Software Defined Network Partitioning with Graph Partitioning Algorithms

  • Shivaleela ArlimattiEmail author
  • Walid Elbrieki
  • Suhaidi Hassan
  • Adib Habbal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1073)


Software Defined Networks is an emerging paradigm in Internet communication world that increases the flexibility of today’s networks by decoupling control plane and data plane of the network devices. The fundamental aim is to centralize the control and reduce the complexity of the networks. The communication medium between control and data plane is through OpenFlow protocol, an open standard network protocol designed to manage the network traffic by software programs. To increase the scalability and flexibility of controllers the OpenFlow controllers are distributed based on location and network types. However, most critical issue is minimizing the communication cost between the controller domains. In this paper, two graph partitioning algorithms Fiduccia-Matthyses algorithm and Kernighan-Lin algorithm are used to minimize the communication cost between distributed OpenFlow controller domains. The implementation of the algorithms is under Matlab simulation environment. The methodology used for the proposed algorithms is to interchange the elements from one domain to other domain to calculate the gain. The simulated results show that Kernighan-Lin algorithm minimizes more communication cost rather than the Fiduccia-Matthyses algorithm.


Fiduccia-Matthyses Kernighan-Lin Communication cost OpenFlow 


  1. 1.
    Al-Najjar, A., Layeghy, S., Portmann, M.: Pushing SDN to the end-host, network load balancing using OpenFlow. In: IEEE International Conference on Pervasive Computing and Communication Workshops (2016)Google Scholar
  2. 2.
    Hassas Yeganeh, S., Ganjali, Y.: Kandoo: a framework for efficient and scalable offloading of control applications. In: Proceedings of the First Workshop on Hot Topics in Software Defined Networks, pp. 19–24, August 2012Google Scholar
  3. 3.
    Fazea, Y.: Numerical simulation of helical structure mode-division multiplexing with nonconcentric ring vortices. Opt. Commun. 437, 303–311 (2019)CrossRefGoogle Scholar
  4. 4.
    Fazea, Y.: Mode division multiplexing and dense WDM-PON for Fiber-to-the-Home. Optik 183, 994–998 (2019)CrossRefGoogle Scholar
  5. 5.
    Fazea, Y., Alobaedy, M.M., Ibraheem, Z.T.: Performance of a direct-detection spot mode division multiplexing in multimode fiber. J. Opt. Commun. 40, 161–166 (2019)CrossRefGoogle Scholar
  6. 6.
    Fazea, Y., Amphawan, A., Qtaish, O.: Mode division multiplexing of helical-phased spot mode and donut mode in multimode fiber interconnects. In: 2017 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), pp. 200–205 (2017)Google Scholar
  7. 7.
    Fazea, Y., Mezhuyev, V.: Selective mode excitation techniques for mode-division multiplexing: a critical review. Opt. Fiber Technol. 45, 280–288 (2018)CrossRefGoogle Scholar
  8. 8.
    Fazea, Y., Sajat, M.S., Ahmad, A., Alobaedy, M.M.: Channel optimization in mode division multiplexing using neural networks. In: 2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA), pp. 173–175 (2018)Google Scholar
  9. 9.
    Hassan, S., Fazea, Y., Habbal, A., Ibrahim, H.: Twisted Laguerre-Gaussian mode division multiplexing to support blockchain applications. In: Region 10 Conference, TENCON 2017–2017. IEEE, pp. 2421–2425 (2017)Google Scholar
  10. 10.
    Bari, M.F., Roy, A.R., Chowdhury, S.R., Zhang, Q., Zhani, M.F., Ahmed, R., Boutaba, R.: Dynamic controller provisioning in software defined networks. In: CNSM, pp. 18–25 (2013)Google Scholar
  11. 11.
    Casado, M., Freedman, M.J., Pettit, J., Luo, J., Gude, N., McKeown, N., Shenker, S.: Rethinking enterprise network control. IEEE/ACM Trans. Netw. (ToN) 17(4), 270–1283 (2009)CrossRefGoogle Scholar
  12. 12.
    Foster, N., Guha, A., Reitblatt, M., Story, A., Freedman, M.J., Katta, N.P., Monsanto, C., Reich, J., Rexford, J., Schlesinger, C., Walker, D.: Languages for software-defined networks. IEEE Commun. Mag. 51(2), 128–134 (2013)CrossRefGoogle Scholar
  13. 13.
    Casado, M., Freedman, M.J., Pettit, J., Luo, J., McKeown, N., Shenker, S.: Ethane: taking control of the enterprise. In: ACM SIGCOMM Computer Communication Review, vol. 37, no. 4, pp. 1–12. ACM, August 2007Google Scholar
  14. 14.
    Das, S., Parulkar, G., McKeown, N.: Unifying packet and circuit switched networks with OpenFlow (2009)Google Scholar
  15. 15.
    Feldmann, A.E., Foschini, L.: Balanced partitions of trees and applications. Algorithmica 71(2), 354–376 (2015)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Liyanage, M., Gurtov, A., Ylianttila, M. (eds.): Software Defined Mobile Networks (SDMN): Beyond LTE Network Architecture. Wiley, Hoboken (2015)Google Scholar
  17. 17.
    Cui, L., Yu, F.R., Yan, Q.: When big data meets software-defined networking: SDN for big data and big data for SDN. IEEE Netw. 30(1), 58–65 (2016)CrossRefGoogle Scholar
  18. 18.
    Dabkiewicz, S., van der Pol, R., van Malenstein, G.: OpenFlow network virtualization with FlowVisor. research project 2, University of Amsterdam (2012)Google Scholar
  19. 19.
    Heller, B., Sherwood, R., McKeown, N.: The controller placement problem. In: Proceedings of the First Workshop on Hot Topics in Software Defined Networks, pp. 7–12. ACM, August 2012Google Scholar
  20. 20.
    Casado, M., Garfinkel, T., Akella, A., Freedman, M.J., Boneh, D., McKeown, N., Shenker, S.: SANE: a protection architecture for enterprise networks. In: USENIX Security Symposium 2006, vol. 49, p. 50, August, 2006Google Scholar
  21. 21.
    Han, B., Gopalakrishnan, V., Ji, L., Lee, S.: Network function virtualization: challenges and opportunities for innovations. IEEE Commun. Mag. 53(2), 90–97 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Shivaleela Arlimatti
    • 1
    Email author
  • Walid Elbrieki
    • 2
  • Suhaidi Hassan
    • 2
  • Adib Habbal
    • 2
    • 3
  1. 1.Shaikh College of Engineering and TechnologyBelgaumIndia
  2. 2.InterNetWorks Research Laboratory, School of ComputingUniversiti Utara MalaysiaChanglunMalaysia
  3. 3.Computer Engineering Department, Faculty of EngineeringKarabuk UniversityKarabukTurkey

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