Video Quality Representation Classification of Encrypted HTTP Adaptive Video Streaming

2018 KSII Transactions on Internet and Information Systems  
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
more » ... 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 machine learning method and show for the first time that video quality representation classification for (YouTube) encrypted HTTP adaptive streaming is possible. The crawler codes and the datasets are provided in [43, 44, 51] . An extensive empirical evaluation shows that our method is able to independently classify every video segment into one of the quality representation layers with 97% accuracy if the browser is Safari with a Flash Player and 77% accuracy if the browser is Chrome, Explorer, Firefox or Safari with an HTML5 player. A preliminary version of this paper appeared in IEEE DMIAF, June 4-6, Santorini, Greece. In this version we added a testbed that has all four leading browsers with a HTML5 player (Chrome, Explorer, Firefox and Safari) whereas in the DMAIF paper we had only Safari with a Flash player; The new testbed is much larger and contains 500 streams of 100 movies, whereas the DMAIF paper had only 120 streams and 40 movies; We also extended the analysis of our algorithm with a different network conditions, different training size.
doi:10.3837/tiis.2018.08.014 fatcat:miqee236ifh7vonh2fj6gozb7y