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Miquel Ferriol Galmés edited this page Dec 20, 2022 · 44 revisions

PAPERS

  • Miquel Ferriol-Galmés, José Suárez-Varela, Jordi Paillissé, Bo Wu, Shihan Xiao, Xiangle Cheng, Pere Barlet-Ros and Albert Cabellos-Aparicio; "Building a Digital Twin for network optimization using Graph Neural Networks", Computer Networks, November 2022. [DOI]

  • Miquel Ferriol-Galmés, Krzysztof Rusek, José Suárez-Varela, Shihan Xiao, Xiang Shi, Xiangle Cheng, Bo Wu, Pere Barlet-Ros and Albert Cabellos-Aparicio; "RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation", IEEE INFOCOM 2022-IEEE Conference on Computer Communications, May 2022. [DOI] [ArXiv]

  • José Suárez-Varela, Paul Almasan, Miquel Ferriol-Galmés, Krzysztof Rusek, Fabien Geyer, Xiangle Cheng, Xiang Shi, Shihan Xiao, Franco Scarselli, Albert Cabellos-Aparicio, Pere Barlet-Ros; “Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities”, IEEE Network, Jul. 2022. [DOI][ArXiv]

  • Paul Almasan, Miquel Ferriol-Galmés, Jordi Paillisse, José Suárez-Varela, Diego Perino, Diego López, Antonio Agustin Pastor Perales, Paul Harvey, Laurent Ciavaglia, Leon Wong, Vishnu Ram, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros; “Network Digital Twin: Context, Enabling Technologies and Opportunities”, IEEE Communications Magazine, May. 2022. [DOI] [ArXiv]

  • Carlos Güemes-Palau, Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio; “Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies”, IEEE NOMS, Feb. 2022. [ArXiv]

  • David Pujol-Perich, José Suárez-Varela, Miquel Ferriol, Shihan Xiao, Bo Wu, Albert Cabellos-Aparicio, Pere Barlet-Ros; “IGNNITION: Bridging the Gap Between Graph Neural Networks and Networking Systems”, IEEE Network, Nov. 2021. [ArXiv]

  • Guillermo Bernárdez, José Suárez-Varela, Albert López, Bo Wu, Shihan Xiao, Xiangle Cheng, Pere Barlet-Ros and Albert Cabellos-Aparicio; "Is Machine Learning Ready for Traffic Engineering Optimization?", IEEE International Conference on Network Protocols (ICNP), Nov. 2021. [ArXiv]

  • Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio; “ENERO: Efficient real-time WAN routing optimization with Deep Reinforcement Learning”, Computer Networks, Jul. 2022. [DOI] [ArXiv]

  • David Pujol-Perich, José Suárez-Varela, Miquel Ferriol-Galmés, Bo Wu, Shihan Xiao, Xiangle Cheng, Albert Cabellos-Aparicio, and Pere Barlet-Ros; "IGNNITION: fast prototyping of graph neural networks for communication networks", ACM SIGCOMM Posters and Demos, Aug. 2021. [Paper] [Video] [iGNNition]

  • David Pujol-Perich, José Suárez-Varela, Shihan Xiao, Bo Wu, Albert Cabellos-Aparicio, Pere Barlet-Ros; "NetXplain: Real-time explainability of Graph Neural Networks applied to networking", ITU Journal on Future and Evolving Technologies (J-FET), Vol 2, No. 4, Aug. 2021. [Paper]

  • José Suárez-Varela, et al.; "The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks", ACM SIGCOMM Computer Communication Review, July 2021. [ArXiv] [DOI]

  • David Pujol-Perich, José Suárez-Varela, Albert Cabellos-Aparicio, and Pere Barlet-Ros; “Unveiling the potential of Graph Neural Networks for robust Intrusion Detection”, Workshop on AI in Networks and Distributed Systems, July 2021. [ArXiv]

  • Paul Almasan, José Suárez-Varela, Bo Wu, Shihan Xiao, Pere Barlet-Ros, and Albert Cabellos-Aparicio; "Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges", IEEE HPSR Semantic Addressing and Routing for Future Networks Workshop, June 2021. [ArXiv]

  • Sergi Abadal, Akshay Jain, Robert Guirado, Jorge López-Alonso, and Eduard Alarcón; "Computing Graph Neural Networks: A Survey from Algorithms to Accelerators", ACM Computing Surveys, July 2021. [Paper]

  • David Pujol-Perich, José Suárez-Varela, Shihan Xiao, Bo Wu, Albert Cabellos-Aparicio and Pere Barlet-Ros; "NetXplain: Real-time explainability of Graph Neural Networks applied to Computer Networks", Workshop on Graph Neural Networks and Systems (GNNSys), April 2021. [Paper]

  • David Pujol-Perich, José Suárez-Varela, Miquel Ferriol-Galmés, Shihan Xiao, Bo Wu, Albert Cabellos-Aparicio and Pere Barlet-Ros; "IGNNITION: A framework for fast prototyping of Graph Neural Networks", Workshop on Graph Neural Networks and Systems (GNNSys), April 2021. [Paper]

  • Krzysztof Rusek, José Suárez-Varela, Paul Almasan, Pere Barlet-Ros, Albert Cabellos-Aparicio; "RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN", IEEE Journal on Selected Areas in Communications (JSAC), June 2020. [ArXiv] [DOI]

  • Paul Almasan, José Suárez-Varela, Arnau Badia-Sampera, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio "Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case", February 2020. [ArXiv]

  • Arnau Badia-Sampera, José Suárez-Varela, Paul Almasan, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio; "Towards more realistic network models based on Graph Neural Networks", in ACM CoNEXT Student Workshop, December 2019.

  • José Suárez-Varela, Albert Mestres, Junlin Yu, Li Kuang, Haoyu Feng, Albert Cabellos-Aparicio, Pere Barlet-Ros; "Routing in Optical Transport Networks with Deep Reinforcement Learning", Journal of Optical Communications and Networking, vol. 11, pp 547-558, September 2019 [proceedings]

  • José Suárez-Varela, Sergi Carol-Bosch, Krzysztof Rusek, Paul Almasan, Marta Arias, Pere Barlet-Ros, Albert Cabellos-Aparicio; "Challenging the generalization capabilities of Graph Neural Networks for network modeling," in ACM SIGCOMM Posters and Demos, August 2019

  • José Suárez-Varela, Albert Mestres, Junlin Yu, Li Kuang, Haoyu Feng, Pere Barlet-Ros, Albert Cabellos-Aparicio; "Feature Engineering for Deep Reinforcement Learning Based Routing," in IEEE International Conference on Communications (ICC), May 2019 [proceedings]

  • Krzysztof Rusek, José Suárez-Varela, Albert Mestres, Pere Barlet-Ros, Albert Cabellos-Aparicio; "Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN," in and in ACM Symposium on SDN Research (SOSR) , pp. 140-151, April 2019

  • José Suárez-Varela, Albert Mestres, Junlin Yu, Li Kuang, Haoyu Feng, Pere Barlet-Ros, Albert Cabellos-Aparicio; "Routing based on Deep Reinforcement Learning in Optical Transport Networks," in Proceedings of the Optical Fiber Communication Conference (OFC), San Diego, USA, March 2019 [paper]

  • Albert Mestres, Eduard Alarcón, Yusheng Ji, Albert Cabellos-Aparicio; "Understanding the Modeling of Computer Network Delays using Neural Networks," in Proceedings of the ACM SIGCOMM Workshop on Big Data Analytics and Machine Learning for Data Communication Networks (Big-DAMA), August 2018

  • Careglio, D., Spadaro, S., Cabellos, A., Lazaro, J. A., Perelló, J., Barlet, P., ... & Paillissé, J. (2018, July). "ALLIANCE Project: Architecting a knowledge-defined 5G-enabled network infrastructure". In 2018 20th International Conference on Transparent Optical Networks (ICTON) (pp. 1-6). IEEE. July 2018 [proceedings]

  • José Suárez-Varela, Pere Barlet-Ros, Albert Mestres, Albert Cabellos; "QoE-aware network management based on Deep Reinforcement Learning," in Network Traffic Measurement and Analysis Conference (TMA), Poster session, Viena, Austria, June 2018

  • José Suárez-Varela, Pere Barlet-Ros; "Flow monitoring in Software-Defined Networks: Finding the accuracy/performance tradeoffs," Computer Networks, vol. 135, pp 289-301, April 2018 [paper]

  • Albert Mestres, Eduard Alarcón, Albert Cabellos, "A machine learning-based approach for virtual network function modeling", in Wireless Communications and Networking Conference Workshops (WCNCW), April 2018 [proceedings]

  • José Suárez-Varela, Pere Barlet-Ros; "SBAR: SDN flow-Based monitoring and Application Recognition, in ACM Symposium on SDN Research (SOSR), Demo session, Los Angeles, USA, March 2018 [preprint] [proceedings]

  • Giorgio Stampa, Marta Arias, David Sanchez-Charles, Victor Muntes-Mulero, Albert Cabellos; "A Deep-Reinforcement Learning Approach for Software-Defined Networking Routing Optimization" in [ACM CoNEXT 2017 Student Workshop], December 2017 [ArXiv] [program]

  • Albert Mestres, Alberto Rodriguez-Natal, Josep Carner, Pere Barlet-Ros, Eduard Alarcón, Marc Solé, Victor Muntés, David Meyer, Sharon Barkai, Mike J Hibbett, Giovani Estrada, Florin Coras, Vina Ermagan, Hugo Latapie, Chris Cassar, John Evans, Fabio Maino, Jean Walrand, Albert Cabellos; "Knowledge-Defined Networking," in ACM SIGCOMM Computer Communication Review, vol. 47, number 3, pp. 2-10, July 2017

  • Josep Carner, Albert Mestres, Eduard Alarcón, Albert Cabellos, "Machine learning-based network modeling: An artificial neural network model vs a theoretical inspired model", in Ubiquitous and Future Networks (ICUFN), 2017 Ninth International Conference on, July 2017 [proceedings]

  • Rodriguez-Natal, A., Paillisse, J., Coras, F., Lopez-Bresco, A., Jakab, L., Portoles-Comeras, M., ... & Maino, F. (2017). "Programmable overlays via OpenOverlayRouter". IEEE Communications Magazine, 55(6), pp. 32-38, June 2017 [paper]

  • José Suárez-Varela, Pere Barlet-Ros; "A QoE-aware management system for Software-Defined Networks," in Network Traffic Measurement and Analysis Conference (TMA), Poster session, Dublin, Ireland, June 2017

  • José Suárez-Varela, Pere Barlet-Ros; "Early Classification of Network Traffic for Software-Defined Network Management," in Network Traffic Measurement and Analysis Conference (TMA), Poster session, Louvain La Neuve, Belgium, April 2016

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