22 research outputs found
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
Scaling limits for infinite-server systems in a random environment
This paper studies the effect of an overdispersed arrival process on the
performance of an infinite-server system. In our setup, a random environment is
modeled by drawing an arrival rate from a given distribution every
time units, yielding an i.i.d. sequence of arrival rates
. Applying a martingale central limit theorem, we
obtain a functional central limit theorem for the scaled queue length process.
We proceed to large deviations and derive the logarithmic asymptotics of the
queue length's tail probabilities. As it turns out, in a rapidly changing
environment (i.e., is small relative to ) the overdispersion
of the arrival process hardly affects system behavior, whereas in a slowly
changing random environment it is fundamentally different; this general finding
applies to both the central limit and the large deviations regime. We extend
our results to the setting where each arrival creates a job in multiple
infinite-server queues
Networks of Server Queues with Shot-Noise-Driven Arrival Intensities
We study infinite-server queues in which the arrival process is a Cox process
(or doubly stochastic Poisson process), of which the arrival rate is given by
shot noise. A shot-noise rate emerges as a natural model, if the arrival rate
tends to display sudden increases (or: shots) at random epochs, after which the
rate is inclined to revert to lower values. Exponential decay of the shot noise
is assumed, so that the queueing systems are amenable for analysis. In
particular, we perform transient analysis on the number of customers in the
queue jointly with the value of the driving shot-noise process. Additionally,
we derive heavy-traffic asymptotics for the number of customers in the system
by using a linear scaling of the shot intensity. First we focus on a one
dimensional setting in which there is a single infinite-server queue, which we
then extend to a network setting