Maha Idrissi Aouad

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Reducing memory energy consumption in embedded systems is crucial. In this paper, we propose new sequential and distributed algorithms based on Simulated Annealing (SA) in order to reduce memory 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%(More)
In this paper, we propose a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and on Simulated Annealing (SA) for reducing memory energy consumption in embedded systems. Our hybrid algorithm outperforms the Tabu Search (TS) approach. In fact, nearly from 76% up to 98% less energy consumption is recorded.
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