Title: A fuzzy inference system confidence dynamic concept simulated annealing strategy for wireless sensor networks

Authors: K. Selvamani; S. Kanimozhi; N.R. Rejin Paul; M. Arun Manicka Raja; S. Venkatasubramanian; Anuradha Thakare

Addresses: Department of Computer Science and Engineering, Anna University, CEG Campus, Chennai, 600 025, Tamil Nadu, India ' Department of Information Technology, Panimalar Engineering College, Chennai City campus, Chennai, 600029, Tamil Nadu, India ' Department of Computer Science and Engineering, R.M.K College of Engineering and Technology, Tamil Nadu, 601 206, India ' Department of Computer Science and Engineering, R.M.K College of Engineering and Technology, Tamil Nadu, 601 206, India ' Department of Computer Science and Business Systems, Saranathan College of Engineering, Trichy, 620012, Tamil Nadu, India ' Department of Computer Engineering, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, 411044, India

Abstract: Scientific study has focused on extending the lifespan of wireless sensor networks, a cost-effective technique to collect data from a specific area. Previous studies offered a low-energy heterogeneous wireless sensor network (WSN) routing technique. Few writers proposed the algorithm for finding and calculating critical node linkages. Installing more mobile nodes improved WSN's topological connection earlier. Path design was also proposed to maximise longevity and decrease connected key node effects. Some geo-cast methods used hop-to-hop neighbour data. Dynamic resource routing for WSNs is advocated using an FIS and area segmentation. Thus, correct device data flow saves energy and prolongs channel life. This work introduces geographic routing. Fuzzy logic determines neural source coordinates, and weighted centroid identification is suggested. A wireless fuzz version measures flow to determine anchor-edge device distance. It decreases localised standard errors and node placement errors. Second, boost messages to the next bounce member nodes with the latest version. Smart next-hop selection reduces node energy usage and extends network lifetime. The suggested thing outperforms existing ways in power utilisation, completion time, and location errors, according to simulations.

Keywords: WSN; wireless sensor network; IoT; internet of things; segmentation; classification; communication; fuzzy logic; FIS; fuzzy inference system.

DOI: 10.1504/IJSSE.2025.146195

International Journal of System of Systems Engineering, 2025 Vol.15 No.2, pp.112 - 132

Received: 22 Mar 2023
Accepted: 25 May 2023
Published online: 12 May 2025 *

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