Open Access

ARTICLE

An Energy-Efficient and Reliability-Aware Climate-Conscious Clustered Routing Framework for Sustainable Ocean Observation in Underwater Wireless Sensor Networks

Kiran Saleem¹, Upinder Kaur^2,*, Abdulrahman Mohammed Alamoudi³, Mai Alduailij⁴, Ahmad Subhi Salem Mufleh⁵, Ateeq Ur Rehman^6,*, Salil Bharany⁷

1 School of Computing, Horizon University College, Ajman, United Arab Emirates
2 School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India
3 Electrical and Electronic Engineering Department, Engineering Faculty, University of Jeddah, Jeddah, Saudi Arabia
4 Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
5 Preparatory Year Deanship, Basic Science Department, Prince Sattam bin Abdulaziz University, 151, Al-Kharj, Saudi Arabia
6 School of Computing, Gachon University, Seongnam-si, Republic of Korea
7 Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India

* Corresponding Authors: Upinder Kaur. Email: ; Ateeq Ur Rehman. Email:

Computers, Materials & Continua 2026, 89(1), 59 https://doi.org/10.32604/cmc.2026.083670

Received 08 April 2026; Accepted 24 June 2026; Issue published 13 August 2026

Abstract

Underwater Wireless Sensor Networks (UWSNs) are exceedingly critical for large-scale underwater applications, such as environmental monitoring, infrastructure inspection, target tracking, and marine surveillance. Nevertheless, network lifetime and communication reliability are severely constrained by harsh underwater acoustic conditions, limited battery power, large propagation delays, node mobility, and uneven energy consumption. In response to these issues, this study proposes a Climate-Aware Hybrid Clustering and Routing (CA-HCR-UWSN) framework to enable sustainable, long-term underwater monitoring. This work proposes a hybrid framework that combines Elephant Herding Optimization (EHO) with the Gravitational Search Algorithm (GSA) to provide an effective solution to these challenges. To minimize unnecessary transmissions and energy usage within the clusters, a chain-oriented data aggregation mechanism based on Chain-Oriented Sensor Network (COSEN) is used, with the parameters of the climate and the underwater acoustic channel clearly taken into consideration. Moreover, a reliability-conscious inter-cluster routing policy that accounts for signal-to-noise ratio, packet error rate, and link reliability is also established to ensure reliable data delivery in a dynamic underwater environment. Extensive simulation results indicate that CA-HCR-UWSN consistently outperforms state-of-the-art protocols, including FCMMFO, MCR-UWSN, EE-UWSN, WDFAD-DBR, and EESLEPRP. The proposed framework achieves an 18%–25% increase in the network’s common lifetime, a 15%–20% increase in packet delivery, 20%–26% energy savings, and a 17%–22% decrease in end-to-end delay compared with existing methods, along with better load balancing and network stability. These findings verify that CA-HCR-UWSN is a strong, scalable, and energy-efficient solution for long-term, climate-conscious underwater sensing applications.

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