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Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning.

S Ramesh1, R Rajalakshmi2, Jaiprakash Narain Dwivedi3

  • 1Department of Artificial Intelligence and Machine Learning, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India.

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Summary
This summary is machine-generated.

This study enhances Wireless Sensor Network (WSN) efficiency by modifying the k-means clustering algorithm with the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. The optimized approach improves network lifetime and data transfer success rates.

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Area of Science:

  • Computer Science
  • Machine Learning
  • Wireless Communication

Background:

  • Wireless Sensor Networks (WSNs) are crucial for data collection in inaccessible areas.
  • Existing routing protocols, like Low Energy Adaptive Clustering Hierarchy (LEACH), face efficiency limitations.
  • Optimizing cluster head selection is vital for improving WSN performance and network longevity.

Purpose of the Study:

  • To enhance the efficiency and network lifetime of Wireless Sensor Networks (WSNs).
  • To optimize the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol using a modified k-means clustering algorithm.
  • To improve the cluster head selection process for more efficient data routing.

Main Methods:

  • Integration of a modified k-means clustering algorithm with the LEACH protocol.
  • Implementation of a weighted cluster head selection mechanism.
  • Utilization of the Euclidean distance formula for cluster formation.

Main Results:

  • The proposed modified k-means with LEACH achieved a 48.85% efficiency improvement over existing protocols.
  • Demonstrated a higher rate of successful data transfer to the sink node.
  • The optimized cluster head selection led to a reduced failure rate and balanced network energy consumption.

Conclusions:

  • The modified k-means algorithm significantly enhances WSN performance and network lifetime.
  • The proposed approach offers a more robust and energy-efficient solution for WSN data routing.
  • This optimization balances energy consumption and ensures successful data transmission in WSNs.