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ATHENA Papers Accepted at ACM MMSys’21 Doctoral Symposium

ACM Multimedia Systems Conference (MMSys) 2021 | Doctoral Symposium

September 28 – October 01, 2021 | Istanbul, Turkey

Conference Website

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Paper published at Frontiers in Robotics and AI: Information Distribution in Multi-Robot Systems: Generic, Utility-Aware Optimization Middleware

Authors: M. Barciś, A. Barciś, N. Tsiogkas, H. Hellwagner.

Title: Information Distribution in Multi-Robot Systems: Generic, Utility-Aware Optimization Middleware.

Frontiers in Robotics and AI 8:685105, July 2021.

This work addresses the problem of what information is worth sending in a multi-robot system under generic constraints, e.g., limited throughput or energy. Our decision method is based on Monte Carlo Tree Search. It is designed as a transparent middleware that can be integrated into existing systems to optimize communication among robots. Furthermore, we introduce techniques to reduce the decision space of this problem to further improve the performance. We evaluate our approach using a simulation study and demonstrate its feasibility in a real-world environment by realizing a proof of concept in ROS 2 on mobile robots.

Published paper

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Paper accepted at IEEE ACCESS: LwTE: Light-weight Transcoding at the Edge

Authors: Alireza Erfanian* (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Hadi Amirpour*, (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Farzad Tashtarian (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt),  Christian Timmerer (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Hermann Hellwagner (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt)

*These authors contributed equally to this work.

Link: IEEE Access

Abstract: Due to the growing demand for video streaming services, providers have to deal with increasing resourcerequirements for increasingly heterogeneous environments. To mitigate this problem, many works have beenproposed which aim to (i) improve cloud/edge caching efficiency, (ii) use computation power available in thecloud/edge for on-the-fly transcoding, and (iii) optimize the trade-off among various cost parameters,e.g.,storage, computation, and bandwidth. In this paper, we proposeLwTE, a novelLight-weightTranscodingapproach at theEdge, in the context of HTTP Adaptive Streaming (HAS). During the encoding processof a video segment at the origin side, computationally intense search processes are going on. The mainidea ofLwTEis to store the optimal results of these search processes as metadata for each video bitrateand reuse them at the edge servers to reduce the required time and computational resources for on-the-fly transcoding.LwTEenables us to store only the highest bitrate plus corresponding metadata (of verysmall size) for unpopular video segments/bitrates. In this way, in addition to the significant reduction inbandwidth and storage consumption, the required time for on-the-fly transcoding of a requested segment isremarkably decreased by utilizing its corresponding metadata; unnecessary search processes are avoided.Popular video segments/bitrates are being stored. We investigate our approach for Video-on-Demand (VoD)streaming services by optimizing storage and computation (transcoding) costs at the edge servers and thencompare it to conventional methods (store all bitrates, partial transcoding). The results indicate that ourapproach reduces the transcoding time by at least 80% and decreases the aforementioned costs by 12% to70% compared to the state-of-the-art approaches.

Keywords: Video streaming, transcoding, video on demand, edge computing.

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Paper accepted at IEEE 23rd International Workshop on Multimedia Signal Processing – WISH: User-centric Bitrate Adaptation for HTTP Adaptive Streaming on Mobile Devices

Title: WISH: User-centric Bitrate Adaptation for HTTP Adaptive Streaming on Mobile Devices

IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)

October 06-08, Tampere, Finland

Authors: Minh Nguyen (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Ekrem Çetinkaya (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Hermann Hellwagner (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), and Christian Timmerer (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt)

Abstract: Recently, mobile devices have become paramount in online video streaming. Adaptive bitrate (ABR) algorithms of players responsible for selecting the quality of the videos face critical challenges in providing a high Quality of Experience (QoE) for end users. One open issue is how to ensure the optimal experience for heterogeneous devices in the context of extreme variation of mobile broadband networks. Additionally, end users may have different priorities on video quality and data usage (i.e., the amount of data downloaded to the devices through the mobile networks). A generic mechanism for players that enables specification of various policies to meet end users’ needs is still missing. In this paper, we propose a weighted sum model, namely WISH, that yields high QoE of the video and allows end users to express their preferences among different parameters (i.e., data usage, stall events, and video quality) of video streaming. WISH has been implemented into ExoPlayer, a popular player used in many mobile applications. The experimental results show that WISH improves the QoE by up to 17.6% while saving 36.4% of data usage compared to state-of-the-art ABR algorithms and provides dynamic adaptation to end users’ requirements.

Keywords: ABR Algorithms, HTTP Adaptive Streaming, ITU-T P.1203, WISH


Successful completion and demo of the Karl Popper Kolleg (KPK) Networked Autonomous Aerial Vehicles (NAV)

Robotics research in Klagenfurt enjoys international success

With a total of 9 contributions at this year’s ICRA, one of the flagship conferences in the field of robotics, the University of Klagenfurt has joined the league of the world’s most important robotics hubs. Among the contributors are the young researchers from the Karl Popper Doktorats- und Wissenschaftskolleg “Networked Autonomous Aerial Vehicles (NAV)”, which is currently celebrating its conclusion with a drone flight demonstration in Klagenfurt. Read more at the University Klagenfurt blog and here.


Paper accepted at EuroPar LSDVE Workshop 2021

Title: SMART: a Tool for Trust and Reputation Management in Social Media

Authors: Manuel Herold, Nishant Saurabh, Hamid Mohammadi Fard, Radu Prodan

Abstract: Social media platforms are becoming increasingly popular and essential for next-generation connectivity. However, the emergence of social media also poses critical trust challenges due to the vast amount of created and propagated content. This paper proposes a data-driven tool called SMART for trust and reputation management based on community engagement and rescaled sigmoid model. SMART’s integrated design adopts a set of expert systems with a unique inference logic for trust estimation to compute weighted trust ratings of social media content. SMART further utilizes the trust ratings to compute user reputation and represent them using a sigmoid curve that prevents infinite accumulation of reputation ratings by a user. We demonstrate the SMART tool prototype using a pilot social media application and highlight its user-friendly interfaces for trustworthy content exploration.

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KWF/EFRE project “ONTIS” accepted

The project “ONTIS” (Ontology-based Interoperability of Systems) has been accepted in the EFRE call of KWF (Kärntner Wirtschaftsförderungs Fonds).

The ONTIS project targets the development of methodologies for automatically establishing interoperability between information systems through the combination of ontological expert knowledge and machine learning-based models. With the specific goal of improving the error-prone manual integration of ontological knowledge, ONTIS focuses on applying deep neural networks for processing natural language and visual concepts for automatic semantic annotation.

Project duration: 18 months


Farzad Tashtarian and Christian Timmerer Co-Chairs of ViSNext 2021 Workshop at the ACM CoNEXT 2021 Conference

ViSNext’21: 1st ACM CoNEXT Workshop on Design, Deployment, and Evaluation of Network-assisted Video Streaming

In recent years, we have witnessed phenomenal growth in live video traffic over the Internet, accelerated by the rise of novel video streaming technologies, advancements in networking paradigms, and our ability to generate, process, and display videos on heterogeneous devices. Regarding the existing constraints and limitations in different components on the video delivery path from the origin server to clients, the network plays an essential role in boosting the perceived Quality of Experience (QoE) by clients. The ViSNext workshop aims to bring together researchers and developers working on all aspects of video streaming, in particular network-assisted concepts backed up by experimental evidence. Read more about the workshop, call for papers at ViSNext2021 and registration here.


Paper acepted @ GoodIT 2021

The paper “The ADAPT Project: Adaptive and Autonomous Data” has been accepted to appear at the conference ACM International Conference on Information Technology for Social Good (GoodIT 2021) as a regular paper.

Authors: Nishant Saurabh, Vladislav Kashanskii, Radu Prodan, Aso Validi, Christina Olaverri-Monreal

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Master thesis at ITEC wins Dynatrace Outstanding IT-Thesis Award

With his master thesis about “Animating Characters using Deep Learning based Pose Estimation”, Fabian Schober won the “Dynatrace Outstanding IT-Thesis Award” (DO*IT*TA). The award brings attention to extraordinary theses, motivates creativity, and provides insight into modern technologies.
In his thesis, Fabian Schober focuses on animating 2D (video game) characters using the PoseNet pose estimation model. He delivers a proof of concept on how new machine learning technologies can assist in video game development. Read more at the University press release (German only).