Ordonnancement temps réel multiprocesseur pour la réduction de la consommation énergétique des systèmes embarqués

Abstract : Reducing the energy consumption of multiprocessor real-time embedded systems is a growing concern to increase their autonomy. In thisthesis, we aim to reduce the energy consumption of the processors, it includes both static and dynamic consumption and it is nowdominated by static consumption as the semiconductor technology moves to deep sub-micron scale. Existing solutions mainly focused ondynamic consumption. On the other hand, we target static consumption by efficiently using the low-power states of the processors. In alow-power state, the processor is not active and the deeper the low-power state is, the lower is the energy consumption but the higher isthe transition delay to come back to the active state. In this thesis, we propose the first optimal multiprocessor real-time schedulingalgorithms minimizing the static energy consumption. They optimize the duration of the idle periods to activate the most appropriate lowpowerstates. We target hard real-time systems with periodic tasks and also mixed-criticality systems where tasks with lower criticalitiescan tolerate deadline misses, therefore allowing us to be more aggressive while trying to reduce the energy consumption. We use anadditional task to model the idle time and mixed integer linear programming to compute offline a schedule minimizing the energyconsumption. Evaluations have been performed using existing optimal multiprocessor real-time scheduling algorithms. Results show thatthe energy consumption while processors are idle is up to ten times reduced with our solutions compared to the existing multiprocessor real-time scheduling algorithms.
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Vincent Legout. Ordonnancement temps réel multiprocesseur pour la réduction de la consommation énergétique des systèmes embarqués. Calcul parallèle, distribué et partagé [cs.DC]. Télécom ParisTech, 2014. Français. ⟨NNT : 2014ENST0019⟩. ⟨tel-01540387⟩

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