Prof. Radu Prodan

The project “Kärntner Fog: A 5G-Enabled Fog Infrastructure for Automated Operation of Carinthia’s 5G Playground Application Use Cases” proposes a new infrastructure automation use case in the 5G Playground Carinthia (5GPG). Kärntner Fog plans to create and deploy a
distributed service middleware infrastructure over a diverse set of novel heterogeneous 5G edge devices, complemented by a high-performance Cloud data center accessible with low latency according to 5G standards. Such an infrastructure is currently missing in the 5GPG and will represent a horizontal backbone that interconnects and integrates the application use cases. Kärtner Fog will automate the development and operation of the applications use cases in the 5GPG in an integrated and more cost-effective fashion to enable more science and innovation within a limited budget.

Involved Organisations: BABEG, ITEC@AAU, ONDA TLC GmbH, FFG/KWF

Coordinator: Prof. Radu Prodan
Project Start: 01.01.2021
Project Duration: 48 months

Dr. Shajulin Benedict war 2019 an der Alpen Adria Universität Klagenfurt im Rahmen einer Forschungskooperation tätig. Heute ist es soweit, die Kooperation des build! mit dem IIIT-Kottayam Startup Center startet. Build! startet 2021 mit einem Startup in Residence Programm (geplanter Rollout Sommer) – erster Partner ist Indien. Ein Austausch für Entrepreneurs in Startups zwischen Kottayam und Kärnten ist ab Q3 geplant. Mehr Informationen finden Sie hier.
Prof. Radu Prodan

IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC) accepted the paper “Dynamic Multi-objective Scheduling of Microservices in the Cloud”.

Authors: Hamid Mohammadi Fard, Radu Prodan, Felix Wolf

Abstract: For many applications, a microservices architecture promises better performance and flexibility compared to a conventional monolithic architecture. In spite of the advantages of a microservices architecture, deploying microservices poses various challenges for service developers and providers alike. One of these challenges is the efficient placement of microservices on the cluster nodes. Improper allocation of microservices can quickly waste resource capacities and cause low system throughput. In the last few years, new technologies in orchestration frameworks, such as the possibility of multiple schedulers for pods in Kubernetes, have improved scheduling solutions of microservices but using these technologies needs to involve both the service developer and the service provider in the behavior analysis of workloads. Using memory and CPU requests specified in the service manifest, we propose a general microservices scheduling mechanism that can operate efficiently in private clusters or enterprise clouds. We model the scheduling problem as a complex variant of the knapsack problem and solve it using a multi-objective optimization approach. Our experiments show that the proposed mechanism is highly scalable and simultaneously increases utilization of both memory and CPU, which in turn leads to better throughput when compared to the state-of-the-art.

Prof. Radu Prodan

Prof. Radu Prodan ist guest of honor at the 9th International Workshop on Soft Computing Applications (SOFA), 27-29 Nov 2020, Arad, Romania. The title of his talk is “Distribute one Billion”.

Prof. Radu Prodan

The newspaper “Kronen Zeitung” published the article “IM KAMPF GEGEN CORONA: Universität Klagenfurt forscht mit den Chinesen” with Prof. Radu Prodan.

Prof. Radu Prodan

The newspaper “Kleine Zeitung” published the article “Medizinische Schutzausrüstung: Neue IT-Lösung soll Menschenleben retten” with Prof. Radu Prodan.

 

Authors: Dragi Kimovski, Dijana C. Bogatinoska, Narges Mehran, Aleksandar Karadimce, Natasha Paunkoska, Radu Prodan, Ninoslav Marina

Abstract: The proliferation of smart sensing and computing devices, capable of collecting a vast amount of data, has made the gathering of the necessary vehicular traffic data relatively easy. However, the analysis of these big data sets requires computational resources, which are currently provided by the Cloud Data Centers. Nevertheless, the Cloud Data Centers can have unacceptably high latency for vehicular analysis applications with strict time requirements. The recent introduction of the Edge computing paradigm, as an extension of the Cloud services, has partially moved the processing of big data closer to the data sources, thus addressing this issue. Unfortunately, this unlocked multiple challenges related to resources management. Therefore, we present a model for scheduling of vehicular traffic analysis applications with partial task offloading across the Cloud — Edge continuum. The approach represents the traffic applications as a set of interconnected tasks composed into a workflow that can be partially offloaded to the Edge. We evaluated the approach through a simulated Cloud — Edge environment that considers two representative vehicular traffic applications with a focus on video stream analysis. Our results show that the presented approach reduces the application response time up to eight times while improving energy efficiency by a factor of four.

Prof. Radu Prodan

This project started during the most critical phase of the COVID-19 outbreak in Europe where the demand for Personal Protective Equipment (PPE) from each country’s health care system has
surpassed national stock amounts by far. Therefore, the ADAPT consortia agreed to bundle its joint resources to develop and adaptive and autonomous decision-making network to support the involved stakeholders along the PPE Supply Chain in their endeavour to save and protect human lives as quickly as possible.

The partners will do that by providing a Blockchain solution capable of optimizing supply, demand and transport capacities between them, elaborating a technical solution for transparent and realtime certification checks on equipment and production documentation as well as distributed and parallel decision-making capabilities on all levels of this multi-dimensional research problem.

In total, the world community will spent more than € 49,6 billion on PPE medical equipment in 2020, € 7,7 billion thereof could be saved with the transport optimization of ADAPT and additional € 5,18 billion could be freed up in the financing and banking sector which could be reinvested immediately into the expansion of the world’s national health care systems.

ADAPT is a 36-month duration project submitted to 6th Call for Austrian-Chinese Coop. RTD Projects FFG & CAS.

Partners:

  • Alpen-Adria Universität Klagenfurt, Institute of Information Technology (UNI-KLU)
  • Johannes-Kepler-Universität Linz, Intelligent Transport Systems-Sustainable Transport Logistics 4.0. (JKU)
  • Logoplan – Logistik, Verkehrs und Umweltschutz Consulting GmbH (LP)
  • Intact GmbH (INTACT)
  • Chinese Academy of Sciences, Institute of Computing Technology (ICTCAS)