4.6 Article

An Efficient Metaheuristic-Based Clustering with Routing Protocol for Underwater Wireless Sensor Networks

Journal

SENSORS
Volume 22, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/s22020415

Keywords

clustering; routing; energy efficiency; underwater wireless sensor network; metaheuristics; fitness function

Funding

  1. Taif University [TURSP-2020/313]

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In recent years, the underwater wireless sensor network (UWSN) has gained significant attention for various applications. Energy efficiency is a major challenge for UWSN due to restricted sensor energy and the difficulty of recharging or replacing batteries. This study focuses on designing a metaheuristics-based clustering and routing protocol called MCR-UWSN, which addresses the issues of underwater current, low bandwidth, high water pressure, propagation delay, and error probability. By utilizing cultural emperor penguin optimizer-based clustering (CEPOC) and grasshopper optimization (MHR-GOA) for routing, the MCR-UWSN technique demonstrates improved performance compared to existing techniques.
In recent years, the underwater wireless sensor network (UWSN) has received a significant interest among research communities for several applications, such as disaster management, water quality prediction, environmental observance, underwater navigation, etc. The UWSN comprises a massive number of sensors placed in rivers and oceans for observing the underwater environment. However, the underwater sensors are restricted to energy and it is tedious to recharge/replace batteries, resulting in energy efficiency being a major challenge. Clustering and multi-hop routing protocols are considered energy-efficient solutions for UWSN. However, the cluster-based routing protocols for traditional wireless networks could not be feasible for UWSN owing to the underwater current, low bandwidth, high water pressure, propagation delay, and error probability. To resolve these issues and achieve energy efficiency in UWSN, this study focuses on designing the metaheuristics-based clustering with a routing protocol for UWSN, named MCR-UWSN. The goal of the MCR-UWSN technique is to elect an efficient set of cluster heads (CHs) and route to destination. The MCR-UWSN technique involves the designing of cultural emperor penguin optimizer-based clustering (CEPOC) techniques to construct clusters. Besides, the multi-hop routing technique, alongside the grasshopper optimization (MHR-GOA) technique, is derived using multiple input parameters. The performance of the MCR-UWSN technique was validated, and the results are inspected in terms of different measures. The experimental results highlighted an enhanced performance of the MCR-UWSN technique over the recent state-of-art techniques.

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