Sustainable Cloud Computing
abstract: Energy consumption of the data centers worldwide is rapidly growing fueled by ever-increasing demand for Cloud computing applications ranging from social networking to e-commerce. Understandably, ensuring energy-efficiency and sustainability of Cloud data centers without compromising perfo...
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2014
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Online Access: | http://hdl.handle.net/2286/R.I.27461 |
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ndltd-asu.edu-item-274612018-06-22T03:05:43Z Sustainable Cloud Computing abstract: Energy consumption of the data centers worldwide is rapidly growing fueled by ever-increasing demand for Cloud computing applications ranging from social networking to e-commerce. Understandably, ensuring energy-efficiency and sustainability of Cloud data centers without compromising performance is important for both economic and environmental reasons. This dissertation develops a cyber-physical multi-tier server and workload management architecture which operates at the local and the global (geo-distributed) data center level. We devise optimization frameworks for each tier to optimize energy consumption, energy cost and carbon footprint of the data centers. The proposed solutions are aware of various energy management tradeoffs that manifest due to the cyber-physical interactions in data centers, while providing provable guarantee on the solutions' computation efficiency and energy/cost efficiency. The local data center level energy management takes into account the impact of server consolidation on the cooling energy, avoids cooling-computing power tradeoff, and optimizes the total energy (computing and cooling energy) considering the data centers' technology trends (servers' power proportionality and cooling system power efficiency). The global data center level cost management explores the diversity of the data centers to minimize the utility cost while satisfying the carbon cap requirement of the Cloud and while dealing with the adversity of the prediction error on the data center parameters. Finally, the synergy of the local and the global data center energy and cost optimization is shown to help towards achieving carbon neutrality (net-zero) in a cost efficient manner. Dissertation/Thesis Abbasi, Zahra (Author) Gupta, Sandeep K. S. (Advisor) Chakrabarti, Chaitali (Committee member) Shrivastava, Aviral (Committee member) Wu, Carole-Jean (Committee member) Arizona State University (Publisher) Computer science Cloud computing Data Centers Electricty cost Energy efficiency Renewable energy Thermal efficiency eng 280 pages Doctoral Dissertation Computer Science 2014 Doctoral Dissertation http://hdl.handle.net/2286/R.I.27461 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2014 |
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English |
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Doctoral Thesis |
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Computer science Cloud computing Data Centers Electricty cost Energy efficiency Renewable energy Thermal efficiency |
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Computer science Cloud computing Data Centers Electricty cost Energy efficiency Renewable energy Thermal efficiency Sustainable Cloud Computing |
description |
abstract: Energy consumption of the data centers worldwide is rapidly growing fueled by ever-increasing demand for Cloud computing applications ranging from social networking to e-commerce. Understandably, ensuring energy-efficiency and sustainability of Cloud data centers without compromising performance is important for both economic and environmental reasons. This dissertation develops a cyber-physical multi-tier server and workload management architecture which operates at the local and the global (geo-distributed) data center level. We devise optimization frameworks for each tier to optimize energy consumption, energy cost and carbon footprint of the data centers. The proposed solutions are aware of various energy management tradeoffs that manifest due to the cyber-physical interactions in data centers, while providing provable guarantee on the solutions' computation efficiency and energy/cost efficiency. The local data center level energy management takes into account the impact of server consolidation on the cooling energy, avoids cooling-computing power tradeoff, and optimizes the total energy (computing and cooling energy) considering the data centers' technology trends (servers' power proportionality and cooling system power efficiency). The global data center level cost management explores the diversity of the data centers to minimize the utility cost while satisfying the carbon cap requirement of the Cloud and while dealing with the adversity of the prediction error on the data center parameters. Finally, the synergy of the local and the global data center energy and cost optimization is shown to help towards achieving carbon neutrality (net-zero) in a cost efficient manner. === Dissertation/Thesis === Doctoral Dissertation Computer Science 2014 |
author2 |
Abbasi, Zahra (Author) |
author_facet |
Abbasi, Zahra (Author) |
title |
Sustainable Cloud Computing |
title_short |
Sustainable Cloud Computing |
title_full |
Sustainable Cloud Computing |
title_fullStr |
Sustainable Cloud Computing |
title_full_unstemmed |
Sustainable Cloud Computing |
title_sort |
sustainable cloud computing |
publishDate |
2014 |
url |
http://hdl.handle.net/2286/R.I.27461 |
_version_ |
1718700613249794048 |