Improving the performance of embedded systems with variable neighborhood search

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.

Publication
Applied Soft Computing
Jesús Sánchez-Oro
Jesús Sánchez-Oro
Associate Professor

Associate Professor at the Computer Science Department, being one of the senior researchers of the Group for Research on Algorithms For Optimization GRAFO.

Abraham Duarte
Abraham Duarte
Full Professor

Abraham Duarte is Full Professor in the Computer Science Department at the Rey Juan Carlos University (Madrid, Spain). He has done extensive research in the interface between computer science, artificial intelligence, and operations research to develop solution methods based on Computational Intelligence (metaheuristics) for practical problems in operations-management areas such as logistics and supply chains, telecommunications, decision-making under uncertainty and optimization of simulated systems.