基于改进粒子群算法的无线传感器网络覆盖策略

doi:10.16088/j.issn.1001-6600.2018.03.002

Abstract

Abstract: As particle swarm optimization algorithm in the optimization of wireless sensor networks is easy to fall into local optimal solution and slow late convergence as well as other shortcomings, an improved particle swarm optimization algorithm based on dynamic acceleration factor (PSO-DAC) is proposed. It adopts decreasing inertia weight coefficients and introduces dynamic acceleration coefficients. The experimental results show that the algorithm has improved the coverage ratio by 34.6% than that of the basic particle swarm algorithm, which is 29.3% higher than that of the particle swarm algorithm based on decreasing inertia weight coefficient. It is proved that the PSO-DAC algorithm can effectively increase the convergence speed and improve the coverage rate of nodes, so as to improve the coverage effect of the whole network and prolong the network lifetime.

Key words: wireless sensor network, PSO-DAC algorithm, acceleration coefficients, network coverage, coverage rate

CLC Number:

TP18

TENG Zhijun, LÜ Jinling, GUO Liwen, XU Yuanyuan. Coverage Strategy of Wireless Sensor Network Based on Improved Particle Swarm Optimization Algorithm[J].Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(3): 9-16.

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