Title: Mobile nodes localisation based on hill climbing optimisation

Authors: Wenjie Hu; Yao Chen; Jincai Yang; Xianjun Shen

Addresses: College of Information Engineering, Xianning Vocational Technical College, Xianning, Hubei, China ' School of Computer, Central China Normal University, Wuhan, Hubei, China ' School of Computer, Central China Normal University, Wuhan, Hubei, China ' School of Computer, Central China Normal University, Wuhan, Hubei, China; Collaborative & Innovative Center for Educational Technology, Central China Normal University, Wuhan, Hubei, China

Abstract: Aiming at the critical drawbacks of low sampling rate and less accuracy in Monte Carlo Localisation (MCL) algorithm, a novel mobile nodes localisation algorithm based on the hill climbing optimisation strategy is proposed, namely HCPSO-MCL (Hill Climbing Particle Swarm Optimisation-MCL). The HCPSO-MCL algorithm combines the hill climbing strategy and particle swarm optimisation to correct the location estimated by the MCL algorithm, which results in effective implementation and accurate positioning of the mobile nodes. The experimental results indicate that the HCPSO-MCL algorithm improves the positioning accuracy greatly compared to the MCL algorithm and that it has a faster position velocity than the PSO-MCL algorithm.

Keywords: wireless sensor network; WSNs; Monte Carlo localisation; particle swarm optimisation; PSO; hill climbing optimisation; mobile nodes; node localisation; node positioning.

DOI: 10.1504/IJWMC.2016.079463

International Journal of Wireless and Mobile Computing, 2016 Vol.11 No.1, pp.18 - 23

Received: 20 May 2016
Accepted: 26 Jun 2016
Published online: 28 Sep 2016 *

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