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Evolutionary Algorithms for Design of Virtual Private Networks

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Intelligent Distributed Computing XII (IDC 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 798))

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Abstract

Virtual Private Networks (VPNs) is a most known technology to create the protected communication links via the Internet. The paper offers a new approach to solve the problem of VPN network design based on evolutionary algorithms (genetic and differential evolution). The joint accounting of network bandwidth, reliability and cost, which indices are calculated on the basis of the offered queuing theory models, is the feature of the considered problem. The experimental assessment of the suggested decisions shows that the evolutionary algorithms can improve the VPN network efficiency up to 40% in comparison with the standard variants of its creation. The comparative assessment of the suggested evolutionary algorithms shows higher convergence of the differential evolution algorithm.

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Acknowledgment

This work was supported by grants of RFBR (projects No. 16-29-09482, 18-07-01369 and 18-07-01488), by the budget (the project No. AAAA-A16-116033110102-5), and by Government of Russian Federation (Grant 08-08).

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Authors and Affiliations

  1. St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, 14-th Liniya, 39, St. Petersburg, 199178, Russia

    Igor Kotenko & Igor Saenko

  2. ITMO University, 49, Kronverkskiy prospekt, St. Petersburg, Russia

    Igor Kotenko & Igor Saenko

Authors
  1. Igor Kotenko
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  2. Igor Saenko
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Corresponding author

Correspondence to Igor Kotenko .

Editor information

Editors and Affiliations

  1. Basque Center for Applied Mathematics (BCAM), TECNALIA, University of the Basque Country (UPV/EHU), Derio, Bizkaia, Spain

    Javier Del Ser

  2. TECNALIA, Derio, Bizkaia, Spain

    Eneko Osaba

  3. University of the Basque Country (UPV/EHU), Bilbao, Bizkaia, Spain

    Miren Nekane Bilbao

  4. Computer Science Department, University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Javier J. Sanchez-Medina

  5. OpenIoT Reesarch Unit, FBK CREATE-NET, Trento, Italy

    Massimo Vecchio

  6. Department of Design Engineering and Mathematics, Middlesex University, London, UK

    Xin-She Yang

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Kotenko, I., Saenko, I. (2018). Evolutionary Algorithms for Design of Virtual Private Networks. In: Del Ser, J., Osaba, E., Bilbao, M., Sanchez-Medina, J., Vecchio, M., Yang, XS. (eds) Intelligent Distributed Computing XII. IDC 2018. Studies in Computational Intelligence, vol 798. Springer, Cham. https://doi.org/10.1007/978-3-319-99626-4_25

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  • DOI: https://doi.org/10.1007/978-3-319-99626-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99625-7

  • Online ISBN: 978-3-319-99626-4

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