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Author 1
Yujiang Li
School of Mathematics and Statistics, Lingnan Normal University, Zhanjiang 524048, China
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IECE Contributions
Research Article | Feature Paper | 17 April 2023
Adaptive Binary Particle Swarm Optimization for WSN Node Optimal Deployment Algorithm
IECE Transactions on Internet of Things | Volume 1, Issue 1: 1-8, 2023 | DOI:10.00000/TIOT.2023.100001
Abstract
In order to optimize the deployment of wireless sensor network nodes, and avoid network energy consumption increase due to node redundancy and uneven coverage, the multi-objective mathematical optimization problem of area coverage is transformed into a function problem. Aiming at network coverage rate, node dormancy rate and network coverage uniformity, the idea of genetic algorithm mutation is introduced based on the discrete binary particle swarm optimization and the global optimal speed is mutated to avoid the algorithm falling into the local optimal solution. In order to further improve the optimization ability of the algorithm, the adaptive learning factor and inertia weight are introdu... More >

Graphical Abstract
Adaptive Binary Particle Swarm Optimization for WSN Node Optimal Deployment Algorithm