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Stochastic comparisons for fork-join queues with exponential processing times

Part of:Special processes

Published online by Cambridge University Press:  14 July 2016

Esther Frostig and
Tapani Lehtonen
Esther Frostig*
Affiliation:
Haifa University
Tapani Lehtonen*
Affiliation:
Helsinki School of Economics
*
∗ Postal address: Department of Statistics, Haifa University, Haifa, Israel, 31905.
∗∗ Postal address: Helsinki School of Economics, Runebergink 14-16, 00100 Helsinki, Finland.
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Abstract

Consider a fork-join queue, where each job upon arrival splits into k tasks and each joins a separate queue that is attended by a single server. Service times are independent, exponentially distributed random variables. Server i works at rate , where μ is constant. We prove that the departure process becomes stochastically faster as the service rates become more homogeneous in the sense of stochastic majorization. Consequently, when all k servers work with equal rates the departure process is stochastically maximized.

Keywords

FORK-JOIN QUEUESSTOCHASTIC ORDERINGWEAK MAJORIZATION

MSC classification

Primary:60K25: Queueing theory

Information

Type
Research Article
Information
Journal of Applied Probability , Volume 34 , Issue 2 , June 1997, pp. 487 - 497
Copyright
Copyright © Applied Probability Trust 1997 

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References

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