Title: A novel DV-Hop method based on coupling algorithm used for wireless sensor network localisation

Authors: Yechuang Wang; Penghong Wang; Jiangjiang Zhang; Xingjuan Cai; Wuchao Li; Yanyan Ma

Addresses: Complex System and Computational Intelligence Laboratory, TaiYuan University of Science and Technology, Taiyuan 003024, China ' Complex System and Computational Intelligence Laboratory, TaiYuan University of Science and Technology, Taiyuan 003024, China ' Complex System and Computational Intelligence Laboratory, TaiYuan University of Science and Technology, Taiyuan 003024, China ' Complex System and Computational Intelligence Laboratory, TaiYuan University of Science and Technology, Taiyuan 003024, China ' Jiaxing Vocational Technical College, Zhejiang Sheng 314001, China ' Shanxi Cloud Era TISCO Information Automation Technology Co., Ltd., Taiyuan, 030003, China

Abstract: Wireless Sensor Network (WSN) localisation is an essential requirement in the increasing prevalence of WSN applications. It is an important part of the Internet of Things (IOT) and has become a hot research area. Distance Vector-Hop algorithm (DV-Hop), a range-free algorithm, is widely deployed to solve the localisation problem in WSN. However, the results of the estimation precision are usually not satisfactory. In order to improve the WSN positioning accuracy, in this paper, we propose a new coupling algorithm based on Bacterial Foraging Algorithm (BFA) and Glow-worm Swarm Optimisation (GSO) (BFO-GSO). The algorithm has good convergence speed, local search ability of BFO and global convergence of GSO. The optimisation performance is verified by CEC2013 benchmarks in those designs against the original algorithm. Furthermore, Wilcoxon's rank-sum non-parametric statistical test and Friedman test are carried out to judge whether the results of the proposed algorithm differ from those of the other algorithms in a statistically significant way. The numerical results prove that it is able to significantly outperform others on majority of the benchmark functions. Finally, the proposed algorithm is also combined into the DV-Hop algorithm to improve the WSN positioning accuracy. Experimental results show that our improved algorithm achieves better performance when compared with other DV-Hop algorithms.

Keywords: WSN; wireless sensor network; localisation; DV-Hop; distance vector-hop; coupling algorithm; BFO algorithm; GSO; Glow-worm swarm optimisation; CEC2013.

DOI: 10.1504/IJWMC.2019.099027

International Journal of Wireless and Mobile Computing, 2019 Vol.16 No.2, pp.128 - 137

Received: 20 Sep 2018
Accepted: 25 Oct 2018
Published online: 12 Apr 2019 *

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