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Client-side energy costs of video streaming

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Ejembi_2015_Client_side_DSDIS_AAM.pdf (2.513Mb)
Date
04/02/2016
Author
Ejembi, Oche
Bhatti, Saleem N.
Keywords
Energy efficiency
Green ICT
Green IT
Quality of experience (QoE)
Sustainability
Video
QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
Computational Theory and Mathematics
Computer Networks and Communications
Theoretical Computer Science
NDAS
BDC
R2C
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Abstract
Through measurements on our testbed, we show how users of Netflix could make energy savings of up to 34% by adjusting video quality settings. We estimate the impacts of these quality settings on the energy consumption of client systems and the network. If users exercise choice in their video streaming habits, over 100 GWh of energy a year could be saved on a global scale. We discuss how providing energy usage information to users of digital video could enable them to make choices of video settings to reduce energy usage, and we estimate savings on associated electricity costs and carbon emissions.
Citation
Ejembi , O & Bhatti , S N 2016 , Client-side energy costs of video streaming . in J Chen & L T Yang (eds) , Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems : 11–13 December 2015 Sydney, Australia . , 7396511 , Institute of Electrical and Electronics Engineers Inc. , pp. 252-259 , 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015 , Sydney , Australia , 11/12/15 . https://doi.org/10.1109/DSDIS.2015.49
 
conference
 
Publication
Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems
DOI
https://doi.org/10.1109/DSDIS.2015.49
Type
Conference item
Rights
Copyright © 2015 IEEE. This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://dx.doi.org/10.1109/DSDIS.2015.49
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  • Computer Science Research
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/9353

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