Queue-length balance equations in multiclass multiserver queues and their generalizations

A classical result for the steady-state queue-length distribution of single-class queueing systems is the following: the distribution of the queue length just before an arrival epoch equals the distribution of the queue length just after a departure epoch. The constraint for this result to be valid is that arrivals, and also service completions, with probability one occur individually, i.e., not in batches. We show that it is easy to write down somewhat similar balance equations for {\em multidimensional} queue-length processes for a quite general network of multiclass multiserver queues. We formally derive those balance equations under a general framework. They are called distributional relationships, and are obtained for any external arrival process and state dependent routing as long as certain stationarity conditions are satisfied and external arrivals and service completions do not simultaneously occur. We demonstrate the use of these balance equations, in combination with PASTA, by (i) providing very simple derivations of some known results for polling systems, and (ii) obtaining new results for some queueing systems with priorities. We also extend the distributional relationships for a non-stationary framework

Simple bounds for queues fed by Markovian sources: a tool for performance evaluation

ATM traffic is complex but only simple statistical models are amenable to mathematical analysis. We discuss a class of queuing models which is wide enough to provide models which can reflect the features of real traffic, but which is simple enough to be analytically tractable, and review the bounds on the queue-length distribution that have been obtained. We use them to obtain bounds on QoS parameters and to give approximations to the effective bandwidth of such sources. We present some numerical techniques for calculating the bounds efficiently and describe an implementation of them in a computer package which can serve as a tool for qualitative investigations of performance in queuing systems

An MDP decomposition approach for traffic control at isolated signalized intersections

This article presents a novel approach for the dynamic control of a signalized intersection. At the intersection, there is a number of arrival flows of cars, each having a single queue (lane). The set of all flows is partitioned into disjoint combinations of nonconflicting flows that will receive green together. The dynamic control of the traffic lights is based on the numbers of cars waiting in the queues. The problem concerning when to switch (and which combination to serve next) is modeled as a Markovian decision process in discrete time. For large intersections (i.e., intersections with a large number of flows), the number of states becomes tremendously large, prohibiting straightforward optimization using value iteration or policy iteration. Starting from an optimal (or nearly optimal) fixed-cycle strategy, a one-step policy improvement is proposed that is easy to compute and is shown to give a close to optimal strategy for the dynamic proble