Employing mobile devices to perform data analytics is a typical fog computing application that utilizes the intelligence at the edge of networks. Such an application relies on the knowledge of the mobility of mobile devices and their users, e.g., to deploy computation tasks efficiently at the edge. This paper surveys the literature on the mobility-related utilization of operator-collected CDR (charging data records)-the most sig-nificant proxy of large-scale human mobility studies. We provide an innovative introductory guide to the CDR data preliminary. It reveals original issues regarding CDR-based mobility feature computation and applications at the edge. Our survey plays an important role in utilizing mobile devices in terms of both human mobility investigation and fog computing.

Takeaways in Large-scale Human Mobility Data Mining

Fiore Marco
2018

Abstract

Employing mobile devices to perform data analytics is a typical fog computing application that utilizes the intelligence at the edge of networks. Such an application relies on the knowledge of the mobility of mobile devices and their users, e.g., to deploy computation tasks efficiently at the edge. This paper surveys the literature on the mobility-related utilization of operator-collected CDR (charging data records)-the most sig-nificant proxy of large-scale human mobility studies. We provide an innovative introductory guide to the CDR data preliminary. It reveals original issues regarding CDR-based mobility feature computation and applications at the edge. Our survey plays an important role in utilizing mobile devices in terms of both human mobility investigation and fog computing.
2018
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
9781538645338
Mobile phone data
Call detail records
Data processing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/342844
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