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Title:
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SEQUENTIAL AND DISTRIBUTED HYBRID GA-SA ALGORITHMS FOR ENERGY OPTIMIZATION IN EMBEDDED SYSTEMS |
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Author(s):
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Maha Idrissi Aouad, Lhassane Idoumghar, René Schott, Olivier Zendra |
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ISBN:
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978-972-8939-30-4 |
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Editors:
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Hans Weghorn, Pedro Isaías and Radu Vasiu |
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Year:
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2010 |
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Edition:
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Single |
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Keywords:
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Distributed systems, embedded systems, genetic algorithms, memory management, optimization, simulated annealing. |
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Type:
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Full Paper |
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First Page:
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167 |
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Last Page:
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174 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Reducing memory energy consumption in embedded systems is crucial. In this paper, we propose new hybrid sequential and distributed algorithms based on Simulated Annealing (SA) and Genetic Algorithms (GA) in order to reduce memory energy consumption in embedded systems. Our algorithms outperform the Tabu Search (TS) approach. In fact, our hybrid algorithms manage to consume nearly from 76% up to 98% less memory energy than TS. Execution time savings for the distributed version (nearly from 72% up to 74% for a cluster of 4 PCs) are also recorded. |
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