A Reliable and Hybrid Scheduling Algorithm based on Cost and Time Balancing for Computational Grid

Abstract

Grid computing system is different from conventional distributed computing systems by its focus on large-scale resource sharing and open architecture for services. tasks scheduling is a crucial problem in Grid environments. Many of grid scheduling systems optimize completion time and cost separately. In this paper, for solving the scheduling problem of computational grid system used a combination of genetic algorithm and Gravitational Emulation Local Search (GELS) algorithm and a hybrid scheduling algorithm (RHGGSA) which considers both the completion time and execution cost is introduced. The algorithm applies a weighted objective function that takes into account both the completion time and execution cost of the tasks. To show the out performance of the proposed task scheduling algorithm, the obtained results are compared with those of Min-Min, GA and GA-VNS. Simulation results and comparisons based on a set of problem demonstrated the efficiency and effectiveness of our proposed approach.