VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances
Authors: 
Sandro Linder, Samira Afzal, Christian Bauer, 
Hadi Amirpour, Radu Prodan, 
Christian TimmererAuthors Info & Claims
Pages 332 - 338
Abstract
Video streaming constitutes 65 % of global internet traffic, prompting an investigation into its energy consumption and CO2 emissions. Video encoding, a computationally intensive part of streaming, has moved to cloud computing for its scalability and flexibility. However, cloud data centers' energy consumption, especially video encoding, poses environmental challenges. This paper presents VEED, a FAIR Video Encoding Energy and CO2 Emissions Dataset for Amazon Web Services (AWS) EC2 instances. Additionally, the dataset also contains the duration, CPU utilization, and cost of the encoding. To prepare this dataset, we introduce a model and conduct a benchmark to estimate the energy and CO2 emissions of different Amazon EC2 instances during the encoding of 500 video segments with various complexities and resolutions using Advanced Video Coding (AVC) and High-Efficiency Video Coding (HEVC). VEED and its analysis can provide valuable insights for video researchers and engineers to model energy consumption, manage energy resources, and distribute workloads, contributing to the sustainability of cloud-based video encoding and making them cost-effective. VEED is available at https://github.com/cd-athena/VEED-dataset.
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Index Terms
- VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances
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Published In
April 2024
557 pages
ISBN:9798400704123
DOI:10.1145/3625468
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
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Published: 17 April 2024
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- Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, and the Christian Doppler Research Association
- Austrian Research Promotion Agency (FFG)
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