In this paper, the binary quantum-inspired gravitational search algorithm is adapted to dynamically optimize the design of a wireless sensor network towards improving energy consumption and extending the lifetime of the network, so that the application-specific requirem More
In this paper, the binary quantum-inspired gravitational search algorithm is adapted to dynamically optimize the design of a wireless sensor network towards improving energy consumption and extending the lifetime of the network, so that the application-specific requirements and communication constraints are fulfilled. The proposed approach is applied on a wireless sensor network used in the application of precise agriculture to monitor environmental conditions. This algorithm would present an optimal design detecting operational mode of each sensor including cluster head, high signal range, low signal range and inactive modes taking into consideration the constraints of the network. The simulation results indicate the most performance of the proposed method in comparison with binary genetic algorithm and particle swarm optimization.
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