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dc.contributor.authorLatah, Majd
dc.contributor.authorToker, L.
dc.date.accessioned2020-09-08T06:06:13Z
dc.date.available2020-09-08T06:06:13Z
dc.date.issued2019-03
dc.identifier.issn2047-4954en_US
dc.identifier.urihttp://hdl.handle.net/10679/6915
dc.identifier.urihttps://digital-library.theiet.org/content/journals/10.1049/iet-net.2018.5082
dc.description.abstractSoftware-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.en_US
dc.language.isoengen_US
dc.publisherThe Institution of Engineering and Technologyen_US
dc.relation.ispartofIET Networks
dc.rightsrestrictedAccess
dc.titleArtificial intelligence enabled software-defined networking: A comprehensive overviewen_US
dc.typeArticleen_US
dc.peerreviewedyesen_US
dc.publicationstatusPublisheden_US
dc.contributor.departmentÖzyeğin University
dc.identifier.volume8en_US
dc.identifier.issue2en_US
dc.identifier.startpage79en_US
dc.identifier.endpage99en_US
dc.identifier.wosWOS:000475949300001
dc.identifier.doi10.1049/iet-net.2018.5082en_US
dc.identifier.scopusSCOPUS:2-s2.0-85065877629
dc.contributor.ozugradstudentLatah, Majd
dc.contributor.authorMale1
dc.relation.publicationcategoryArticle - International Refereed Journal - Institution PhD Student


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