Two-parameter Sample Path Large Deviations for Infinite Server Queues
classification
🧮 math.PR
keywords
lambdaarrivaldeviationsinfinitelargelikelyobtainpath
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Let $Q_{\lambda}(t,y) $ be the number of people present at time $t$ with $y$ units of remaining service time in an infinite server system with arrival rate equal to $\lambda>0$. In the presence of a non-lattice renewal arrival process and assuming that the service times have a continuous distribution, we obtain a large deviations principle for $Q_{\lambda}(\cdot) /\lambda$ under the topology of uniform convergence on $[0,T]\times\lbrack0,\infty)$. We illustrate our results by obtaining the most likely path, represented as a surface, to ruin in life insurance portfolios, and also we obtain the most likely surfaces to overflow in the setting of loss queues.
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