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Efficient important sampling for a feed-forward network

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Stochastic Processes in Communication Sciences

We consider a feedforward network with a single server station serving two classes of jobs, where one class of jobs has preemptive priority over the other. The rare event of interest is total population overflow. We rigorously identify the large deviation rate of the rare event probabilities and construct piecewise constant, asymptotically optimal importance sampling schemes.

This talk is part of the Isaac Newton Institute Seminar Series series.

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