Advanced

Understanding the WiFi usage of university students

Redondi, Alessandro; Weibull, Daniel; Cesana, Matteo and Fitzgerald, Emma LU (2016) 7th International Workshop on TRaffic Analysis and Characterization In 7th International Workshop on TRaffic Analysis and Characterization (TRAC)
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
7th International Workshop on TRaffic Analysis and Characterization (TRAC)
conference name
7th International Workshop on TRaffic Analysis and Characterization
external identifiers
  • scopus:84994087165
ISSN
2376-6506
DOI
10.1109/IWCMC.2016.7577031
language
English
LU publication?
yes
id
a45bcafd-7cd4-4db0-89d5-82bb85320250
date added to LUP
2016-04-26 09:57:33
date last changed
2017-04-11 10:33:15
@inproceedings{a45bcafd-7cd4-4db0-89d5-82bb85320250,
  abstract     = {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.},
  author       = {Redondi, Alessandro and Weibull, Daniel and Cesana, Matteo and Fitzgerald, Emma},
  booktitle    = {7th International Workshop on TRaffic Analysis and Characterization (TRAC)},
  issn         = {2376-6506},
  language     = {eng},
  title        = {Understanding the WiFi usage of university students},
  url          = {http://dx.doi.org/10.1109/IWCMC.2016.7577031},
  year         = {2016},
}