Central limit theorem for a many-server queue with random service rates

TL;DR

This paper establishes a central limit theorem for a many-server queue with random service rates, showing convergence to a diffusion process with a random drift under heavy traffic conditions.

Contribution

It introduces a novel CLT for queues with random service rates in the Halfin-Whitt regime, accounting for different routing schemes and random environments.

Findings

Queue length process converges to a diffusion with random drift.

Routing scheme affects the law of the limiting diffusion.

Results extend to nonrandom environments.

Abstract

Given a random variable $N$ with values in ${\mathbb{N}}$, and $N$ i.i.d. positive random variables $\{\mu_k\}$, we consider a queue with renewal arrivals and $N$ exponential servers, where server $k$ serves at rate $\mu_k$, under two work conserving routing schemes. In the first, the service rates $\{\mu_k\}$ need not be known to the router, and each customer to arrive at a time when some servers are idle is routed to the server that has been idle for the longest time (or otherwise it is queued). In the second, the service rates are known to the router, and a customer that arrives to find idle servers is routed to the one whose service rate is greatest. In the many-server heavy traffic regime of Halfin and Whitt, the process that represents the number of customers in the system is shown to converge to a one-dimensional diffusion with a random drift coefficient, where the law of the drift depends on the routing scheme. A related result is also provided for nonrandom environments.