A Q-learning strategy for federation of 5G services

e-Archivo Repository

Show simple item record

dc.contributor.author Antevski, Kiril
dc.contributor.author Martín Pérez, Jorge
dc.contributor.author Garcia Saavedra, Andres
dc.contributor.author Bernardos Cano, Carlos Jesús
dc.contributor.author Li, Xi
dc.contributor.author Baranda, Jorge
dc.contributor.author Mangues-Bafalluy, Josep
dc.contributor.author Martínez, Ricardo
dc.contributor.author Vettori, Luca
dc.date.accessioned 2020-10-29T11:22:42Z
dc.date.available 2020-10-29T11:22:42Z
dc.date.issued 2020-07-27
dc.identifier.bibliographicCitation Antevski, K., Martín Pérez, J., García Saavedra, ... Vettori, L. (2020). A Q-learning strategy for federation of 5G services. In ICC 2020 - 2020 IEEE International Conference on Communications (ICC).
dc.identifier.isbn 978-1-7281-5089-5
dc.identifier.uri http://hdl.handle.net/10016/31319
dc.description This paper has been presented at the 2020 IEEE International Conference on Communications
dc.description.abstract 5G networks aim to provide orchestration of services across multiple administrative domains through the concept of federation. In this paper, we are exploring the federation feature of a platform for 5G transport network of vertical services. Then we formulate the decision problem that directly impacts the revenue of 5G administrative domains, and we propose as solution a Q-learning algorithm. The simulation results show near optimum profit maximization and a well-trained Q-learning algorithm can outperform the intuitive "greedy" approach in a realistic scenario.
dc.description.sponsorship This work has been partially funded by the EC H2020 5G-TRANSFORMER Project (grant no. 761536) and the EU H2020 5GROWTH Project (grant no. 856709).
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2020 IEEE.
dc.subject.other Federation
dc.subject.other Algorithms
dc.subject.other Machine-Learning
dc.subject.other Multi-domain
dc.subject.other NFV
dc.title A Q-learning strategy for federation of 5G services
dc.type bookPart
dc.type conferenceObject
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi https://doi.org/10.1109/ICC40277.2020.9149082
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/761536
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/856709
dc.type.version acceptedVersion
dc.relation.eventdate 07-11 June 2020
dc.relation.eventplace Dublin, Ireland
dc.relation.eventtitle 2020 IEEE International Conference on Communications
dc.relation.eventtype proceeding
dc.identifier.publicationtitle Proceedings of the ICC 2020 - 2020 IEEE International Conference on Communications (ICC)
dc.identifier.uxxi CC/0000031100
dc.contributor.funder European Commission
 Find Full text

Files in this item

*Click on file's image for preview. (Embargoed files's preview is not supported)


This item appears in the following Collection(s)

Show simple item record