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Automating Ethernet VPN Deployment in SDN-based Data Centers
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-9866-8209
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-7734-1653
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-9446-8143
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-8802-504x
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2017 (English)In: 2017 FOURTH INTERNATIONAL CONFERENCE ON SOFTWARE DEFINED SYSTEMS (SDS), IEEE, 2017, p. 61-66Chapter in book (Other academic)
Abstract [en]

Layer 2 Virtual Private Network (L2VPN) is widely deployed in both service provider networks and enterprises. However, legacy L2VPN solutions have scalability limitations in the context of Data Center (DC) interconnection and networking which require new approaches that address the requirements of service providers for virtual private cloud services. Recently, Ethernet VPN (EVPN) has been proposed to address many of those concerns and vendors started to deploy EVPN based solutions in DC edge routers. However, manual configuration leads to a time-consuming, error-prone configuration and high operational costs. Automating the EVPN deployment from cloud platforms such as OpenStack enhances both the deployment and flexibility of EVPN Instances (EVIs). This paper proposes a Software Defined Network (SDN) based framework that automates the EVPN deployment and management inside SDN-based DCs using OpenStack and OpenDaylight (ODL). We implemented and extended several modules inside ODL controller to manage and interact with EVIs and an interface to OpenStack that allows the deployment and configuration of EVIs. We conclude with scalability analysis of our solution.

Place, publisher, year, edition, pages
IEEE, 2017. p. 61-66
Series
2017 FOURTH INTERNATIONAL CONFERENCE ON SOFTWARE DEFINED SYSTEMS (SDS)
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-65690ISI: 000405190400010ISBN: 978-1-5386-2855-3 (print)OAI: oai:DiVA.org:kau-65690DiVA, id: diva2:1175623
Available from: 2018-01-18 Created: 2018-01-18 Last updated: 2018-06-26Bibliographically approved

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Alizadeh Noghani, KyomaarsHernandez Benet, CristianKassler, AndreasAntonio, Marotta

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  • apa
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