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Hadoop MapReduce in Eucalyptus Private Cloud
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2011 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis investigates how setting up a private cloud using the Eucalyptus Cloud system could be done along with it's usability, requirements and limitations as an open-source cloud platform providing private cloud solutions. It also studies if using the MapReduce framework through Apache Hadoop's implementation on top of the private Eucalyptus Cloud can provide near linear scalability in terms of time and the amount of virtual machines in the cluster.

Analysis has shown that Eucalyptus is lacking in a few usability areas when setting up the cloud infrastructure in terms of private networking and DNS lookups, yet the API that Eucalyptus provides gives benefits when migrating from public clouds like Amazon. The MapReduce framework is showing an initial near-linear relation which is declining when the amount of virtual machines is reaching the maximum of the cloud infrastructure.

Place, publisher, year, edition, pages
, UMNAD, 889
National Category
Engineering and Technology
URN: urn:nbn:se:umu:diva-51309OAI: diva2:478959
Educational program
Master of Science Programme in Computing Science and Engineering
Available from: 2012-01-17 Created: 2012-01-17 Last updated: 2012-01-17Bibliographically approved

Open Access in DiVA kB)1901 downloads
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