Section: New Results
Predicting the effect of home Wi-Fi quality on Web QoE
Participants: Diego Neves da Hora, Renata Teixeira, Karel Van Doorselaer (Technicolor), Koen Van Oost (Technicolor)
We developed a model that predicts the effect of Wi-Fi quality on Web QoE, using solely Wi-Fi metrics commonly available in commercial APs. We trained our predictor during controlled experiments on a Wi-Fi testbed and assess its accuracy through cross-validation, obtaining an RMSE of 0.6432 MO, and by applying it on a separate validation dataset, obtained on an uncontrolled environment, finding an RMSE of 0.9283. Finally, we apply our predictor on Wi-Fi metrics collected in the wild from 4,880 APs over a period of 40 days. We find that Wi-Fi quality is mostly good for Web—in more than 60% of samples Wi-Fi quality does not degrade Web QoE. When we consider average complexity Web pages, however, Wi-Fi quality degrades Web QoE in of samples. Moreover, we saw that of devices present more than of poor Web QoE samples, with of these showing highly intermittent QoE degradations, which are particularly hard to diagnose, indicating the need for a long-term monitoring approach to detect and fix problems.