Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Fusion in sensor networks with communication constraints
Proceedings of the 3rd international symposium on Information processing in sensor networks
Adaptive design optimization of wireless sensor networks using genetic algorithms
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy-aware topology control for wireless sensor networks using memetic algorithms
Computer Communications
Power control based topology construction for the distributed wireless sensor networks
Computer Communications
Transmission power adjustment of wireless sensor networks using fuzzy control algorithm
Wireless Communications & Mobile Computing
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Minimum energy mobile wireless networks
IEEE Journal on Selected Areas in Communications
A novel approach for automated music composition using memetic algorithms
Proceedings of the 49th Annual Southeast Regional Conference
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We present a memetic algorithm that dynamically optimizes the design of a wireless sensor network towards energy conservation and extension of the life span of the network, taking into consideration application-specific requirements, communication constraints and energy consumption of operation and communication tasks of the sensors. The memetic algorithm modifies an already successful genetic algorithm design system and manages to improve its performance. The obtained optimal sensor network designs satisfy all application-specific requirements, fulfill the existing connectivity constraints and incorporate energy conservation characteristics stronger than those of the original genetic algorithm system. Energy management is optimized to guarantee maximum life span of the network without lack of the network characteristics that are required by the specific sensing application.