Beyond throughput: the next Generation a 5G dataset with channel and context metrics

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dc.contributor.authorRaca, Darijo
dc.contributor.authorLeahy, Dylan
dc.contributor.authorSreenan, Cormac J.
dc.contributor.authorQuinlan, Jason J.
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.date.accessioned2020-04-15T10:01:38Z
dc.date.available2020-04-15T10:01:38Z
dc.date.issued2020-06
dc.date.updated2020-04-15T09:45:11Z
dc.description.abstractIn this paper, we present a 5G trace dataset collected from a major Irish mobile operator. The dataset is generated from two mobility patterns (static and car), and across two application patterns (video streaming and file download). The dataset is composed of client-side cellular key performance indicators (KPIs) comprised of channel-related metrics, context-related metrics, cell-related metrics and throughput information. These metrics are generated from a well-known non-rooted Android network monitoring application, G-NetTrack Pro. To the best of our knowledge, this is the first publicly available dataset that contains throughput, channel and context information for 5G networks. To supplement our realtime 5G production network dataset, we also provide a 5G large scale multi-cell ns-3 simulation framework. The availability of the 5G/mmwave module for the ns-3 mmwave network simulator provides an opportunity to improve our understanding of the dynamic reasoning for adaptive clients in 5G multi-cell wireless scenarios. The purpose of our framework is to provide additional information (such as competing metrics for users connected to the same cell), thus providing otherwise unavailable information about the eNodeB environment and scheduling principle, to end user. Our framework, permits other researchers to investigate this interaction through the generation of their own synthetic datasets.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRaca, D., Leahy, D., Sreenan, C. J. and Quinlan, J. J. (2020) 'Beyond Throughput: The Next Generation a 5G Dataset with Channel and Context Metrics', ACM Multimedia Systems Conference (MMSys '20), Istanbul, Turkey, 8-11 June, [To Appear]en
dc.identifier.endpage6en
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/9826
dc.language.isoenen
dc.publisherAssociation for Computing Machineryen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/13/RC/2077/IE/CONNECT: The Centre for Future Networks & Communications/en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Investigator Programme/13/IA/1892/IE/An Internet Infrastructure for Video Streaming Optimisation (iVID)/en
dc.relation.urihttps://2020.acmmmsys.org/
dc.rights© 2020 Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution.en
dc.subjectDataseten
dc.subject5Gen
dc.subjectNRen
dc.subjectMobilityen
dc.subjectThroughputen
dc.subjectContext informationen
dc.subjectAdaptive video streamingen
dc.subjectmmwaveen
dc.subjectPublic Interneten
dc.subjectWireless access networksen
dc.subjectNetwork measurementen
dc.subjectMultimedia streamingen
dc.titleBeyond throughput: the next Generation a 5G dataset with channel and context metricsen
dc.typeConference itemen
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