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dc.contributor.authorMárquez, Cristina
dc.contributor.authorGramaglia, Marco 
dc.contributor.authorFiore, Marco 
dc.contributor.authorBanchs, Albert 
dc.contributor.authorSmoreda, Zbigniew
dc.date.accessioned2021-07-13T09:43:03Z
dc.date.available2021-07-13T09:43:03Z
dc.date.issued2020-06-17
dc.identifier.urihttp://hdl.handle.net/20.500.12761/833
dc.description.abstractIn this paper, we investigate the existence and prevalence of comparable dynamics in the temporal fluctuations for the traffic demands generated by mobile applications. To this end, we hinge upon a spectral analysis framework, by computing Discrete Fourier Transforms of the typical demands for tens of popular mobile services observed in an operational metropolitan-scale network. We filter, cluster, and analyse hundreds of frequency components, and identify a substantial set of regular patterns that are common across most service demands. We also unveil how several mobile services defy classification, and have instead highly distinguishing temporal dynamics.
dc.language.isoeng
dc.titleIdentifying Common Periodicities in Mobile Service Demands with Spectral Analysisen
dc.typeconference object
dc.conference.date17-19 June 2020
dc.conference.placeArona, Italy
dc.conference.titleThe 18th Mediterranean Communication and Computer Networking Conference (IEEE MedComNet 2020)*
dc.event.typeconference
dc.pres.typepaper
dc.rights.accessRightsopen access
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttp://eprints.networks.imdea.org/id/eprint/2166


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