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Conference Paper: Short-term traffic forecasting in a campus-wide wireless network

TitleShort-term traffic forecasting in a campus-wide wireless network
Authors
Issue Date2005
Citation
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2005, v. 3, p. 1446-1452 How to Cite?
AbstractOur goal is to characterize the traffic load in an IEEE802.11 infrastructure. This can be beneficial in many domains, including coverage planning, resource reservation, network monitoring for anomaly detection, and producing more accurate simulation models. The key issue that drives this study is traffic forecasting at each wireless access point (AP) in an hourly timescale. We conducted an extensive measurement study of wireless users on a major university campus using the IEEE802.11 wireless infrastructure. We propose several traffic models that take into account the periodicity and recent traffic history for each AP and present a time-series forecasting methodology. Finally, we build and evaluate these forecasting algorithms and discuss our findings. © 2005 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/219532

 

DC FieldValueLanguage
dc.contributor.authorPapadopouli, Maria-
dc.contributor.authorShen, Haipeng-
dc.contributor.authorRaftopoulos, Elias-
dc.contributor.authorPloumidis, Manolis-
dc.contributor.authorHernandez-Campos, Felix-
dc.date.accessioned2015-09-23T02:57:19Z-
dc.date.available2015-09-23T02:57:19Z-
dc.date.issued2005-
dc.identifier.citationIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2005, v. 3, p. 1446-1452-
dc.identifier.urihttp://hdl.handle.net/10722/219532-
dc.description.abstractOur goal is to characterize the traffic load in an IEEE802.11 infrastructure. This can be beneficial in many domains, including coverage planning, resource reservation, network monitoring for anomaly detection, and producing more accurate simulation models. The key issue that drives this study is traffic forecasting at each wireless access point (AP) in an hourly timescale. We conducted an extensive measurement study of wireless users on a major university campus using the IEEE802.11 wireless infrastructure. We propose several traffic models that take into account the periodicity and recent traffic history for each AP and present a time-series forecasting methodology. Finally, we build and evaluate these forecasting algorithms and discuss our findings. © 2005 IEEE.-
dc.languageeng-
dc.relation.ispartofIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC-
dc.titleShort-term traffic forecasting in a campus-wide wireless network-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-34047102422-
dc.identifier.volume3-
dc.identifier.spage1446-
dc.identifier.epage1452-

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