Abstract

In this paper we study monotonicity results for optimal policies of various queueing and resource sharing models. The standard approach is to propagate, for each specific model, certain properties of the dynamic programming value function. By concentrating on the events and the properties instead of on the value function we propose a unified treatment of monotonicity results for Markovian models. This is illustrated with one and two-dimensional models. 1 Introduction Monotonicity results for optimal policies for queuing models are usually derived in the following way. After having formulated the value function of a particular model, it is shown inductively that this value function satisfies certain properties, from which the results are derived. The first to apply this approach, to an admission control problem for a single queue, was Lippman [11]. He proved that the dynamic programming (dp) value function of his specific model is convex, from which it follows that the optimal pol...

Citations

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