An FL-based Energy-Efficient Opportunistic Intelligent Node Selection Scheme for Healthcare IoV Applications
Pallati Narsimhulu, Rashmi Sahay · 2025
The complexity of managing the energy and operational needs in large-scale Wireless Sensor Networks (WSNs) emphasizes the importance of energy-aware routing. This paper proposes an energy-efficient routing protocol that uses an intelligent node selection scheme to address energy-aware routing in the healthcare Internet of Vehicles (IoV). The protocol identifies the most suitable cluster leader based on dynamic criteria. By building on a ranking system that considers factors like location and remaining energy, the protocol selects the next intelligent node to establish the most energy-efficient route within the Internet of Things (IoT) context. The energy-aware routing scheme is tested across various clustering systems to evaluate its impact on route discovery based on system size and time. Experimental results show that the model reduces energy consumption during broadcast operations. Performance metrics such as Jitter and Packet Loss Ratio (PLR) further illustrate the protocol’s energy optimization. Simulation results across diverse network conditions demonstrate the superiority of adaptive ranking and intelligent forwarder node selection over competing strategies. Overall, the proposed protocol presents a promising solution for achieving energy-efficient routing in IoV, offering insights into optimized strategies and their benefits for IoT applications.