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Understanding Human Mobility and Workload Dynamics Due to Different Large-Scale Events Using Mobile Phone Data

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Abstract

The analysis of mobile phone data can help carriers to improve the way they deal with unusual workloads imposed by large-scale events. This paper analyzes human mobility and the resulting dynamics in the network workload caused by three different types of large-scale events: a major soccer match, a rock concert, and a New Year’s Eve celebration, which took place in a large Brazilian city. Our analysis is based on the characterization of records of mobile phone calls made around the time and place of each event. That is, human mobility and network workload are analyzed in terms of the number of mobile phone calls, their inter-arrival and inter-departure times, and their durations. We use heat maps to visually analyze the spatio-temporal dynamics of the movement patterns of the participants of the large-scale event. The results obtained can be helpful to improve the understanding of human mobility caused by large-scale events. Such results could also provide valuable insights for network managers into effective capacity management and planning strategies. We also present PrediTraf, an application built to help the cellphone carriers plan their infrastructure on large-scale events.

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Notes

  1. People who live or work in the same area of the event are also considered attendees. We understand that the neighborhood of an event place should also be included in the carriers capacity management.

  2. An official stadium of the 2014 FIFA World Cup and Rio 2016 Olympics.

  3. http://www.mathwave.com/help/easyfit.

  4. http://www.nirsoft.net/utils/web_site_screenshot.html.

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Acknowledgements

This work is supported by FIP PUC Minas (Fundo de Incentivo à Pesquisa of Pontifical Catholic University of Minas Gerais), FAPEMIG (Fundação de Amparo à Pesquisa do Estado de Minas Gerais), FAPERJ (Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro), CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior), CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico), InWeb (MCT CNPq 5738712008-6), INCT-CiD (MCTIC CNPq 465.560/2014-8), and the STIC-AmSud Program (Project 18-STIC-07).

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Authors and Affiliations

  1. Department of Computer Science, PUC MINAS, Belo Horizonte, Brazil

    Humberto T. Marques-Neto, Faber H. Z. Xavier & Wender Z. Xavier

  2. Oi Telecom – Board for Special Projects, Rio de Janeiro, Brazil

    Carlos Henrique S. Malab

  3. National Laboratory for Scientific Computing (LNCC), Petrópolis, Brazil

    Artur Ziviani

  4. Department of Computer Science, UFMG, Belo Horizonte, Brazil

    Lucas M. Silveira & Jussara M. Almeida

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  1. Humberto T. Marques-Neto
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Correspondence to Humberto T. Marques-Neto.

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Marques-Neto, H.T., Xavier, F.H.Z., Xavier, W.Z. et al. Understanding Human Mobility and Workload Dynamics Due to Different Large-Scale Events Using Mobile Phone Data. J Netw Syst Manage 26, 1079–1100 (2018). https://doi.org/10.1007/s10922-018-9454-3

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