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

During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This poses the need to count on new generations of student...

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Autores: Suárez-Varela Maciá, José Rafael|||0000-0002-7141-3414, Ferriol Galmés, Miquel|||0000-0002-7806-2979, López Brescó, Albert, Almasan Puscas, Felician Paul|||0000-0003-3903-6759, Bernárdez Gil, Guillermo, Pujol Perich, David, Rusek, Krzysztof, Bonniot, Loïck, Neumann, Christoph, Schnitzler, François, Taïani, François, Happ, Martin, Barlet Ros, Pere|||0000-0001-7837-0886, Cabellos Aparicio, Alberto|||0000-0001-9329-7584
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/360063
Acceso en línea:https://hdl.handle.net/2117/360063
https://dx.doi.org/10.1145/3477482.3477485
Access Level:acceso abierto
Palabra clave:Machine learning
Computer networks
Network AI
Graph neural networks
Aprenentatge automàtic
Ordinadors, Xarxes d'
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
id ES_8d2eef9ab8d085f7cc7aabed1ff210e2
oai_identifier_str oai:upcommons.upc.edu:2117/360063
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
title The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
spellingShingle The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
Suárez-Varela Maciá, José Rafael|||0000-0002-7141-3414
Machine learning
Computer networks
Network AI
Graph neural networks
Aprenentatge automàtic
Ordinadors, Xarxes d'
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
title_short The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
title_full The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
title_fullStr The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
title_full_unstemmed The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
title_sort The graph neural networking challenge: a worldwide competition for education in AI/ML for networks
dc.creator.none.fl_str_mv Suárez-Varela Maciá, José Rafael|||0000-0002-7141-3414
Ferriol Galmés, Miquel|||0000-0002-7806-2979
López Brescó, Albert
Almasan Puscas, Felician Paul|||0000-0003-3903-6759
Bernárdez Gil, Guillermo
Pujol Perich, David
Rusek, Krzysztof
Bonniot, Loïck
Neumann, Christoph
Schnitzler, François
Taïani, François
Happ, Martin
Barlet Ros, Pere|||0000-0001-7837-0886
Cabellos Aparicio, Alberto|||0000-0001-9329-7584
author Suárez-Varela Maciá, José Rafael|||0000-0002-7141-3414
author_facet Suárez-Varela Maciá, José Rafael|||0000-0002-7141-3414
Ferriol Galmés, Miquel|||0000-0002-7806-2979
López Brescó, Albert
Almasan Puscas, Felician Paul|||0000-0003-3903-6759
Bernárdez Gil, Guillermo
Pujol Perich, David
Rusek, Krzysztof
Bonniot, Loïck
Neumann, Christoph
Schnitzler, François
Taïani, François
Happ, Martin
Barlet Ros, Pere|||0000-0001-7837-0886
Cabellos Aparicio, Alberto|||0000-0001-9329-7584
author_role author
author2 Ferriol Galmés, Miquel|||0000-0002-7806-2979
López Brescó, Albert
Almasan Puscas, Felician Paul|||0000-0003-3903-6759
Bernárdez Gil, Guillermo
Pujol Perich, David
Rusek, Krzysztof
Bonniot, Loïck
Neumann, Christoph
Schnitzler, François
Taïani, François
Happ, Martin
Barlet Ros, Pere|||0000-0001-7837-0886
Cabellos Aparicio, Alberto|||0000-0001-9329-7584
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Machine learning
Computer networks
Network AI
Graph neural networks
Aprenentatge automàtic
Ordinadors, Xarxes d'
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
topic Machine learning
Computer networks
Network AI
Graph neural networks
Aprenentatge automàtic
Ordinadors, Xarxes d'
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
description During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This poses the need to count on new generations of students, researchers and practitioners with a solid background in ML applied to networks. During 2020, the International Telecommunication Union (ITU) has organized the "ITU AI/ML in 5G challenge", an open global competition that has introduced to a broad audience some of the current main challenges in ML for networks. This large-scale initiative has gathered 23 different challenges proposed by network operators, equipment manufacturers and academia, and has attracted a total of 1300+ participants from 60+ countries. This paper narrates our experience organizing one of the proposed challenges: the "Graph Neural Networking Challenge 2020". We describe the problem presented to participants, the tools and resources provided, some organization aspects and participation statistics, an outline of the top-3 awarded solutions, and a summary with some lessons learned during all this journey. As a result, this challenge leaves a curated set of educational resources openly available to anyone interested in the topic.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-07-01
2022
2022-01-20
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/360063
https://dx.doi.org/10.1145/3477482.3477485
url https://hdl.handle.net/2117/360063
https://dx.doi.org/10.1145/3477482.3477485
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 871528 NGI Program for Open INTErnet Renovation
Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 TEC2017-90034-C2-1-R DISEÑANDO UNA INFRAESTRUCTURA DE RED 5G DEFINIDA MEDIANTE CONOCIMIENTO HACIA LA PROXIMA SOCIEDAD DIGITAL
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869413024221102080
spelling The graph neural networking challenge: a worldwide competition for education in AI/ML for networksSuárez-Varela Maciá, José Rafael|||0000-0002-7141-3414Ferriol Galmés, Miquel|||0000-0002-7806-2979López Brescó, AlbertAlmasan Puscas, Felician Paul|||0000-0003-3903-6759Bernárdez Gil, GuillermoPujol Perich, DavidRusek, KrzysztofBonniot, LoïckNeumann, ChristophSchnitzler, FrançoisTaïani, FrançoisHapp, MartinBarlet Ros, Pere|||0000-0001-7837-0886Cabellos Aparicio, Alberto|||0000-0001-9329-7584Machine learningComputer networksNetwork AIGraph neural networksAprenentatge automàticOrdinadors, Xarxes d'Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadorsÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàticDuring the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This poses the need to count on new generations of students, researchers and practitioners with a solid background in ML applied to networks. During 2020, the International Telecommunication Union (ITU) has organized the "ITU AI/ML in 5G challenge", an open global competition that has introduced to a broad audience some of the current main challenges in ML for networks. This large-scale initiative has gathered 23 different challenges proposed by network operators, equipment manufacturers and academia, and has attracted a total of 1300+ participants from 60+ countries. This paper narrates our experience organizing one of the proposed challenges: the "Graph Neural Networking Challenge 2020". We describe the problem presented to participants, the tools and resources provided, some organization aspects and participation statistics, an outline of the top-3 awarded solutions, and a summary with some lessons learned during all this journey. As a result, this challenge leaves a curated set of educational resources openly available to anyone interested in the topic.This work has received funding from the European Union’s H2020 research and innovation programme within the framework of the NGI-POINTER Project funded under grant agreement No. 871528. This paper reflects only the authors’ view; the European Commission is not responsible for any use that may be made of the information it contains. This work was also supported by the Spanish MINECO under contract TEC2017-90034-C2-1-R (ALLIANCE), the Catalan Institution for Research and Advanced Studies (ICREA), and by FI-AGAUR grant by the Catalan Government. Salzburg Research is grateful for the support by the WISS 2025 (Science and Innovation Strategy Salzburg 2025) project ”IDALab Salzburg” (20204-WISS/225/197-2019 and 20102-F1901166-KZP) and the 5G-AI-MLab by the Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and the Austrian state Salzburg.Peer ReviewedArticle escrit per 24 autors/autores: José Suárez-Varela (1), Miquel Ferriol-Galmés (1), Albert López (1), Paul Almasan (1), Guillermo Bernárdez (1), David Pujol-Perich (1), Krzysztof Rusek (1,2), Loïck Bonniot (3, 4), Christoph Neumann (3), François Schnitzler (3), François Taïani (4), Martin Happ (5, 6), Christian Maier (5), Jia Lei Du (5), Matthias Herlich (5), Peter Dorfinger (5), Nick Vincent Hainke (7), Stefan Venz (7), Johannes Wegener (7), Henrike Wissing (7), Bo Wu (8), Shihan Xiao (8), Pere Barlet-Ros (1), Albert Cabellos-Aparicio (1). 1- Barcelona Neural Networking center, Universitat Politècnica de Catalunya, Spain. 2- AGH University of Science and Technology, Department of Telecommunications, Poland. 3- InterDigital, France. 4- Univ. Rennes, Inria, CNRS, IRISA, France. 5- Salzburg Research Forschungsgesellschaft mbH, Austria. 6- IDA Lab, University of Salzburg, Austria. 7- Fraunhofer HHI, Germany. 8- Network Technology Lab., Huawei Technologies Co., Ltd., China.20212021-07-0120222022-01-20journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/360063https://dx.doi.org/10.1145/3477482.3477485reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 871528 NGI Program for Open INTErnet RenovationAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 TEC2017-90034-C2-1-R DISEÑANDO UNA INFRAESTRUCTURA DE RED 5G DEFINIDA MEDIANTE CONOCIMIENTO HACIA LA PROXIMA SOCIEDAD DIGITALopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3600632026-05-27T15:37:01Z
score 15,300719

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