multiple class memory constrained queueing networks
Most computer systems have a memory constraint: a limit on the number of requests that can actively compete for processing resources, imposed by finite memory resources. This characteristic violates the conditions required for queueing network performance models to be  separable,  i.e., amenable to efficient analysis by standard algorithms. Useful algorithms for analyzing models of memory constrained systems have been devised only for models with a single customer class. In this paper we consider the multiple class case. We introduce and evaluate an algorithm for analyzing multiple class queueing networks in which the classes have independent memory constraints. We extend this algorithm to situations in which several classes share a memory constraint. We sketch a generalization to situations in which a subsystem within an overall system model has a population constraint. Our algorithm is compatible with the extremely time- and space-efficient iterative approximate solution techniques for separable queueing networks. This level of efficiency is mandatory for modelling large systems.
memory constraint population constraint approximate solution technique computer system performance evaluation queueing network model