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Virtual Network Function Placement: Towards Minimizing Network Latency and Lead Time
2017 (English)In: 2017 9TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 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 efficiently allocate Virtual Network Functions (VNF) to Virtual Machines (VMs). Although a significant amount of work/research has been already conducted for the generic VNF placement problem, network latency among various network components has not been comprehensively considered yet. To address this concern, in this article, we design a more comprehensive model based on real measurements to capture network latency among VNFs with more granularity to optimize placement of VNFs in CDCs. Experimental results are promising and indicate that our approach, namely VNF Low-Latency Placement (VNF-LLP), can reduce network latency by up to 64.24% (50.33% in average) compared with two generic algorithms. Furthermore, it has a lower lead time (time to find a suitable VM to host a VNF) as compared with two classic approaches.

Place, publisher, year, edition, pages
2017. p. 90-97
Series
International Conference on Cloud Computing Technology and Science, ISSN 2330-2194
Identifiers
URN: urn:nbn:se:kau:diva-66938DOI: 10.1109/CloudCom.2017.12ISI: 000427727800012ISBN: 978-1-5386-0692-6 OAI: oai:DiVA.org:kau-66938DiVA, id: diva2:1195822
Conference
9th IEEE International Conference on Cloud Computing Technology and Science (CloudCom), DEC 11-14, 2017, Hong Kong Polytechn Univ, Dept Comp, Hong Kong, HONG KONG
Available from: 2018-04-06 Created: 2018-04-06 Last updated: 2018-04-06

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
  • en-GB
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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