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Developing a new simulation and visualization platform for researching aspects of mobile network performance

2022-02-07Conference object Open access
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dc.contributor.authorAmaro, C.
dc.contributor.authorSaraiva, T.
dc.contributor.authorDuarte, D.
dc.contributor.authorVieira, Pedro
dc.contributor.authorQueluz, Maria Paula
dc.contributor.authorRodrigues, A.
dc.date.accessioned2022-02-16T11:25:20Z
dc.date.available2022-02-16T11:25:20Z
dc.date.issued2022-02-07
dc.description.abstractNowadays, mobile networks represent one of the most innovative and challenging technological and research-oriented fields of work. The growth on user subscriptions and the advances introduced by Artificial Intelligence (AI) and Internet of Things (IoT), greatly enhanced the complexity and potential of communication networks. The increase on variety of devices and exchanged mobile data traffic resulted in demanding requirements for the network providers. As networks tend to scale and data to increase, some problems start to arise. Traffic congestion, packet loss and high latency being some examples. Therefore, it is important to introduce powerful tools and methods to tackle these challenges. On this perspective, several studies have highlighted AI systems, mainly Machine Learning (ML) algorithms, as the most promising methods, in the context of wireless networks, by improving the overall performance and efficiency. This work proposes to integrate several network optimization algorithms, already developed, in a common and unified visualization platform. These algorithms were developed in C# and Python and some of them use supervised and unsupervised ML techniques. The proposed solution includes multi-threading processes to deal with concurrent simulations, a proxy to communicate between platforms and a dynamic visual interface.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAMARO, C.; [et al] – Developing a new simulation and visualization platform for researching aspects of mobile network performance. In 2021 24th International Symposium on Wireless Personal Multimedia Communications (WPMC). Okayama, Japan: IEEE, 2022. ISBN 978-1-6654-2760-9. Pp. 1-6.pt_PT
dc.identifier.doi10.1109/WPMC52694.2021.9700408pt_PT
dc.identifier.eissn1882-5621
dc.identifier.isbn978-1-6654-2760-9
dc.identifier.isbn978-1-6654-2761-6
dc.identifier.issn1347-6890
dc.identifier.urihttp://hdl.handle.net/10400.21/14300
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationCOMPETE/FEDER, under the project Artificial Intelligence for Green Networks (AI4GREEN) 16/SI/2019 - I&DT Empresarial (Projetos Copromoção)pt_PT
dc.relationInternational project CELTIC - NEXT/EUREKA (C2018/1-5)pt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9700408pt_PT
dc.subjectMobile networkspt_PT
dc.subjectMachine learningpt_PT
dc.subjectVisualization platformpt_PT
dc.subjectMulti-threadingpt_PT
dc.subjectProxypt_PT
dc.titleDeveloping a new simulation and visualization platform for researching aspects of mobile network performancept_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlace14-16 Dec. 2021 - Okayama, Japanpt_PT
oaire.citation.endPage6pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2021 24th International Symposium on Wireless Personal Multimedia Communications (WPMC)pt_PT
person.familyNameVieira
person.familyNameQueluz
person.givenNamePedro
person.givenNameMaria Paula
person.identifier.ciencia-id071B-9A70-15B8
person.identifier.ciencia-idC210-DAC9-D03A
person.identifier.orcid0000-0003-0279-8741
person.identifier.orcid0000-0003-0266-4022
person.identifier.scopus-author-id7004567421
person.identifier.scopus-author-id6602528040
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication51ae3527-d4ea-46f4-b6c9-62c7b77ac728
relation.isAuthorOfPublication59d5af5d-9c01-4147-a3a9-c1ea74ef3a4d
relation.isAuthorOfPublication.latestForDiscovery51ae3527-d4ea-46f4-b6c9-62c7b77ac728

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