76 citations · 170 across the 12 of their papers we have counts for
7 papers · 1 filter
Leveraging Multi-Step Traffic Forecasts for Multi-Period Planning Optical Networks
Giannis Savva, Hafsa Maryam, Venkatesh Chebolu +2
In this work, multi-step traffic predictions are leveraged to enable multi-period planning in reconfigurable optical networks. The proposed framework aims to achieve spectrum savin…
A Fair Federated Learning Framework for Collaborative Network Traffic Prediction and Resource Allocation
Saroj Kumar Panda, Tania Panayiotou, Georgios Ellinas +1
In the beyond 5G era, AI/ML empowered realworld digital twins (DTs) will enable diverse network operators to collaboratively optimize their networks, ultimately improving end-user…
Multi-Step Traffic Prediction for Multi-Period Planning in Optical Networks
Hafsa Maryam, Tania Panayiotou, Georgios Ellinas
A multi-period planning framework is proposed that exploits multi-step ahead traffic predictions to address service overprovisioning and improve adaptability to traffic changes, wh…
Survey on Machine Learning for Traffic-Driven Service Provisioning in Optical Networks
Tania Panayiotou, Maria Michalopoulou, Georgios Ellinas
The unprecedented growth of the global Internet traffic, coupled with the large spatio-temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are…
Fair Resource Allocation in Optical Networks under Tidal Traffic
Tania Panayiotou, Georgios Ellinas
We propose an alpha-fair routing and spectrum allocation (RSA) framework for reconfigurable elastic optical networks under modeled tidal traffic, that is based on the maximization…
Centralized and Distributed Machine Learning-Based QoT Estimation for Sliceable Optical Networks
Tania Panayiotou, Giannis Savva, Ioannis Tomkos +1
Dynamic network slicing has emerged as a promising and fundamental framework for meeting 5G's diverse use cases. As machine learning (ML) is expected to play a pivotal role in the…
Machine Learning for QoT Estimation of Unseen Optical Network States
Tania Panayiotou, Giannis Savva, Behnam Shariati +2
We apply deep graph convolutional neural networks for Quality-of-Transmission estimation of unseen network states capturing, apart from other important impairments, the inter-core…