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Energy Efficient Video Encoding for
Cloud and Edge Computing Instances
Samira Afzal
Institute of Information Technology (ITEC), Alpen-Adria-Universität Austria
samira.afzal@aau.at | https://athena.itec.aau.at/gaia
2
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
3
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
4
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
5
Storage/CDN
Encoded video
Video
Coordinator
Storage
Energy Efficient Video Encoding
6
Energy Efficient Video Encoding
VEEP-Match
Storage/CDN
Encoded video
Video
Storage
7
Coordinator
VEEP-Match Architecture
8
VEEP-Match Architecture
9
VEEP
VEEP-Match Architecture
10
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
Match
VEEP
11
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
12
The Video Analyzer Submodule in VEEP
13
The Predictor Submodule in VEEP
14
The Calculator Submodule in VEEP
15
The Data Source Submodule in VEEP
16
Annual Overview
CO₂ emissions over the year 2023 in Austria.
17
Daily Overview
17 18
The Calculator Submodule in VEEP
19
VEEP-Match Architecture
Match
VEEP
20
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
21
Evaluation
22
Germany Austria
Cheapest with
highest energy consumption
Most expensive with
Lowest energy consumption
Experimental Infrastructure
23
500 video encoding segments
VEEP-Match Experimental Results
77.85% cost reduction
45.42% energy reduction
24
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
25
Thank you
Have a
great day
ahead!
Institute of Information Technology (ITEC) Alpen-Adria-Universität Austria
samira.afzal@aau.at

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