Approximating Systems Fed by Poisson Processes with Rapidly Changing Arrival Rates

Publication Date: July 18, 2018

Zeyu Zheng, Harsha Honnappa, Peter W. Glynn. “Approximating Systems Fed by Poisson Processes with Rapidly Changing Arrival Rates“. Operations Research

Abstract: This paper introduces a new asymptotic regime for simplifying stochastic models having non-stationary effects, such as those that arise in the presence of time-of-day effects. This regime describes an operating environment within which the arrival process to a service system has an arrival intensity that is fluctuating rapidly. We show that such a service system is well approximated by the corresponding model in which the arrival process is Poisson with a constant arrival rate. In addition to the basic weak convergence theorem, we also establish a first order correction for the distribution of the cumulative number of arrivals over [0,t], as well as the number-in-system process for an infinite-server queue fed by an arrival process having a rapidly changing arrival rate. This new asymptotic regime provides a second regime within which non-stationary stochastic models can be reasonably approximated by a process with stationary dynamics, thereby complementing the previously studied setting within which rates vary slowly in time.