{"title":"Poster abstract: Location-centric relationship graph for indoor mobility using WLANs","authors":"Mimonah Al Qathrady, A. Helmy","doi":"10.1109/INFCOMW.2017.8116542","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":306731,"journal":{"name":"2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFCOMW.2017.8116542","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.