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Majorization and Stochastic Comparison Techniques for Scheduling of Parallel Systems

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Quantitative Methods in Parallel Systems

Part of the book series: Esprit Basic Research Series ((ESPRIT BASIC))

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Summary

Stochastic scheduling of parallel systems is a recent research area in computer science as well as in operations research. The problem under consideration in this chapter is the scheduling of parallel computations which are modeled by task graphs in multiprocessor systems. The particularity of this study is that task running times are assumed to be random variables, instead of known constants as in the literature of deterministic scheduling. Our goal here is to illustrate one of the most successful approaches, based on sample path analysis and stochastic comparison techniques, for solving such scheduling problems. Both monoprogrammed and multiprogrammed parallel systems are analyzed. New results are presented for these models.

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Author information

Authors and Affiliations

  1. INRIA Sophia Antipolis, France

    Z. Liu

Authors
  1. Z. Liu
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Editor information

Editors and Affiliations

  1. INRIA Institut National de Recherche en Informatique et en Automatique 2004, route des Lucioles, F-06561, Valbonne Cedex, France

    François Baccelli  & Alain Jean-Marie  & 

  2. Department of Computing Science, University of Newcastle, Newcastle upon Tyne, NE1 7RU, UK

    Isi Mitrani

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© 1995 ECSC-EC-EAEC, Brussels-Luxembourg

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Liu, Z. (1995). Majorization and Stochastic Comparison Techniques for Scheduling of Parallel Systems. In: Baccelli, F., Jean-Marie, A., Mitrani, I. (eds) Quantitative Methods in Parallel Systems. Esprit Basic Research Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79917-4_14

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  • DOI: https://doi.org/10.1007/978-3-642-79917-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-79919-8

  • Online ISBN: 978-3-642-79917-4

  • eBook Packages: Springer Book Archive

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