Sharp results on convergence rates for the distribution of GI/M/1/K queues as K tends to infinity

Bong Dae Choi, Bara Kim

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In this paper, we investigate how fast the stationary distribution π(K) of an embedded Markov chain (time-stationary distribution q(K)) of the GI/M/1/K queue converges to the stationary distribution π of the embedded Markov chain (time-stationary distribution q) of the GI/M/1 queue as K tends to infinity. Simonot (1997) proved certain equalities. We obtain sharper results than these by finding limit values limK → ∞ σ−K∼∼π(K) − π∼∼ and limK→∞σ−K∼∼q(K) − q∼∼ explicitly.

Original languageEnglish
Pages (from-to)1010-1019
Number of pages10
JournalJournal of Applied Probability
Volume37
Issue number4
DOIs
Publication statusPublished - 2000 Jan 1

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Stationary Distribution
Queue
Convergence Rate
Infinity
Tend
Embedded Markov Chain
Equality
Converge
Stationary distribution
Convergence rate
Markov chain

Keywords

  • Convergence rate
  • Dual sequence
  • GI/M/1/K queue
  • Stationary distribution
  • Stationary measure

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Statistics, Probability and Uncertainty

Cite this

Sharp results on convergence rates for the distribution of GI/M/1/K queues as K tends to infinity. / Choi, Bong Dae; Kim, Bara.

In: Journal of Applied Probability, Vol. 37, No. 4, 01.01.2000, p. 1010-1019.

Research output: Contribution to journalArticle

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