The analysis of a multiserver queue fed by a discrete autoregressive process of order 1

Bong Dae Choi, Bara Kim, Gang U. Hwang, Jae Kyoon Kim

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

A multiserver queue fed by a discrete autoregressive process of order 1 was analyzed. The stationary distributions of the system size and the waiting time in a multiserver queue was obtained by using matrix analytic methods and the theory of Markov regenerative processes. It was found that the distributions for the system size and the waiting time increase stochastically when either the decay rate of the autocorrelation function of the input traffics or the variance of a batch arriving in a slot increases.

Original languageEnglish
Pages (from-to)85-93
Number of pages9
JournalOperations Research Letters
Volume32
Issue number1
DOIs
Publication statusPublished - 2004 Jan 1

Fingerprint

Multi-server
Autoregressive Process
Autocorrelation
Waiting Time
Queue
Matrix Analytic Methods
Regenerative Process
Autocorrelation Function
Stationary Distribution
Decay Rate
Markov Process
Batch
Traffic
Autoregressive process
Waiting time
Matrix analytic methods
Decay
Stationary distribution
Markov process

Keywords

  • DAR(1)
  • Markov regenerative theory
  • Matrix analytic methods
  • Multiserver ATM multiplexer
  • Multiserver queue
  • Performance analysis
  • Teleconference traffic

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Discrete Mathematics and Combinatorics
  • Modelling and Simulation

Cite this

The analysis of a multiserver queue fed by a discrete autoregressive process of order 1. / Choi, Bong Dae; Kim, Bara; Hwang, Gang U.; Kim, Jae Kyoon.

In: Operations Research Letters, Vol. 32, No. 1, 01.01.2004, p. 85-93.

Research output: Contribution to journalArticle

Choi, Bong Dae ; Kim, Bara ; Hwang, Gang U. ; Kim, Jae Kyoon. / The analysis of a multiserver queue fed by a discrete autoregressive process of order 1. In: Operations Research Letters. 2004 ; Vol. 32, No. 1. pp. 85-93.
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