Entries by Rudolf Messner

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Paper accepted in IEEE Transactions on Services Computing (TSC)

The manuscript “Mobility-Aware IoT Application Placement in the Cloud — Edge Continuum” has been accepted for publication in the A* (IF: 5.823) Journal – IEEE Transactions on Services Computing (TSC). Autors: Dragi Kimovski, Narges Mehran, Christopher Kerth, Radu Prodan Abstract: The Edge computing extension of the Cloud services towards the network boundaries raises important placement […]

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Paper about: Energy Consumption Analysis of R-Based Machine Learning Algorithms for Pandemic Predictions

  Authors: Shajulin Benedict, Prateek Agrawal, Radu Prodan Link: Advanced Informatics for Computing Research, CCIS-Springer, 4th ICAICR 2020, Vol. 1393 Abstract: The push for agile pandemic analytic solutions has attained development-stage software modules of applications instead of functioning as full-fledged production-stage applications – i.e., performance, scalability, and energy-related concerns are not optimized for the underlying […]

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Paper accepted in Elsevier’s Journal of Blockchain: Research and Applications

Authors: Nikita Karandikar, Rockey Abhishek, Nishant Saurabh, Zhiming Zhao, Alexander Lercher, Ninoslav Marina, Radu Prodan, Chunming Rong, Antorweep Chakravorty DOI: https://doi.org/10.1016/j.bcra.2021.100016 Abstract: Peak mitigation is of interest to power companies as peak periods may require the operator to over provision supply in order to meet the peak demand. Flattening the usage curve can result in […]

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Paper About Lens Irregularity Detection in Cataract Surgery Accepted at MICCAI 2021

Our paper about LensID – a CNN-RNN-based framework for irregularity detection in cataract surgery videos has been accepted at the prestigious MICCAI 2021 conference (International Conference on Medical Image Computing & Computer Assisted Intervention). Negin Ghamsarian will present the details of her work on this topic in the end of September. Authors: Negin Ghamsarian, Mario […]

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Paper accepted in 17th IEEE eScience conference

Conference: https://escience2021.org/ Title: Where to Encode: A Performance Analysis of x86 and Arm-based Amazon EC2 Instances Authors: Roland Mathá, Dragi Kimovski, Anatoliy Zabrovskiy, Christian Timmerer and Radu Prodan Abstract: Video streaming became an undivided part of the Internet. To efficiently utilise the limited network bandwidth it is essential to encode the video content. However, encoding […]

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Paper accepted in Springer’s Journal of Computing

Title: Handover Authentication Latency Reduction using Mobile Edge Computing and Mobility Patterns Authors: Fatima Abdullah, Dragi Kimovski, Radu Prodan, and Kashif Munir Abstract: With the advancement in technology and the exponential growth of mobile devices, network traffic has increased manifold in cellular networks. Due to this reason, latency reduction has become a challenging issue for mobile devices. In […]

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FusionCL: a machine-learning based approach for OpenCL kernel fusion to increase system performance

Authors:Yasir Noman Khalid, Muhammad Aleem, Usman Ahmed, Radu Prodan, Muhammad Arshad Islam & Muhammad Azhar Iqbal Abstract: Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL has resulted in greatly reducing the execution time of data-parallel applications by taking advantage of the massive available parallelism. However, when a small data size application is […]

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Paper accepted: Efficient Content-Adaptive Feature-based Shot Detection for HTTP Adaptive Streaming

At IEEE International Conference on Image Processing (ICIP) on September 19-22, 2021, Alaska, USA. Authors: Vignesh V Menon (Alpen-Adria-Universität Klagenfurt),  Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt). Abstract: Video delivery over the Internet has been becoming a commodity in […]

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This paper won the second best paper award at the CCGrid 2021 conference.

Title: “A Two-Sided Matching Model for Data Stream Processing in the Cloud-Fog Continuum” by: Narges Mehran, Dragi Kimovski and Radu Prodan, was virtually presented in the CCgrid2021 conference. We at @alpenadriauni are proud of Narges and her work in the @EU_H2020 @DataCloud2020 project awarded at http://cloudbus.org/ccgrid2021/. Watch award presentation at: https://www.youtube.com/watch?v=aSnzDpd5Kqc