Modeling Time-Variant User Mobility in Wireless Mobile Networks

By Wei-jen Hsu, Thrasyvoulos Spyropoulos, Konstantinos Psounis, Ahmed G. Helmy. IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications, 2007

369 citations recorded by the source corpus.

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SLAW: A New Mobility Model for Human Walks (2009, neutral): “While other work [14], [ 22 ], [26] exists in expressing the regularity of daily trip patterns of humans, none of the existing work reflects realistic statistical patterns appearing in real human walk traces.”
A parsimonious model of mobile partitioned networks with clustering (2009, background): “The Community Based Mobility Model proposed by Spyropoulos et al. in [26], and further extended in [ 11 ], is designed to recreate t he characteristics of mobility in sparse networks.”
Time-varying graphs and dynamic networks (2010, methodology): “Mobility models from social networks include the Time-Variant Community model (TVC) [39], and the more recent Home-cell Community-based Mobility Model (HCMM) [13].”
Serendipity: enabling remote computing among intermittently connected mobile devices (2012, methodology): “Speci.cally, we use Levy Walk Model [28], Random WayPoint Model (RWP) [29], and Time-Variant Community Mobility Model (TVCM) [21].”
Human mobility models for opportunistic networks (2011, methodology): “The Time-Variant Community model [11] is the most popular solution in this class.”
Human mobility modeling at metropolitan scales (2012, methodology): “[15] used WLAN traces to extract a time-variant community mobility model that showed good performance via simulation.”