What is it about?
It focuses on efficient load balancing between WiFi and LiFi networks to maximize overall network performance. The method uses ensemble machine learning models to intelligently predict and manage traffic distribution. It aims to achieve stable, high-speed, and energy-efficient communication in hybrid wireless systems.
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Why is it important?
It enables high-speed and reliable connectivity by intelligently distributing traffic across WiFi and LiFi. It reduces network congestion, latency, and signal drop issues, especially in dense environments. It supports the evolution toward next-generation wireless systems that demand seamless, energy-efficient communication.
Perspectives
The approach can be extended to 6G and IoT ecosystems for intelligent network management. Future work may integrate reinforcement learning for real-time adaptive decision-making. It opens possibilities for energy-aware and context-driven load balancing in dynamic wireless environments.
Dr ARUL KING J
St.Xavier's Catholic College of Engineering
Read the Original
This page is a summary of: Optimized load balancing in hybrid WiFi-LiFi networks using ensemble learning methods, IET Conference Proceedings, March 2025, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/icp.2025.0958.
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