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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...
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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...
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01/21/2023
Leveraging Spatial and Temporal Correlations for Network Traffic Compression
The deployment of modern network applications is increasing the network ...
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12/22/2022
RouteNet-Fermi: Network Modeling with Graph Neural Networks
Network models are an essential block of modern networks. For example, t...
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05/27/2022
Network Digital Twin: Context, Enabling Technologies and Opportunities
The proliferation of emergent network applications (e.g., telesurgery, m...
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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...
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01/04/2022
Digital Twin Network: Opportunities and Challenges
The proliferation of emergent network applications (e.g., AR/VR, telesur...
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12/29/2021
Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities
Graph neural networks (GNN) have shown outstanding applications in many ...
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09/22/2021
ENERO: Efficient Real-Time Routing Optimization
Wide Area Networks (WAN) are a key infrastructure in today's society. Du...
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03/07/2021
Improving Text-to-SQL with Schema Dependency Learning
Text-to-SQL aims to map natural language questions to SQL queries. The s...
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02/21/2018