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Optimized Service Chain Placement Using Genetic Algorithm
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)ORCID iD: 0000-0002-6101-4305
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)ORCID iD: 0000-0001-9194-010X
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)ORCID iD: 0000-0002-9446-8143
2019 (English)In: Proceedings of the 2019 IEEE Conference on Network Softwarization NetSoft 2019, Unleashing the Power of Network Softwarization / [ed] Christian Jacquenet, Filip De Turck, Prosper Chemouil, Flavio Esposito, Olivier Festor, Walter Cerroni, Stefano Secci, IEEE, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Network Function Virtualization (NFV) is anemerging technology to consolidate network functions onto highvolume storages, servers and switches located anywhere in thenetwork. Virtual Network Functions (VNFs) are chainedtogether to provide a specific network service. Therefore, aneffective service chain placement strategy is required tooptimize the resource allocation and consequently to reduce theoperating cost of the substrate network. To this end, we proposefour genetic-based algorithms using roulette wheel andtournament selection techniques in order to place service chainsconsidering two different placement strategies. Since mappingof service chains sequentially (One-at-a-time strategy) may leadto suboptimal placement, we also propose Simultaneous strategythat places all service chains at the same time to improveperformance. Our goal in this work is to reduce deployment costof VNFs while satisfying constraints. We consider Geantnetwork as the substrate network along with its characteristicsextracted from SndLib. The proposed algorithms are able toplace service chains with any type of service graph. Theperformance benefits of the proposed algorithms arehighlighted through extensive simulations.

Place, publisher, year, edition, pages
IEEE, 2019.
Keywords [en]
Network Function Virtualization, Optimization, Genetic Algorithm, Service Chain Placement
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-74619DOI: 10.1109/NETSOFT.2019.8806644ISBN: 978-1-5386-9376-6 (electronic)ISBN: 978-1-5386-9377-3 (print)OAI: oai:DiVA.org:kau-74619DiVA, id: diva2:1348310
Conference
Network Softwarization (NetSoft), IEEE Conference on 24-28 June Paris, France
Projects
HITS, 4707
Funder
Knowledge Foundation, 20140037Available from: 2019-09-04 Created: 2019-09-04 Last updated: 2019-12-12Bibliographically approved

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Khoshkholghi, Mohammad AliTaheri, JavidBhamare, DevalKassler, Andreas
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