ATHENA Christian Doppler (CD) Laboratory

Klagenfurt, July 10, 2024

Congratulations to Dr. Babak Taraghi for successfully defending his dissertation on “End-to-end Quality of Experience Evaluation for HTTP Adaptive Streaming” at Universität Klagenfurt in the context of the Christian Doppler Laboratory ATHENA.

Abstract

HTTP Adaptive Streaming (HAS) has risen to prominent acclaim as the prevailing approach for distributing video content across the Internet. The emergence of popular online streaming platforms, which mainly leverage HAS, has led to a surge in the number of users actively generating and consuming high-quality content. Nonetheless, this remarkable surge presents an intricate puzzle for scholars and service providers, who must contend with varying network conditions and limited network resources to meet user expectations for quality.

In response to these challenges, this dissertation explores the end-to-end evaluation of Quality of Experience (QoE) in the context of HAS. This dissertation investigates evaluation methodologies and frameworks designed to measure QoE and end-to-end latency, particularly in live HAS deployments. We identified the gaps and challenges in current QoE evaluation methodologies through extensive literature reviews and analysis of existing approaches. This thesis proposes novel contributions to address these gaps, encompassing the development of evaluation frameworks, enhancing the understanding of QoE, in-depth studies on QoE impacting factors, and curating a comprehensive dataset.

This dissertation’s first category of contributions is the development of two evaluation frameworks, CAdViSE and LLL-CAdViSE. These frameworks provide researchers and developers with powerful tools to assess the performance and QoE of HAS systems. By harnessing the potential of cloud-based architectures and cuttingedge testing functionalities, these frameworks empower the undertaking of expansive evaluations, incorporating various streaming protocols, codecs, and various network
scenarios. As a result, they contribute significantly to the refinement of streaming systems. Notably, both frameworks are available to the public as open-source projects, marking a noteworthy stride in advancing the field.

As a second category of contributions, we present two extensive studies
investigating the metrics and factors influencing QoE. We investigated the impact of the performance of heuristic-based algorithms on QoE by employing subjective assessment methods and analyzing the influence of algorithmic decisions on user perception. We did an in-depth analysis of stall events and quality switches by conducting subjective assessments and Analysis of Variance (ANOVA) to unveil their influence on QoE. We found that the longer stall events led to greater dissatisfaction.
Further investigation focused on stall event duration and rebuffering’s impact on QoE. Our evaluations revealed that stall events under 4ms went unnoticed by users. Shorter stall durations were generally more tolerable, and improved buffering strategies helped mitigate stall effects on QoE.

In the third contribution category, this thesis fulfills the requirement for contemporary datasets that mirror the latest progress in video technology. A thoroughgoing collection named the ”Multi-codec Ultra High Definition 8K MPEG DASH Dataset” has been meticulously curated. It encompasses a wide array of video content, encoded with cutting-edge codecs like VVC and boasting resolutions up to 8K. This comprehensive dataset forms the bedrock for evaluations across diverse streaming scenarios.

This dissertation advances the field of QoE evaluation for HAS through the development of evaluation frameworks, insightful studies, in-depth analysis, and the presentation of a comprehensive dataset. It provides a ground for researchers and developers to assess and enhance the streaming experience, leading to improved algorithms, optimized systems, and enhanced user satisfaction in HAS.

Slides are available here.

COBIRAS: Offering a Continuous Bit Rate Slide to Maximize DASH Streaming Bandwidth Utilization

ACM Transactions on Multimedia Computing Communications and Applications (ACM TOMM)

[PDF]

Michael Seufert (University of Augsburg, Germany), Marius Spangenberger (University of Würzburg, Germany), Fabian Poignée (University of Würzburg, Germany), Florian Wamser (Lucerne University of Applied Sciences and Arts, Switzerland), Werner Robitza (AVEQ GmbH, Austria), Christian Timmerer (Christian Doppler-Labor ATHENA, Alpen-Adria-Universität, Austria), Tobias Hoßfeld (University of Würzburg, Germany)

Comparison of classical DASH system to proposed DASH system with COBIRAS, JITE at the DASH server, and MinOff at the DASH client.}

Abstract: Reaching close-to-optimal bandwidth utilization in Dynamic Adaptive Streaming over HTTP (DASH) systems can, in theory, be achieved with a small discrete set of bit rate representations. This includes typical bit rate ladders used in state-of-the-art DASH systems. In practice, however, we demonstrate that bandwidth utilization, and consequently the Quality of Experience (QoE), can be improved by offering a continuous set of bit rate representations, i.e., a continuous bit rate slide (COBIRAS). Moreover, we find that the buffer fill behavior of different standard adaptive bit rate (ABR) algorithms is sub-optimal in terms of bandwidth utilization. To overcome this issue, we leverage COBIRAS’ flexibility to request segments with any arbitrary bit rate and propose a novel ABR algorithm MinOff, which helps maximizing bandwidth utilization by minimizing download off-phases during streaming. To avoid extensive storage requirements with COBIRAS and to demonstrate the feasibility of our approach, we design and implement a proof-of-concept DASH system for video streaming that relies on just-in-time encoding (JITE), which reduces storage consumption on the DASH server. Finally, we conduct a performance evaluation on our testbed and compare a state-of-the-art DASH system with few bit rate representations and our JITE DASH system, which can offer a continuous bit rate slide, in terms of bandwidth utilization and video QoE for different ABR algorithms.

Additional Key Words and Phrases: Dynamic Adaptive Streaming over HTTP, DASH, HTTP Adaptive Streaming, HAS, Encoding, Bit Rate Representations, Adaptive Bit Rate, ABR, Bandwidth Utilization, Quality of Experience, QoE

The paper titled “Beyond Curves and Thresholds – Introducing Uncertainty Estimation to Satisfied User Ratios for Compressed Video,” co-authored by Jingwen Zhu, Hadi Amirpour, Raimund Shatz, Patrick Le Callet, and Christian Timmerer, received the Best Paper Award at the 37th Picture Coding Symposium.

This special issue aims to collect extended versions of the accepted papers at ACM Multimedia Systems 2024 and co-located workshops (i.e., NOSSDAV, MMVE, and GMSys). Similarly, as for 2023, it is planned that all accepted MMSys full research papers and workshop papers are eligible for submission, which must have at least 25% new material compared to the accepted paper at MMSys or co-located workshops, respectively.

The ACM Multimedia Systems Conference and associated workshops seek to bring together experts from academia and industry to share their latest research findings in the field of multimedia systems. While research about specific aspects of multimedia systems is regularly published in various venues covering networking, operating systems, real-time systems, databases, mobile computing, distributed systems, computer vision, and middleware communities, MMSys aims to cut across these domains in the context of multimedia data types. This provides a unique opportunity to investigate the intersections and the interplay of the various approaches and solutions developed across these domains.
Topics Submissions are solicited on all aspects of multimedia systems, including but not limited to:

• Content generation, adaptation, and summarization
• Adaptive streaming of multimedia content
• AI (e.g., machine/deep learning) for all aspects of multimedia systems
• Network and system support for multimedia
• Video games and cloud gaming
• Virtual and augmented reality content and systems
• Multiview, 360 degrees, 3D, and volumetric videos
• Internet of Things (IoTs) and multimedia
• Mobile multimedia and 5G/6G
• Wearable multimedia
• Cloud and edge computing for multimedia systems
• Digital twins
• Cyber-physical systems
• Multi-sensory experiences
• Autonomous multimedia systems
• Quality of Experience (QoE)
• Multimedia systems for robotics and unmanned vehicles
• Multimedia systems for health
• Audio, image and video coding for humans and machines
• Analytics for multimedia systems
• Sustainable (green) multimedia systems

Important Dates

• Open for submissions: July 15, 2024
• Submission deadline: September 15, 2024
• First-round review decisions: November 15, 202
• Deadline for revision submissions: January 15, 2025
• Notification of final decisions: March 15, 2025
• Tentative publication: April 2025

Submission Information

Prospective authors are invited to submit their manuscripts electronically adhering to the ACM TOMM journal guidelines (see https://tomm.acm.org/authors.cfm). The manuscript will not be entertained if guidelines are not followed. The manuscript should be within the scope of ACM TOMM. Please submit your papers through the online system (https://mc.manuscriptcentral.com/tomm) and be sure to select the special issue. Manuscripts should not be published or currently submitted for publication elsewhere.

Guest Editors

• Christian Timmerer, University of Klagenfurt, Austria, christian.timmerer@aau.at
• Maria Martini, Kingston University, M.Martini@kingston.ac.uk
• Ali C. Begen, Ozyegin University, Türkiye, ali.begen@ozyegin.edu.tr
• Lucca De Cicco, Politecnico di Bari, Italy, luca.decicco@poliba.it

For questions and further information, please contact guest editors using acm-tomm-si-msys2024@itec.aau.at.

HTTP Adaptive Streaming – Quo Vadis?

Jun 27, 2024, 04:00 PM Dubai

[Slides]

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 more than 20 patent applications 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.

Per-Title Encoding Using Spatial and Temporal Resolution Downscaling

US Patent

[PDF]

Hadi Amirpour (Alpen-Adria-Universität Klagenfurt, Austria) and Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria)

Abstract: Techniques relating to per-title encoding using spatial and temporal resolution downscaling is disclosed. A method for per-title encoding includes receiving a video input comprised of video segments, spatially downscaling the video input, temporally downscaling the video input, encoding the video input to generate an encoded video, then temporally and spatially upscaling the encoded video. Spatially downscaling may include reducing a resolution of the video input, and temporally downscaling may include reducing a framerate of the video input. Objective metrics for the upscaled encoded video show improved quality over conventional methods.