2017/05/24 by Dimitrios Tsilimantos, Theodoros Karagkioules, Tsilimantos, Dimitrios +5
Computer Science · #FOS: Computer and information sciences #Multimedia (cs.MM) #cs.MM
paper · pdf · doi:10.48550/arxiv.1705.08733
7 pages, 11 figures. Accepted for publication in the proceedings of IEEE ICC'17
arxiv created 2017/05/24 · arxiv updated 2017/05/25
This paper describes a novel system that provides key parameters of HTTP Adaptive Streaming (HAS) sessions to the lower layers of the protocol stack. A non-intrusive traffic profiling solution is proposed that observes packet flows at the transmit queue of base stations, edge-routers, or gateways. By analyzing IP flows in real time, the presented scheme identifies different phases of an HAS session and estimates important application-layer parameters, such as play-back buffer state and video encoding rate. The introduced estimators only use IP-layer information, do not require standardization and work even with traffic that is encrypted via Transport Layer Security (TLS). Experimental results for a popular video streaming service clearly verify the high accuracy of the proposed solution. Traffic profiling, thus, provides a valuable alternative to cross-layer signaling and Deep Packet Inspection (DPI) in order to perform efficient network optimization for video streaming.