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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-19701
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dc.contributor.authorGuner, Selcan-
dc.contributor.authorGür, Gürkan-
dc.contributor.authorAlagöz, Fatih-
dc.date.accessioned2020-03-07T13:31:13Z-
dc.date.available2020-03-07T13:31:13Z-
dc.date.issued2020-
dc.identifier.isbn978-1-7281-4199-2de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/19701-
dc.description​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.de_CH
dc.description.abstractA sizeable software defined network with a single controller responsible for all forwarding elements is potentially failure-prone and inadequate for dynamic network loads. To this end, having multiple controllers improves resilience and distributes network control overhead. However, when there is a disruption in the control plane, a rapid and performant controller-switch assignment is critical, which is a challenging technical question. In this work, we propose a proactive switch assignment approach in case of controller failures using a genetic algorithm based heuristic that considers controller load distribution, reassignment cost and probability of failure. Moreover, we compare the performance of our scheme with random and greedy algorithms. Experiment results show that our proposed PREFCP framework has better performance in terms of probability of failure and controller load distributionde_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc004: Informatikde_CH
dc.titleProactive controller assignment schemes in SDN for fast recoveryde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1109/ICOIN48656.2020.9016544de_CH
dc.identifier.doi10.21256/zhaw-19701-
zhaw.conference.details2020 International Conference on Information Networking (ICOIN), Barcelona, Spain, 7-10 January 2020de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end141de_CH
zhaw.pages.start136de_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedings2020 International Conference on Information Networking (ICOIN)de_CH
zhaw.webfeedInformation Securityde_CH
zhaw.author.additionalNode_CH
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Guner, S., Gür, G., & Alagöz, F. (2020). Proactive controller assignment schemes in SDN for fast recovery [Conference paper]. 2020 International Conference on Information Networking (ICOIN), 136–141. https://doi.org/10.1109/ICOIN48656.2020.9016544
Guner, S., Gür, G. and Alagöz, F. (2020) ‘Proactive controller assignment schemes in SDN for fast recovery’, in 2020 International Conference on Information Networking (ICOIN). IEEE, pp. 136–141. Available at: https://doi.org/10.1109/ICOIN48656.2020.9016544.
S. Guner, G. Gür, and F. Alagöz, “Proactive controller assignment schemes in SDN for fast recovery,” in 2020 International Conference on Information Networking (ICOIN), 2020, pp. 136–141. doi: 10.1109/ICOIN48656.2020.9016544.
GUNER, Selcan, Gürkan GÜR und Fatih ALAGÖZ, 2020. Proactive controller assignment schemes in SDN for fast recovery. In: 2020 International Conference on Information Networking (ICOIN). Conference paper. IEEE. 2020. S. 136–141. ISBN 978-1-7281-4199-2
Guner, Selcan, Gürkan Gür, and Fatih Alagöz. 2020. “Proactive Controller Assignment Schemes in SDN for Fast Recovery.” Conference paper. In 2020 International Conference on Information Networking (ICOIN), 136–41. IEEE. https://doi.org/10.1109/ICOIN48656.2020.9016544.
Guner, Selcan, et al. “Proactive Controller Assignment Schemes in SDN for Fast Recovery.” 2020 International Conference on Information Networking (ICOIN), IEEE, 2020, pp. 136–41, https://doi.org/10.1109/ICOIN48656.2020.9016544.


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