Understanding the WiFi usage of university students

Alessandro Redondi, Daniel Weibull, Matteo Cesana, Emma Fitzgerald

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review


In this work, we analyze the use of a WiFi network deployed in a large-scale technical university. To this extent, we leverage three weeks of WiFi traffic data logs and characterize the spatio-temporal correlation of the traffic at different granularities (each individual access point, groups of access points, entire network). The spatial correlation of traffic across nearby access points is also assessed. Then, we search for distinctive fingerprints left on the WiFi traffic by different situations/conditions; namely, we answer the following questions: Do students attending a lecture use the wireless network in a different way than students not attending a lecture?, and Is there any difference in the usage of the wireless network during architecture or engineering classes? A supervised learning approach based on Quadratic Discriminant Analysis (QDA) is used to classify empty vs. occupied rooms and engineering vs. architecture lectures using only WiFi traffic logs with promising results.
Titel på värdpublikation7th International Workshop on TRaffic Analysis and Characterization (TRAC)
StatusPublished - 2016
Evenemang7th International Workshop on TRaffic Analysis and Characterization - Paphos, Cypern
Varaktighet: 2016 sep. 52016 sep. 9


ISSN (tryckt)2376-6506


Workshop7th International Workshop on TRaffic Analysis and Characterization

Ämnesklassifikation (UKÄ)

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