Learning-Based Edge Computing Services

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dc.contributor.authorChen, Minko
dc.contributor.authorWang, Haiyangko
dc.contributor.authorHwang, Kaiko
dc.contributor.authorFortino, Giancarloko
dc.contributor.authorSong, Jeungeunko
dc.contributor.authorPeng, Limeiko
dc.contributor.authorGuna, Jozeko
dc.date.accessioned2021-04-20T05:30:05Z-
dc.date.available2021-04-20T05:30:05Z-
dc.date.created2021-04-19-
dc.date.created2021-04-19-
dc.date.created2021-04-19-
dc.date.created2021-04-19-
dc.date.issued2021-01-
dc.identifier.citationIEEE NETWORK, v.35, no.1, pp.138 - 140-
dc.identifier.issn0890-8044-
dc.identifier.urihttp://hdl.handle.net/10203/282482-
dc.description.abstractThe recent revival of artificial intelligence (AI) is revolutionizing almost every branch of science and technology. Given the ubiquitous smart mobile terminals and Internet of Things (IoT) devices, it is expected that a majority of intelligent applications will be deployed at the edge networks. Therefore, providing intelligent and sustainable edge computing services will be a hot topic in IoT and 5G services as sustainability of edge systems becomes a necessity with the rapid constant growth of edge devices/sensors.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleLearning-Based Edge Computing Services-
dc.typeArticle-
dc.identifier.wosid000641159800021-
dc.identifier.scopusid2-s2.0-85101135660-
dc.type.rimsART-
dc.citation.volume35-
dc.citation.issue1-
dc.citation.beginningpage138-
dc.citation.endingpage140-
dc.citation.publicationnameIEEE NETWORK-
dc.identifier.doi10.1109/MNET.2021.9355037-
dc.contributor.localauthorPeng, Limei-
dc.contributor.nonIdAuthorChen, Min-
dc.contributor.nonIdAuthorWang, Haiyang-
dc.contributor.nonIdAuthorHwang, Kai-
dc.contributor.nonIdAuthorFortino, Giancarlo-
dc.contributor.nonIdAuthorSong, Jeungeun-
dc.contributor.nonIdAuthorGuna, Joze-
dc.description.isOpenAccessN-
dc.type.journalArticleEditorial Material-
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