Publication:
Applications of Machine Learning in Networking: A Survey of Current Issues and Future Challenges

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dc.citedby13
dc.contributor.authorRidwan M.A.en_US
dc.contributor.authorRadzi N.A.M.en_US
dc.contributor.authorAbdullah F.en_US
dc.contributor.authorJalil Y.E.en_US
dc.contributor.authorid57193648099en_US
dc.contributor.authorid57218936786en_US
dc.contributor.authorid56613644500en_US
dc.contributor.authorid55257996600en_US
dc.date.accessioned2023-05-29T09:11:57Z
dc.date.available2023-05-29T09:11:57Z
dc.date.issued2021
dc.descriptionIntrusion detection; Machine learning; Quality of service; Complex problems; Computational model; Future challenges; Improve performance; Ml algorithms; Performance issues; Resource management; Rule based algorithms; Complex networksen_US
dc.description.abstractCommunication networks are expanding rapidly and becoming increasingly complex. As a consequence, the conventional rule-based algorithms or protocols may no longer perform at their best efficiencies in these networks. Machine learning (ML) has recently been applied to solve complex problems in many fields, including finance, health care, and business. ML algorithms can offer computational models that can solve complex communication network problems and consequently improve performance. This paper reviews the recent trends in the application of ML models in communication networks for prediction, intrusion detection, route and path assignment, Quality of Service improvement, and resource management. A review of the recent literature reveals extensive opportunities for researchers to exploit the advantages of ML in solving complex performance issues in a network, especially with the advancement of software-defined networks and 5G. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9388670
dc.identifier.doi10.1109/ACCESS.2021.3069210
dc.identifier.epage52556
dc.identifier.scopus2-s2.0-85103772902
dc.identifier.spage52523
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85103772902&doi=10.1109%2fACCESS.2021.3069210&partnerID=40&md5=6cbfdc0edb975cc53d7c41a5a26fdc5a
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26559
dc.identifier.volume9
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.titleApplications of Machine Learning in Networking: A Survey of Current Issues and Future Challengesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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