User Demand Aware Scheduling Algorithm for Data Intensive Tasks in Grid Environment
Computational grids use heterogeneous geographically distributed resources and solves large scale applications by sharing computational capacity. Effective utilization of grid resources requires efficient scheduling of jobs which identifies resource for the submitted jobs. Many researchers adopted several heuristic scheduling algorithms for efficient scheduling. But most of these heuristic algorithms do not provide user satisfaction. A new heuristic scheduling algorithm is proposed which considers user satisfaction. Also this algorithm is designed for jobs which require more data transfers. This uses the additional parameters namely user deadline and data transfer time for scheduling. The proposed algorithm is verified using GridSim simulation toolkit. The simulation results show that the proposed algorithm achieves reduced makespan and more user satisfaction when compared to the existing heuristic algorithms.