Sequential and Distributed SA-Type Algorithms for Energy Optimization in Embedded Systems
Résumé
Reducing energy consumption in embedded systems is a major crucial issue. In this paper, we propose new sequential and distributed algorithms based on Simulated Annealing (SA) in order to reduce energy consumption in embedded systems. Our algorithms outperform the Tabu Search (TS) approach. In fact, our algorithms manage to consume nearly from 76% up to 98% less memory energy than TS.