Optimized Resource Selection to Promote Grid Scheduling Using Hill Climbing Algorithm

Grid computing is gaining ground in academia and commerce moving from scientific-based applications to service oriented problem solving environments. Grid is a distributed large-scale computing infrastructure providing dependable, secure, transparent, pervasive, inexpensive, and coordinated resource sharing. Resource selection and use are necessary to enhance application performance. Grid task scheduling is a most important grid system technology being a NP complete problem to schedule tasks on appropriate grid nodes. This study uses hillclimbing heuristics for optimizing the scheduling. Simulations validate the proposed algorithm’s performance, and results are evaluated by Makespan. Makespan values of best solutions are recorded throughout optimization iterations and minimum time cost time for all tasks completed.