Understanding Human Mobility and Workload Dynamics Due to Different Large-Scale Events Using Mobile Phone Data.
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| Title: | Understanding Human Mobility and Workload Dynamics Due to Different Large-Scale Events Using Mobile Phone Data. |
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| Authors: | Marques-Neto, Humberto T.1 humberto@pucminas.br, Xavier, Faber H. Z.1 faber.xavier@sga.pucminas.br, Xavier, Wender Z.1 wender.xavier@sga.pucminas.br, Malab, Carlos Henrique S.2 malab@oi.net.br, Ziviani, Artur3 ziviani@lncc.br, Silveira, Lucas M.4 lmsilveira@dcc.ufmg.br, Almeida, Jussara M.4 jussara@dcc.ufmg.br |
| Source: | Journal of Network & Systems Management. Oct2018, Vol. 26 Issue 4, p1079-1100. 22p. |
| Subjects: | Workload of computer networks, Capacity management (Computers), Cell phones, Information superhighway, Social mobility |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Network & Systems Management is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 131436378 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Understanding Human Mobility and Workload Dynamics Due to Different Large-Scale Events Using Mobile Phone Data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Marques-Neto%2C+Humberto+T%2E%22">Marques-Neto, Humberto T.</searchLink><relatesTo>1</relatesTo><i> humberto@pucminas.br</i><br /><searchLink fieldCode="AR" term="%22Xavier%2C+Faber+H%2E+Z%2E%22">Xavier, Faber H. Z.</searchLink><relatesTo>1</relatesTo><i> faber.xavier@sga.pucminas.br</i><br /><searchLink fieldCode="AR" term="%22Xavier%2C+Wender+Z%2E%22">Xavier, Wender Z.</searchLink><relatesTo>1</relatesTo><i> wender.xavier@sga.pucminas.br</i><br /><searchLink fieldCode="AR" term="%22Malab%2C+Carlos+Henrique+S%2E%22">Malab, Carlos Henrique S.</searchLink><relatesTo>2</relatesTo><i> malab@oi.net.br</i><br /><searchLink fieldCode="AR" term="%22Ziviani%2C+Artur%22">Ziviani, Artur</searchLink><relatesTo>3</relatesTo><i> ziviani@lncc.br</i><br /><searchLink fieldCode="AR" term="%22Silveira%2C+Lucas+M%2E%22">Silveira, Lucas M.</searchLink><relatesTo>4</relatesTo><i> lmsilveira@dcc.ufmg.br</i><br /><searchLink fieldCode="AR" term="%22Almeida%2C+Jussara+M%2E%22">Almeida, Jussara M.</searchLink><relatesTo>4</relatesTo><i> jussara@dcc.ufmg.br</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Network+%26+Systems+Management%22">Journal of Network & Systems Management</searchLink>. Oct2018, Vol. 26 Issue 4, p1079-1100. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Workload+of+computer+networks%22">Workload of computer networks</searchLink><br /><searchLink fieldCode="DE" term="%22Capacity+management+%28Computers%29%22">Capacity management (Computers)</searchLink><br /><searchLink fieldCode="DE" term="%22Cell+phones%22">Cell phones</searchLink><br /><searchLink fieldCode="DE" term="%22Information+superhighway%22">Information superhighway</searchLink><br /><searchLink fieldCode="DE" term="%22Social+mobility%22">Social mobility</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Network & Systems Management is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10922-018-9454-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 1079 Subjects: – SubjectFull: Workload of computer networks Type: general – SubjectFull: Capacity management (Computers) Type: general – SubjectFull: Cell phones Type: general – SubjectFull: Information superhighway Type: general – SubjectFull: Social mobility Type: general Titles: – TitleFull: Understanding Human Mobility and Workload Dynamics Due to Different Large-Scale Events Using Mobile Phone Data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Marques-Neto, Humberto T. – PersonEntity: Name: NameFull: Xavier, Faber H. Z. – PersonEntity: Name: NameFull: Xavier, Wender Z. – PersonEntity: Name: NameFull: Malab, Carlos Henrique S. – PersonEntity: Name: NameFull: Ziviani, Artur – PersonEntity: Name: NameFull: Silveira, Lucas M. – PersonEntity: Name: NameFull: Almeida, Jussara M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 10647570 Numbering: – Type: volume Value: 26 – Type: issue Value: 4 Titles: – TitleFull: Journal of Network & Systems Management Type: main |
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