Swarm Intelligence Driven CH Selection for Energy Optimization in IoT Enabled WSNs
Journal of Future Networks and Communications
Received On : 01 November 2024
Revised On : 02 December 2024
Accepted On : 15 December 2024
Published On : 05 January 2025
Volume 01, Issue 01
Pages : 023-032
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Abstract
Wireless Sensor Networks (WSNs) are an important part of the Internet of Things (IoT), where saving energy is crucial because sensor nodes run on batteries. Choosing the best cluster heads (CHs) in these networks helps improve performance and save energy. This analysis introduces a way to pick CHs using a swarm intelligence technique called Ant Colony Optimization (ACO). The goal is to reduce energy use and extend the network's life by choosing the best Cluster Head for each group of sensors. This method involves sensor nodes clustering according to proximity, while ACO identifies the optimal Cluster Head by balancing energy levels and communication loads. The technique undergoes testing through MATLAB simulations, demonstrating a 20% decrease in energy consumption and an extended network lifespan relative to established methods such as LEACH and EECHIGWO. This swarm intelligence technique improves network performance by minimizing superfluous data transmission and optimizing energy consumption, rendering it a promising strategy for IoT-enabled WSNs.
Keywords
Swarm Intelligence, CH Selection, Energy Optimization, Ant Colony Optimization, Network Lifetime, Energy Consumption.
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Wasif Akbar, "Swarm Intelligence Driven CH Selection for Energy Optimization in IoT Enabled WSNs", Journal of Future Networks and Communications, vol.1, no.1, pp. 023-032, January 2025. doi: XXXX/XXXX/JFNC202501003.
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© 2025 Wasif Akbar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.