System disruptions
We are currently experiencing disruptions on the search portals due to high traffic. We are working to resolve the issue, you may temporarily encounter an error message.
Change search
CiteExportLink to record
Permanent link

Direct link
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
An Analysis of Energy-Efficient Approaches Used for Virtual Machines and Data Centres
Department of Computer Sci, COMSATS Institute of Information Technology Abbottabad. Pakistan.
Jönköping University, Jönköping International Business School, JIBS, Informatics.
Faculty of Engineering and IT, University of Technology Sydney, Australia.
2017 (English)In: 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), IEEE, 2017, p. 91-96, article id 8119135Conference paper, Published paper (Refereed)
Abstract [en]

For online business markets with a large customer base, the use of market-platforms is leading to a rapid generation of a huge amount of data. Such businesses face challenges to satisfy their users. A quantitative research approach has been used to examine big data in online markets, but there is also a need for qualitative research in this area, so as to understand the relationship between big data, online markets. The present research presents an analysis of the various case study approaches that are employed by researchers in this area. We also analyze trends in case study techniques in this area. The research problem is taken on as a research case for the present study. The results of the study should contribute the implementation of big-data in online markets research.

Place, publisher, year, edition, pages
IEEE, 2017. p. 91-96, article id 8119135
Keywords [en]
Energy consumption, Energy efficiency, Resource management, Virtual machining, Cloud computing, Algorithm design and analysis, Virtual machines, Data centres
National Category
Energy Systems Computer Systems
Identifiers
URN: urn:nbn:se:hj:diva-38167DOI: 10.1109/ICEBE.2017.23ISI: 000426981100013Scopus ID: 2-s2.0-85041668650ISBN: 978-1-5386-1412-9 (electronic)ISBN: 978-1-5386-1413-6 (print)OAI: oai:DiVA.org:hj-38167DiVA, id: diva2:1165791
Conference
2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), 4-6 Nov. 2017, Shanghai, China
Available from: 2017-12-13 Created: 2017-12-13 Last updated: 2021-03-03Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Manzoor, Mirfa
By organisation
JIBS, Informatics
Energy SystemsComputer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 258 hits
CiteExportLink to record
Permanent link

Direct link
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