Hybrid Heuristics for Optimizing Energy Consumption in Embedded Systems

Maha Idrissi Aouad (1) , René Schott (2, 3) , Olivier Zendra (1)

1 TRIO - Real time and interoperability
2 LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
3 IECN - Institut Élie Cartan de Nancy

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.

Mots clés: Energy consumption reduction; Genetic heuristics; hybrid heuristics; memory allocation management; optimizations; Tabu Search.; Tabu Search

Domaines: Systèmes embarqués; Intelligence artificielle [cs.AI]; Langage de programmation [cs.PL]; Optimisation et contrôle [math.OC]; Modélisation et simulation

Maha Idrissi Aouad, René Schott, Olivier Zendra. Hybrid Heuristics for Optimizing Energy Consumption in Embedded Systems. ISCIS 2010 - 25th International Symposium on Computer and Information Sciences, Sep 2010, Londres, United Kingdom. pp.409 - 414. ⟨inria-00524320⟩