Integrating virtualization, speed scaling, and powering on/off servers in data centers for energy efficiency

Julian A. Gallego Arrubla, Young Myoung Ko, Ronny J. Polansky, Eduardo Pérez, Lewis Ntaimo, Natarajan Gautam

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Data centers consume a phenomenal amount of energy, which can be significantly reduced by appropriately allocating resources using technologies such as virtualization, speed scaling, and powering off servers. This article proposes a unified methodology that combines these technologies under a single framework to efficiently operate data centers. In particular, a large-scale Mixed Integer Program (MIP) is formulated that prescribes optimal allocation of resources while incorporating inherent variability and uncertainty of workload experienced by the data center. However, only for small to medium-sized clients it is possible to solve the MIP using commercial optimization software packages in a reasonable time. Thus, for large-sized clients a heuristic method is developed that is effective and fast. An extensive set of numerical experiments is performed to illustrate the methodology, obtain insights on the allocation policies, evaluate the quality of the proposed heuristic, and test the validity of the assumptions made in the literature. The results show that gains of up to 40% can be obtained by using the integrated approach rather than the traditional approach where virtualization, dynamic voltage/frequency scaling, and powering off servers are done separately.

Original languageEnglish (US)
Pages (from-to)1114-1136
Number of pages23
JournalIIE Transactions (Institute of Industrial Engineers)
Volume45
Issue number10
DOIs
StatePublished - Oct 1 2013
Externally publishedYes

Keywords

  • Data center operations
  • energy conservation
  • heuristic method
  • mixed integer programming
  • non-homogeneous systems

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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