Regression Cloud Models and Their Applications in Energy Consumption of Data Center
As cloud data center consumes more and more energy, both researchers and engineers aim to minimize energy consumption while keeping its services available. A good energy model can reflect the relationships between running tasks and the energy consumed by hardware and can be further used to schedule...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2015/143071 |
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| _version_ | 1832558921512910848 |
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| author | Yanshuang Zhou Na Li Hong Li Yongqiang Zhang |
| author_facet | Yanshuang Zhou Na Li Hong Li Yongqiang Zhang |
| author_sort | Yanshuang Zhou |
| collection | DOAJ |
| description | As cloud data center consumes more and more energy, both researchers and engineers aim to minimize energy consumption while keeping its services available. A good energy model can reflect the relationships between running tasks and the energy consumed by hardware and can be further used to schedule tasks for saving energy. In this paper, we analyzed linear and nonlinear regression energy model based on performance counters and system utilization and proposed a support vector regression energy model. For performance counters, we gave a general linear regression framework and compared three linear regression models. For system utilization, we compared our support vector regression model with linear regression and three nonlinear regression models. The experiments show that linear regression model is good enough to model performance counters, nonlinear regression is better than linear regression model for modeling system utilization, and support vector regression model is better than polynomial and exponential regression models. |
| format | Article |
| id | doaj-art-3af5abbe8baa4669a15c491230f236f4 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-3af5abbe8baa4669a15c491230f236f42025-02-03T01:31:17ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552015-01-01201510.1155/2015/143071143071Regression Cloud Models and Their Applications in Energy Consumption of Data CenterYanshuang Zhou0Na Li1Hong Li2Yongqiang Zhang3Handan College, Handan, Hebei 056005, ChinaHandan College, Handan, Hebei 056005, ChinaHandan College, Handan, Hebei 056005, ChinaHandan College, Handan, Hebei 056005, ChinaAs cloud data center consumes more and more energy, both researchers and engineers aim to minimize energy consumption while keeping its services available. A good energy model can reflect the relationships between running tasks and the energy consumed by hardware and can be further used to schedule tasks for saving energy. In this paper, we analyzed linear and nonlinear regression energy model based on performance counters and system utilization and proposed a support vector regression energy model. For performance counters, we gave a general linear regression framework and compared three linear regression models. For system utilization, we compared our support vector regression model with linear regression and three nonlinear regression models. The experiments show that linear regression model is good enough to model performance counters, nonlinear regression is better than linear regression model for modeling system utilization, and support vector regression model is better than polynomial and exponential regression models.http://dx.doi.org/10.1155/2015/143071 |
| spellingShingle | Yanshuang Zhou Na Li Hong Li Yongqiang Zhang Regression Cloud Models and Their Applications in Energy Consumption of Data Center Journal of Electrical and Computer Engineering |
| title | Regression Cloud Models and Their Applications in Energy Consumption of Data Center |
| title_full | Regression Cloud Models and Their Applications in Energy Consumption of Data Center |
| title_fullStr | Regression Cloud Models and Their Applications in Energy Consumption of Data Center |
| title_full_unstemmed | Regression Cloud Models and Their Applications in Energy Consumption of Data Center |
| title_short | Regression Cloud Models and Their Applications in Energy Consumption of Data Center |
| title_sort | regression cloud models and their applications in energy consumption of data center |
| url | http://dx.doi.org/10.1155/2015/143071 |
| work_keys_str_mv | AT yanshuangzhou regressioncloudmodelsandtheirapplicationsinenergyconsumptionofdatacenter AT nali regressioncloudmodelsandtheirapplicationsinenergyconsumptionofdatacenter AT hongli regressioncloudmodelsandtheirapplicationsinenergyconsumptionofdatacenter AT yongqiangzhang regressioncloudmodelsandtheirapplicationsinenergyconsumptionofdatacenter |