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Generating Random Service Function Chain Embedding Problems
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). ] Deggendorf Inst Technol, Elect Engn Media Tech & Comp Sci, Deggendorf, Germany.ORCID iD: 0000-0002-0074-5411
2017 (English)In: 2017 IEEE Conference On Network Function Virtualization And Software Defined Networks (Nfv-Sdn), IEEE, 2017, p. 79-84Chapter in book (Other academic)
Abstract [en]

The combination of Software Defined Networking (SDN) and Network Function Virtualization (NFV) promises to provide highly flexible and configurable network infrastructures. This relies, however, on an efficient assignment of the respective Service Function Chain (SFC). This is related to Virtual Network Embedding (VNE), where algorithms are devised to provide such an assignment. To evaluate and compare the efficiency of such algorithms, well-designed embedding problems have to be generated. This paper presents a new mechanism for generating embedding problems: Problems are generated from a given set of SFCs such that each generated problem is known in advance to have an optimal solution. Experimenters can use this approach to investigate specific properties of embedding algorithms. The approach, thereby, facilitates more detailed evaluation.

Place, publisher, year, edition, pages
IEEE, 2017. p. 79-84
Series
2017 IEEE CONFERENCE ON NETWORK FUNCTION VIRTUALIZATION AND SOFTWARE DEFINED NETWORKS (NFV-SDN)
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-66887ISI: 000426936400012ISBN: 978-1-5386-3285-7 (print)OAI: oai:DiVA.org:kau-66887DiVA, id: diva2:1194206
Available from: 2018-03-29 Created: 2018-03-29 Last updated: 2018-06-26Bibliographically approved

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