Abstract
In this paper, we explore a data center's performance with a call for energy efficiency through green computing. Some performance metrics we examine in data centers are server energy usage, Power Usage Effectiveness and utilization rate, i.e., the extent to which data center servers are being used. Recent literature indicates that utilization rates at many internal data centers are quite low, resulting in poor usage of resources such as energy and materials. Based on our study, we attribute these low utilization rates to not fully taking advantage of virtualization, and not retiring phantom (unused) servers. This paper describes our initiative corroborated with real data in a university setting. We suggest that future data centers will need to increase their utilization rates for better energy efficiency, and moving towards a cloud provider would help. However, we argue that neither a pure in-house data center or cloud model is the best solution. Instead we recommend, from a decision support perspective, a hybrid model in data center management to lower costs and increase services, while also providing greater energy efficiency.
| Original language | English |
|---|---|
| Pages (from-to) | 45-51 |
| Number of pages | 7 |
| Journal | SIGMOD Record |
| Volume | 43 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2014 |
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Keywords
- Cloud
- Data Centers
- Energy Efficiency
- Green IT
- Utilization Rates
Cite this
}
A call for energy efficiency in data centers. / Pawlish, Michael; Varde, Aparna; Robila, Stefan; Ranganathan, Anand.
In: SIGMOD Record, Vol. 43, No. 1, 01.01.2014, p. 45-51.Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - A call for energy efficiency in data centers
AU - Pawlish, Michael
AU - Varde, Aparna
AU - Robila, Stefan
AU - Ranganathan, Anand
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In this paper, we explore a data center's performance with a call for energy efficiency through green computing. Some performance metrics we examine in data centers are server energy usage, Power Usage Effectiveness and utilization rate, i.e., the extent to which data center servers are being used. Recent literature indicates that utilization rates at many internal data centers are quite low, resulting in poor usage of resources such as energy and materials. Based on our study, we attribute these low utilization rates to not fully taking advantage of virtualization, and not retiring phantom (unused) servers. This paper describes our initiative corroborated with real data in a university setting. We suggest that future data centers will need to increase their utilization rates for better energy efficiency, and moving towards a cloud provider would help. However, we argue that neither a pure in-house data center or cloud model is the best solution. Instead we recommend, from a decision support perspective, a hybrid model in data center management to lower costs and increase services, while also providing greater energy efficiency.
AB - In this paper, we explore a data center's performance with a call for energy efficiency through green computing. Some performance metrics we examine in data centers are server energy usage, Power Usage Effectiveness and utilization rate, i.e., the extent to which data center servers are being used. Recent literature indicates that utilization rates at many internal data centers are quite low, resulting in poor usage of resources such as energy and materials. Based on our study, we attribute these low utilization rates to not fully taking advantage of virtualization, and not retiring phantom (unused) servers. This paper describes our initiative corroborated with real data in a university setting. We suggest that future data centers will need to increase their utilization rates for better energy efficiency, and moving towards a cloud provider would help. However, we argue that neither a pure in-house data center or cloud model is the best solution. Instead we recommend, from a decision support perspective, a hybrid model in data center management to lower costs and increase services, while also providing greater energy efficiency.
KW - Cloud
KW - Data Centers
KW - Energy Efficiency
KW - Green IT
KW - Utilization Rates
UR - http://www.scopus.com/inward/record.url?scp=84901660119&partnerID=8YFLogxK
U2 - 10.1145/2627692.2627703
DO - 10.1145/2627692.2627703
M3 - Article
VL - 43
SP - 45
EP - 51
JO - SIGMOD Record
JF - SIGMOD Record
SN - 0163-5808
IS - 1
ER -