SAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3

Dynamic Adaptive Streaming over HTTP (DASH) is a widely used standard for video content delivery. Video traffic, most of which is generated from mobile devices, is shortly to become the most significant part of Internet traffic. Current DASH solutions only consider either client- or server-side opti...

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Bibliographic Details
Main Authors: Luis Guillen, Satoru Izumi, Toru Abe, Takuo Suganuma
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Electronics
Subjects:
SDN
QoE
Online Access:https://www.mdpi.com/2079-9292/8/8/864
Description
Summary:Dynamic Adaptive Streaming over HTTP (DASH) is a widely used standard for video content delivery. Video traffic, most of which is generated from mobile devices, is shortly to become the most significant part of Internet traffic. Current DASH solutions only consider either client- or server-side optimization, leaving other components in DASH (e.g., at the transport layer) to default solutions that cause a performance bottleneck. In that regard, although it is assumed that HTTP must be necessarily transported on top of TCP, with the latest introduction of HTTP/3, it is time to re-evaluate its effects on DASH. The most substantial change in HTTP/3 is having Quick UDP Internet Connections (QUIC) as its primary underlying transport protocol. However, little is still know about the effects on standard DASH client-based adaption algorithms when exposed to the future HTTP/3. In this paper, we present SAND/3, an SDN (Software Defined Networking)-based Quality of Experience (QoE) control method for DASH over HTTP/3. Since the official deployment of HTTP/3 has not been released yet, we used the current implementation of Google QUIC. Preliminary results show that, by applying SAND/3, which combines information from different layers orchestrated by SDN to select the best QoE, we can obtain steadier media throughput, reduce the number of quality shifts in at least 40%, increase the amount downloaded content at least 20%, and minimize video interruptions compared to the current implementations regardless of the client adaption algorithm.
ISSN:2079-9292