Q-RPL: Q-Learning-Based Routing Protocol for Advanced Metering Infrastructure in Smart Grids

• DOI: 10.3390/s24154818
• Publication Date: 2024-07-25T10:11:36Z
• Authors: Carlos Lester Due...; Ahmad Mohamad Mezher; Juan Pablo Astudi...; Julian Cardenas B...; Eduardo Castillo ...; Julian Meng
• Keywords: Zone Routing Protocol

Efficient and reliable data routing is critical in Advanced Metering Infrastructure (AMI) within Smart Grids, dictating the overall network performance resilience. This paper introduces Q-RPL, a novel Q-learning-based Routing Protocol designed to enhance decisions AMI deployments based on wireless mesh technologies. Q-RPL leverages principles of Reinforcement Learning (RL) dynamically select optimal next-hop forwarding candidates, adapting changing conditions. The protocol operates top standard IPv6 for Low-Power Lossy Networks (RPL), integrating it with intelligent decision-making capabilities. Through extensive simulations carried out real map scenarios, demonstrates significant improvement key metrics such as packet delivery ratio, end-to-end delay, compliant factor compared RPL implementation other benchmark algorithms found literature. adaptability robustness mark advancement evolution protocols Grid AMI, promising enhanced efficiency reliability future energy systems. findings this study also underscore potential improve networking protocols.