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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Improved Metaheuristics-Based Clustering with Multihop Routing Protocol for Underwater Wireless Sensor Networks.

Prakash Mohan1, Neelakandan Subramani2, Youseef Alotaibi3

  • 1Department of Computer Science and Engineering, Karpagam College of Engineering, Coimbatore 641032, India.

Sensors (Basel, Switzerland)
|February 26, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an improved metaheuristics-based protocol for underwater wireless sensor networks (UWSNs) to enhance energy efficiency. The new technique optimizes cluster head selection and routing, significantly extending network lifetime.

Keywords:
communicationenergy efficiencymetaheuristicsnetwork lifetimeroutingunderwater sensor networks

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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.