Hybrid Heuristics for Optimizing Energy Consumption in Embedded Systems
Identifieur interne : 002B29 ( Main/Merge ); précédent : 002B28; suivant : 002B30Hybrid Heuristics for Optimizing Energy Consumption in Embedded Systems
Auteurs : Maha Idrissi Aouad [France] ; René Schott [France] ; Olivier Zendra [France]Source :
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Abstract
In this paper, we propose new hybrid heuristics for memory management which outperform the best known existing heuristic (BEH). In fact, nearly from 76% up to 98% less energy consumption is recorded. Contrary to BEH, our hybrid heuristics do not require list sorting.
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<profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>Energy consumption reduction</term>
<term>Genetic heuristics</term>
<term>Tabu Search</term>
<term>Tabu Search.</term>
<term>hybrid heuristics</term>
<term>memory allocation management</term>
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<front><div type="abstract" xml:lang="en">In this paper, we propose new hybrid heuristics for memory management which outperform the best known existing heuristic (BEH). In fact, nearly from 76% up to 98% less energy consumption is recorded. Contrary to BEH, our hybrid heuristics do not require list sorting.</div>
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