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

Bruno Gaujal 1 Alain Girault 2 Stéphan Plassart 1, 2
1 POLARIS - Performance analysis and optimization of LARge Infrastructures and Systems
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
2 SPADES - Sound Programming of Adaptive Dependable Embedded Systems
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
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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https://hal.inria.fr/hal-02391948
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Submitted on : Tuesday, December 3, 2019 - 5:40:46 PM
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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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