An adaptive stochastic central force optimisation algorithm for node localisation in wireless sensor networks. (14th February 2022)

• Record Type: Journal Article
• Authors: Song, Pei-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Wu, Tsu-Yang
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 39:Number 1/2(2022)
• Page Start: 1
• Page End: 19
• Publication Date: 2022-02-14
• Subjects: central force optimisation -- CFO -- restart strategy -- adaptive -- stochastic -- MDS-MAP -- wireless sensor network -- WSN; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

Abstract

Node localisation in wireless sensor networks is a common and important practical application problem. Among the many localisation algorithms, the MDS-MAP algorithm is a more effective one. However, the positioning effect of the MDS-MAP algorithm is not accurate in some cases, so the metaheuristic algorithm is implemented to further optimise the estimation results of the MDS-MAP algorithm in this paper. The improved central force optimisation algorithm uses adaptive parameters to achieve randomness, while adding the restart strategy and accelerate strategy so as to avoid getting stuck in a local optimum. The CEC2013 and CEC2014 benchmark test suites used to verify the proposed algorithm are more competitive than some other existing algorithms. The improved central force optimisation algorithm is applied to the MDS-MAP localisation algorithm. The experimental results show that the improved central force optimisation algorithm has a further optimisation effect on the position estimation results of MDS-MAP.