Optimal Resource Allocation in Grid using Hybrid Efficient Genetic Algorithm (ORAG using HEGA)

Grid computing plays the major role to solve very complex and computational problems in Scientific as well as in engineering fields where Resource management and Job scheduling plays crucial role. Most of the scheduling algorithms in Grid environment are based on FCFS with priority which is not suitable to give most optimal resource selection/job scheduling. We converted job scheduling problem in Grids into an optimization problem and implemented the job scheduler based on Hybrid Efficient Genetic Algorithm (HEGA). In this paper we presented HEGA based schedulers for efficiently allocating jobs into optimal resources in Grid systems and HEGA used to select an optimal or suboptimal scheduling of the jobs. These preliminary test results show, how the solution founded maximize the total machine throughput by considering not only the single job request, but all the job requests during the scheduling process. The proposed HEGA based grid scheduler utilizes the Elitism with permutation property to minimize the overall execution time. Our HEGA has been developed to dynamically schedule the heterogeneous tasks on to heterogeneous processors in Grid Environment and simulation results shows that proposed algorithm minimize the makespan and flowtime and maximize the overall throughput of the system.