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International Parallel Processing Symposium

IPPS 1998: Parallel and Distributed Processing pp 279–287Cite as

An evolutionary approach to multiprocessor scheduling of dependent tasks

  • Workshop on Biologically Inspired Solutions to Parallel Processing Problems Albert Y. Zomaya, The University of Western Australia Fikret Ercal, University of Missouri-Rolla Stephan Olariu, Old Dominion University
  • Conference paper
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1388))

Abstract

The scheduling of application tasks is a problem that occurs in all multiprocessor systems. This problem becomes even more complicated if the tasks are not independent but are interrelated by mutual exclusion and precedence constraints.

This paper presents an approach for pre-runtime scheduling of periodic tasks on multiple processors for a real-time system that must meet hard deadlines. The tasks can be related to each other by mutual exclusion and precedence forming an acyclic graph. The proposed scheduler is based on Genetic Algorithms, which relieves the user from knowing how to construct a solution. Consequently, the paper focuses on the problem encoding, i.e., the representation of the problem by genes and chromosomes, and the derivation of an appropriate fitness function. The main benefit of the approach is that it is scalable to any number of processors and can easily be extended to incorporate further requirements.

This work was in part supported by HP Labs, Palo Alto, California.

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Authors and Affiliations

  1. Vienna University of Technology, Treitlstr. 3/182-1, A-1040, Vienna, Austria

    Roman Nossal

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  1. Roman Nossal
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José Rolim

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© 1998 Springer-Verlag Berlin Heidelberg

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Nossal, R. (1998). An evolutionary approach to multiprocessor scheduling of dependent tasks. In: Rolim, J. (eds) Parallel and Distributed Processing. IPPS 1998. Lecture Notes in Computer Science, vol 1388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64359-1_698

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  • DOI: https://doi.org/10.1007/3-540-64359-1_698

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64359-3

  • Online ISBN: 978-3-540-69756-5

  • eBook Packages: Springer Book Archive

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