Rapid, efficient analysis of the lambda (n)/C sub k/r/N queue, with application to decomposition of closed queuing networks

A paper exploits advances in computational linear algebra and computing power to solve for the stationary probability vector of the related continuous time Markov chain (CTMC) of a lambda (n)/C sub k/r/N queue. The insights gained from studying the transition rate matrix of this chain are used to de...

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Bibliographic Details
Published inComputers & operations research Vol. 25; no. 7,8; p. 543
Main Authors Willits, C J, Dietz, D C
Format Journal Article
LanguageEnglish
Published New York Pergamon Press Inc 01.07.1998
Subjects
Linear algebra
Markov analysis
Operations research
Queuing
Studies
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Summary:A paper exploits advances in computational linear algebra and computing power to solve for the stationary probability vector of the related continuous time Markov chain (CTMC) of a lambda (n)/C sub k/r/N queue. The insights gained from studying the transition rate matrix of this chain are used to develop a list of candidate solution methods, each of which is used to calculate stationary probabilities for a set of 46 representative large-dimension problems. Based on this computational experience, a preferred solution approach for this type of CTMC is proposed. The effectiveness of the solution approach is demonstrated by using Marie's method to decompose 4 queuing networks containing stations with multiple k-phase Coaxian servers.
ISSN:0305-0548
0305-0548