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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.
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https://hal.inria.fr/inria-00524975
Contributor : Maha Idrissi Aouad <>
Submitted on : Sunday, October 10, 2010 - 1:39:44 AM
Last modification on : Monday, January 6, 2020 - 10:42:03 PM

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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. ⟨inria-00524975⟩

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