Solving dynamic memory allocation problems in embedded systems with parallel variable neighborhood search strategies
International audience; Embedded systems have become an essential part of our lives, thanks to their evolution in the recent years, but the main drawback is their power consumption. This paper is focused on improving the memory allocation of embedded systems to reduce their power consumption. We propose a parallel variable neighborhood search algorithm for the dynamic memory allocation problem, and compare it with the state of the art. Computational results and statistical tests applied show that the proposed algorithm produces significantly better outcomes than the previous algorithm in shorter computing time.
Improving the performance of embedded systems with variable neighborhood search
Graphical abstractDisplay Omitted 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 se…