Predicting the effect of home Wi-Fi on Web QoE



Predicting the effect of home Wi-Fi on Web QoE

Predicting the effect of home Wi-Fi on Web QoE
Research Paper / SIGCOMM Internet-QoE workshop 16 / Aug 2016 / Wireless Communications, Machine/Deep Learning/AI

Wi-Fi is the preferred way of accessing the Internet for many devices at home, but it is vulnerable to performance problems. The analysis of Wi-Fi quality metrics such as RSSI or PHY rate may indicate a number of problems, but users may not notice many of these problems if they don't degrade the performance of the applications they are using. In this work, we study the effects of the home Wi-Fi quality on Web browsing experience. We instrument a commodity access point (AP) to passively monitor Wi-Fi metrics and study the relationship between Wi-Fi metrics and Web QoE through controlled experiments in a Wi-Fi testbed. We use support vector regression to build a predictor of Web QoE when given Wi-Fi quality metrics available in most commercial APs. Our validation shows root-mean square errors on MOS predictions of 0.6432 in a controlled environment and of 0.9283 in our lab. We apply our predictor on Wi-Fi metrics collected in the wild from 4,880 APs to shed light on how Wi-Fi quality affects Web QoE in real homes.