A performance comparison of dynamic vs. static load balancing policies in a mainframe-personal computer network model

Abstract

Distributed computer systems can share job processing in the event of overloads. Load balancing involves the distribution of jobs throughout a networked computer system, thus increasing throughput without having to obtain additional or faster computer hardware. Load balancing policies may be either static or dynamic. Static load balancing policies are generally based on the information about the average behavior of system; transfer decisions are independent of the actual current system state. Dynamic policies, on the other hand, react to the actual current system state in making transfer decisions. This makes dynamic policies necessarily more complex than static ones, and truly optimal dynamic policies are known only for special systems. This study focuses on performance comparison between static and dynamic load balancing policies in a distributed computer system where truly optimal solutions of both dynamic and static policies have been characterized. The system consists of two types of service facilities, a mainframe node and an unlimited number of personal computer nodes. The results suggest that, in the model examined, the dynamic policy outperforms the static one in the mean response time, at most about 30 percent and for the range of parameter values such that the arrival rate is near the processing rate of the mainframe.