A Optimized 3D DV-Hop Localization Algorithm Based on Hop Count and Differential Evolution Methods
Keywords:Underwater wireless sensor network, 3D DV-Hop, Trust degree, Differential evolutionary algorithm.
The location problem is a fundamental problem in underwater wireless sensor networks. This paper focuses on the distance vector hopping (DV-Hop) localization algorithm, which is most widely used in underwater wireless sensor networks (UWSNs). The algorithm does not require distance measurement and is simple to implement, but the research on DV-Hop algorithm in 3D space is not mature, which leads to large positioning errors. Based on the error analysis of the 3D DV-Hop algorithm, this paper proposes a 3D differential evolutionary hop count DV-Hop (DEHDV-Hop) algorithm to reduce the localization error. We define a continuous hop value based on the number relationship of adjacent nodes and solve the upper bound of the hop count under this definition. The discrete values of the global hop count are converted to continuous values using the broadcasted node information. The concept of trust is introduced by analyzing the error between the actual and estimated distances between anchor nodes. The method of obtaining the average hop distance of unknown nodes in the original algorithm is replaced so that the estimated distance is calculated using the new hop count and hop distance. Finally, the hop count information is segmented, a new fitness function is constructed, and the coordinates of the unknown nodes are solved iteratively using a differential evolutionary algorithm.
Qu F, Wang S, Wu Z, et al. A survey of ranging algorithms and localization schemes in underwater acoustic sensor network [J]. Wireless Communication Over Zigbee for Automotive Inclination Measurement China Communications, 2016, 13 (3): 66-81.
Heidemann J, Ye W, Wills J. Research challenges and applications for underwater sensor networking [C]. Wireless Communications and Networking Conference. Las Vegas: IEEE, 2006: 228-235.
Pompili D, Akyildiz I F. Overview of networking protocols for underwater wireless communications [J]. IEEE Communications Magazine, 2009, 47 (1): 97-102.
Kumari J, Kumar P, Singh S K. Localization in three-dimensional wireless sensor networks: a survey[J]. The Journal of Supercomputing, 2019, 75: 5040-5083.
Gong D W, Wang G X, Sun X Y, Han Y Y. A set-based genetic algorithm for solving the many-objective optimization problem[J]. Soft Computing 2015, 19(6): 1477-1495.
Souravlias D, Parsopoulos K E, et al. Particle swarm optimization with neighborhood -based budget allocation[J]. International Journal of Machine Learning and Cybernetics, 2016, 7(3): 451-477.
Mohamed A W, Mohamed A K, et al. Adaptive guided differential evolution algorithm with novel mutation for numerical optimization[J]. International Journal of Machine Learning and Cybernetics, 2017, 10(2): 253-277.
Sharma G, Kumar A. Improved range-free localization for three-dimensional wireless sensor networks using genetic algorithm[J]. Computers & Electrical Engineering, 2018, 72: 808-827.
Singh S P, Sharma S C. A PSO ased improved localization algorithm for wireless sensor network[J]. Wireless Personal Communications, 2018, 98: 487-503.
Singh P, Khosla A, Kumar A, et al. 3D localization of moving target nodes using single anchor node in anisotropic wireless sensor networks[J]. AEU- International Journal of Electronics and Communications, 2017, 82: 543-552.
Liu Zhiliang, Liu Shuan. Elliptical ranging-based DV-hop localization algorithm for 3D underwater wirelesssensor networks [J]. Computer Engineering and Design, 2017, 38(12): 3218-3223.
Cui L, Xu C, Li G, et al. A high accurate localization algorithm with DV-Hop and differential evolution for wireless sensor network[J]. Applied Soft Computing, 2018: 39-52.
Peng B, Li L. An improved localization algorithm based on genetic algorithm in wireless sensor networks[J]. Cognit Neurodyn 2015, 9(2): 249–256.
Xue D. Research on range-free location algorithm for wireless sensor network based on particle swarm optimization[J]. EURASIP Journal on Wireless Communications and Networking, 2019(221): 1-8.
How to Cite
This work is licensed under a Creative Commons Attribution 4.0 International License.