Abstract:
Today’s traffic projections speak of almost 58% video traffic across the Internet. Nearly all video traffic is encrypted, accounting for more than 50% encrypted traffic w...Show MoreMetadata
Abstract:
Today’s traffic projections speak of almost 58% video traffic across the Internet. Nearly all video traffic is encrypted, accounting for more than 50% encrypted traffic worldwide. To analyze video traffic today, or even estimate its quality in the network, a deep look into the traffic characteristics has to be done. But then, important quality metrics from the traffic behavior can be derived. Based on extensive measurements we show in this work how to measure and estimate video stalls for mobile adaptive streaming. The underlying dataset includes more than 900 hours of video footage from the native YouTube app, measured over 18 different videos in 56 network scenarios in two cities in Europe. We outline a possible approach to estimate the video playback buffer size based on uplink video chunk requests in real-time to break down the video stalls. This work is intended as a tool for network operators to receive further knowledge of the characteristics of video streaming traffic to quantify the most important QoE degradation factors of one of the most important applications today.
Date of Conference: 20-24 April 2020
Date Added to IEEE Xplore: 08 June 2020
ISBN Information: