ABSTRACT
In this paper, we introduce a user mobility modeling framework that accounts for both the users' social structure as well as the geographic diversity of the region of interest. SAGA, or Socially- and Geography-Aware mobility model, captures social features through the use of communities which cluster users with similar features such as average time in a cell, average speed, and pause time. SAGA accounts for geographic diversity by considering that different communities exhibit different interests for different locales; therefore, different communities are attracted to certain physical locations with different intensities. Besides introducing SAGA, the contributions of this work include: a model calibration approach based on formal statistical procedures to extract social structures and geographical diversity from real traces and set SAGA's parameters; and validation of SAGA by applying it to real mobility traces. Our experimental results show that, when compared to existing mobility regimes such as Random-Waypoint and Preferential-Attachment based mobility, SAGA is able to preserve the desired non-uniform node spatial density present in real user mobility, creating and maintaining clusters and accounting for differential node popularity and transitivity.
- T. Camp, J. Boleng, and V. Davies, "A survey of mobility models for ad hoc network research," Wireless Communications and Mobile Computing, vol. 2, pp. 483--502, 2002.Google ScholarCross Ref
- C. Bettstetter, M. Gyarmati, and U. Schilcher, "An inhomogeneous spatial node distribution and its stochastic properties," in Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems, MSWiM '07, 2007. Google ScholarDigital Library
- M. Musolesi and C. Mascolo, "Mobility models for systems evaluation," in Middleware for Network Eccentric and Mobile Applications, pp. 43--62, Springer, 2009.Google Scholar
- A. Balachandran, G. M. Voelker, P. Bahl, and P. V. Rangan, "Characterizing user behavior and network performance in a public wireless lan," in ACM SIGMETRICS 2002. Google ScholarDigital Library
- M. Balazinska and P. Castro, "Characterizing mobility and network usage in a corporate wireless local-area network," in MobiSys 2003, pp. 303--316. Google ScholarDigital Library
- D. Tang and M. Baker, "Analysis of a local-area wireless network," in ACM MOBICOM 2000. Google ScholarDigital Library
- T. Henderson, D. Kotz, and I. Abyzov, "The changing usage of a mature campus-wide wireless network," in ACM MOBICOM 2004. Google ScholarDigital Library
- R. Albert and A.-L. Barabási, "Statistical mechanics of complex networks," Rev. Mod. Phys., vol. 74, no. 1, pp. 47--97, 2002.Google ScholarCross Ref
- A. Jardosh, E. Belding-Royer, K. Almeroth, and S. Suri, "Real-world environment models for mobile network evaluation," Selected Areas in Communications, IEEE Journal on, vol. 23, no. 3, pp. 622 -- 632, 2005. Google ScholarDigital Library
- M. Kim and D. Kotz, "Extracting a mobility model from real user traces," in IEEE INFOCOM, 2006.Google Scholar
- V. Borrel, M. D. de Amorim, and S. Fdida, "On natural mobility models," in WAC, 2005. Google ScholarDigital Library
- A. Mei and J. Stefa, "Swim: A simple model to generate small mobile worlds," in IEEE INFOCOM 2009.Google Scholar
- M. Musolesi and C. Mascolo, "Designing mobility models based on social network theory," ACM SIGMOBILE Mobile Computing and Communication Review, vol. 11, pp. 59--70, 2007. Google ScholarDigital Library
- S. Lim, C. Yu, and C. Das, "Clustered mobility model for scale-free wireless networks," in Local Computer Networks, Proceedings 2006 31st IEEE Conference on, 2006.Google Scholar
- B. A. Nunes and K. Obraczka, "On the invariance of spatial node density for realistic mobility modeling," in Mobile Adhoc and Sensor Systems (MASS), 2011 IEEE 8th International Conference on, pp. 322--331, oct. 2011. Google ScholarDigital Library
- S. Yang, X. Yang, C. Zhang, and E. Spyrou, "Using social network theory for modeling human mobility," Network, IEEE, vol. 24, pp. 6--13, september-october 2010. Google ScholarDigital Library
- C. Zhao and M. Sichitiu, "N-body: Social based mobility model for wireless ad hoc network research," in Sensor Mesh and Ad Hoc Communications and Networks (SECON), 2010 7th Annual IEEE Communications Society Conference on, pp. 1--9, june 2010.Google Scholar
- V. Borrel, F. Legendre, M. Dias de Amorim, and S. Fdida, "Simps: Using sociology for personal mobility," Networking, IEEE/ACM Transactions on, vol. 17, pp. 831--842, june 2009. Google ScholarDigital Library
- L. Harfouche, S. Boumerdassi, and E. Renault, "Towards a social mobility model," in Personal, Indoor and Mobile Radio Communications, 2009 IEEE 20th International Symposium on, pp. 2876--2880, sept. 2009.Google ScholarCross Ref
- J. Wang, J. Yuan, X. Shan, Z. Feng, J. Geng, and I. You, "Samob: A social attributes based mobility model for ad hoc networks," in Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), 2011 Fifth International Conference on, pp. 444--449, 30 2011-july 2 2011. Google ScholarDigital Library
- D. Fischer, K. Herrmann, and K. Rothermel, "Gesomo: A general social mobility model for delay tolerant networks," in Mobile Adhoc and Sensor Systems (MASS), 2010 IEEE 7th International Conference on, pp. 99--108, nov. 2010.Google Scholar
- H. White, S. Boorman, and R. Breiger, "Social structure from multiple networks: I. blockmodels of roles and positions," American Journal of Sociology, vol. 81, no. 4, pp. 730--80, 1976.Google ScholarCross Ref
- S. Wasserman and K. Faust, Social Network Analysis: Methods and Applications. No. 8, Cambridge University Press, 1994.Google ScholarCross Ref
- M. McPherson, L. Smith-Lovin, and J. M. Cook, "Birds of a feather: Homophily in social networks," Annual Review of Sociology, vol. 27, no. 1, pp. 415--444, 2001.Google ScholarCross Ref
- T. Azevedo, R. Bezerra, C. Campos, and L. de Moraes, "An analysis of human mobility using real traces," in IEEE WCNC 2009. Google ScholarDigital Library
- I. Rhee, M. Shin, S. Hong, K. Lee, and S. Kim, "CRAWDAD http://crawdad.cs.dartmouth.edu/ ncsu/mobilitymodels/GPS/KAIST v.2009-07-23," July 2009.Google Scholar
- B. S. Everitt, S. Landau, M. Leese, and D. Stahl, "Cluster analysis," Wiley. Fifth Edition, 2011. Google ScholarDigital Library
- C. Fraley and A. E. R. (2002), "Model-based clustering, discriminant analysis, and density estimation," Journal of the American Statistical Association, 2002.Google Scholar
- "R: A language and environment for statistical computing."Google Scholar
- A. Rodriguez and B. A. A. Nunes and K. Obraczka, "http://inrg.cse.ucsc.edu/inrgwiki/projects," 2012.Google Scholar
- K. Train, "Discrete choice modelling, with simulations," Cambridge University Press, 2004.Google Scholar
- The Scenario Generator, "http://isis.poly.edu/ qiming/scengen/index.html."Google Scholar
- L. Harfouche, S. Boumerdassi, and E. Renault, "Weighted social manhattan: Modeling and performance analysis of a mobility model," in Personal Indoor and Mobile Radio Communications (PIMRC), 2010 IEEE 21st International Symposium on, 2010.Google Scholar
- W. J. Hsu, T. Spyropoulos, K. Psounis, and A. Helmy, "Modeling time-variant user mobility in wireless mobile networks," IEEE Infocom, 2007.Google Scholar
- C. Boldrini and A. Passarella, "Hcmm: Modelling spatial and temporal properties of human mobility driven by users social relationships," Elsevier Computer Commununication, 2010. Google ScholarDigital Library
- M. E. J. Newman, "The structure and function of complex networks," March, 2003.Google Scholar
- I. Rhee, M. Shin, S. Hong, K. Lee, and S. Chong, "On the levy-walk nature of human mobility," IEEE Infocom, 2008.Google Scholar
- T. Hossmann, T. Spyropoulos, and F. Legendre, "Putting contacts into context: mobility modeling beyond inter-contact times," in Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc '11, 2011. Google ScholarDigital Library
Index Terms
- SAGA: socially- and geography-aware mobility modeling framework
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