An Adaptive Job Scheduling with efficient Fault Tolerance Strategy in Computational Grid

Abstract—Grid computing is an emerging technology which has the potential to solve large scale scientific problems in an integrated heterogeneous environment. However, in the grid computing environment there are certain aspects which reduces efficiency of the system. Scheduling the jobs to the best suited resources, achieving the load balancing and fault tolerance are the key aspects to improve the efficiency and to exploit the capabilities of emergent computational systems. Because of dynamic and distributed nature of the grid, the traditional methodologies of scheduling are inefficient for the effective utilization of the available resources. In this paper, an efficient adaptive job scheduling algorithm is proposed to improve the efficiency of the grid system for a large number of tasks. Moreover, the proposed adaptive job scheduling in addition to the fault tolerance strategy with check pointing approach shows the improvement in performance of the overall computation time even in worst scenario under the heterogeneous grid environment. The simulation results illustrates that the proposed strategy effectively schedules the grid jobs with more than 10 % increase in overall performance thus resulting in minimization of overall execution time