14th ACM Multimedia Systems Conference (MMSys)

7 – 10 June 2023 | Vancouver, BC, Canada

Conference Website

[PDF][Slides][Poster]

Daniele Lorenzi (AAU, Austria)

Abstract: Video streaming services account for the majority of today’s traffic on the Internet, and according to recent studies, this share is expected to continue growing. Given this broad utilization, research in video streaming is recently moving towards energy-aware approaches, which aim at reducing the energy consumption of the devices involved in the streaming process. On the other side, the perception of quality delivered to the user plays an important role, and the advent of HTTP Adaptive Streaming (HAS) changed the way quality is perceived. The focus is not any more exclusively on the Quality of Service (QoS) but rather oriented towards the Quality of Experience (QoE) of the user taking part in the streaming session. Therefore video streaming services need to develop Adaptive BitRate (ABR) techniques to deal with different network conditions on the client side or appropriate end-to-end strategies to provide high QoE to the users. The scope of this doctoral study is within the end-to-end environment with a focus on the end-users domain, referred to as the player environment, including video content consumption and interactivity. This thesis aims to investigate and develop different techniques to increase the delivered QoE to the users and minimize the energy consumption of the end devices in HAS context. We present four main research questions to target the related challenges in the domain of content consumption for HAS systems.

Keywords: Multi-codec, HTTP/3, machine learning, green computing, HAS

IEEE International Conference on Multimedia and Expo (ICME), 2023

10-14 July 2023, Brisbane, Australia

[PDF] [Slides]

Vignesh V Menon (Alpen-Adria-Universität Klagenfurt), Jingwen Zhu (Nantes Universite), Prajit T Rajendran (Universite Paris-Saclay), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Patrick Le Callet (Nantes Universite),  and Christian Timmerer (Alpen-Adria-Universität Klagenfurt).

Abstract:

In video streaming applications, a fixed set of bitrate-resolution pairs (known as a bitrate ladder) is typically used during the entire streaming session. However, an optimized bitrate ladder per scene may result in (i) decreased storage or delivery costs or/and (ii) increased Quality of Experience. This paper introduces a Just Noticeable Difference (JND)-aware per-scene bitrate ladder prediction scheme (JASLA) for adaptive video-on-demand streaming applications. JASLA predicts jointly optimized resolutions and corresponding constant rate factors (CRFs) using spatial and temporal complexity features for a given set of target bitrates for every scene, which yields an efficient constrained Variable Bitrate encoding. Moreover, bitrate-resolution pairs that yield distortion lower than one JND are eliminated. Experimental results show that, on average, JASLA yields bitrate savings of 34.42% and 42.67% to maintain the same PSNR and VMAF, respectively, compared to the reference HTTP Live Streaming (HLS) bitrate ladder Constant Bitrate encoding using x265 HEVC encoder, where the maximum resolution of streaming is Full HD (1080p). Moreover, a 54.34% average cumulative decrease in storage space is observed.

JASLA architecture.

IEEE ComSoc MMTC Distinguished Lecture Series

Speaker: Prof. Christian Timmerer, Alpen-Adria-Universität Klagenfurt (AAU), Austria

Date/Time: Thursday, Apr 20, 2023, 10:00 AM Pacific Time (US and Canada), CET Time 7:00 PM Austria
Title: HTTP Adaptive Streaming (HAS) — Quo Vadis? (2023; for the 2021 version, see here)

Abstract: Video traffic on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research and of industrial networked multimedia services certainly was the HTTP Adaptive Streaming (HAS) technique. This resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) which, together with HTTP Live Streaming (HLS), is widely used for multimedia delivery in today’s networks. Existing challenges in multimedia systems research deal with the trade-off between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, latency), and (iii) quality of experience (QoE). Optimizing towards one aspect usually negatively impacts at least one of the other two aspects if not both. This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry. In this talk, we will present selected novel approaches and research results of the first year of the ATHENA CD Lab’s operation. We will highlight HAS-related research on (i) multimedia content provisioning (machine learning for video encoding); (ii) multimedia content delivery (support of edge processing and virtualized network functions for video networking); (iii) multimedia content consumption and end-to-end aspects (player-triggered segment retransmissions to improve video playout quality); and (iv) novel QoE investigations (adaptive point cloud streaming). We will also put the work into the context of international multimedia systems research.

Biography: Christian Timmerer is a full professor of computer science at Alpen-Adria-Universität Klagenfurt (AAU), Institute of Information Technology (ITEC) and he is the director of the Christian Doppler (CD) Laboratory ATHENA (https://athena.itec.aau.at/). His research interests include multimedia systems, immersive multimedia communication, streaming, adaptation, and quality of experience where he co-authored seven patents and more than 300 articles. He was the general chair of WIAMIS 2008, QoMEX 2013, MMSys 2016, and PV 2018 and has participated in several EC-funded projects, notably DANAE, ENTHRONE, P2P-Next, ALICANTE, SocialSensor, COST IC1003 QUALINET, ICoSOLE, and SPIRIT. He also participated in ISO/MPEG work for several years, notably in the area of MPEG-21, MPEG-M, MPEG-V, and MPEG-DASH where he also served as standard editor. In 2012 he cofounded Bitmovin (http://www.bitmovin.com/) to provide professional services around MPEG-DASH where he holds the position of the Chief Innovation Officer (CIO) –- Head of Research and Standardization. Further information at http://timmerer.com.

Multimedia Tools and Applications

[PDF]

Minh Nguyen (AAU, Austria), Hadi Amirpour (AAU, Austria), Farzad Tashtarian (AAU, Austria), Christian Timmerer (AAU, Austria) and Hermann Hellwagner (AAU, Austria)

Abstract: HTTP Adaptive Streaming (HAS) plays a key role in over-the-top video streaming with the ability to reduce the video stall duration by adapting the quality of transmitted video segments to the network conditions. However, HAS still suffers from two problems. First, it incurs variations in video quality because of throughput fluctuation. Adaptive bitrate (ABR) algorithms at the HAS client usually select a low-quality segment when the throughput drops to avoid stall events, which impairs the Quality of Experience (QoE) of the end-users. Second, many ABR algorithms choose the lowest-quality segments at the beginning of a video streaming session to ramp up the playout buffer early on. Although this strategy decreases the startup time, clients can be annoyed as they have to watch a low-quality video initially.

To address these issues, we introduced the H2BR technique (HTTP/2-Based Retransmission) that utilizes certain features of HTTP/2 (including server push, multiplexing, stream priority, and stream termination) for late transmissions of higher-quality versions of video segments already in the client buffer, in order to improve video quality. Although H2BR was shown to enhance the QoE, limited streaming scenarios were considered resulting in a lack of general conclusions on H2BR’s performance. Thus, this article provides a profound evaluation to answer three open questions: (i) how H2BR’s performance is impacted by parameters at the server side (i.e., various encoding specifications), at the network side (i.e., packet loss rate), and at the client side (i.e., buffer size) on the performance of H2BR; (ii) how H2BR outperforms other state-of-the-art approaches in different configurations of the parameters above; (iii) how to effectively utilize H2BR on top of ABR algorithms in various streaming scenarios.

The experimental results show that H2BR’s performance increases with the buffer size and decreases with increasing packet loss rates and/or video segment duration. The number of quality levels can negatively or positively impact on H2BR’s performance, depending on the ABR algorithm deployed. In general, H2BR is able to enhance the video quality by up to and 14% in scalablevideo streaming and in non-scalable video streaming, respectively. Compared with an existing retransmission technique (i.e., SQUAD), H2BR shows better results with more than 10% in QoE and 9% in the average video quality.

Keywords: HTTP adaptive streaming, DASH, Retransmission, QoE, HTTP/2, H2BR