Description

In Grid System independent job scheduling is manifold beneficial account of happening of scheduling. In grid system independent user complied jobs or applications to grid resources. The scheduler desire to estimate adequate and excellent formulation of jobs to the available resources in grid environment. The formulation of jobs to the available resources is estimated beneath tremendous amplitude of heterogeneity of resources, the abundant degree and aggressive of the system. Due to the above issues, the heuristic and meta-heuristic which are most possible methods are used for scheduling in grids in order to convey high quality solutions in reasonable computing time. Hierarchic Genetic Strategy (HGS) is one of such meta-heuristic approach which is different from Genetic Algorithms (GAs) by its simultaneous search of the solution space. The Hierarchic Genetic Strategy is used for independent job scheduling in aggressive grid environment. The HGS scheduling method is improved in order to minimize the makespan and flow time which outperforms the GA-based schedulers but the time taken to complete the process is too large. For this purpose we propose Bacterial Forging Optimization algorithm, which reduce the cost to complete the process submitted by client. By using this algorithm the scheduler will schedule the job to one of the available resources in which the job can be completed with minimal cost.