Reduction of Energy Consumption in Embedded Systems: A Hybrid Evolutionary Algorithm

Abstract : In this paper, we propose a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and on Simulated Annealing (SA) for reducing memory energy consumption in embedded systems. Our hybrid algorithm outperforms the Tabu Search (TS) approach. In fact, nearly from 76% up to 98% less energy consumption is recorded.
Type de document :
Communication dans un congrès
META'10 - 3rd International Conference on Metaheuristics and Nature Inspired Computing, Oct 2010, Djerba, Tunisia. 95, 2010
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https://hal.inria.fr/inria-00524975
Contributeur : Maha Idrissi Aouad <>
Soumis le : dimanche 10 octobre 2010 - 01:39:44
Dernière modification le : mercredi 14 mars 2018 - 16:40:45

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  • HAL Id : inria-00524975, version 1

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Maha Idrissi Aouad, Lhassane Idoumghar, René Schott, Olivier Zendra. Reduction of Energy Consumption in Embedded Systems: A Hybrid Evolutionary Algorithm. META'10 - 3rd International Conference on Metaheuristics and Nature Inspired Computing, Oct 2010, Djerba, Tunisia. 95, 2010. 〈inria-00524975〉

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