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
* Corresponding author
1 MUSE - Measuring networks for enhancing USer Experience
Inria de Paris
2 Technicolor
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.
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Submitted on : Wednesday, March 23, 2016 - 2:50:06 PM
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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. ⟨hal-01292633⟩

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