Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/62967
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dc.contributor.authorAslam, Saaden
dc.contributor.authorAlam, Fakhrulen
dc.contributor.authorHasan, Syed Farazen
dc.contributor.authorRashid, Mohammaden
dc.date.accessioned2024-09-18T05:59:58Z-
dc.date.available2024-09-18T05:59:58Z-
dc.date.issued2019-
dc.identifier.citationProceedings of the 29th International Telecommunication Networks and Applications Conference, ITNAC 2019, p. 302-308en
dc.identifier.isbn9781728136738en
dc.identifier.isbn9781728136721en
dc.identifier.isbn9781728136745en
dc.identifier.issn2474-154Xen
dc.identifier.issn2474-1531en
dc.identifier.urihttps://hdl.handle.net/1959.11/62967-
dc.description.abstract<p>5G networks are expected to be content-centric which present various research challenges. Content-Sharing via Device-to-Device (D2D) clustered networks has emerged as a popular approach of alleviating the burden on the 5G network. A novel channel-based clustering algorithm, for grouping the D2D User Equipment (DUEs) sharing a common interest, is proposed in this paper. Performance parameters such as energy consumption of devices and area spectral efficiencies (ASE) are considered for evaluating the performance of the D2D clustered network in a simulation study. The proposed algorithm exhibits better node energy consumptions as compared to several existing clustering algorithms. It also yields better ASE compared to the existing algorithms for various node densities. Effect of the number of clusters on the performance parameters is also discussed.</p>en
dc.languageenen
dc.publisherInstitute of Electrical and Electronics Engineersen
dc.relation.ispartofProceedings of the 29th International Telecommunication Networks and Applications Conference, ITNAC 2019en
dc.titlePerformance Analysis of Clustering Algorithms for Content-Sharing Based D2D Enabled 5G Networksen
dc.typeConference Publicationen
dc.relation.conferenceITNAC 2019: 29th International Telecommunication Networks and Applications Conferenceen
dc.identifier.doi10.1109/ITNAC46935.2019.9077986en
local.contributor.firstnameSaaden
local.contributor.firstnameFakhrulen
local.contributor.firstnameSyed Farazen
local.contributor.firstnameMohammaden
local.profile.schoolResearch Servicesen
local.profile.emailshasan3@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference27th - 29th November, 2019en
local.conference.placeAuckland, New Zealanden
local.publisher.placeUnited States of Americaen
local.format.startpage302en
local.format.endpage308en
local.peerreviewedYesen
local.contributor.lastnameAslamen
local.contributor.lastnameAlamen
local.contributor.lastnameHasanen
local.contributor.lastnameRashiden
dc.identifier.staffune-id:shasan3en
local.profile.orcid0009-0006-5345-2790en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/62967en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitlePerformance Analysis of Clustering Algorithms for Content-Sharing Based D2D Enabled 5G Networksen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsITNAC 2019: 29th International Telecommunication Networks and Applications Conference, Auckland, New Zealand, 27th - 29th November, 2019en
local.search.authorAslam, Saaden
local.search.authorAlam, Fakhrulen
local.search.authorHasan, Syed Farazen
local.search.authorRashid, Mohammaden
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2019en
local.subject.for20204006 Communications engineeringen
local.subject.seo2020tbden
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-09-19en
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