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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Queueing Systemsarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Queueing Systems
Article . 1986 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 1986
Data sources: zbMATH Open
DBLP
Article . 1986
Data sources: DBLP
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Queueing systems with vacations ? A survey

Queueing systems with vacations - a survey
Authors: Bharat T. Doshi;

Queueing systems with vacations ? A survey

Abstract

In this excellent review article single-server queueing models with vacations are discussed. The author aims at (and succeeds in) providing a methodological overview with the objective to illustrate how the seemingly diverse mix of problems where vacation models arise in some form is closely related in structure and can be understood in a common framework. After describing a large number of problems which can be addressed by vacation-type models, the author selects two models for detailed treatment. For these models, which are generalizations of the standard GI/G/1 queue, a variety of techniques used (to obtain decomposition results, in particular) and the scope and limitations of each is discussed. It is then shown how understanding the behaviour of these two models helps to analyse other vacation models using similar techniques. Some applications and a discussion of some unsolved problems conclude the paper.

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Keywords

decomposition results, review article single-server queueing models, Queues and service in operations research, vacation models, Queueing theory (aspects of probability theory)

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    886
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 0.01%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
886
Top 0.1%
Top 0.01%
Top 10%
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