State of a network when one node overloads

We delve into a couple of topics in the theory of Markov chains and stochastic networks. The properties of a stable Markov chain X = (Xi,X) will be investigated when X\ tends to infinity. We derive the distribution of X when X\ passes a threshold for the first time as the threshold tends to infinity. Moreover, the exact asymptotics of the mean time until X\ reaches the threshold is given. In addition, we present a new approach to determine the exact asymptotics of the X's steady state. The results are applied to an open modified Jackson network with two partially coupled processors. Finally, a ratio limit property is established for a Markovian kernel which has unbounded jumps.

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