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 effectively balanced 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 that existed physically in various LANs. The proposed load balancing policy reflects the heterogeneity of the computational resources in deciding load distributions decisions. It balances the system's load according to the computing nodes capacity. Therefore, system's overall job response time and utilization are minimized and maximized respectively. An analytical model is developed to gauge 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 results revealed that the performance of the suggested load balancing strategy outperforms that of the random and uniform distribution load balancing strategies 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% within the studied system parameters values.