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A Discrete Time Markov Decision Process for Energy Minimization Under Deadline Constraints

Un processus à décision de Markov en temps discret pour minimiser l'énergie sous des contraintes d'échéances

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Abstract

This paper proposes a Discrete Time Markov Decision Process (MDP) 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.
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Dates and versions

hal-02391948 , version 1 (03-12-2019)

Identifiers

  • HAL Id : hal-02391948 , version 1

Cite

Bruno Gaujal, Alain Girault, Stéphan Plassart. A Discrete Time Markov Decision Process for Energy Minimization Under Deadline Constraints. [Research Report] RR-9309, Grenoble Alpes; Inria Grenoble Rhône-Alpes, Université de Grenoble. 2019, pp.46. ⟨hal-02391948⟩
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