Improved Metaheuristics-Based Clustering with Multihop Routing Protocol for Underwater Wireless Sensor Networks.

Area of Science:

• Marine technology
• Wireless communication networks
• Sensor networks

Background:

• Underwater wireless sensor networks (UWSNs) are crucial for marine applications but face energy constraints due to limited battery life and difficult recharging.
• Energy efficiency is a primary challenge in UWSN design, impacting network longevity and operational capabilities.
• Clustering and routing are recognized as effective strategies for improving energy efficiency in UWSNs.

Purpose of the Study:

• To introduce an improved metaheuristics-based clustering with multihop routing protocol for UWSNs, named IMCMR-UWSN.
• To enhance the energy efficiency and lifetime of underwater wireless sensor networks.
• To optimize the selection of cluster heads and the determination of optimal routes for data transmission.

Main Methods:

• The IMCMR-UWSN technique employs a two-stage approach: chaotic krill head algorithm (CKHA) for clustering and self-adaptive glow worm swarm optimization (SA-GSO) for multihop routing.
• CKHA selects cluster heads based on residual energy, intra-cluster distance, and inter-cluster distance.
• SA-GSO utilizes a fitness function incorporating residual energy, delay, distance, and trust for route optimization.

Main Results:

• The IMCMR-UWSN technique significantly improves the energy efficiency of UWSNs.
• The proposed protocol effectively extends the operational lifetime of underwater wireless sensor networks.
• Simulation results demonstrate the superiority of IMCMR-UWSN over existing methods in various performance metrics.

Conclusions:

• The IMCMR-UWSN technique offers a promising solution for addressing energy efficiency challenges in UWSNs.
• The integration of metaheuristic algorithms like CKHA and SA-GSO enhances network performance.
• This approach contributes to the development of more sustainable and effective underwater sensing systems.