Publication:
Identifying common periodicities in mobile service demands with spectral analysis

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2020-09-20
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IEEE
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Abstract
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.
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Proceeding of: 2020 Mediterranean Communication and Computer Networking Conference (MedComNet), Aroa, Italy, 17-19 June 2020
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Time series analysis, Discrete Fourier transforms, Spectral analysis, Time-frequency analysis, Electronic mail, Urban areas, Europe
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2020 Mediterranean Communication and Computer Networking Conference (MedComNet), Aroa, Italy, 17-19 June 2020. IEEE, 2020, 8 Pp.