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NFV-Inspector: A Systematic Approach to Profile and Analyze Virtual Network Functions
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-4825-8831
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-9194-010X
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-9446-8143
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2018 (English)In: 2018 IEEE 7th International Conference on Cloud Networking (CloudNet), IEEE, 2018, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

Network Function Virtualization (NFV) focuses on decoupling network functions from proprietary hardware (i.e., middleboxes) by leveraging virtualization technology. Combining it with Software Defined Networking (SDN) enables us to chain network services much easier and faster. The main idea of using these technologies is to consolidate several Virtual Network Functions (VNFs) into a fewer number of commodity servers to reduce costs, increase VNFs fluidity and improve resource efficiency. However, the resource allocation and placement of VNFs in the network is a multifaceted decision problem that depends on many factors, including VNFs resource demand characteristics, arrival rate, configuration of underlying infrastructure, available resources and agreed Quality of Services (QoS) in Service Level Agreements (SLAs). This paper presents a bottom-up open-source NFV analysis platform (NFV-Inspector) to (1) systematically profile and classify VNFs based on resource capacities, traffic demand rate, underlying system properties, placement of VNFs in the network, etc. and (2) extract/calculate the correlation among the QoS metrics and resource utilization of VNFs. We evaluated our approach using an emulated virtual Evolved Packet Core platform (Open5GCore) to showcase how complex relation among various NFV service chains can be systematically profiled and analyzed.

Place, publisher, year, edition, pages
IEEE, 2018. p. 1-7
Series
IEEE International Conference on Cloud Networking, ISSN 2374-3239
Keywords [en]
Classification, Network Function Virtualization, Profiling, Quality of Service, Software Defined Networking, Classification (of information), Open source software, Open systems, Outsourcing, Transfer functions, Virtual reality, Decoupling network, Evolved packet cores, Resource efficiencies, Resource utilizations, Service level agreement (SLAs), Software defined networking (SDN), Virtualization technologies
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-71277DOI: 10.1109/CloudNet.2018.8549333ISI: 000465081600016Scopus ID: 2-s2.0-85060215258ISBN: 9781538668313 (print)OAI: oai:DiVA.org:kau-71277DiVA, id: diva2:1290792
Conference
7th IEEE International Conference on Cloud Networking, CloudNet 2018, 22 October 2018 through 24 October 2018
Projects
NFV Optimizer, 5276
Funder
Knowledge Foundation, 20160182Available from: 2019-02-21 Created: 2019-02-21 Last updated: 2019-07-03Bibliographically approved

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Gokan Khan, MichelTaheri, JavidKassler, Andreas

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