| Speaker : | Diego Hora |
| INRIA/LINCS | |
| Date: | 30/03/2016 |
| Time: | 2:00 pm - 2:30 pm |
| Location: | LINCS Meeting Room 40 |
Abstract
Wi-Fi is the preferred way of accessing the internet for many devices at home, but it is vulnerable to performance problems due to sharing an unlicensed medium. In this work, we propose a method to estimate the link capacity of a Wi-Fi link, using physical layer metrics that can be passively sampled on commodity access points. We build a model that predicts the maximum UDP throughput a device can sustain, extending previous models that do not consider IEEE 802.1n optimizations such as frame aggregation. We validate our method through controlled experiments in an anechoic chamber and artificially create different link quality conditions. We estimate the link capacity using our method and compare it to the state of the art. Over 95% of the link capacity predictions present errors below 5% when using our method with reference data. We show how the 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.