Improving the performance of embedded systems with variable neighborhood search

Jesús Sánchez-Oro 1 Marc Sevaux 2 André Rossi 3 Rafael Marti 4 Abraham Duarte 1
2 Lab-STICC_UBS_CID_DECIDE
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192), Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : Embedded systems have become an essential part of our lives, mainly due to the evolution of technology in the last years. However, the power consumption of these devices is one of their most important drawbacks. It has been proven that an efficient use of the memory of the device also improves its energy performance. This work efficiently solves the dynamic memory allocation problem, which can be formally defined as follows: given a program that has to be executed by a circuit, the objective is to fit that program in memory in such a way that the computing time required to execute it is minimized. In this work, we propose a parallel variable neighborhood search strategy to address this problem. We additionally compare this parallel procedure with the sequential version of the algorithm and with the best previous approach. Computational results show the superiority of our proposal, backed up with statistical tests.
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Article dans une revue
Applied Soft Computing, Elsevier, 2017, 53, pp.217-226. 〈10.1016/j.asoc.2016.12.034〉
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https://hal.archives-ouvertes.fr/hal-01438796
Contributeur : Marc Sevaux <>
Soumis le : mercredi 18 janvier 2017 - 10:01:23
Dernière modification le : jeudi 5 avril 2018 - 18:16:02

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Jesús Sánchez-Oro, Marc Sevaux, André Rossi, Rafael Marti, Abraham Duarte. Improving the performance of embedded systems with variable neighborhood search. Applied Soft Computing, Elsevier, 2017, 53, pp.217-226. 〈10.1016/j.asoc.2016.12.034〉. 〈hal-01438796〉

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