4 research outputs found
Rare-event analysis of mixed Poisson random variables, and applications in staffing
A common assumption when modeling queuing systems is that arrivals behave
like a Poisson process with constant parameter. In practice, however, call
arrivals are often observed to be significantly overdispersed. This motivates
that in this paper we consider a mixed Poisson arrival process with arrival
rates that are resampled every time units, where and a
scaling parameter. In the first part of the paper we analyse the asymptotic
tail distribution of this doubly stochastic arrival process. That is, for large
and i.i.d. arrival rates , we focus on the evaluation of
, the probability that the scaled number of arrivals exceeds .
Relying on elementary techniques, we derive the exact asymptotics of :
For we identify (in closed-form) a function
such that tends to as .
For and we find a partial
solution in terms of an asymptotic lower bound. For the special case that the
s are gamma distributed, we establish the exact asymptotics across all . In addition, we set up an asymptotically efficient importance sampling
procedure that produces reliable estimates at low computational cost. The
second part of the paper considers an infinite-server queue assumed to be fed
by such a mixed Poisson arrival process. Applying a scaling similar to the one
in the definition of , we focus on the asymptotics of the probability
that the number of clients in the system exceeds . The resulting
approximations can be useful in the context of staffing. Our numerical
experiments show that, astoundingly, the required staffing level can actually
decrease when service times are more variable
Exact asymptotics in an infinite-server system with overdispersed input
This short communication considers an infinite-server system with
overdispersed input. The objective is to identify the exact tail asymptotics of
the number of customers present at a given point in time under a specific
scaling of the model (which involves both the arrival rate and time). The
proofs rely on a change-of-measure approach. The results obtained are
illustrated by a series of examples.Comment: Short communicatio