José Suárez-Varela

IEEE/ACM Trans. Netw., December, 2023

MAGNNETO: A Graph Neural Network-Based Multi-Agent System for Traffic Engineering.

[BibT_eX]

[DOI]

IEEE Trans. Cogn. Commun. Netw., April, 2023

Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities.

[BibT_eX]

[DOI]

IEEE Netw., 2023

GraphCC: A Practical Graph Learning-based Approach to Congestion Control in Datacenters.

[BibT_eX]

[DOI]

CoRR, 2023

Detecting Contextual Network Anomalies with Graph Neural Networks.

[BibT_eX]

[DOI]

Hamid Latif

Proceedings of the 2nd on Graph Neural Networking Workshop 2023, 2023

Enhancing 5G Radio Planning with Graph Representations and Deep Learning.

[BibT_eX]

[DOI]

Andra Lutu

Proceedings of the 3rd ACM Workshop on 5G and Beyond Network Measurements, 2023

2022

Unveiling the potential of Graph Neural Networks for robust Intrusion Detection.

[BibT_eX]

[DOI]

David Pujol-Perich

SIGMETRICS Perform. Evaluation Rev., 2022

RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation.

[BibT_eX]

[DOI]

CoRR, 2022

Digital Twin Network: Opportunities and Challenges.

[BibT_eX]

[DOI]

Antonio Agustin Pastor Perales

CoRR, 2022

Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case.

[BibT_eX]

[DOI]

Comput. Commun., 2022

Building a Digital Twin for network optimization using Graph Neural Networks.

[BibT_eX]

[DOI]

Comput. Networks, 2022

Network Digital Twin: Context, Enabling Technologies, and Opportunities.

[BibT_eX]

[DOI]

Antonio Agustin Pastor Perales

IEEE Commun. Mag., 2022

Exploring the Limitations of Current Graph Neural Networks for Network Modeling.

[BibT_eX]

[DOI]

Proceedings of the 2022 IEEE/IFIP Network Operations and Management Symposium, 2022

RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2022, 2022

Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing.

[BibT_eX]

[DOI]

Proceedings of the 18th International Conference on Network and Service Management, 2022

2021

IGNNITION: Bridging the Gap between Graph Neural Networks and Networking Systems.

[BibT_eX]

[DOI]

IEEE Netw., 2021

Scaling Graph-based Deep Learning models to larger networks.

[BibT_eX]

[DOI]

Krzysztof Rusek

CoRR, 2021

The graph neural networking challenge: a worldwide competition for education in AI/ML for networks.

[BibT_eX]

[DOI]

Comput. Commun. Rev., 2021

IGNNITION: fast prototyping of graph neural networks for communication networks.

[BibT_eX]

[DOI]

David Pujol-Perich

Bo Wu

Shihan Xiao

Xiangle Cheng

Proceedings of the SIGCOMM '21: ACM SIGCOMM 2021 Conference, 2021

Is Machine Learning Ready for Traffic Engineering Optimization?

[BibT_eX]

[DOI]

Proceedings of the 29th IEEE International Conference on Network Protocols, 2021

Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges.

[BibT_eX]

[DOI]

José Rafael Suárez-Varela Macià

Proceedings of the 22nd IEEE International Conference on High Performance Switching and Routing, 2021

2020

Enabling knowledge-defined networks : deep reinforcement learning, graph neural networks and network analytics.

[BibT_eX]

[DOI]

PhD thesis, 2020

RouteNet: Leveraging Graph Neural Networks for Network Modeling and Optimization in SDN.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2020

Applying Graph-based Deep Learning To Realistic Network Scenarios.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Routing in optical transport networks with deep reinforcement learning.

[BibT_eX]

[DOI]

JOCN, 2019

Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case.

[BibT_eX]

[DOI]

CoRR, 2019

Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN.

[BibT_eX]

[DOI]

Proceedings of the 2019 ACM Symposium on SDN Research, 2019

Challenging the generalization capabilities of Graph Neural Networks for network modeling.

[BibT_eX]

[DOI]

Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos, 2019

Routing Based on Deep Reinforcement Learning in Optical Transport Networks.

[BibT_eX]

[DOI]

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2019

Detecting cryptocurrency miners with NetFlow/IPFIX network measurements.

[BibT_eX]

[DOI]

Jordi Zayuelas i Muñoz

Proceedings of the 5th IEEE International Symposium on Measurements & Networking, 2019

Feature Engineering for Deep Reinforcement Learning Based Routing.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Communications, 2019

Towards more realistic network models based on Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies, 2019

2018

Flow monitoring in Software-Defined Networks: Finding the accuracy/performance tradeoffs.

[BibT_eX]

[DOI]

Comput. Networks, 2018

SBAR: SDN flow-Based monitoring and Application Recognition.

[BibT_eX]

[DOI]

Proceedings of the Symposium on SDN Research, 2018

Towards accurate classification of HTTPS traffic in Software-Defined Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2018

2017

Reinventing NetFlow for OpenFlow Software-Defined Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Towards a NetFlow Implementation for OpenFlow Software-Defined Networks.

[BibT_eX]

[DOI]