Approximations for time-dependent distributions in Markovian fluid models

In this paper we study the distribution of the level at time $θ$ of Markovian fluid queues and Markovian continuous time random walks, the maximum (and minimum) level over $[0,θ]$, and their joint distributions. We approximate $θ$ by a random variable $T$ with Erlang distribution and we use an alternative way, with respect to the usual Laplace transform approach, to compute the distributions. We present probabilistic interpretation of the equations and provide a numerical illustration.

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