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Article . 1990 . Peer-reviewed
License: Wiley Online Library User Agreement
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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
zbMATH Open
Article . 1990
Data sources: zbMATH Open
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Multiple finite source queueing model with dynamic priority scheduling

Authors: Tosirisuk, Phadhana; Chandra, Jeya;

Multiple finite source queueing model with dynamic priority scheduling

Abstract

AbstractThis article involves the study of a multiple finite source queueing model with a single server and dynamic, nonpreemptive priority service discipline. The input to the queue is comprised of customers from multiple finite sources. The time which the customers spend at the corresponding sources are exponentially distributed. The service times of the customers can follow exponential, Erlang, or hyperexponential probability density function, with the same mean regardless of the class. Using an extension of mean value analysis, a recursive algorithm is developed to obtain approximate values of the mean waiting time in queues for each priority class. The mean number of waiting customers and the server utilization of each priority class can be obtained using the result of this recursive algorithm and Little's formula. Numerical examples are presented to illustrate the methodology. The algorithm developed in this article is validated using simulation.

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Keywords

dynamic, recursive algorithm, Deterministic scheduling theory in operations research, nonpreemtive priority service discipline, Queueing theory (aspects of probability theory), mean waiting time, approximate values, multiple finite source queueing, single server, mean number of waiting customers, Queues and service in operations research, Performance evaluation, queueing, and scheduling in the context of computer systems

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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).
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!
6
Average
Average
Average
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