Rational Interpolation for Rare Event Probabilities
We propose to use rational interpolants to tackle some computationally complex performance analysis problems such as rare-event probabilities in stochastic networks. Our main example is the computation of the cell loss probabilities in ATM multiplexers. The basic idea is to use the values of the performance function when the system size is small, together with the asymptotic behaviour when the size is very large, to obtain a rational interpolant which can be used for medium or large systems. This approach involves the asymptotic analysis of the rare-event probability as a function of the system size, the convergence analysis of rational interpolants on the positive real line, and the quasi-Monte Carlo analysis of discrete event simulation.
KeywordsImportance Sampling Loss Probability Interpolation Point Discrete Time Markov Chain Rational Interpolation
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