Novel Adaptive Job Scheduling Algorithm on Heterogeneous Grid Resources

Abstract

Grid provides an infrastructure for sharing geographically distributed heterogeneous resources to process many applications and mainly used for solving scientific problems that requires more computation time. Problem statement: Grid is a dynamic environment, where the resources may join or leave the environment at any time and the jobs also arrives at different intervals of time. To meet the demands and requirements of the dynamic environment, to maximize the resource utilization and to minimize the makespan an effective grid scheduling technique is needed. Approach: We propose grid architecture as a collection of clusters with multiple worker nodes in each cluster. We propose a new scheduling algorithm Novel Adaptive Decentralized Job Scheduling Algorithm (NADJSA) that applies both Divisible Load Theory (DLT) and Least Cost Method (LCM) and also considers the user demands. Results: The proposed Novel Adaptive Decentralized Job Scheduling Algorithm is compared with the Decentralized Hybrid Job Scheduling Algorithm. Conclusion: The proposed Novel Adaptive Decentralized Job Scheduling Algorithm minimizes the makespan, improves the resource utilization and satisfies the user demands and well suits for the grid environment.