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The fork-join queue and related systems with synchronization constraints: stochastic ordering and computable bounds

Published online by Cambridge University Press:  01 July 2016

François Baccelli ,
Armand M. Makowski  and
Adam Shwartz
François Baccelli*
Affiliation:
INRIA
Armand M. Makowski*
Affiliation:
University of Maryland
Adam Shwartz*
Affiliation:
Technion–Israel Institute of Technology
*
∗ Postal address: INRIA—Centre de Sophia Antipolis, Avenue E. Hughes, 06565, Valbonne Cedex, France.
∗∗ Postal address: Electrical Engineering Department and Systems Research Center, University of Maryland, College Park, Maryland 20742, USA.
∗∗∗ Postal address: Electrical Engineering Department, Technion–Israel Institute of Technology, Haifa 32000, Israel.
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Abstract

A simple queueing system, known as the fork-join queue, is considered with basic performance measure defined as the delay between the fork and join dates. Simple lower and upper bounds are derived for some of the statistics of this quantity. They are obtained, in both transient and steady-state regimes, by stochastically comparing the original system to other queueing systems with a structure simpler than the original system, yet with identical stability characteristics. In steady-state, under renewal assumptions, the computation reduces to standard GI/GI/1 calculations and the bounds constitute a first sizing-up of system performance. These bounds can also be used to show that for homogeneous fork-join queue system under assumptions, the moments of the system response time grow logarithmically in the number of parallel processors provided the service time distribution has rational Laplace–Stieltjes transform. The bounding arguments combine ideas from the theory of stochastic ordering with the notion of associated random variables, and are of independent interest to study various other queueing systems with synchronization constraints. The paper is an abridged version of a more complete report on the matter [6].

Keywords

STOCHASTIC BOUNDSINCREASING CONVEX ORDERINGASSOCIATED RANDOM VARIABLES

Information

Type
Research Article
Information
Advances in Applied Probability , Volume 21 , Issue 3 , September 1989 , pp. 629 - 660
Copyright
Copyright © Applied Probability Trust 1989 

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Footnotes

The work of this author was supported partially through a grant from AT & T Bell Laboratories and partially through a grant from the Minta Martin Aeronautical Research Fund, College of Engineering, University of Maryland, College Park, MD 20742, USA.

The work of this author was supported partially through ONR Grant N00014-84-K-0614, partially through NSF Grant ECS-83–51836 and partially through a grant from AT & T Bell Laboratories.

The work of this author was supported through a grant from AT & T Bell Laboratories.

References

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