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
Optimising for Energy or Robustness? Trade-off for VM Consolidation under Uncertainty
Universitat Politècnica de Catalunya (UPC), Barcelona.
Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science. Karlstad University, Faculty of Economic Sciences, Communication and IT, Centre for HumanIT. (DISCO)ORCID iD: 0000-0002-9446-8143
2016 (English)In: Optimization Letters, ISSN 1862-4472, E-ISSN 1862-4480Article in journal (Refereed) Published
Abstract [en]

Reducing the energy consumption of virtualized datacenters and the Cloud is very important in order to lower CO2 footprint and operational cost of a Cloud operator. However, there is a trade-off between energy consumption and perceived application performance. In order to save energy, Cloud operators want to consolidate as many Virtual Machines (VM) on the fewest possible physical servers, possibly involving overbooking of resources. However, that may involve SLA violations when many VMs run on peak load. Such consolidation is typically done using VM migration techniques, which stress the network. As a consequence, it is important to find the right balance between the energy consumption and the number of migrations to perform. Unfortunately, the resources that a VM requires are not precisely known in advance, which makes it very difficult to optimise the VM migration schedule. In this paper, we therefore propose a novel approach based on the theory of robust optimisation. We model the VM consolidation problem as a robust Mixed Integer Linear Program and allow to specify bounds for e.g. resource requirements of the VMs. We show that, by using our model, Cloud operators can effectively trade-off uncertainty of resource requirements with total energy consumption. Also, our model allows us to quantify the price of the robustness in terms of energy saving against resource requirement violations.

Place, publisher, year, edition, pages
Springer, 2016.
Keyword [en]
Virtual machine consolidation · Energy saving, Mixed integer optimisation, Robust optimisation, Green datacenter
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-47724DOI: 10.1007/s11590-016-1065-xOAI: oai:DiVA.org:kau-47724DiVA: diva2:1068461
Funder
Knowledge Foundation
Available from: 2017-01-25 Created: 2017-01-25 Last updated: 2017-08-07Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Kassler, Andreas
By organisation
Department of Computer ScienceCentre for HumanIT
In the same journal
Optimization Letters
Computer Science

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 114 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