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Continuous Datacenter Consolidation
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
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2015 (English)In: 2015 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 2015, 387-396 p.Conference paper, Published paper (Refereed)
Abstract [en]

Efficient mapping of Virtual Machines (VMs) onto physical servers is a key problem for cloud infrastructure providers as hardware utilization directly impacts profit. Today, this mapping is commonly only performed when new VMs are created, but as VM workloads fluctuate and server availability varies, any initial mapping is bound to become suboptimal over time. We introduce a set of heuristic methods for continuous optimization of the VM-to-server mapping based on combinations of fundamental management actions, namely suspending and resuming physical machines, migrating VMs, and suspending and resuming VMs. By using these methods, cloud infrastructure providers can continuously optimize their server resources regardless of the predictability of the workload. To verify that our approach is applicable in real-world scenarios, we build a proof-of-concept datacenter management system that implements the proposed algorithms. The feasibility of our approach is evaluated through a combination of simulations and real experiments where our system provisions a workload of benchmark applications. Our results indicate that the proposed algorithms are feasible, that the combined management approach achieves the best results, and that the VM suspend and resume mechanism has the largest impact on provider profit.

Place, publisher, year, edition, pages
2015. 387-396 p.
Keyword [en]
Cloud Computing, Scheduling, Heuristic Methods, Consolidation, VM Migration, Power Management
National Category
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-125614DOI: 10.1109/CloudCom.2015.11ISI: 000380458100051ISBN: 978-1-4673-9560-1 (print)OAI: oai:DiVA.org:umu-125614DiVA: diva2:1032957
Conference
IEEE 7th International Conference on Cloud Computing Techonology and science, Vancouver, Canada, Nov 30-Dec 03, 2015.
Available from: 2016-10-05 Created: 2016-09-13 Last updated: 2016-10-05Bibliographically approved

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Svärd, PetterLi, WubinWadbro, EddieTordsson, JohanElmroth, Erik
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • 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