3D Wireless Sensor Network Deployment based on TCPSO
Three-dimensional wireless sensor networks(3D WSNs)are communication networks consisting of numerous wireless sensor nodes.Aiming at the node deployment problem of 3D WSNs,a solution based on the two-layer chaotic particle swarm optimization(TCPSO)algorithm is proposed.TCPSO is utilized to optimize the deployment of nodes and improve the spatial coverage of the network.The TCPSO algorithm divides the population into elite and ordinary subpopulations based on nonlinear classification coefficients,adopting different velocity and position update formulas for iterative optimization.TCPSO introduces a decreasing inertia weight based on Logistic chaotic mapping to control the local exploitation of the algorithm.To avoid premature convergence,levy flight strategy is introduced to enhance the global search ability of the algorithm.Simulation experiments are conducted in three-dimensional grid space to verify the ability of TCPSO and particle swarm optimization(PSO)algorithms to solve the node deployment problem of 3D WSNs.Three sets of experiments are conducted with different numbers of nodes communication radii,and population sizes,respectively.The control variable method is adopted to observe the performance of TCPSO under different conditions.The node deployment solutions proposed by TCPSO in all experiments are significantly superior to those of PSO.The experimental results indicate that the proposed scheme can effectively improve the spatial coverage of 3D WSNs,reduce the cost of network construction,and provide strong support for practical applications.
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