José Suárez-Varela
José Suárez-Varela
Postdoctoral Reasearcher, Barcelona Neural Networking Center, Universitat Politècnica de Catalunya
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Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN
K Rusek, J Suárez-Varela, A Mestres, P Barlet-Ros, A Cabellos-Aparicio
Proceedings of the ACM Symposium on SDN Research (SOSR), 140-151, 2019
RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN
K Rusek, J Suárez-Varela, P Almasan, P Barlet-Ros, A Cabellos-Aparicio
IEEE Journal on Selected Areas in Communications (JSAC), 2020
Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case
P Almasan, J Suárez-Varela, A Badia-Sampera, K Rusek, P Barlet-Ros, ...
arXiv, arXiv: 1910.07421, 2019
Routing in optical transport networks with deep reinforcement learning
J Suárez-Varela, A Mestres, J Yu, L Kuang, H Feng, A Cabellos-Aparicio, ...
Journal of Optical Communications and Networking 11, 547-558, 2019
Feature engineering for Deep Reinforcement Learning based routing
J Suárez-Varela, A Mestres, J Yu, L Kuang, H Feng, P Barlet-Ros, ...
IEEE International Conference on Communications (ICC), 2019
Routing Based on Deep Reinforcement Learning in Optical Transport Networks
J Suárez-Varela, A Mestres, J Yu, L Kuang, H Feng, P Barlet-Ros, ...
Optical Fiber Communications Conference and Exhibition (OFC), San Diego, USA, 2019
Flow monitoring in Software-Defined Networks: Finding the accuracy/performance tradeoffs
J Suárez-Varela, P Barlet-Ros
Computer Networks 135, 289-301, 2018
Towards a NetFlow implementation for OpenFlow Software-Defined Networks
J Suárez-Varela, P Barlet-Ros
29th International Teletraffic Congress (ITC), 2017 1, 187-195, 2017
Challenging the generalization capabilities of Graph Neural Networks for network modeling
J Suárez-Varela, S Carol-Bosch, K Rusek, P Almasan, M Arias, ...
Proceedings of ACM SIGCOMM Posters and Demos, 114-115, 2019
Detecting cryptocurrency miners with NetFlow/IPFIX network measurements
J Zayuelas i Muñoz, J Suárez-Varela, P Barlet-Ros
IEEE International Symposium on Measurements and Networking (M&N), 2019
SBAR: SDN flow-Based monitoring and Application Recognition
J Suárez-Varela, P Barlet-Ros
Proceedings of the Symposium on SDN Research (SOSR), 2018
Reinventing NetFlow for OpenFlow Software-Defined Networks (technical report)
J Suárez-Varela, P Barlet-Ros
arXiv preprint arXiv:1702.06803, 2017
Towards more realistic network models based on Graph Neural Networks
A Badia-Sampera, J Suárez-Varela, P Almasan, K Rusek, P Barlet-Ros, ...
Proceedings of ACM CoNEXT student workshop, 14-16, 2019
Is Machine Learning Ready for Traffic Engineering Optimization?
G Bernárdez, J Suárez-Varela, A López, B Wu, S Xiao, X Cheng, ...
IEEE International Conference on Network Protocols (ICNP), 2021
IGNNITION: Bridging the Gap between Graph Neural Networks and Networking Systems
D Pujol-Perich, J Suárez-Varela, M Ferriol, S Xiao, B Wu, ...
IEEE Network 35 (6), 171-177, 2021
Applying Graph-based Deep Learning To Realistic Network Scenarios
M Ferriol-Galmés, J Suárez-Varela, P Barlet-Ros, A Cabellos-Aparicio
arXiv preprint arXiv:2010.06686, 2020
Network Digital Twin: Context, Enabling Technologies and Opportunities
P Almasan, M Ferriol-Galmés, J Paillisse, J Suárez-Varela, D Perino, ...
arXiv preprint arXiv:2205.14206, 2022
The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks
J Suárez-Varela, M Ferriol-Galmés, A López, P Almasan, G Bernárdez, ...
ACM SIGCOMM Computer Communication Review 51 (3), 2021
Scaling Graph-based Deep Learning models to larger networks
M Ferriol-Galmés, J Suárez-Varela, K Rusek, P Barlet-Ros, ...
arXiv preprint arXiv:2110.01261, 2021
Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges
P Almasan, J Suárez-Varela, B Wu, S Xiao, P Barlet-Ros, ...
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