Simulation Study of a Coverage Enhancement Scheme in Directional Sensor Network Based on Particle Swarm Algorithm

doi:10.16182/j.issn1004731x.joss.201701024

Abstract

Abstract: A Dezert-Smarandache theory (DSmT) data fusion scheme was proposed based on the probability sensing model of directional sensor. In order to enhance the coverage ratio of directional sensor network, a sensor node deployment strategy was presented based on particle swarm optimization algorithm. Overlap rate was reduced by iteratively adjusting the sensing direction, which was regarded as fitness function in the algorithm, and the reliability of data was enhanced. The simulation results show that this algorithm has a fast convergence speed for the random deployment of sensor network nodes with continuously adjustable sensing direction, can effectively enhance the utilization rate of network nodes, and improve the coverage rate of the sensor network.

Key words: directional sensor networks, particle swarm optimization, probabilistic sensing model, data fusion, coverage

CLC Number:

TP393

Zhang Juwei, Wang Yu. Simulation Study of a Coverage Enhancement Scheme in Directional Sensor Network Based on Particle Swarm Algorithm[J]. Journal of System Simulation, 2017, 29(1): 181-189.

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