Passive Wi-Fi Link Capacity Estimation on Commodity Access Points

Diego Neves da Hora 1, * Karel Van Doorselaer 2 Koen Van Oost 2 Renata Teixeira 1 Christophe Diot 3
* Auteur correspondant
1 MUSE - Measuring networks for enhancing USer Experience
Inria de Paris
2 Technicolor - Technicolor (Entreprise)
3 SAFRAN Group
Abstract : Wi-Fi is the preferred way of accessing the internet for many devices at home, but it is vulnerable to performance problems. In this work, we propose a method to estimate the link capacity of a Wi-Fi link using physical layer metrics passively sampled on commodity access points. We build a model that predicts the maximum UDP throughput a device can sustain, which extends previous models to consider IEEE 802.11n optimizations such as frame aggregation. We validate our model through controlled experiments in an anechoic chamber. Over 95% of the link capacity predictions present errors below 5% when using our model with reference data. We show how link capacity estimation enables Wi-Fi diagnosis in two case studies where we predict the available bandwidth under microwave interference and in an office environment.
Type de document :
Communication dans un congrès
Traffic Monitoring and Analysis Workshop (TMA) 2016, Apr 2016, Louvain-la-Neuve, Belgium. 2016
Liste complète des métadonnées

Littérature citée [18 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01292633
Contributeur : Diego Neves da Hora <>
Soumis le : mercredi 23 mars 2016 - 14:50:06
Dernière modification le : jeudi 7 février 2019 - 17:34:57
Document(s) archivé(s) le : vendredi 24 juin 2016 - 13:39:29

Fichier

article.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01292633, version 1

Collections

INRIA | INRIA-ROCQ

Citation

Diego Neves da Hora, Karel Van Doorselaer, Koen Van Oost, Renata Teixeira, Christophe Diot. Passive Wi-Fi Link Capacity Estimation on Commodity Access Points. Traffic Monitoring and Analysis Workshop (TMA) 2016, Apr 2016, Louvain-la-Neuve, Belgium. 2016. 〈hal-01292633〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

373

Téléchargements de fichiers

708

Contact


archive-ouverte@inria.fr