Energy Efficient Video Encoding for Cloud and Edge Computing Instances
christian.timmerer
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26 slides
Jun 12, 2024
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About This Presentation
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Size: 4.07 MB
Language: en
Added: Jun 12, 2024
Slides: 26 pages
Slide Content
Energy Efficient Video Encoding for
Cloud and Edge Computing Instances
Samira Afzal
Institute of Information Technology (ITEC), Alpen-Adria-Universität Austria [email protected] | https://athena.itec.aau.at/gaia
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GAIA (the Greek goddess of Earth, mother of all life, personification of the
Earth)
Funded by the Austrian Research Promotion Agency FFG (Basisprogramm)
A cooperative project between Bitmovin and Alpen-Adria-Universität
Klagenfurt (AAU)
: Intelligent Climate-Friendly Video
Platform
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Complete energy awareness and accountability, including energy
consumption and GHG emissions along the entire delivery chain, from
content creation and server-side encoding to video transmission and
client-side rendering
Reduced energy consumption and GHG emissions through advanced
analytics and optimizations on all phases of the video delivery chain
: Intelligent Climate-Friendly Video
Platform
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VEEP-Match: Energy
Efficient Video
Encoding for
Cloud and Edge
Computing Instances
Main Objectives
To select Cloud/Edge Instances for video encoding/transcoding operations,
aiming at:
Minimizing cost, energy consumption, CO2 emission or encoding time
Making a trade-off between these priorities
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Storage/CDN
Encoded video
Video
Coordinator
Storage
Energy Efficient Video Encoding
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Energy Efficient Video Encoding
VEEP-Match
Storage/CDN
Encoded video
Video
Storage
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Coordinator
VEEP-Match Architecture
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VEEP-Match Architecture
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VEEP
VEEP-Match Architecture
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Lachini, Armin, et al. "VEEP: Video Encoding Energy and CO2 Emission Prediction." Proceedings of the
Second International ACM Green Multimedia Systems Workshop. 2024.
VEEP-Match Architecture
MatchVEEP
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Afzal, Samira, et al. "VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing
Instances." Proceedings of the First International Workshop on Green Multimedia Systems. 2023.
VEEP Submodules
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The Video Analyzer Submodule in VEEP
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The Predictor Submodule in VEEP
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The Calculator Submodule in VEEP
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The Data Source Submodule in VEEP
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Annual Overview
CO₂ emissions over the year 2023 in Austria.
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Daily Overview
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The Calculator Submodule in VEEP
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VEEP-Match Architecture
MatchVEEP
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Afzal, Samira, et al. "VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing
Instances." Proceedings of the First International Workshop on Green Multimedia Systems. 2023.
Match Submodules
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Evaluation
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Germany
Austria
Cheapest with
highest energy consumption
Most expensive with
Lowest energy consumption
Experimental Infrastructure
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500 video encoding segments
VEEP-Match Experimental Results
77.85% cost reduction
45.42% energy reduction
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Conclusions
Proposed VEEP-Match for optimized scheduling of adaptive
encoding/transcoding processes in cloud and edge environments
Proposed a game-theoretic optimization model
Highlighted factors:
Providers' priorities: cost, energy, CO2 and/or time priorities
Resources properties: location, type, cost
Encoding parameters: codec, bitrate, resolution
Segment features: complexity
Evaluated VEEP-Match on a set of cloud AWS and edge resource instances
Achieved significant savings:
17%-78% in cost-optimized scenarios
38%-45% in energy-optimized scenarios
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Thank you
Have a
great day
ahead!
Institute of Information Technology (ITEC) Alpen-Adria-Universität Austria [email protected]