An analytic finite capacity queueing network model capturing blocking, congestion and spillbacks

Analytic queueing network models often assume infinite capacity for all queues. For real systems this infinite capacity assumption does not hold, but is often maintained due to the difficulty of grasping the between-queue correlation structure present in finite capacity networks. This correlation structure helps explain bottleneck effects and spillbacks, the latter being of special interest in networks containing loops because they are a source of potential deadlock. We present an analytic queueing network model which acknowledges the finite capacity of the different queues. By explicitly modeling the blocking phase the model yields a description of the congestion effects. The model is adapted for multiple server finite capacity queueing networks with an arbitrary topology and blocking-after-service. A decomposition method allowing the evaluation of the model is described. The method is validated, by comparison to both pre-existing methods and simulation results. A real application to the study of patient flow in a network of operative and post-operative units of the Geneva University Hospital is also presented.