Seminar Details
2026-02-25 (11:00) : Closed Loop Automation System for xG networks
At Shannon
Organized by Computer Science and Engineering
Speakers :
Stefano Secci (CNAM, France)
,
and
Patient NTUMBA WA NTUMBA (CNAM Paris)
Abstract :
In this presentation, we present a closed-loop automation system that leverages in-network distributed learning to automatically mitigate anomalous states in the connect-compute software infrastructure. We describe the key components of the automation system, including: an anomaly detection module based on federated learning; AI function scheduling to meet detection performance targets while mitigating federated learning stragglers; a data-pipeline design that supports high accuracy, real-time preprocessing, and timely data delivery; a network data sources load-balancing strategy for federated-learning clients; and automated reconfiguration management using deep reinforcement learning (DRL). We also deliver a live demo of the core system blocks—showing, in real time, the anomalies detected during the inference phase using federated learning with real-time data pipelining.