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A novel network lifetime maximization technique in WSN using energy efficient algorithms.

K Vijayalakshmi1, A Maheshwari1, K Saravanan2

  • 1Department of Computational Intelligence, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India.

Scientific Reports
|March 28, 2025
PubMed
Summary

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This summary is machine-generated.

This study introduces a new routing method for Wireless Sensor Networks (WSNs) using genetic and exhaustive search algorithms. It significantly extends network lifetime (NL) and optimizes energy use for better performance.

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) are vital for healthcare, environmental monitoring, and industrial automation.
  • Maximizing network lifetime (NL) and energy efficiency are critical challenges in WSNs.
  • Existing routing algorithms often fail to balance energy efficiency and service quality, causing premature network failure.

Purpose of the Study:

  • To propose a novel approach for enhancing network lifetime (NL) in Wireless Sensor Networks (WSNs).
  • To optimize energy-efficient routing by integrating genetic and exhaustive search algorithms.
  • To improve data transmission reliability and energy conservation in WSNs.

Main Methods:

  • Integration of a Single Objective Genetic Algorithm (SOGA) and an Advanced Exhaustive Search Algorithm (AESA).
Keywords:
Energy efficientNetwork lifetimeSearch algorithmWireless sensor network

Related Experiment Videos

  • Optimization of energy-efficient routing using proximity ranging, network lifetime, interaction counting, and link effectiveness.
  • Evaluation using a network simulator to compare against conventional routing protocols.

    • Main Results:

    • The proposed method significantly outperforms existing protocols in energy conservation and data transmission reliability.
    • Extended network lifetime (NL) while maintaining an optimal balance between energy consumption and service quality.
    • Improved key performance indicators including average edge delay, latency, and packet delivery ratio.

    Conclusions:

    • The novel approach effectively extends network lifetime (NL) in Wireless Sensor Networks (WSNs).
    • Achieved an optimal balance between energy consumption and service quality for WSNs.
    • Offers an advanced energy-efficient routing solution with implications for smart cities and industrial IoT.