Christian Timmerer has been appointed IEEE Communications Society Distinguished Lecturer for the term 2021-2022

Posted on January 31, 2021 by

Christian Timmerer, Associate Professor at the Institute of Information Technology (ITEC) and Director of the ATHENA Christian Doppler Laboratory, has been appointed IEEE Communications Society Distinguished Lecturer for the term 2021-2022.

“The Distinguished Lecturer Program (DLP) connects Senior IEEE ComSoc members, who are renowned communications technology experts, with ComSoc chapters so they can share their knowledge, expertise, and insights into the future of communications technology.”

In the context of the Distinguished Lecturer Program (DLP), Christian Timmerer will offer the following (virtual) lecture topics:

HTTP Adaptive Streaming (HAS) — Quo Vadis?
Quality of Experience (QoE) for Traditional and Immersive Media Services
Immersive Media Services: from Encoding to Consumption
20 Years of Streaming in 20 Minutes
Multimedia Communication, Networking, Protocols, Delivery
Multimedia Standards (MPEG, IETF, W3C)

The details of how to request a Distinguished Lecturer can be found here.

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Bitmovin wins Technology & Engineering Emmy® Award

Posted on January 26, 2021 by

We are happy and proud to see Bitmovin among the 72nd Annual Technology & Engineering Emmy® Awards Recipients. The award is received for “Development of Massive Processing Optimized Compression Technologies” which acknowledges Bitmovin’s Encoding product including its reportedly best per-title encoding feature.

Bitmovins press release can be found here and approximately one year we had the official opening ceremony of the ATHENA project that will continue to fed the innovation pipeline with respect to HTTP Adaptive Streaming (HAS) and beyond. Please see our latest publications in this field and in case of questions please do not hesitate to contact us.

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IEEE Transactions on Network and Service Management: OSCAR

Posted on January 13, 2021 by

OSCAR: On Optimizing Resource Utilization in Live Video Streaming

IEEE Transactions on Network and Service Management (TNSM)

[PDF]

DOI: 10.1109/TNSM.2021.3051950

Alireza Erfanian (Alpen-Adria-Universität Klagenfurt), Farzad Tashtarian (Alpen-Adria-Universität Klagenfurt), Anatoliy Zabrovskiy (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: Live video streaming traffic and related applications have experienced significant growth in recent years. However, this has been accompanied by some challenging issues, especially in terms of resource utilization. Although IP multicasting can be recognized as an efficient mechanism to cope with these challenges, it suffers from many problems. Applying software-defined networking (SDN) and network function virtualization (NFV) technologies enable researchers to cope with IP multicasting issues in novel ways. In this paper, by leveraging the SDN concept, we introduce OSCAR (Optimizing reSourCe utilizAtion in live video stReaming) as a new cost-aware video streaming approach to provide advanced video coding (AVC)-based live streaming services in the network. In this paper, we use two types of virtualized network functions (VNFs): virtual reverse proxy (VRP) and virtual transcoder function (VTF). At the edge of the network, VRPs are responsible for collecting clients’ requests and sending them to an SDN controller. Then, by executing a mixed-integer linear program (MILP), the SDN controller determines a group of optimal multicast trees for streaming the requested videos from an appropriate origin server to the VRPs. Moreover, to elevate the efficiency of resource allocation and meet the given end-to-end latency threshold, OSCAR delivers only the highest requested quality from the origin server to an optimal group of VTFs over a multicast tree. The selected VTFs then transcode the received video segments and transmit them to the requesting VRPs in a multicast fashion. To mitigate the time complexity of the proposed MILP model, we present a simple and efficient heuristic algorithm that determines a near-optimal solution in polynomial time. Using the MiniNet emulator, we evaluate the performance of OSCAR in various scenarios. The results show that OSCAR surpasses other SVC- and AVC-based multicast and unicast approaches in terms of cost and resource utilization.

Keywords: Dynamic Adaptive Streaming over HTTP (DASH), Live Video Streaming, Software Defined Networking (SDN), Video Transcoding, Network Function Virtualization (NFV).

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SLFC: Scalable Light Field Coding

Posted on December 28, 2020 by

Data Compression Conference (DCC)

23-26 March 2021, Snowbird, Utah, USA

[PDF][Slides][Video]

Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), and Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK)

Abstract:

Light field imaging enables some post-processing capabilities like refocusing, changing view perspective, and depth estimation. As light field images are represented by multiple views they contain a huge amount of data that makes compression inevitable. Although there are some proposals to efficiently compress light field images, their main focus is on encoding efficiency. However, some important functionalities such as viewpoint and quality scalabilities, random access, and uniform quality distribution have not been addressed adequately. In this paper, an efficient light field image compression method based on a deep neural network is proposed, which classifies multiple views into various layers. In each layer, the target view is synthesized from the available views of previously encoded/decoded layers using a deep neural network. This synthesized view is then used as a virtual reference for the target view inter-coding. In this way, random access to an arbitrary view is provided. Moreover, uniform quality distribution among multiple views is addressed. In higher bitrates where random access to an arbitrary view is more crucial, the required bitrate to access the requested view is minimized.

Keywords: Light field, Compression, Scalable, Random Access.

https://www.slideshare.net/christian.timmerer/slfc-scalable-light-field-coding

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A channel allocation algorithm for cognitive radio users based on channel state predictors

Posted on December 4, 2020 by

International Congress on Information and Communication Technology

25-26 February 2021, London, UK

[PDF][Slides]

Nakisa Shams (ETS, Montreal, Canada), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), and Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK)

Abstract:

Cognitive radio networks by utilizing the spectrum holes in licensed frequency bands are able to efficiently manage the radio spectrum. A significant improvement in spectrum use can be achieved by giving secondary users access to these spectrum holes. Predicting spectrum holes can save significant energy that is consumed to detect spectrum holes. This is because the secondary users can only select the channels that are predicted to be idle channels. However, collisions can occur either between a primary user and secondary users or among the secondary users themselves. This paper introduces a centralized channel allocation algorithm in a scenario with multiple secondary users to control both primary and secondary collisions. The proposed allocation algorithm, which uses a channel status predictor, provides a good performance with fairness among the secondary users while they have the minimal interference with the primary user. The simulation results show that the probability of a wrong prediction of an idle channel state in a multi-channel system is less than 0.9%. In addition, the channel state prediction saves the sensing energy up to 73%, and the utilization of the spectrum can be improved more than 77%.

Keywords: Cognitive radio, Biological neural networks, Prediction, Idle channel.

https://www.slideshare.net/christian.timmerer/a-channel-allocation-algorithm-for-cognitive-radio-users-based-on-channel-state-predictors

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Internship 2021 at ATHENA

Posted on November 27, 2020 by

At Christian Doppler laboratory ATHENA, we offer an internship*) for 2021 for Master Students and we kindly request your applications until 21st of December 2020 with the following data (in German or English):

CV
Record of study/transcript (“Studienerfolgsnachweis”)

*) A 3-month period in 2021 (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”

Please send your application by email to nina.stiller@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

multimedia content provisioning,
content delivery, and
content consumption in the media delivery chain as well as for
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.

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