Category Archives: APOLLO

MPEC2: Multilayer and Pipeline Video Encoding on the Computing Continuum

Posted on November 29, 2022 by

MPEC2: Multilayer and Pipeline Video Encoding on the Computing Continuum conference website: IEEE NCA 2022 Samira Afzal (Alpen-Adria-Universität Klagenfurt), Zahra Najafabadi Samani (Alpen-Adria-Universität Klagenfurt), Narges Mehran (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), and Radu Prodan (Alpen-Adria-Universität Klagenfurt) Abstract: Video streaming is the dominating … Continue reading →

Posted in APOLLO, ATHENA, GAIA | Comments Off on MPEC2: Multilayer and Pipeline Video Encoding on the Computing Continuum

OTEC: An Optimized Transcoding Task Scheduler for Cloud and Fog Environments

Posted on October 24, 2022 by

ACM CoNEXT 2022 – ViSNext 22 Workshop 6 – 9 December, 2022 | Rome, Italy                                                     … Continue reading →

Posted in APOLLO, ATHENA, GAIA | Comments Off on OTEC: An Optimized Transcoding Task Scheduler for Cloud and Fog Environments

Paper in CMC-Computers, Materials & Continua Journal accepted

Posted on November 23, 2021 by

Title: FSpot: Fast Multi-Objective Heuristic for Efficient Video Encoding Workloads over AWS EC2 Spot Instance Fleet [PDF] *** open access *** Authors: Anatoliy Zabrovskiy, Prateek Agrawal, Vladislav Kashansky, Roland Kersche, Christian Timmerer, and Radu Prodan Abstract: HTTP Adaptive Streaming (HAS) … Continue reading →

Posted in APOLLO, ATHENA | Comments Off on Paper in CMC-Computers, Materials & Continua Journal accepted

FAUST: Fast Per-Scene Encoding Using Entropy-Based Scene Detection and Machine Learning

Posted on September 29, 2021 by

FAUST: Fast Per-Scene Encoding Using Entropy-Based Scene Detection and Machine Learning 30th IEEE Conference of the Open Innovations Association FRUCT 27-29 October 2021 https://www.fruct.org/ [PDF][Slides][Video] Anatoliy Zabrovskiy, Prateek Agrawal, Christian Timmerer, and Radu Prodan Abstract: HTTP adaptive video streaming is … Continue reading →

Posted in APOLLO, ATHENA | Comments Off on FAUST: Fast Per-Scene Encoding Using Entropy-Based Scene Detection and Machine Learning

IEEE eScience 2021: Where to Encode: A Performance Analysis of Intel x86 and Arm-based Amazon EC2 Instances

Posted on August 18, 2021 by

17th IEEE eScience 2021 20-23 September 2021 // Innsbruck, Austria // Online Conference Conference Website [PDF][Slides][Video] Roland Matha´∗, Dragi Kimovski*, Anatoliy Zabrovskiy*‡, Christian Timmerer*†, Radu Prodan* Institute of Information Technology (ITEC), University of Klagenfurt, Austria* Bitmovin, Klagenfurt, Austria† Petrozavodsk State … Continue reading →

Posted in APOLLO, ATHENA | Comments Off on IEEE eScience 2021: Where to Encode: A Performance Analysis of Intel x86 and Arm-based Amazon EC2 Instances

Cluster Computing paper: FastTTPS: Fast Approach for Video Transcoding Time Prediction and Scheduling for HTTP Adaptive Streaming Videos

Posted on November 3, 2020 by

Cluster Computing paper: FastTTPS: Fast Approach for Video Transcoding Time Prediction and Scheduling for HTTP Adaptive Streaming Videos Cluster Computing (Springer Journal) [PDF] Prateek Agrawal (University of Klagenfurt, Austria), Anatoliy Zabrovskiy (University of Klagenfurt, Austria), Adithyan Ilagovan (Bitmovin Inc., CA, … Continue reading →

Posted in APOLLO, ATHENA | Comments Off on Cluster Computing paper: FastTTPS: Fast Approach for Video Transcoding Time Prediction and Scheduling for HTTP Adaptive Streaming Videos

MTAP paper: Automated Bank Cheque Verification Using Image Processing and Deep Learning Methods

Posted on September 15, 2020 by

MTAP paper: Automated Bank Cheque Verification Using Image Processing and Deep Learning Methods Multimedia tools and applications (Springer Journal) [PDF] Prateek Agrawal (University of Klagenfurt, Austria), Deepak Chaudhary (Lovely Professional University, India), Vishu Madaan (Lovely professional University, India), Anatoliy Zabrovskiy … Continue reading →

Posted in APOLLO, ATHENA | Comments Off on MTAP paper: Automated Bank Cheque Verification Using Image Processing and Deep Learning Methods