Modelling And Analyses Of Dynamic Load-Balancing Policies By State Aggregation

Abstract

Exact performance analysis of dynamic load-balancing policies for distributed systems is known to be very difficult owing to the facts that the state space is multidimensional and that load-balancing decisions are state dependent. In this paper, a state-aggregation method is proposed to model and analyze dynamic load-balancing policies. Those states with the same number of jobs are aggregated into a single state. The number of jobs in the system is modelled by a birth-death Markov process. The state transition rates are estimated by an iterative procedure. The procedure is developed according to the operation of the load-balancing policy. The proposed method is used to analyze the performance of a dynamic load-balancing policy, namely, symmetric policy. Extensive simulations are performed to study the accuracy of the method. This method provides accurate performance estimates for the symmetric policy for systems of various sizes when the mean job transfer delay is small compared to the average job service time.