Analysis of Dynamic Load Balancing Strategies Using a Combination of Stochastic Petri Nets and Queueing Networks

This paper is concerned with the analytical evaluation of two well known dynamic load balancing strategies, namely, shortest queue routing (SQR) and shortest expected delay routing (SEDR). We overcome the limitations of existing analysis methodologies, using a well known hybrid performance model that combines generalized stochastic Petri nets and product form queueing networks. Our methodology is applicable to both open queueing network and closed queueing network models of load balancing in distributed computing systems. The results show that for homogeneous distributed systems, SQR outperforms all other policies. For heterogeneous systems, SEDR surprisingly performs worse than SQR at low levels of imbalance in loads. However, with increase in imbalance in load, SEDR expeetedly performs better than SQR. 1 I n t r o d u c t i o n The problem of balancing the load over the entire system so that its overall performance is optimized is an important research problem [20] in Distributed Computing Systems(DCSs). Routing an arriving job to the processor with the shortest queue length(SQR, shortest queue routing) [17] in the case of homogeneous systems and routing to the processor with the shortest expected delay (SEDR, shortest expected delay routing) [4] in the case of heterogeneous systems have been found to be close to optimal heuristic load balancing strategies. Analysis of the performance of SQR and SEDR policies through simulation will be computationally expensive. It has been reported by Nelson and Philips