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Energy efficient coverage control in wireless sensor networks based on multi-objective genetic algorithm
Authors:Jie Jia   Jian Chen   Guiran Chang  Zhenhua Tan  
Affiliation:aSchool of Information Science and Engineering, Northeastern University, Shenyang, 110004, China;bComputing Center, Northeastern University, Shenyang, 110004, China;cSchool of Software, Northeastern University, Shenyang, 110004, China
Abstract:
Due to the constrained energy and computational resources available to sensor nodes, the number of nodes deployed to cover the whole monitored area completely is often higher than if a deterministic procedure were used. Activating only the necessary number of sensor nodes at any particular moment is an efficient way to save the overall energy of the system. A novel coverage control scheme based on multi-objective genetic algorithm is proposed in this paper. The minimum number of sensors is selected in a densely deployed environment while preserving full coverage. As opposed to the binary detection sensor model in the previous work, a more precise detection model is applied in combination with the coverage control scheme. Simulation results show that our algorithm can achieve balanced performance on different types of detection sensor models while maintaining high coverage rate. With the same number of deployed sensors, our scheme compares favorably with the existing schemes.
Keywords:Coverage control   Energy   Multi-objective genetic algorithm   Wireless sensor network
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