Dragi Kimovski | Alpen-Adria-Universität Klagenfurt | Friday, December 18, 2020 | 11:00 (CET, 10:00 UTC) | online

Abstract: The computing continuum extends the high-performance cloud data centers with energy-efficient and low-latency devices close to the data sources located at the edge of the network. However, the heterogeneity of the computing continuum raises multiple challenges related to application and data management. These include (i) how to efficiently provision compute and storage resources across multiple control domains across the computing continuum, (ii) how to decompose and schedule an application, and (iii) where to store an application source and the related data. To support these decisions, we explore in this thesis, novel approaches for (i) resource characterization and provisioning with detailed performance, mobility, and carbon footprint analysis, (ii) application and data decomposition with increased reliability, and (iii) optimization of application storage repositories. We validate our approaches based on a selection of use case applications with complementary resource requirements across the computing continuum over a real-life evaluation testbed.

Bio: Dragi Kimovski is a postdoctoral researcher with “Zielvereinbarung” at the Institute of Information Technology (ITEC), University of Klagenfurt. He earned his doctoral degree in 2013 from the Technical University of Sofia. He was an assistant professor at the University for Information Science and Technology in Ohrid, and a senior researcher and lecturer at the University of Innsbruck. During his career, he conducted multiple research stays at the University of Michigan, University of Bologna, and University of Granada. He was a work package leader and scientific coordinator in two Horizon 2020 projects (ENTICE and ASPIDE), and coordinated the OeAD AtomicFog project. He co-authored more than 40 articles in international conferences and journals. His research interests include parallel and distributed computing, fog and edge computing, multi-objective optimization, and distributed processing for bioengineering applications.

DI Dr. Verena Radinger-Peer

Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, BOKU Vienna

Friday, October 23rd, 2020 | 9:30  HS10 | via classroom: https://classroom.aau.at/b/szo-n09-fyn-ovf

Abstract: Locating universities in regions where they should spur regional development has been recognized as an important regional political “instrument“ since the middle of the twentieth century. The expected impacts on regional development range from economic, political, demographic, infrastructural, cultural, educational, to social. Thereby various studies confirm that a) the university-region setting is unique and context-specific and b) universities will not spur regional development autonomously or inevitably.

The presentation will show the potentials but also challenges of universities being located in rural regions. This refers to balancing acts between internationality and regional focus, economic performance and societal engagement, curriculum development and demands of the regional/national labor market etc. Particular attention is paid to income students (origin, attraction) as well as the migration of graduates. Hereby the presentations builds on insights from former and ongoing projects with national and international case studies (Germany, The Netherlands). The presentation will conclude with insights on strategies how universities in rural siting regions dealt with this multiple challenges as well as how the regional environment influenced the role the universities resumed.

CV: Verena Radinger-Peer (Dr. nat. techn., Dipl.-Ing.) is trained as spatial and environmental planner and gained her PhD in regional development and economics at the University of Natural Resources and Life Sciences Vienna (BOKU). She was a visiting scholar at the Fraunhofer Institute ISI in Karlsruhe (Germany) as well as at the CHEPS (Center for Higher Education Policy Studies) at the University of Twente (The Netherlands).

Currently she is a FWF Hertha Firnberg Grant holder and investigates the interaction between universities and their surrounding region, with a special focus on knowledge transfer, student intake and mobility, labour market issues as well as regional engagement activities of universities.

Angeliki Katsenou | University of Bristol | September 29, 2020 | 10:00 (CET, 08:00 UTC)

Abstract: Cisco reported in the past reports that the video data share was expected to reach 80% by the year 2023. However, due to the pandemic and recently imposed a remote work lifestyle, this figure is expected to increase even more. Except for the on-demand and conferencing services, the number of users that are generating, storing, and sharing their content usually through either social media platforms or video-sharing platforms is increasing. Meanwhile from the video coding perspective, as video technologies evolve towards improved compression performance, their complexity inversely increases.

A challenge that many video service providers face is the heterogeneity of networks and display devices for streaming, as well as dealing with a wide variety of content with different encoding performance. In the past, a fixed bit rate ladder solution based on a „fitting all“ approach has been employed. However, such a content-tailored solution is highly demanding; the computational and financial cost of constructing the convex hull per video by encoding at all resolutions and quantization levels is huge. In this talk, we present a content-agnostic approach that exploits machine learning to predict the bit rate ladder with only a small number of encodes required.

Bio: Angeliki Katsenou is a Leverhulme Early Career Fellow and is with the Visual Information Lab at the University of Bristol since 2015. She obtained her Ph.D. degree from the Department of Computer Science and Engineering, University of Ioannina, Greece (2014). She received her Diploma in Electrical and Computer Engineering and an M.Sc. degree in Signal and Image Processing from the University of Patras, Greece. She has experience in several FP7 EC-funded and EPSRC projects, such as MSCA-ITN PROVISION and EPSRC Platform Grant EP/M000885/1. Her research interests include perceptual video analysis, video compression, image/video quality, and resource allocation for video communication systems. She has also been involved with conference organization activities and is currently one of the Technical Program Co-Chairs for Picture Coding Symposium (PCS) 2021, Bristol, UK.