Scaling Graph Neural Networks (GNN) for Real-Time Modeling of Network Behaviour

Network modeling has long been a well-established field of study. More recently, Graph Neural Network based models have demonstrated remarkable capability in capturing complex interactions in network data without assumptions about physical networks. While this characteristic facilitates integration across various telecom access networks, current benchmark models remain impractical for real-world deployment, due to real-time demands of modern infrastructure.