research
∙
09/07/2023
Enhancing 5G Radio Planning with Graph Representations and Deep Learning
The roll out of new mobile network generations poses hard challenges due...
share
research
∙
08/09/2023
GraphCC: A Practical Graph Learning-based Approach to Congestion Control in Datacenters
Congestion Control (CC) plays a fundamental role in optimizing traffic i...
research
∙
03/31/2023
MAGNNETO: A Graph Neural Network-based Multi-Agent system for Traffic Engineering
Current trends in networking propose the use of Machine Learning (ML) fo...
research
∙
12/22/2022
RouteNet-Fermi: Network Modeling with Graph Neural Networks
Network models are an essential block of modern networks. For example, t...
research
∙
09/21/2022
Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing
Emerging applications such as the metaverse, telesurgery or cloud comput...
research
∙
05/27/2022
Network Digital Twin: Context, Enabling Technologies and Opportunities
The proliferation of emergent network applications (e.g., telesurgery, m...
research
∙
02/28/2022
RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation
Network modeling is a fundamental tool in network research, design, and ...
research
∙
01/04/2022
Digital Twin Network: Opportunities and Challenges
The proliferation of emergent network applications (e.g., AR/VR, telesur...
research
∙
12/29/2021
Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities
Graph neural networks (GNN) have shown outstanding applications in many ...
research
∙
10/04/2021
Scaling Graph-based Deep Learning models to larger networks
Graph Neural Networks (GNN) have shown a strong potential to be integrat...
research
∙
07/30/2021
Unveiling the potential of Graph Neural Networks for robust Intrusion Detection
The last few years have seen an increasing wave of attacks with serious ...
research
∙
10/13/2020
Applying Graph-based Deep Learning To Realistic Network Scenarios
Recent advances in Machine Learning (ML) have shown a great potential to...
research
∙
10/16/2019
Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case
Recent advances in Deep Reinforcement Learning (DRL) have shown a signif...
research
∙
10/03/2019
RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN
Network modeling is a key enabler to achieve efficient network operation...
research
∙
01/23/2019