A methodology for assessing the predictable behaviour of mobile users in wireless networks. (20th June 2013)

• Record Type: Journal Article
• Authors: Marin, Radu‐Corneliu; Dobre, Ciprian; Xhafa, Fatos; Xhafa, Fatos; Chen, Xiaofeng; Huang, Xinyi; Kolici, Vladi
• Is Part Of: Concurrency and computation. Volume 26:Number 5(2014:Apr.)
• Page Start: 1215
• Page End: 1230
• Publication Date: 2013-06-20
• Subjects: Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.3064
• Languages: English
• ISSNs: 1532-0626

Abstract

<abstract abstract-type="main" id="cpe3064-abs-0001"> <title>SUMMARY</title> <p id="cpe3064-para-0001">The analysis of the predictability of human behaviour is an emerging topic in the ubiquitous computing community. Recent endeavours in studying the human behaviour are either based on synthetic models or on real mobile user traces, but what they are mainly focusing on is location: discovering travel patterns or anticipating the whereabouts of mobile users. We extend the analysed context by studying the wireless behaviour of mobile users: interactions with both peers and network devices in academic and office environments. We propose a methodology and a set of guidelines to assess and aid in analysing wireless mobile traces. We prove that the human behaviour is predictable when the studied traced sets are convergent, complete and correct, and we obtain a surprising invariability in interacting with wireless access points, as we are able to pinpoint a wireless user to one of two locations at any specific hour. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>