Analysis of a local-area wireless network
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Characterizing user behavior and network performance in a public wireless LAN
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
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Characterizing mobility and network usage in a corporate wireless local-area network
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An inhomogeneous spatial node distribution and its stochastic properties
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Designing mobility models based on social network theory
ACM SIGMOBILE Mobile Computing and Communications Review
Cluster Analysis
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IEEE/ACM Transactions on Networking (TON)
An analysis of human mobility using real traces
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Using social network theory for modeling human mobility
IEEE Network: The Magazine of Global Internetworking
SaMob: A Social Attributes Based Mobility Model for Ad Hoc Networks
IMIS '11 Proceedings of the 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing
On the Invariance of Spatial Node Density for Realistic Mobility Modeling
MASS '11 Proceedings of the 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems
Putting contacts into context: mobility modeling beyond inter-contact times
MobiHoc '11 Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing
WAC'05 Proceedings of the Second international IFIP conference on Autonomic Communication
Real-world environment models for mobile network evaluation
IEEE Journal on Selected Areas in Communications
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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.