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

被引:16
|
作者
Marques-Neto, Humberto T. [1 ]
Xavier, Faber H. Z. [1 ]
Xavier, Wender Z. [1 ]
Malab, Carlos Henrique S. [2 ]
Ziviani, Artur [3 ]
Silveira, Lucas M. [4 ]
Almeida, Jussara M. [4 ]
机构
[1] Pontificia Univ Catolica Minas Gerais, Dept Comp Sci, Belo Horizonte, MG, Brazil
[2] Oi Telecom Board Special Projects, Rio De Janeiro, Brazil
[3] Natl Lab Sci Comp LNCC, Petropolis, Brazil
[4] Univ Fed Minas Gerais, Dept Comp Sci, Belo Horizonte, MG, Brazil
关键词
Mobile network traffic analysis; Characterizing user behavior; Human mobility on large-scale events; Analyzing mobile phone dataset; NETWORKS;
D O I
10.1007/s10922-018-9454-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1079 / 1100
页数:22
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