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International Conference on Quantitative Evaluation of Systems

QEST 2018: Quantitative Evaluation of Systems pp 273–288Cite as

Biased Processor Sharing in Fork-Join Queues

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11024))

Abstract

We consider a fork-join system in which a fixed amount of computational resources has to be distributed among the K tasks forming the jobs. The queueing disciplines of the fork- and join- queues are First Come First Served. At each epoch, at most K tasks are in service while the others wait in the fork-queues. We propose an algorithm with a very simple implementation that allocates the computational resources in a way that aims at minimizing the join-queue lengths, and hence at reducing the expected job service time. We study its performance in saturation and under exponential service time and provide a methodology to derive the relevant performance indices. Explicit closed-form expressions for the expected response time and join-queue length are given for the cases of jobs consisting of two, three and four tasks.

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Authors and Affiliations

  1. DAIS, Università Ca’ Foscari, Venezia, Italy

    Andrea Marin, Sabina Rossi & Matteo Sottana

Authors
  1. Andrea Marin
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  2. Sabina Rossi
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  3. Matteo Sottana
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Corresponding author

Correspondence to Andrea Marin .

Editor information

Editors and Affiliations

  1. Macquarie University , Sydney, New South Wales, Australia

    Annabelle McIver

  2. University of Turin , Turin, Italy

    Andras Horvath

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Marin, A., Rossi, S., Sottana, M. (2018). Biased Processor Sharing in Fork-Join Queues. In: McIver, A., Horvath, A. (eds) Quantitative Evaluation of Systems. QEST 2018. Lecture Notes in Computer Science(), vol 11024. Springer, Cham. https://doi.org/10.1007/978-3-319-99154-2_17

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  • DOI: https://doi.org/10.1007/978-3-319-99154-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99153-5

  • Online ISBN: 978-3-319-99154-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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