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Identifying Common Periodicities in Mobile Service Demands with Spectral Analysis

Authors :
Zbigniew Smoreda
Marco Fiore
Cristina Marquez
Albert Banchs
Marco Gramaglia
Universidad Carlos III de Madrid [Madrid] (UC3M)
Institute IMDEA Networks [Madrid]
Orange Labs [Issy les Moulineaux]
France Télécom
ANR-18-CE25-0011,CANCAN,Adaptation basée sur le contenu et le contexte dans les réseaux mobiles(2018)
Fiore, Marco
Infrastructures de communication hautes performances (réseau, calcul et stockage), Sciences et technologies logicielles - Adaptation basée sur le contenu et le contexte dans les réseaux mobiles - - CANCAN2018 - ANR-18-CE25-0011 - AAPG2018 - VALID
European Commission
Source :
IEEE MedComNet, IEEE MedComNet, Jun 2020, Arona, Italy, IMDEA Networks Institute Digital Repository, IMDEA Networks Institute, instname, MedComNet, e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid, e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid, Universidad Carlos III de Madrid (UC3M), 2020 Mediterranean Communication and Computer Networking Conference (MedComNet)
Publication Year :
2020
Publisher :
HAL CCSD, 2020.

Abstract

Proceeding of: 2020 Mediterranean Communication and Computer Networking Conference (MedComNet), Aroa, Italy, 17-19 June 2020 In 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. The work of Orange Labs was supported by ANR through the CANCAN project (ANR-18-CE25-0011). The work of UC3M was supported by the H2020 5G-TOURS project (grant agreement no. 856950).

Details

Language :
English
ISBN :
978-1-72816-248-5
ISBNs :
9781728162485
Database :
OpenAIRE
Journal :
IEEE MedComNet, IEEE MedComNet, Jun 2020, Arona, Italy, IMDEA Networks Institute Digital Repository, IMDEA Networks Institute, instname, MedComNet, e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid, e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid, Universidad Carlos III de Madrid (UC3M), 2020 Mediterranean Communication and Computer Networking Conference (MedComNet)
Accession number :
edsair.doi.dedup.....7a49265cec3ca710a044b723dcdf6a34