Publication: OTEC: An Optimized Transcoding Task Sch...
Master data
Title: | OTEC: An Optimized Transcoding Task Scheduler for Cloud and Fog Environments |
Subtitle: | |
Abstract: | Encoding and transcoding videos into multiple codecs and representations is a significant challenge that requires seconds or even days on high-performance computers depending on many technical characteristics, such as video complexity or encoding parameters. Cloud computing offering on-demand computing resources optimized to meet the needs of customers and their budgets is a promising technology for accelerating dynamic transcoding workloads. In this work, we propose OTEC, a novel multi-objective optimization method based on the mixed-integer linear programming model to optimize the computing instance selection for transcoding processes. OTEC determines the type and number of cloud and fog resource instances for video encoding and transcoding tasks with optimized computation cost and time. We evaluated OTEC on AWS EC2 and Exoscale instances for various administrator priorities, the number of encoded video segments, and segment transcoding times. The results show that OTEC can achieve appropriate resource selections and satisfy the administrator's priorities in terms of time and cost minimization. |
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Publication type: | Article in Proceedings (Authorship) |
Publication date: | 09.12.2022 (Print) |
Published by: |
ViSNext'22 Proceedings of the 2nd International Workshop on Design, Deployment, and Evaluation of Network-Assisted Video Streaming
ViSNext'22 Proceedings of the 2nd International Workshop on Design, Deployment, and Evaluation of Network-Assisted Video Streaming
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ACM Digital Library;
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to publication |
Title of the series: | - |
Volume number: | - |
First publication: | Yes |
Version: | - |
Page: | pp. 21 - 26 |
Versionen
Keine Version vorhanden |
Publication date: | 06.12.2022 |
ISBN (e-book): | - |
eISSN: | - |
DOI: | http://dx.doi.org/10.1145/3565476.3569099 |
Homepage: | https://dl.acm.org/doi/abs/10.1145/3565476.3569099 |
Open access |
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Publication date: | 09.12.2022 |
ISBN: | - |
ISSN: | - |
Homepage: | https://dl.acm.org/doi/abs/10.1145/3565476.3569099 |
Authors
Samira Afzal (internal) |
Farzad Tashtarian (internal) |
Hamid Hadian (internal) |
Alireza Erfanian (internal) |
Christian Timmerer (internal) |
Radu Aurel Prodan (internal) |
Assignment
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Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
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AT - 9020 Klagenfurt am Wörthersee |
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Peer reviewed |
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