The morphing of fluid queues into Markov-modulated Brownian motion

Abstract

Ramaswami showed recently that standard Brownian motion arises as the limit of a family of Markov-modulated linear fluid processes.We pursue this analysis with a fluid approximation for Markov-modulated Brownian motion. We follow a Markov-renewal approach and we prove that the stationary distribution of a Markov-modulated Brownian motion reflected at zero is the limit from the well-analyzed stationary distribution of approximating linear fluid processes. Thus, we provide a new approach for obtaining the stationary distribution of a reflected MMBM without time-reversal or solving partial differential equations. Our results open the way to the analysis of more complex Markov-modulated processes. Key matrices in the limiting stationary distribution are shown to be solutions of a matrix-quadratic equation, and we describe how this equation can be efficiently solved.

Keywords

• Markov-modulated linear fluid models
• Markov-modulated Brownian motion
• weak convergence
• stationary distribution
• computational methods