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Improving the energy efficiency of virtual data centers in an IT service provider through proactive fuzzy rules-based multicriteria decision making.

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Title: Improving the energy efficiency of virtual data centers in an IT service provider through proactive fuzzy rules-based multicriteria decision making.
Authors: Cocaña-Fernández, Alberto1, Rodríguez-Soares, Julio1, Sánchez, Luciano1, Ranilla, José1
Source: Journal of Supercomputing. Mar2019, Vol. 75 Issue 3, p1078-1093. 16p.
Subjects: Data libraries, Energy consumption of computers, Multiple criteria decision making, Evolutionary algorithms, Fuzzy systems, Mathematical optimization
Abstract: A proactive multicriteria mechanism for virtual data center optimization through server consolidation is proposed. In contrast with previous works where heuristic mechanisms were designed using expert knowledge, the new proactive approach uses multiobjective evolutionary algorithms to learn fuzzy rule-based systems that determine optimal reallocation decisions according to the preferences of the data center operator and a prediction of the load. Experimental evaluations based on an actual IT service provider show that the proactive mechanism is capable of improving energy savings compared to commercial hypervisors while complying with service provider's preferences and constraints. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A proactive multicriteria mechanism for virtual data center optimization through server consolidation is proposed. In contrast with previous works where heuristic mechanisms were designed using expert knowledge, the new proactive approach uses multiobjective evolutionary algorithms to learn fuzzy rule-based systems that determine optimal reallocation decisions according to the preferences of the data center operator and a prediction of the load. Experimental evaluations based on an actual IT service provider show that the proactive mechanism is capable of improving energy savings compared to commercial hypervisors while complying with service provider's preferences and constraints. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11227-018-2301-1
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        Text: English
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        Type: general
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      – SubjectFull: Multiple criteria decision making
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      – SubjectFull: Evolutionary algorithms
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      – SubjectFull: Fuzzy systems
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              Text: Mar2019
              Type: published
              Y: 2019
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