Quality of Experience-Centric Management of Adaptive Video Streaming Services

Abstract

Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming (HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this paper, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years.

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

“…Wang et al [19] 2016 Architecture for personalized QoE management Yes No No Peng et al [35] 2017 QoE-oriented mobile edge service management Yes MEC only No Sousa et al [26] 2017 QoE-based scheduling strategies No No No Skorin-Kapov et al [25], Petrangeli et al [31] 2018…”

“…QoE modeling, QoE monitoring and management [25], QoEcentric management of adaptive video streaming services [31] To some extent ICN only [31], MEC only [25] AR/VR & multisensory Barman and Martini [30] Yes ** QoE in New Domains: We refer to aspects of QoE in new domains such as AR/VR, mulsemedia and gaming video streaming applications. It is to be noted that with the exception of Skorin-Kapov et al [25] and Petrangeli et al [31] which discuss AR/VR & multisensory applications, other survey papers are limited in this aspect which is covered in this work. **…”

“…In these approaches, viewport-dependent solutions [287], [288] have been proposed for 360 • video streaming, because they can reduce the bandwidth required to stream the video. The user in VR is immersed in a virtual environment and can dynamically and freely decide the preferred viewpoint [31]. In viewpoint-dependent streaming, the portion outside the viewpoint is streamed at an average or lower quality while the part of the video watched by the user is streamed at the highest possible quality.…”

“…Emerging Multimedia Applications [31], [287]- [289], [321], [292], [293], [336], [332], [333], [335], [341] Mechanisms for ensuring the QoE for VR/AR, Mulsemedia, Video gaming and light field display. The current QoE models for delivery of adaptive video streams have three limitations: (1) they are developed to capture the behavior of the "average" user, and hence some of them are not personalized, (2) they do not consider the context in which the streaming session takes place, and (3) only the QoE model of the users is inserted into the control loop, but not the user herself [31]. Therefore, using the network, application and user-level parameters could potentially allow creating QoE personalized models of emerging multimedia services.…”

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

“…Although there is a large body of knowledge about DASH and how to perform the adaption [11,13]. in this section, we briefly present the related work focused on SDN-based solutions to improve video delivery in DASH over traditional TCP.…”