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Takeaways in Large-scale Human Mobility Data Mining

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 significant 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.
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Submitted on : Friday, May 18, 2018 - 4:09:03 PM
Last modification on : Friday, April 30, 2021 - 9:54:19 AM
Long-term archiving on: : Tuesday, September 25, 2018 - 8:05:31 AM


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  • HAL Id : hal-01795633, version 1



Guangshuo Chen, Aline Carneiro Viana, Marco Fiore. Takeaways in Large-scale Human Mobility Data Mining. IEEE International Symposium on Local and Metropolitan Area Networks, Jun 2018, Washington, United States. ⟨hal-01795633⟩



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