Caracterização e Modelagem Temporal de Chamadas de Telefonia Móvel em Grandes Eventos
Abstract
The increasing use of mobile phones challenges operators to evolve and improve their services based on the behavior of their users. In particular, large-scale events may impose standards that differ strongly from those observed in normal daily use of the mobile networks. This paper presents the impact of football matches on the workload of a mobile network based on the use of a proposed methodology. The results show the dynamics of the workload surrounding the times of these events featuring the increased use of voice services due to the displacement of both participants and the nature of the event itself.References
Balcan, D. et al. Multiscale mobility networks and the spatial spreading of infectious diseases. Proceedings of the National Academy of Sciences, v. 106, n. 51, p. 21484– 21489, 2009. Disponível em: <http://www.pnas.org/content/106/51/21484.abstract>.
Bagrow, J. P.; Wang, D.; Barabási, A.-L. Collective response of human populations to large-scale emergencies. PLoS ONE, Public Library of Science, v. 6, n. 3, p. e17680, 03 2011.
Bleicher, A. The on-demand olympics. IEEE Spectrum, jul 2012.
Candia, J. et al. Uncovering individual and collective human dynamics from mobile phone records. Journal of Physics A: Mathematical and Theoretical, v. 41, n. 22, p. 224015, 2008. Disponível em: <http://stacks.iop.org/1751-8121/41/i=22/a=224015>.
Eagle, N.; Pentland, A.; Lazer, D. Inferring social network structure using mobile phone data. Proceedings of the National Academy of Sciences (PNAS), v. 106, n. 36, p. 15274–15278, 2009.
González, M. C.; Barabási, A.-L. Complex networks – from data to models. Nature Physics, v. 3, p. 224–225, 2007.
González, M. C.; Hidalgo, C. A.; Barabási, A.-L. Understanding individual human mobility patterns. Nature Publishing Group, v. 453, 2008. Disponível em: <http://dx.doi.org/10.1038/nature06958>.
Mitchell, T. M. Mining our reality. Science, v. 326, n. 5960, p. 1644–1645, 2009. Disponível em: <http://www.sciencemag.org/content/326/5960/1644.short>.
Schopenhauer, A.Simonite, T. Mobile Data: A Gold Mine for Telcos. may 2010. Intelligent Community Forum.
Song, C. et al. Modelling the scaling properties of human mobility. Nature Publishing Group, v. 6, 2010. Disponível em: <http://dx.doi.org/10.1038/nphys1760>.
Song, C. et al. Limits of predictability in human mobility. Science, v. 327, n. 5968, p. 1018–1021, 2010. Disponível em: <http://www.sciencemag.org/content/327/5968/1018.abstract>.
Soper, D. Is human mobility tracking a good idea? Communications of the ACM, ACM, New York, NY, USA, v. 55, n. 4, p. 35–37, abr. 2012. ISSN 0001-0782. Disponível em: <http://doi.acm.org/10.1145/2133806.2133819>.
Xavier, F. H. Z., Silveira, L. M., Almeida, J. M., Ziviani, A., Malab, C. H. S., e Marques-Neto, H. (2012). Analyzing the workload dynamics of a mobile phone network in large scale events. Em Proceedings ofthe UrbaNe Workshop – ACM CoNEXT 2012.
Bagrow, J. P.; Wang, D.; Barabási, A.-L. Collective response of human populations to large-scale emergencies. PLoS ONE, Public Library of Science, v. 6, n. 3, p. e17680, 03 2011.
Bleicher, A. The on-demand olympics. IEEE Spectrum, jul 2012.
Candia, J. et al. Uncovering individual and collective human dynamics from mobile phone records. Journal of Physics A: Mathematical and Theoretical, v. 41, n. 22, p. 224015, 2008. Disponível em: <http://stacks.iop.org/1751-8121/41/i=22/a=224015>.
Eagle, N.; Pentland, A.; Lazer, D. Inferring social network structure using mobile phone data. Proceedings of the National Academy of Sciences (PNAS), v. 106, n. 36, p. 15274–15278, 2009.
González, M. C.; Barabási, A.-L. Complex networks – from data to models. Nature Physics, v. 3, p. 224–225, 2007.
González, M. C.; Hidalgo, C. A.; Barabási, A.-L. Understanding individual human mobility patterns. Nature Publishing Group, v. 453, 2008. Disponível em: <http://dx.doi.org/10.1038/nature06958>.
Mitchell, T. M. Mining our reality. Science, v. 326, n. 5960, p. 1644–1645, 2009. Disponível em: <http://www.sciencemag.org/content/326/5960/1644.short>.
Schopenhauer, A.Simonite, T. Mobile Data: A Gold Mine for Telcos. may 2010. Intelligent Community Forum.
Song, C. et al. Modelling the scaling properties of human mobility. Nature Publishing Group, v. 6, 2010. Disponível em: <http://dx.doi.org/10.1038/nphys1760>.
Song, C. et al. Limits of predictability in human mobility. Science, v. 327, n. 5968, p. 1018–1021, 2010. Disponível em: <http://www.sciencemag.org/content/327/5968/1018.abstract>.
Soper, D. Is human mobility tracking a good idea? Communications of the ACM, ACM, New York, NY, USA, v. 55, n. 4, p. 35–37, abr. 2012. ISSN 0001-0782. Disponível em: <http://doi.acm.org/10.1145/2133806.2133819>.
Xavier, F. H. Z., Silveira, L. M., Almeida, J. M., Ziviani, A., Malab, C. H. S., e Marques-Neto, H. (2012). Analyzing the workload dynamics of a mobile phone network in large scale events. Em Proceedings ofthe UrbaNe Workshop – ACM CoNEXT 2012.
Published
2013-07-23
How to Cite
SILVEIRA, Lucas Maia; MARQUES-NETO, Humberto T..
Caracterização e Modelagem Temporal de Chamadas de Telefonia Móvel em Grandes Eventos. In: SBC UNDERGRADUATE RESEARCH CONTEST (CTIC-SBC), 32. , 2013, Maceió.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2013
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p. 201-210.
