Cristina Marquez
Marco Fiore
ABSTRACT
We investigate how individual mobile services are consumed at a national scale, by studying data collected in a 3G/4G mobile network deployed over a major European country. Through correlation and clustering analyses, our study unveils a strong heterogeneity in the demand for different mobile services, both in time and space. In particular, we show that: (i) somehow surprisingly, almost all considered services exhibit quite different temporal usage patterns; (ii) in contrast to such temporal behavior, spatial patterns are fairly uniform across all services; (iii) when looking at usage patterns at different locations, the average traffic volume per user is dependent on the urbanization level, yet its temporal dynamics are not. Our findings do not only have sociological implications, but are also relevant to the orchestration of network resources.
- China Mobile Research Institute, "C-RAN: The Road Towards Green RAN," White Paper, 2011Google Scholar
- T.X. Tran, A. Hajisami, P. Pandey, D. Pompili, "Collaborative Mobile Edge Computing in 5G Networks: New Paradigms, Scenarios, and Challenges," IEEE Communications Magazine, 55(4):54--61, 2017. Google ScholarDigital Library
- D. Tuncer, M. Charalambides, S. Clayman, G. Pavlou, "Adaptive Resource Management and Control in Software Defined Networks," IEEE Transactions on Network and Service Management, 12(1):18--33, 2015.Google ScholarDigital Library
- P. Rost, C. Mannweiler, D. S. Michalopoulos, C. Sartori, V. Sciancalepore, N. Sastry, O. Holland, S. Tayade, B. Han, D. Bega, D. Aziz, H. Bakker, "Network Slicing to Enable Scalability and Flexibility in 5G Mobile Networks," IEEE Communications Magazine, 55(5):72--79, 2017. Google ScholarDigital Library
- M. De Nadai, J. Staiano, R. Larcher, N. Sebe, D. Quercia, B. Lepri, "The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective," ACM WWW, Montreal, QC, Canada, 2016. Google ScholarDigital Library
- B. Cici, M. Gjoka, A. Markopoulou, C.T. Butts, "On the Decomposition of Cell Phone Activity Patterns and their Connection with Urban Ecology," ACM MobiHoc, Hangzhou, China, 2015. Google ScholarDigital Library
- A. Furno, M. Fiore, R. Stanica, C. Ziemlicki, Z. Smoreda, "A Tale of Ten Cities: Characterizing Signatures of Mobile Traffic in Urban Areas," IEEE Transactions on Mobile Computing, 16(10):2682--2696, 2017.Google ScholarDigital Library
- D. Naboulsi, M. Fiore, S. Ribot, R. Stanica, "Large-scale Mobile Traffic Analysis: A Survey," IEEE Communications Surveys and Tutorials, 18(1):124--161, 2016.Google ScholarDigital Library
- C. Williamson, E. Halepovic, H. Sun, Y. Wu, "Characterization of CDMA2000 Cellular Data Network Traffic," IEEE LCN, Sydney, Australia, 2005. Google ScholarDigital Library
- U. Paul, A.P. Subramanian, M.M. Buddhikot, S.R. Das, "Understanding Traffic Dynamics in Cellular Data Networks," IEEE INFOCOM, Shanghai, PRC, 2011.Google Scholar
- F. Xu, Y. Li, H. Wang, P. Zhang, D.Jin, "Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment," IEEE/ACM Transactions on Networking, to appear. Google ScholarDigital Library
- I. Trestian, S. Ranjan, A. Kuzmanovic, A. Nucci, "Measuring Serendipity: Connecting People, Locations and Interests in a Mobile 3G Network," ACM IMC, Chicago, IL, USA, 2009. Google ScholarDigital Library
- Q. Xu, J. Erman, A. Gerber, Z. Mao, J. Pang, S. Venkataraman, "Identifying diverse usage behaviors of smartphone apps," ACM IMC, Berlin, Germany, 2011. Google ScholarDigital Library
- M.Z. Shafiq, L. Ji, A.X. Liu, J. Pang, J. Wang, "Characterizing Geospatial Dynamics of Application Usage in a 3G Cellular Data Network," IEEE INFOCOM, Orlando, FL, USA, 2012.Google Scholar
- M.Z. Shafiq, L. Ji, A.X. Liu, J. Wang, "Characterizing and Modeling Internet Traffic Dynamics of Cellular Devices," ACM SIGMETRICS, San Jose, CA, USA, 2011. Google ScholarDigital Library
- R. Keralapura, A. Nucci, Z.-L. Zhang, L. Gao, "Profiling Users in a 3G Network Using Hourglass Co-Clustering," ACM MobiCom, Chicago, IL, USA, 2010. Google ScholarDigital Library
- H. Li, X. Lu, X. Liu, T. Xie, K. Bian, F.X. Lin, Q. Mei, F. Feng, "Characterizing Smartphone Usage Patterns from Millions of Android Users," ACM IMC, Tokyo, Japan, 2015. Google ScholarDigital Library
- P. Fiadino, M. Schiavone, P. Casas, "Vivisecting WhatsApp through Large-scale Measurements in Mobile Networks," ACM SIGCOMM Computer Communication Review, 44(4), 2014. Google ScholarDigital Library
- Q. Deng, Z. Li, Q. Wu, C. Xu, G. Xie, "An Empirical Study of the WeChat Mobile Instant Messaging Service," Global Internet Symposium, Altanta, GA, USA, 2017.Google Scholar
- J. Erman, A. Gerber, K.K. Ramadrishnan, S. Sen, O. Spatscheck, "Over the top video: the gorilla in cellular networks," ACM IMC, Berlin, Germany, 2011. Google ScholarDigital Library
- Z. Li, X. Wang, N. Huang, M.A. Kaafar, Z. Li, J. Zhou, G. Xie, P. Steenkiste, "An Empirical Analysis of a Large-scale Mobile Cloud Storage Service," ACM IMC, Santa Monica, CA, USA, 2016. Google ScholarDigital Library
- Y. Zhang, A. Arvidsson, "Understanding the Characteristics of Cellular Data Traffic," ACM CellNet, Helsinki, Finland, 2012. Google ScholarDigital Library
- Q. Xu, A. Gerber, Z. Morley, J. Pang, "AccuLoc: Practical Localization of Performance Measurements in 3G Networks," ACM MobiSys, Bethesda, MA, USA, 2011. Google ScholarDigital Library
- Cisco, "Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2016--2021," 2017.Google Scholar
- J. Paparrizos, L. Gravano, "k-Shape: Efficient and Accurate Clustering of Time Series," ACM SIGMOD, Melbourne, Victoria, Australia, May 2015. Google ScholarDigital Library
- G.W. Milligan, M.C. Cooper, "An Examination of Procedures for Determining the Number of Clusters in a Data Set," Psychometrika, 50(2):159--179, 1985.Google ScholarCross Ref
Index Terms
- Not All Apps Are Created Equal: Analysis of Spatiotemporal Heterogeneity in Nationwide Mobile Service Usage
Recommendations
Serving Mobile Apps: A Slice at a Time
EuroSys '19: Proceedings of the Fourteenth EuroSys Conference 2019End users wanting to do more and more with mobile apps has led to explosive growth in the number of available apps. This has widened the gap between developers making apps available and end users being able to install all the apps they want on their ...
Comments