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These three short papers presented at MHV´23 are published at ACM Digital Library

  • CP-Steering: CDN- and Protocol-Aware Content Steering Solution for HTTP Adaptive Video Streaming
    Reza Farahani (University of Klagenfurt, Austria), Abdelhak Bentaleb (Concordia University, Canada), Mohammad Shojafar (University of Surrey, UK), Hermann Hellwagner (University of Klagenfurt, Austria)
    https://dl.acm.org/doi/10.1145/3588444.3591044
  • Context-Aware HTTP Adaptive Video Streaming Utilizing QUIC’s Stream Priority
    Sindhu Chellappa (University of New Hampshire), Reza Farahani (University of Klagenfurt, Austria), Radim Bartos (University of New Hampshire, USA), Hermann Hellwagner (University of Klagenfurt, Austria)
    https://dl.acm.org/doi/10.1145/3588444.3591038
  • Which CDN to Download From? A Client and Server Strategies
    Abdelhak Bentaleb (Concordia University, Canada), Reza Farahani (University of Klagenfurt, Austria), Farzad Tashtarian (University of Klagenfurt, Austria), Hermann Hellwagner (University of Klagenfurt, Austria), Roger Zimmermann (National University of Singapore, Singapore)
    https://dl.acm.org/doi/10.1145/3588444.3591030
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Magazine article published: DataCloud: Resource provisioning, scheduling and deployment of big-data pipelines

HiPEAC magazine https://www.hipeac.net/news/#/magazine/

HiPEACINFO 68, pages 27-28.

Autohrs: Dragi Kimovski (Alpen-Adria-Universität Klagenfurt, Austria), Narges Mehran (Alpen-Adria-Universität Klagenfurt, Austria), Radu Prodan (Alpen-Adria-Universität Klagenfurt, Austria), Souvik Sengupta (iExec Blockchain Tech, France), Anthony Simonet-Boulgone (iExec Blockchain Tech, France), Ioannis Plakas (UBITECH, Greece) , Giannis Ledakis (UBITECH, Greece) and Dumitru Roman (University of Oslo and SINTEF AS, Norway)

Abstract: Modern big-data pipeline applications, such as machine learning, encompass complex workflows for real-time data gathering, storage and analysis. Big-data pipelines often have conflicting requirements, such as low communication latency and high computational speed. These require different kinds of computing resource, from cloud to edge, distributed across multiple geographical locations – in other words, the computing continuum. The Horizon 2020 DataCloud project is creating a novel paradigm for big-data pipeline processing over the computing continuum, covering the complete lifecycle of bigdata pipelines. To overcome the runtime challenges associated with automating big-data pipeline processing on the computing continuum, we’ve created the DataCloud architecture. By separating the discovery, definition, and simulation of big-data pipelines from runtime execution, this architecture empowers domain experts with little infrastructure or software knowledge to take an active part in defining big-data pipelines.

This work received funding from the DataCloud European Union’s Horizon 2020 research and innovation programme under grant agreement no. 101016835.

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Hermann Hellwagner receives Carinthian cultural prize

Every year, Carinthia celebrates its cultural and scientific greats by awarding a total of 13 prizes based on the proposal of the Carinthian Cultural Board. This year Hermann Hellwagner received one of the three appreciation prizes in the natural and technical sciences category. Congratulations! Further information: https://www.aau.at/blog/kulturpreise-des-landes-kaernten-fuer-hermann-hellwagner-roswitha-rissner-und-wolfgang-puschnig/

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Success story @ Game Studies and Engineering

Christina Obmann, one of our first Game Studies and Engineering students, has been recognized as outstanding in the Carinthia region by the local newspaper Kleine Zeitung. Besides her interest and work in games, she’s teaching at the university, learning Chinese, and was awarded a scholarship from Huawei.

 

 

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Education minister´s visit @ AAU

During the visit of our minister of education (Martin Polaschek),  Hermann Hellwagner gave an overview of drone research at the AAU and the use of the drone hall.

Read more about Mr. Polaschek´s visit here.

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Klagenfurt – high-flyer in drone research

Over the past decade, Carinthia has developed into a hotspot in drone research. The heart of the scientific operation is Europe’s largest drone hall in Klagenfurt.

The newspaper “Stuttgarter Nachrichten” reported on our drone work with its own article (link).

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Christian Doppler ‘pilot’ laboratory ATHENA to transition to a regular CD laboratory

Successful review of the first research phase: Christian Doppler ‘pilot’ laboratory ATHENA to transition to a regular CD laboratory two years after launch. Read more about it at ATHENA website and the press release at AAU website.

 

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Bitmovin takes on classroom sponsorship at the University of Klagenfurt

Bitmovin will be sponsoring a classroom in the area of Computer Science for the next five years, starting in June 2021, and thus continuing the long-standing successful cooperation with the University of Klagenfurt.

Read more about our project partner Bitmovin here.

 

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Radu Prodan @ ad astra – ADAPT – make transportation more efficient

Our project „ADAPT“ started in March 2021, during the most critical phase of the COVID-19 outbreak in Europe. The demand for Personal Protective Equipment (PPE) from each country’s health care system has surpassed national stock amounts by far.

Learn more about it in an interview with Univ.-Prof. DI Dr. Radu Aurel Prodan in University Klagenfurt´s journal „ad astra“ (pdf).

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Presentation accepted for ASHPC’21

The presentation has been accepted to the main-track of the Austrian-Slovenian HPC Meeting (ASHPC’21). Meeting will be organized in a hybrid format on 31 May – 2 June, 2021 at the Institute of Information Science in Maribor, Slovenia.

Title: Automated Workflows Scheduling via Two-Phase Event-based MILP Heuristic for MRCPSP Problem

Authors: Vladislav Kashansky, Gleb Radchenko, Radu Prodan, Anatoliy Zabrovskiy and Prateek Agrawal

Abstract: In today’s reality massive amounts of data-intensive tasks are managed by utilizing a large number of heterogeneous computing and storage elements interconnected through high-speed communication networks. However, one issue that still requires research effort is to enable effcient workflows scheduling in such complex environments.
As the scale of the system grows and the workloads become more heterogeneous in the inner structure and the arrival patterns, scheduling problem becomes exponentially harder, requiring problem-specifc heuristics. Many techniques evolved to tackle this problem, including, but not limited to Heterogeneous Earliest Finish Time (HEFT), The Dynamic Scaling Consolidation Scheduling (DSCS), Partitioned Balanced Time Scheduling (PBTS), Deadline Constrained Critical Path (DCCP) and Partition Problem-based Dynamic Provisioning Scheduling (PPDPS). In this talk, we will discuss the two-phase heuristic for makespan-optimized assignment of tasks and computing machines on large-scale computing systems, consisting of matching phase with subsequent event-based MILP method for schedule generation. We evaluated the scalability of the heuristic using the Constraint Integer Programing (SCIP) solver with various configurations based on data sets, provided by the MACS framework. Preliminary results show that the model provides near-optimal assignments and schedules for workflows composed of up to 100 tasks with complex task I/O interactions and demonstrates variable sensitivity with respect to the scale of workflows and resource limitation policies imposed.

Keywords: HPC Schedule Generation, MRCPSP Problem, Workflows Scheduling, Two-Phase Heuristic

Acknowledgement: This work has received funding from the EC-funded project H2020 FETHPC ASPIDE (Agreement #801091)