Poster abstract: Location-centric relationship graph for indoor mobility using WLANs

Understanding the mobile user flow flux patterns is important for numerous applications. Much of the mobility modeling studies have focused on a user-centric approach for outdoors movement. In this study, we take a location-centric approach for indoor mobility to analyze and characterize region relationships as pertains to user flow. Our study is trace-driven, as we use extensive measurements from wireless LANs, and mine them to quantify metrics for influx and outflux for various buildings at a university campus involving more than 84K anonymous mobile users. We derived the regions' relationship graph and compute and contrast its properties in different buildings during both a weekday and a weekend. Then, the influx and outflux degrees are computed for regions during thirty days. Interestingly, the degrees do not follow a power law distribution.