. Hence a new area of research is developed to obtain optimal solution. Using optimal scheduler results in high performance computing, where as poor schedulers provide contrast results. The scheduling in grid environment has to satisfy a number of constraints of different problems. Heuristic approach is mainly focusing area to solve the grid scheduling problem. In this paper, Efficient Ant colony optimization scheduling algorithm is proposed. The proposed scheduler allocates the best suitable resource to each task with minimal execution time. The experimental results are compared which shows that the algorithm produces better results when compared with the existing ant algorithm.