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...
share
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
∙
01/21/2023
Leveraging Spatial and Temporal Correlations for Network Traffic Compression
The deployment of modern network applications is increasing the network ...
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
∙
05/27/2022
Network Digital Twin: Context, Enabling Technologies and Opportunities
The proliferation of emergent network applications (e.g., telesurgery, m...
research
∙
04/01/2022
Convergence analysis of discrete high-index saddle dynamics
Saddle dynamics is a time continuous dynamics to efficiently compute the...
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
∙
02/01/2022
Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies
The recent growth of emergent network applications (e.g., satellite netw...
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
∙
12/23/2021
Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks
Machine learning is gaining growing momentum in various recent models fo...
research
∙
09/22/2021
