ATHENA Christian Doppler (CD) Laboratory

Elsevier Signal Processing

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Lingfeng Qu (Guangzhou University, China), Hui Lu (Guangzhou University, China), Peng Chen (Guangzhou University, China),  Hadi Amirpour (Alpen-Adria-Universität Klagenfurt, Austria), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria)

Abstract:

On behalf of ISO and IEC, this certificate is awarded to

Christian Timmerer

Project Editor in ISO/IEC|TC 1/SC 29/WG 3, MPEG Systems

In recognition of his excellent service to ISO/lEC JTC 1/SC 29, in particular, his exceptional contributions to the development of ISO/EC 23009-2:2020

April 2022

Klagenfurt, November 29, 2023

Reza Ebrahimi successfully defended his Master Thesis on “Quality of Experience Evaluation of Stall Events and Quality Switches in Game Streaming“.

Abstract: The exponential growth of computer game streaming has led to the development of Quality of Experience (QoE) metrics to evaluate user satisfaction and enjoyment during online gameplay and live streaming. Adaptive Bitrate (ABR) streaming is a recent technology that has been suggested to improve QoE. This method enhances the streaming experience, upholds visual quality, minimizes stall events, and boosts player retention. It achieves this by estimating network bottlenecks and selecting appropriate versions of the content that best match the available bandwidth rather than adjusting encoding parameters. To investigate the correlation between quality switching and stall events, a subjective test was conducted separately and comparatively with 71 participants. For more detailed and in-depth research, video games were analyzed with the Video Complexity Analyzer (VCA) tool and divided into three categories of different genres, camera view, and temporal complexity heatmap from the two sets of normal and action scenes. This study seeks to shed light on three unresolved issues pertinent to QoE in game streaming: (i) the user preferences towards quality switching and stall events across varied scenes and games, (ii) the user inclinations towards either a single, prolonged stall event or multiple, shorter stall events, and (iii) the impact of conspicuous quality switching on the user’s QoE. Results from the study provided valuable insights, both qualitatively and quantitatively. The study found a marked preference among users for quality switching over stall events across all types of game streaming, irrespective of the scene’s intensity. Furthermore, it was observed that multiple short-stall events were generally favored over a single long-stall event in streaming first-person shooting games. Interestingly, approximately half of the participants remained oblivious to quality switching during their game viewing sessions, and among those who noticed a change in quality, the alteration did not significantly impact their perceived QoE.

VCIP 2023
Monday, Dec4, 2023
https://vcip2023.iforum.biz/page/goto

Lectures:

• Hadi Amirpour, AAU, AT
• Christian Timmerer, AAU, AT

Abstract: The applications of video streaming are the primary drivers of Internet traffic, as over 82% of IP traffic in 2022. HTTP Adaptive Streaming (HAS) is the prevailing technology to stream live and video-on-demand (VoD) content over the Internet. In HAS, firstly, the video is split into smaller chunks, referred to as segments, each characterized by a short playback time interval. Segments are then encoded at multiple representations (bitrate-resolution pairs), referred to as the bitrate ladder. The clients select the highest possible quality representation for the next segment, which adapts to the current network condition and device type. In this way, HAS enables the continuous delivery of live and VoD content over the Internet. As the demand for video streaming applications is on the rise, new generations of video codecs and video content optimization algorithms are being developed. This tutorial first presents a detailed overview of video codecs, in particular the most recent standard video codec, i.e., Versatile Video Coding (VVC). On top of the video codecs, per-title encoding methods, which optimize bitrate ladders over characteristics of videos, are then introduced. It will be presented how representations are selected in a way that bitrate ladders are optimized over various dimensions, including spatial resolution, frame rate, energy consumption, device type, and network condition. Next, novel methods that optimize bitrate ladders for live video streaming without adding noticeable latency are introduced. Finally, fast multi-rate encoding approaches that reduce the encoding time and cost are introduced.

At Christian Doppler laboratory ATHENA, we offer an internship*)**) for 2024 for Master Students, and we kindly request your applications by the 19th of January 2024 with the following data (in German or English):

• CV
• Record of study/transcript (“Studienerfolgsnachweis”)

*) A 3 months period in 2024 (with an exact time slot to be discussed) with the possibility to spend up to 1-month at the industrial partner; 20h per week “Universitäts-KV, Verwendungsgruppe C1, studentische Hilfskraft”
**) Depending on whether the funding gets approval from the CDG.

Please send your application by email to christian.timmerer@aau.at.

About ATHENA: The Christian Doppler laboratory ATHENA (AdapTive Streaming over HTTP and Emerging Networked MultimediA Services) is jointly proposed by the Institute of Information Technology (ITEC; http://itec.aau.at) at Alpen-Adria-Universität Klagenfurt (AAU) and Bitmovin GmbH (https://bitmovin.com) to address current and future research and deployment challenges of HAS and emerging streaming methods. AAU (ITEC) has been working on adaptive video streaming for more than a decade, has a proven record of successful research projects and publications in the field, and has been actively contributing to MPEG standardization for many years, including MPEG-DASH; Bitmovin is a video streaming software company founded by ITEC researchers in 2013 and has developed highly successful, global R&D and sales activities and a world-wide customer base since then.

The aim of ATHENA is to research and develop novel paradigms, approaches, (prototype) tools, and evaluation results for the phases

1. multimedia content provisioning,
2. content delivery, and
3. content consumption in the media delivery chain as well as for
4. end-to-end aspects, with a focus on, but not being limited to, HTTP Adaptive Streaming (HAS).

The new approaches and insights are to enable Bitmovin to build innovative applications and services to account for the steadily increasing and changing multimedia traffic on the Internet.

ACM Mile-High Video 2024

Marriott DTC, Denver on Feb. 11-14, 2024 

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Daniele Lorenzi (Alpen-Adria-Universität Klagenfurt, Austria), Minh Nguyen (Alpen-Adria-Universität Klagenfurt, Austria), Farzad Tashtarian (Alpen-Adria-Universität Klagenfurt, Austria), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria)

Abstract:

HTTP Adaptive Streaming (HAS) is the de-facto solution for delivering video content over the Internet. The climate crisis has highlighted the environmental impact of information and communication technologies (ICT) solutions and the need for green solutions to reduce ICT’s carbon footprint. As video streaming dominates Internet traffic, research in this direction is vital now more than ever. HAS relies on Adaptive BitRate (ABR) algorithms, which dynamically choose suitable video representations to accommodate device characteristics and network conditions. ABR algorithms typically prioritize video quality, ignoring the energy impact of their decisions. Consequently, they often select the video representation with the highest bitrate under good network conditions, thereby increasing energy consumption. This is problematic, especially for energy-limited devices, because it affects the device’s battery life and the user experience. To address the aforementioned issues, we propose E-WISH, a novel energy-aware ABR algorithm, which extends the already-existing WISH algorithm to consider energy consumption while selecting the quality for the next video segment. According to the experimental findings, E-WISH shows the ability to improve Quality of Experience (QoE) by up to 52% according to the ITU-T P.1203 model (mode 0) while simultaneously reducing energy consumption by up to 12% with respect to state-of-the-art approaches.

Keywords: HTTP adaptive streaming, Energy, Adaptive Bitrate (ABR), DASH

Klagenfurt, August 22, 2023

Congratulations to Dr. Reza Farahani for successfully defending his dissertation on “Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, SDN, and MEC” at Universität Klagenfurt in the context of the Christian Doppler Laboratory ATHENA.

Abstract

Multimedia applications, mainly video streaming services, are currently the dominant source of network load worldwide. In recent Video-on-Demand (VoD) and live video streaming services, traditional streaming delivery techniques have been replaced by adaptive solutions based on the HTTP protocol. Current trends toward high-resolution (e.g., 8K) and/or low- latency VoD and live video streaming pose new challenges to end-to-end (E2E) bandwidth demand and have stringent delay requirements. To do this, video providers typically rely on Content Delivery Networks (CDNs) to ensure that they provide scalable video streaming services. To support future streaming scenarios involving millions of users, it is necessary to increase the CDNs’ efficiency. It is widely agreed that these requirements may be satisfied by adopting emerging networking techniques to present Network-Assisted Video Streaming (NAVS) methods. Motivated by this, this thesis goes one step beyond traditional pure client- based HAS algorithms by incorporating (an) in-network component(s) with a broader view of the network to present completely transparent NAVS solutions for HAS clients.

1. Our first contribution concentrates on leveraging the capabilities of the Software Defined Networking (SDN), Network Function Virtualization (NFV), and Multi-Access Edge Comput- ing (MEC) paradigms to introduce ES-HAS and CSDN as edge- and SDN-assisted frameworks, mainly for VoD and live streaming, respectively. ES-HAS and CSDN introduce Virtual Network Functions (VNFs) named Virtual Reverse Proxy (VRP) servers at the edge of an SDN-enabled network to collect HAS clients’ requests and retrieve networking information. The SDN controller in these systems manages a single domain network. VRP servers perform optimiza- tion models as server/segment selection policies to serve clients’ requests with the shortest fetching time by selecting the most appropriate cache server/video segment quality or by reconstructing the requested quality through transcoding at the edge. Deployment of ES-HAS and CSDN on the cloud-based testbeds and estimation of users’ Quality of Experience (QoE) using objective metrics demonstrates how clients’ requests can be served with higher QoE (by 40%) and lower bandwidth usage (by 63%) compared to state-of-the-art approaches.
2. Our second contribution designs an architecture that simultaneously supports various types of video streaming (live and VoD), considering their versatile QoE and latency require- ments. To this end, the SDN, NFV, and MEC paradigms are leveraged, and three VNFs, i.e., Virtual Proxy Function (VPF), Virtual Cache Function (VCF), and Virtual Transcoding Function (VTF), are designed. We build a series of these function chains through the Service Function Chaining (SFC) paradigm, utilize all CDN and edge server resources, and present SARENA, an SFC-enabled architecture for adaptive video streaming applications. We equip SARENA’s SDN controller with a lightweight request scheduler and edge configurator to make it deployable in practical environments and to dynamically scale edge servers based on service requirements, respectively. Experimental results show that SARENA outperforms baseline schemes in terms of higher users’ QoE figures by 39.6%, lower E2E latency by 29.3%, and lower backhaul traffic usage by 30% for live and VoD services.
3. Our third contribution aims to use the idle resources of edge servers and employ the capabilities of the SDN controller to establish a collaboration between edge servers in addition to collaboration between edge servers and the SDN controller. We introduce two collaborative edge-assisted frameworks working for HAS-based live or VoD scenarios named LEADER and ARARAT. LEADER utilizes sets of actions (e.g., transcode the requested quality in the local edge server or a neighboring edge server with the highest available resources), presented in a so-called Action Tree, formulates the problem as a central optimization model to enhance the HAS clients’ serving time, subject to the network’s and edge servers’ resource constraints, and proposes a lightweight heuristic algorithm to solve the model. ARARAT extends LEADER’s Action Tree, considers network cost in the optimization, devises multiple heuristic algorithms, and runs extensive scenarios. Evaluation results show that LEADER and ARARAT improve users’ QoE by 22%, decrease the streaming cost by 47%, and enhance network utilization by 13%, as compared to their competitors.
4. Our final contribution focuses on incorporating the capabilities of both peer-to-peer (P2P) networks and CDNs, utilizing NFV and edge computing techniques, and then presenting RICHTER and ALIVE as hybrid P2P-CDN frameworks for live streaming scenarios. RICHTER and ALIVE particularly use HAS clients’ (i.e., peers’) potential idle computational resources besides their available bandwidth to provide distributed video processing services, e.g., video transcoding and video super-resolution. Both frameworks introduce multi-layer architectures and design Action Trees that consider all feasible resources (i.e., storage, computation, and bandwidth) provided by peers, edge, and CDN servers for serving clients’ requests with acceptable latency and quality. Moreover, RICHTER proposes an online learning method and ALIVE utilizes a lightweight algorithm distributed over in-network virtualized components, which are designed to play decision-maker roles in large-scale practical scenarios. Evaluation results show that RICHTER and ALIVE improve the users’ QoE by 22%, decrease cost incurred for the streaming service provider by 34%, shorten clients’ serving latency by 39%, enhance edge server energy consumption by 31%, and reduce backhaul bandwidth usage by 24% compared to the baseline approaches.