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

Bruno Gaujal (), Alain Girault () and Stephan Plassart ()
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Bruno Gaujal: Univ. Grenoble Alpes
Alain Girault: Univ. Grenoble Alpes
Stephan Plassart: Univ. Grenoble Alpes

Journal of Scheduling, 2020, vol. 23, issue 5, No 3, 555-574

Abstract: 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.

Keywords: Optimization; Real-time systems; Markov decision process; Dynamic voltage and frequency scaling (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10951-020-00660-9

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