Abstract
The purpose of this paper is to analyze the carbon footprint and utilization rates in a data center. The long-term goal of this work is to give data center administrators an enhanced perspective of data center operations to allow for more energy efficient operation, to lower the carbon footprint, and to promote green data centers. Previous literature shows that low utilization rates in data centers are due to the forecasting of demand to meet spikes in data center use. This management policy has led to many servers running idle the majority of the time which is a waste of resources. We argue that a majority of the data centers should be down sized through decommissioning of phantom servers, virtualization, and shifting spikes in demand to a cloud provider. We use data from the operations of a mid-to-large scale data center in a university. We deploy data mining techniques of decision trees and case-based reasoning to conduct analysis for decision support in cloud computing at data centers. We provide recommendations based on a literature search and our own work. This paper describes our work in progress in the area of developing green data centers.
Original language | English |
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Title of host publication | CloudDB'12 - Proceedings of the 3rd ACM International Workshop on Cloud Data Management, Co-located with CIKM 2012 |
Pages | 43-48 |
Number of pages | 6 |
DOIs | |
State | Published - 10 Dec 2012 |
Event | 3rd ACM International Workshop on Cloud Data Management, CloudDB 2012 - Co-located with CIKM 2012 - Maui, HI, United States Duration: 29 Oct 2012 → 29 Oct 2012 |
Publication series
Name | International Conference on Information and Knowledge Management, Proceedings |
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Other
Other | 3rd ACM International Workshop on Cloud Data Management, CloudDB 2012 - Co-located with CIKM 2012 |
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Country | United States |
City | Maui, HI |
Period | 29/10/12 → 29/10/12 |
Fingerprint
Keywords
- Cloud Computing
- Data Centers
- Decision Support
- Green IT
- Server Utilization
- Sustainable Energy
Cite this
}
Cloud computing for environment-friendly data centers. / Pawlish, Michael; Varde, Aparna; Robila, Stefan.
CloudDB'12 - Proceedings of the 3rd ACM International Workshop on Cloud Data Management, Co-located with CIKM 2012. 2012. p. 43-48 (International Conference on Information and Knowledge Management, Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Cloud computing for environment-friendly data centers
AU - Pawlish, Michael
AU - Varde, Aparna
AU - Robila, Stefan
PY - 2012/12/10
Y1 - 2012/12/10
N2 - The purpose of this paper is to analyze the carbon footprint and utilization rates in a data center. The long-term goal of this work is to give data center administrators an enhanced perspective of data center operations to allow for more energy efficient operation, to lower the carbon footprint, and to promote green data centers. Previous literature shows that low utilization rates in data centers are due to the forecasting of demand to meet spikes in data center use. This management policy has led to many servers running idle the majority of the time which is a waste of resources. We argue that a majority of the data centers should be down sized through decommissioning of phantom servers, virtualization, and shifting spikes in demand to a cloud provider. We use data from the operations of a mid-to-large scale data center in a university. We deploy data mining techniques of decision trees and case-based reasoning to conduct analysis for decision support in cloud computing at data centers. We provide recommendations based on a literature search and our own work. This paper describes our work in progress in the area of developing green data centers.
AB - The purpose of this paper is to analyze the carbon footprint and utilization rates in a data center. The long-term goal of this work is to give data center administrators an enhanced perspective of data center operations to allow for more energy efficient operation, to lower the carbon footprint, and to promote green data centers. Previous literature shows that low utilization rates in data centers are due to the forecasting of demand to meet spikes in data center use. This management policy has led to many servers running idle the majority of the time which is a waste of resources. We argue that a majority of the data centers should be down sized through decommissioning of phantom servers, virtualization, and shifting spikes in demand to a cloud provider. We use data from the operations of a mid-to-large scale data center in a university. We deploy data mining techniques of decision trees and case-based reasoning to conduct analysis for decision support in cloud computing at data centers. We provide recommendations based on a literature search and our own work. This paper describes our work in progress in the area of developing green data centers.
KW - Cloud Computing
KW - Data Centers
KW - Decision Support
KW - Green IT
KW - Server Utilization
KW - Sustainable Energy
UR - http://www.scopus.com/inward/record.url?scp=84870515512&partnerID=8YFLogxK
U2 - 10.1145/2390021.2390030
DO - 10.1145/2390021.2390030
M3 - Conference contribution
AN - SCOPUS:84870515512
SN - 9781450317085
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 43
EP - 48
BT - CloudDB'12 - Proceedings of the 3rd ACM International Workshop on Cloud Data Management, Co-located with CIKM 2012
ER -