par Sericola, Bruno;Remiche, Marie-Ange
Référence Methodology and Computing in Applied Probability, 13, 2, page (307-328)
Publication Publié, 2011-06
Article révisé par les pairs
Résumé : In this work, we expose a clear methodology to analyze maximum level and hitting probabilities in a Markov driven fluid queue for various initial condition scenarios and in both cases of infinite and finite buffers. Step by step we build up our argument that finally leads to matrix differential Riccati equations for which there exists a unique solution. The power of the methodology resides in the simple probabilistic argument used that permits to obtain analytic solutions of these differential equations. We illustrate our results by a comprehensive fluid model that we exactly solve. © 2009 Springer Science + Business Media, LLC.