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

Area of Science:

• Underwater Wireless Sensor Networks (UWSN)
• Network Protocols
• Optimization Algorithms

Background:

• UWSNs are crucial for environmental monitoring and disaster management but face energy constraints.
• Traditional routing protocols struggle with underwater challenges like low bandwidth and high error rates.
• Energy efficiency is a primary challenge in UWSN due to difficulties in battery replacement.

Purpose of the Study:

• To design an energy-efficient clustering and routing protocol for UWSN.
• To address the limitations of existing protocols in underwater environments.
• To enhance the operational lifespan of underwater wireless sensor networks.

Main Methods:

• Developed MCR-UWSN, a metaheuristics-based clustering and routing protocol.
• Utilized Cultural Emperor Penguin Optimizer-based Clustering (CEPOC) for cluster head selection.
• Integrated Multi-Hop Routing with Grasshopper Optimization Algorithm (MHR-GOA) for efficient data transmission.

Main Results:

• MCR-UWSN demonstrated superior performance compared to existing state-of-the-art techniques.
• The protocol effectively addresses challenges like underwater currents and propagation delays.
• Experimental validation confirmed enhanced energy efficiency and network longevity.

Conclusions:

• MCR-UWSN offers a viable solution for energy-efficient routing in UWSN.
• The proposed metaheuristic approach significantly improves network performance.
• This work contributes to the advancement of underwater communication systems.