Task scheduling in Grid computing using Genetic Algorithm

Task scheduling is a key problem in Grid computing in order to benefit from the large computing capacity of such systems. The need of allocating a number of tasks to different resources for the efficient utilization of resources with minimal completion time and economic cost is the essential requirement in such systems. The problem is multi-objective in its general formation, with the objectives being the minimization of makespan and flowtime of the system along the economic cost. An optimal scheduling could be achieved minimizing the completion time and economic cost using the heuristic approach, which is chosen to be Genetic Algorithm. The ability of Genetic Algorithm to simultaneously search different regions of a solution space makes it possible to find a diverse set of solutions for difficult problems. Each individual is represented as possible solution. The solutions are the schedulers for efficiently allocating jobs to resources in a Grid system