Comparing job allocation schemes where service demand is unknown

Abstract

In this paper a novel job allocation scheme in distributed systems (TAGS) is modelled using the Markovian process algebra PEPA. This scheme requires no prior knowledge of job size and has been shown to be more efficient than round robin and random allocation when the job size distribution is heavy tailed and the load is not high. In this paper the job size distribution is assumed to be of a phase-type and the queues are bounded. Numerical results are derived and compared with those derived from models employing random allocation and the shortest queue strategy. It is shown that TAGS can perform well for a range of performance metrics. Furthermore, an attempt is made to characterise those scenarios where TAGS is beneficial in terms of the coefficient of variation and load.