5 papers
Retrieval-Based Cross-Domain Generalization in Optical Networks via Global Features
Ali Al Housseini, Carlos Natalino, Paolo Monti +1
We propose a retrieval-based framework for crossdomain quality-of-transmission (QoT) estimation that leverages transferable feature representations while avoiding reliance on sourc…
Explanation-Based Runtime Verification for Trustworthy ML-driven Optical Networks
Omran Ayoub, Carlos Natalino, Ali Al Housseini +5
Machine learning (ML) models are increasingly integrated into optical network automation frameworks to support tasks such as failure management, performance monitoring and resource…
Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning
Ali Al Housseini, Carlos Natalino, Paolo Monti +1
The robustness of machine learning techniques across heterogeneous network domains remains an open challenge in optical networks. Models trained on data from a specific topology or…
Exploiting the Alternatives: Coordinated Learning via Hierarchical RL for Dynamic VNEAP
Ali Al Housseini, Cristina Rottondi, Omran Ayoub +1
Virtual Network Embedding (VNE) is a key enabler of network slicing, yet most formulations assume that each Virtual Network Request (VNR) has a fixed topology. Recently, VNE with A…
MuMeNet: A Network Simulator for Musical Metaverse Communications
Ali Al Housseini, Jaime Llorca, Luca Turchet +3
The Metaverse, a shared and spatially organized digital continuum, is transforming various industries, with music emerging as a leading use case. Live concerts, collaborative compo…