Scheduling on Power-Heterogeneous Processors

  • Susanne Albers
  • Evripidis Bampis
  • Dimitrios Letsios
  • Giorgio Lucarelli
  • Richard Stotz
Conference paper

DOI: 10.1007/978-3-662-49529-2_4

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9644)
Cite this paper as:
Albers S., Bampis E., Letsios D., Lucarelli G., Stotz R. (2016) Scheduling on Power-Heterogeneous Processors. In: Kranakis E., Navarro G., Chávez E. (eds) LATIN 2016: Theoretical Informatics. LATIN 2016. Lecture Notes in Computer Science, vol 9644. Springer, Berlin, Heidelberg

Abstract

We consider the problem of scheduling a set of jobs, each one specified by its release date, its deadline and its processing volume, on a set of heterogeneous speed-scalable processors, where the energy-consumption rate is processor-dependent. Our objective is to minimize the total energy consumption when both the preemption and the migration of jobs are allowed. We propose a new algorithm based on a compact linear programming formulation. Our method approaches the value of the optimal solution within any desired accuracy for a large set of continuous power functions. Furthermore, we develop a faster combinatorial algorithm based on flows for standard power functions and jobs whose density is lower bounded by a small constant. Finally, we extend and analyze the AVerage Rate (AVR) online algorithm in the heterogeneous setting.

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Susanne Albers
    • 1
  • Evripidis Bampis
    • 2
  • Dimitrios Letsios
    • 3
  • Giorgio Lucarelli
    • 4
  • Richard Stotz
    • 1
  1. 1.Fakultät für InformatikTechnische Universität MünchenMunichGermany
  2. 2.Sorbonne Universités, UPMC Univ. Paris 06, UMR 7606, LIP6ParisFrance
  3. 3.Univ. Nice Sophia Antipolis, CNRS, I3S, UMR 7271Sophia AntipolisFrance
  4. 4.Université Grenoble-Alpes, INP, UMR 5217, LIGSaint-Martin-d’HèresFrance

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