Title: A DV-Hop positioning algorithm based on the glowworm swarm optimisation of mixed chaotic strategy

Authors: Ling Song; Liqin Zhao; Jin Ye

Addresses: School of Computer and Electronic Information, Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China ' School of Computer and Electronic Information, Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China ' School of Computer and Electronic Information, Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China

Abstract: DV-Hop, as a typical location algorithm without ranging, is widely used in node localisation of wireless sensor networks. However, in the third phase of DV-Hop, a least square method is used to solve the nonlinear equations. Using this method to locate the unknown nodes will produce large coordinates errors, poor stability of positioning accuracy, low location coverage and high energy consumption. An improved localisation algorithm based on hybrid chaotic strategy (MGDV-Hop) is proposed in this paper. Firstly, a glowworm swarm optimisation of hybrid chaotic strategy based on chaotic mutation and chaotic inertial weight updating (MC-GSO) is proposed. Then, MC-GSO is used to replace the least square method in estimating node coordinates. By establishing the error fitness function, the linear solution of coordinates is transformed into a two-dimensional combinatorial optimisation problem. Simulation results show that the average location error is reduced, while the location coverage is increased and the energy consumption is decreased.

Keywords: wireless sensor networks; node positioning; DV-hop algorithm; glowworm swarm optimisation algorithm; hybridchaotic strategy; chaotic mutation; chaotic inertial weight updating; least square method; coordinate; location error; location coverage; energy consumption.

DOI: 10.1504/IJSN.2019.098909

International Journal of Security and Networks, 2019 Vol.14 No.1, pp.23 - 33

Received: 17 Sep 2018
Accepted: 17 Sep 2018

Published online: 09 Apr 2019 *

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