BEYOND SIMULATED ANNEALING FOR GRID SCHEDULING

In Grid Environment the number of resources and tasks to be scheduled is usually variable and dynamic in nature. This characteristic emphasizes the scheduling approach as a complex optimization problem. Scheduling is a key issue which must be solved in grid computing study and a better scheduling scheme can greatly improve the efficiency.The objective of this paper is to explore and investigate Simulated Annealing with limited iterations to promote compute intensive grid applications to maximize the Job Completion Ratio based on the comprehensive understanding of the challenges and the state of the art of current research. Experimental results demonstrate the effectiveness and robustness of the proposed algorithm. Further the comparative evaluation with other scheduling algorithms such as First Come First Serve (FCFS), Earliest Deadline First (EDF) is plotted.