Tail behavior of the queue size and waiting time in a queue with discrete autoregressive arrivals

Bara Kim, Khosrow Sohraby

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Autoregressive arrival models are described by a few parameters and provide a simple means to obtain analytical models for matching the first- and second-order statistics of measured data. We consider a discrete-time queueing system where the service time of a customer occupies one slot and the arrival process is governed by a discrete autoregressive process of order 1 (a DAR(1) process) which is characterized by an arbitrary stationary batch size distribution and a correlation coefficient. The tail behaviors of the queue length and the waiting time distributions are examined. In particular, it is shown that, unlike in the classical queueing models with Markovian arrival processes, the correlation in the DAR(1) model results in nongeometric tail behavior of the queue length (and the waiting time) if the stationary distribution of the DAR(1) process has infinite support. A complete characterization of the geometric tail behavior of the queue length (and the waiting time) is presented, showing the impact of the stationary distribution and the correlation coefficient when the stationary distribution of the DAR(1) process has finite support. It is also shown that the stationary distribution of the queue length (and the waiting time) has a tail of regular variation with index -β - 1, by finding an explicit expression for the tail asymptotics when the stationary distribution of the DAR(1) process has a tail of regular variation with index -β.

Original languageEnglish
Pages (from-to)1116-1131
Number of pages16
JournalAdvances in Applied Probability
Volume38
Issue number4
DOIs
Publication statusPublished - 2006 Dec

Keywords

  • Discrete autoregressive process
  • Geometric tail distribution
  • Queue
  • Regular variation

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics

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