Wireless Sensor Network Node Localization Algorithm Based on PSO-MA
DOI:
https://doi.org/10.13052/jwe1540-9589.2048Keywords:
Particle swarm optimization, artificial bee colony algorithm, node location.Abstract
Aiming at the large error and low accuracy of wireless sensor node location, this paper proposes a node location method based on the fusion of Particle Swarm Optimization and Monkey Algorithm (PSO-MA). Firstly, this article describes the node location model based on DV-HOP algorithm; secondly, this article uses PSO in node location, uses place Laplace distribution for population initialization, improves population diversity, and optimizes particle weights to avoid algorithm falling into local optimality. In this paper, dynamic guidance factors are used to update individual positions to improve individual optimization capabilities, and Monkey Algorithm is used to select individuals to improve the quality of optimal solutions. In the simulation experiment, the algorithm PSO and MA of this paper are compared to achieve better positioning results in the reference node ratio, node density and communication radius indicators.
Downloads
References
N. Yu, J.W. Wan, Y.F. Wu. ‘Localization algorithm in wireless sensor networks.’ Journal of Transduction Technology, Vol. 20, No. 1, pp. 187–192, January 2007.
Yun S., Lee J., Chung W., et a1. ‘A soft computing approach to localization in wireless sensor networks.’ Expert System with Applications, Vol. 36, No. 4, pp. 7552–7561, April 2009.
J.B. Xue and X.L. Chang. ‘WSN node localization based on artificial bee colony.’ Journal of Lanzhou University of Technology. Vol. 46, No. 3, pp. 94–99, March 2020.
R. Zhang. ‘Study on Target Localization Algorithm in Wireless Sensor Networks.’ Chinese Journal of Sensors and Actuators, Vol. 31, No. 4, pp. 625–629, April 2018.
M. Pang, Z.H. Feng, W.X. Bai. ‘DV-Hop node location algorithm optimized by improved artificial immune algorithms.’ Journal of Terahertz Science and Electronic Information Technology, Vol. 18, No. 6, pp. 1133–1140, June 2020.
X. Zhang, Y.Y. Mao, P. Xu. ‘Node location algorithm based on distance optimization and improved particle swarm optimization.’ Computer Engineering and Design, Vol. 39, No. 7, pp. 1818–1822. July 2018.
Z.A. Zhou, K. Xu, Q. Cheng et al. ‘Node localization of wireless sensor network by using artificial bee colony algorithm optimizing neural network.’ Journal of Nanjing University of Science and Technology, Vol. 41, No. 4, pp. 466–471, April 2017.
Q.G. Gu. ‘Research on Support Vector Machine’s Mobile Node Positioning Based on Fisherman’s Fishing in WSN.’ Bulletin of Science and Technology, Vol. 32, No. 12, pp. 174–178, December 2016.
H.X. Chen and L.M. Wang. ‘Sensor Node Localization Based on Artificial Bee Colony Algorithm Optimizing Support Vector Machine.’ Journal of Jilin University: Sci Ed, Vol. 55, No. 3, pp. 647–651 March 2017.
J. Zhang, X. Guo and W. Li. ‘Research of WSN Node Localization Based on Fruit Fly Optimization Algorithm.’ Microelectronics & Computer, Vol. 35, No. 4, pp. 89–92, April 2018.
Mohanta T.K., Das D.K. Class Topper Optimization Based Improved Localization Algorithm in Wireless Sensor Network[J]. Wireless Personal Communications, 2021: 1–20.
Huang X., Han D., Cui M., et al. Three-Dimensional Localization Algorithm Based on Improved A* and DV-Hop Algorithms in Wireless Sensor Network[J]. Sensors, 2021, 21(2): 448.