Rare event simulation for a slotted time M/G/s model

This paper develops a rare-event simulation algorithm for a discrete-time version of the M/G/s loss system and a related Markov-modulated variant of the same loss model. The algorithm is shown to be efficient in the many-server asymptotic regime in which the number of servers and the arrival rate increase to infinity in fixed proportion. A key idea is to study the system as a measure-valued Markov chain and to steer the system to the rare event through a randomization of the time horizon over which the rare event is induced.