Deadline-based approach for improving delivery of SVC-based HTTP adaptive streaming contentDeadline-based approach for improving delivery of SVC-based HTTP adaptive streaming content
Faculty of Sciences. Mathematics and Computer Science
Modeling Of Systems and Internet Communication (MOSAIC)
2014New york :Ieee, 2014
2014 IEEE NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM (NOMS)
14th IEEE/IFIP Network Operations and Management Symposium (NOMS), MAY 05-09, 2014, Krakow, POLAND
(2014), p. 1-7, 7 p.
University of Antwerp
HTTP Adaptive Streaming (HAS) has several advantages compared to traditional streaming protocols, such as easy traversal of firewalls and reuse of widely deployed HTTP infrastructure. HAS content is temporally segmented, and encoded at different quality representations, allowing the video player to autonomously adapt to network conditions by adapting play-out quality between subsequent segment downloads. However, to guarantee continuous playback, current-generation HAS protocols require a large play-out buffer. This makes them illsuited for live television, as it significantly increases the live signal delay. This paper proposes a novel HAS solution for live streaming services. A HAS video player was designed that can cope with buffers as small as 2 seconds. This obviously requires the player to more rapidly react to bandwidth changes, which was achieved by using the Scalable Video Coding (SVC) extension of the H.264 Advanced Video Coding (AVC) video codec. Moreover, an intelligent network proxy was developed that guarantees the delivery of the SVC base quality layer using Differentiated Services (DiffServ). Furthermore, a more dynamic deadline-based approach is proposed which allows the client itself to decide which segments should be prioritized based on the risk of running into a buffer starvation. This enables more efficient use of the prioritized channel, leading to less freezes and increased quality and stability. The combination of these technologies allows the video player to align its quality adaptation decisions to the available bandwidth more efficiently and completely avoid buffer starvations. The small buffer size also reduces the total live signal delay from multiple dozens to only a few seconds.