A Load Balancing Policy for Heterogeneous Computational Grids

Computational grids have the potential computing power for solving large-scale scientific computing applications. To improve the global throughput of these applications, workload has to be evenly distributed among the available computational resources in the grid environment. This paper addresses the problem of scheduling and load balancing in heterogeneous computational grids. We proposed a two-level load balancing policy for the multi-cluster grid environment where computational resources are dispersed in different administrative domains or clusters which are located in different local area networks. The proposed load balancing policy takes into account the heterogeneity of the computational resources. It distributes the system workload based on the processing elements capacity which leads to minimize the overall job mean response time and maximize the system utilization and throughput at the steady state. An analytical model is developed to evaluate the performance of the proposed load balancing policy. The results obtained analytically are validated by simulating the model using Arena simulation package. The results show that the overall mean job response time obtained by simulation is very close to that obtained analytically. Also, the simulation results show that the performance of the proposed load balancing policy outperforms that of the random and uniform distribution load balancing policies in terms of mean job response time. The improvement ratio increases as the system workload increases and the maximum improvement ratio obtained is about 72% in the range of system parameter values examined. Keywords-grid computing; resource management; load balancing; performance evaluation; queuing theory; simulation models.