Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Energy Efficient Virtual Machine Consolidation under Uncertain Input Parameters for Green Data Centers
UPC, Dept Network Engn, Barcelona, Spain.
Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science. (DISCO)ORCID iD: 0000-0002-9446-8143
2015 (English)In: 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom), IEEE, 2015, p. 436-439Conference paper, Published paper (Refereed)
Abstract [en]

Reducing the energy consumption of data centers and the Cloud is very important in order to lower CO2 footprint and operational cost (OPEX) of a Cloud operator. To this extent, it becomes crucial to minimise the energy consumption by consolidating the number of powered-on physical servers that host the given virtual machines (VMs). In this work, we propose a novel approach to the energy efficient VM consolidation problem by applying Robust Optimisation Theory. We develop a mathematical model as a robust Mixed Integer Linear Program under the assumption that the input to the problem (e.g. resource demands of the VMs) is not known precisely, but varies within given bounds. A numerical evaluation shows that our model allows the Cloud Operator to tradeoff between the power consumption and the protection from more severe and unlikely deviations of the uncertain input.

Place, publisher, year, edition, pages
IEEE, 2015. p. 436-439
Series
IEEE International Conference on Cloud Computing Technology and Science, ISSN 2330-2186
Keyword [en]
Virtual machine consolidation; energy saving; mixed integer optimisation; robust optimisation
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-38745DOI: 10.1109/CloudCom.2015.15ISI: 000380458100058OAI: oai:DiVA.org:kau-38745DiVA, id: diva2:874776
Conference
IEEE CloudCom 2015 - 7th IEEE International Conference on Cloud Computing Technology and Science, Vancouver, Canada, Nov.30-Dec.3 2015
Funder
Knowledge Foundation, READY
Available from: 2015-11-27 Created: 2015-11-27 Last updated: 2018-01-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Kassler, Andreas

Search in DiVA

By author/editor
Kassler, Andreas
By organisation
Department of Computer Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 161 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf