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Video quality representation classification of Safari encrypted DASH streams

Published on Jul 4, 2016
· DOI :10.1109/DMIAF.2016.7574935
Ran Dubin5
Estimated H-index: 5
(BGU: Ben-Gurion University of the Negev),
Ofer Hadar16
Estimated H-index: 16
(BGU: Ben-Gurion University of the Negev)
+ 3 AuthorsOfir Pele8
Estimated H-index: 8
(Ariel University)
Source
Abstract
The increasing popularity of HTTP adaptive video streaming services has dramatically increased bandwidth requirements on operator networks, which attempt to shape their traffic through Deep Packet Inspection (DPI). However, Google and certain content providers have started to encrypt their video services. As a result, operators often encounter difficulties in shaping their encrypted video traffic via DPI. This highlights the need for new traffic classification methods for encrypted HTTP adaptive video streaming to enable smart traffic shaping. These new methods will have to effectively estimate the quality representation layer and playout buffer. We present a new method and show for the first time that video quality representation classification for (YouTube) encrypted HTTP adaptive streaming is possible. We analyze the performance of this classification method with Safari over HTTPS. Based on a large number of offline and online traffic classification experiments, we demonstrate that it can independently classify, in real time, every video segment into one of the quality representation layers with 96.13% average accuracy.
  • References (39)
  • Citations (5)
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The performance of YouTube in mobile networks is crucial to network operators, who try to find a trade-off between cost-efficient handling of the huge traffic amounts and high perceived end-user Quality of Experience (QoE). This paper introduces YoMoApp (YouTube Performance Monitoring Application), an Android application, which passively monitors key performance indicators (KPIs) of YouTube adaptive video streaming on end-user smartphones. The monitored KPIs (i.e., player state/events, buffer, a...
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Measurement of video Quality of Experience is needed to enable telecommunication service operators to provide acceptable video viewing experience to their customers. Without accurate Quality of Experience measurement, it is hard to predict customer satisfaction. Accessibility and Retain ability failures are important factors that can affect the experience of viewing video on the Internet. Most of the published work in the assessment of Video Quality of Experience has focused on the quality of vi...
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The MPEG-DASH standard allows the client-centric access to different representations of video content via the HTTP protocol. The client can flexibly switch between different qualities, i.e., different bit rates and thus avoid waiting times during the video playback due to empty playback buffers. However, quality switches and the playback of lower qualities is perceived by the user which may reduce the Quality of Experience (QoE). Therefore, novel algorithms are required which manage the streamin...
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Traffic classification has received increasing attention in the last years. It aims at offering the ability to automatically recognize the application that has generated a given stream of packets from the direct and passive observation of the individual packets, or stream of packets, flowing in the network. This ability is instrumental to a number of activities that are of extreme interest to carriers, Internet service providers and network administrators in general. Indeed, traffic classificati...
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This chapter investigates HTTP video streaming over the Internet for the YouTube platform. YouTube is used as concrete example and case study for video delivery over the Internet, since it is not only the most popular online video platform, but also generates a large share of traffic on today's Internet. We will describe the YouTube infrastructure as well as the underlying mechanisms for optimizing content delivery. Such mechanisms include server selection via DNS as well as application-layer tr...
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