Title: An adaptive multi-group slime mould algorithm for node localisation in wireless sensor networks

Authors: Xiankang He; Lijun Yan; Shi-Jian Liu; Jixiang Lv; Jeng-Shyang Pan

Addresses: College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou, 350118, China ' Shenzhen Institute of Information Technology, Shenzhen, 518000, China ' College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou, 350118, China ' College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou, 350118, China ' Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, 350118, China; College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China; Department of Information Management, Chaoyang University of Technology, Taichung, 413310, Taiwan

Abstract: Node localisation is a common and significant practical application question in wireless sensor network (WSN). The goal of this problem is to use anchor nodes in the network to estimate the geographical location of the unknown node. A novel algorithm, named adaptive multi-group slime mould algorithm (AMSMA), is proposed in this study. The improved slime mould algorithm uses the multi-group strategy and adaptive communication mechanism to alleviate the lack of population diversity, development and exploration imbalance of the slime mould algorithm. The proposed AMSMA was tested under CEC2013 test suite. Compared with SMA and corresponding optimisation algorithms, the AMSMA is more effective and efficient. In addition, a novel localisation algorithm based on AMSMA is proposed. The AMSMA-Distance Vector-Hop (AMSMA-DV-Hop) is applied to the localisation of WSN. Compared with some other existing localisation algorithms, the proposed AMSMA-DV-Hop is an effective algorithm for the localisation of WSN.

Keywords: wireless sensor network; WSN; multi-group; adaptive; slime mould algorithm; SMA.

DOI: 10.1504/IJSNET.2022.127842

International Journal of Sensor Networks, 2022 Vol.40 No.4, pp.262 - 276

Received: 10 Jan 2022
Accepted: 02 Aug 2022
Published online: 19 Dec 2022 *

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