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Virtual Network Function Placement: Towards Minimizing Network Latency and Lead Time
Univ. of Sydney, Sydney, NSW, Australia.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (DISCO, Computer Networking)ORCID iD: 0000-0001-9194-010X
School of Information Technologies, University of Sydney.
China Univ. of Geosci., China.
2017 (English)In: IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Piscataway, New Jersey, USA: IEEE, 2017, p. 90-97Conference paper (Refereed)
Abstract [en]

Network Function Virtualization (NFV) is an emerging network architecture to increase flexibility and agility within operator's networks by placing virtualized services on demand in Cloud data centers (CDCs). One of the main challenges for the NFV environment is how to minimize network latency in the rapidly changing network environments. Although many researchers have already studied in the field of Virtual Machine (VM) migration and Virtual Network Function (VNF) placement for efficient resource management in CDCs, VNF migration problem for low network latency among VNFs has not been studied yet to the best of our knowledge. To address this issue in this article, we i) formulate the VNF migration problem and ii) develop a novel VNF migration algorithm called VNF Real-time Migration (VNF-RM) for lower network latency in dynamically changing resource availability. As a result of experiments, the effectiveness of our algorithm is demonstrated by reducing network latency by up to 70.90% after latency-aware VNF migrations.

Place, publisher, year, edition, pages
Piscataway, New Jersey, USA: IEEE, 2017. p. 90-97
Keyword [en]
Network Function Virtualization, Virtual Network Function, Virtual Network Function Placement
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-66137DOI: 10.1109/CLOUD.2017.118ISBN: 978-1-5386-1993-3 (electronic)ISBN: 978-1-5386-1994-0 (print)OAI: oai:DiVA.org:kau-66137DiVA: diva2:1180729
Conference
9th IEEE International Conference on Cloud Computing Technology and Science 11-14 December 2017 • Hong Kong, Hong Kong
Available from: 2018-02-06 Created: 2018-02-06 Last updated: 2018-02-07

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CiteExportLink to record
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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
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