# Heavy-traffic analysis of the $M^X/\text{semi-Markov}/1$ queue

## TL;DR

This paper investigates the heavy-traffic behavior of an $M^X$/semi-Markov/1$ queue with batch arrivals and variable first service times, showing the scaled queue length converges to an exponential distribution.

## Contribution

It introduces a generating function approach to analyze the heavy-traffic limit and identifies conditions for the independence of successive service times in the limit.

## Key findings

- Queue length converges to exponential distribution in heavy traffic
- First service time variability does not affect the limiting distribution
- Conditions for independence of successive service times are established

## Abstract

In this paper we analyze a single server queue with batch arrivals and semi-Markovian service times. We also include the feature that the first service of each busy period might have a different distribution than subsequent service times. Our generating function based approach allows us to determine the heavy traffic limit of the scaled queue-length distribution. It turns out that this distribution converges to an exponential distribution. Nonsurprisingly, the exceptional first service does not influence this limiting distribution. We identify a sufficient and necessary condition under which the dependence between successive service times disappears in the limit, which we illustrate in a numerical example.