Open Access

ARTICLE

An Enhanced Fuzzy Routing Protocol for Energy Optimization in the Underwater Wireless Sensor Networks

Mehran Tarif¹, Mohammadhossein Homaei^2,*, Amir Mosavi^3,4,5

1 Department of Computer Science, University of Verona, Verona, 37134, Italy
2 Department of Computer Systems Engineering and Telematics, University of Extremadura, Cáceres, 10003, Extremadura, Spain
3 Institute of the Information Society, Ludovika University of Public Service, Budapest, 1083, Hungary
4 John Von Neumann Faculty of Informatics, Obuda University, Budapest, 1034, Hungary
5 Department of Information and Computing Systems, Abylkas Saginov Karaganda Technical University, Karaganda, 100000, Kazakhstan

* Corresponding Author: Mohammadhossein Homaei. Email:

Computers, Materials & Continua 2025, 83(2), 1791-1820. https://doi.org/10.32604/cmc.2025.063962

Received 30 January 2025; Accepted 25 March 2025; Issue published 16 April 2025

Abstract

Underwater Wireless Sensor Networks (UWSNs) are gaining popularity because of their potential uses in oceanography, seismic activity monitoring, environmental preservation, and underwater mapping. Yet, these networks are faced with challenges such as self-interference, long propagation delays, limited bandwidth, and changing network topologies. These challenges are coped with by designing advanced routing protocols. In this work, we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks (UWF-RPL), an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes. Our method extends RPL with the aid of fuzzy logic to optimize depth, energy, Received Signal Strength Indicator (RSSI) to Expected Transmission Count (ETX) ratio, and latency. The proposed protocol outperforms other techniques in that it offers more energy efficiency, better packet delivery, low delay, and no queue overflow. It also exhibits better scalability and reliability in dynamic underwater networks, which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized. Compared to other recent methods, it offers improved network convergence time (10%–23%), energy efficiency (15%), packet delivery (17%), and delay (24%).

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Keywords

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