Poster: Continual Network Learning
Nicola Di Cicco, Amir Al Sadi, Chiara Grasselli, Andrea Melis, Gianni Antichi, Massimo Tornatore · 2023
We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forgetting past experiences. We propose implementing Active Learning-based selective data filtering in the data plane, allowing for data-efficient continual updates. We explore relevant challenges and propose future research directions.