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Dynamic speed scaling minimizing expected energy consumption for real-time tasks

Author

Listed:
  • Bruno Gaujal

    (Univ. Grenoble Alpes)

  • Alain Girault

    (Univ. Grenoble Alpes)

  • Stephan Plassart

    (Univ. Grenoble Alpes)

Abstract

This paper proposes a discrete time Markov decision process approach to compute the optimal on-line speed scaling policy to minimize the energy consumption of a single processor executing a finite or infinite set of jobs with real-time constraints. We provide several qualitative properties of the optimal policy: monotonicity with respect to the jobs parameters, comparison with on-line deterministic algorithms. Numerical experiments in several scenarios show that our proposition performs well when compared with off-line optimal solutions and out-performs on-line solutions oblivious to statistical information on the jobs.

Suggested Citation

  • Bruno Gaujal & Alain Girault & Stephan Plassart, 2020. "Dynamic speed scaling minimizing expected energy consumption for real-time tasks," Journal of Scheduling, Springer, vol. 23(5), pages 555-574, October.
    • Handle: RePEc:spr:jsched:v:23:y:2020:i:5:d:10.1007_s10951-020-00660-9
    DOI: 10.1007/s10951-020-00660-9
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    References listed on IDEAS

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    1. W. A. Horn, 1974. "Some simple scheduling algorithms," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 21(1), pages 177-185, March.
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