Skip to main content
Log in

Performance evaluation of Software-Defined Network (SDN) controllers using Dijkstra’s algorithm

  • Original Paper
  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The advancement of technology, specifically the development of information technology (IT) has had a great influence on everyone life. Due to the rapid development of technology, the traditional network architectures are no longer adequate for the nowadays communication, education, businesses, carriers, and end-users, etc. This indeed is a serious issue, as every organization, enterprise, and educational institute, etc. wants to keep itself on top and to facilitate their customers as much as possible by providing high quality services with minimum delay, etc. In order to tackle this problem, a new emerging network architecture known as software defined networking (SDN) may be employed, as it is more interactive, more flexible, controllable, scalable, and programmable. A network system has two main planes known as control and data planes. The SDN architecture/design separates the control and data planes, legalizes network information and state, and keeps the network infrastructure out of the applications. In contrast, a network may reach a point where the computer or network resources restrict the data flow governed by the bandwidth. In SDN architecture, the controller is the most significant and central component, and large SDN networks might have numerous controllers or controller domains that share network administration. Due to the obvious importance of controllers, different studies have been conducted to compare, test, and assess their performance. This study examines the implementation of Dijkstra’s algorithm using two of the most important SDN open-source controllers (POX and RYU), which permits packet acquisition and transmission between end devices via the network’s shortest and/or lowest load pathways. Performance of the two utilized controllers is measured in terms of various quality of service (QoS) metrics such as throughput, packet delivery ratio, jitter, and packet loss on a specific network architecture under a variety of workloads. Further, we developed a customized network topology using the Mininet which is an emulator tool for SDN. In addition, we also measured the performance of the utilized controllers in terms of various QoS metrics, using the Mininet tool. The experimental results show that the proposed system attained promising results in terms of all QoS metrics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Akbar, A., Ibrar, M., Jan, M. A., Bashir, A. K., & Wang, L. (2020). SDN-enabled adaptive and reliable communication in IoT-fog environment using machine learning and multiobjective optimization. IEEE Internet of Things Journal, 8(5), 3057–3065

    Article  Google Scholar 

  2. Zhu, L., Karim, M. M., Sharif, K., Xu, C., Li, F., Du, X., & Guizani, M. (2020). “SDN controllers: A comprehensive analysis and performance evaluation study,“. ACM Computing Surveys (CSUR), 53, 1–40

    Article  Google Scholar 

  3. Trois, C., Del Fabro, M. D., de Bona, L. C., & Martinello, M. (2016). “A survey on SDN programming languages: Toward a taxonomy,“. IEEE Communications Surveys & Tutorials, 18, 2687–2712

    Article  Google Scholar 

  4. Sinha, Y., & Haribabu, K. (2017). A survey: Hybrid sdn,. Journal of Network and Computer Applications, 100, 35–55

    Article  Google Scholar 

  5. Benzekki, K., Fergougui, A. E., & Elbelrhiti Elalaoui, A. (2016). “Software-defined networking (SDN): a survey,“. Security and Communication Networks, 9, 5803–5833

    Article  Google Scholar 

  6. Bannour, F., Souihi, S., & Mellouk, A. (2017). Distributed SDN control: Survey, taxonomy, and challenges,. IEEE Communications Surveys & Tutorials, 20, 333–354

    Article  Google Scholar 

  7. Karakus, M., & Durresi, A. (2017). “A survey: Control plane scalability issues and approaches in software-defined networking (SDN),“ Computer Networks, vol. 112, pp. 279–293,

  8. Han, T., Jan, S. R. U., Tan, Z., Usman, M., Jan, M. A., Khan, R., & Xu, Y. (2020). A comprehensive survey of security threats and their mitigation techniques for next-generation SDN controllers. Concurrency and Computation: Practice and Experience, 32(16), e5300

    Article  Google Scholar 

  9. Campbell, A. T., Katzela, I., Miki, K., & Vicente, J. (1999). “Open signaling for ATM, internet and mobile networks (OPENSIG’98),“ ACM SIGCOMM Computer Communication Review, vol. 29, pp. 97–108,

  10. Nunes, B. A. A., Mendonca, M., Nguyen, X. N., Obraczka, K., & Turletti, T. (2014). A survey of software-defined networking: Past, present, and future of programmable networks,. IEEE Communications surveys & tutorials, 16, 1617–1634

    Article  Google Scholar 

  11. Al-Tam, F., & Correia, N. (2019). Fractional switch migration in multi-controller software-defined networking,. Computer Networks, 157, 1–10

    Article  Google Scholar 

  12. Niculescu, D. (2004). “Survey of active network research,“ Retrieved on Jul, vol. 22, p. 1999

  13. Van der Merwe, J. E., Rooney, S., Leslie, L., & Crosby, S. (1998). The Tempest-a practical framework for network programmability,. IEEE network, 12, 20–28

    Article  Google Scholar 

  14. Gude, N., Koponen, T., Pettit, J., Pfaff, B., Casado, M., McKeown, N., et al. (2008). “NOX: towards an operating system for networks,“ ACM SIGCOMM Computer Communication Review, vol. 38, pp. 105–110,

  15. Tran, H. M., Tumar, I., & Schönwälder, J. (2009). “NETCONF interoperability testing,“ in IFIP International Conference on Autonomous Infrastructure, Management and Security, pp. 83–94,

  16. Azodolmolky, S. (2013). Software defined networking with OpenFlow. Packt Publishing Ltd

  17. Ranjan, P., Pande, P., Oswal, R., Qurani, Z., & Bedi, R. (2014). “A survey of past present and future of software defined networking,“International Journal of Avance Research in Computer Science and Management Studies, vol. 2,

  18. Hande, Y. S., & Akkalakshmi, M. (2015). “A Study on Software Defined Networking,“International Journal of Innovative Research in Computer and Communication Engineering, vol. 3,

  19. Sherwood, R., & Yap, K. (2011). “Cbench controller benchmarker,“ Last accessed, Nov,

  20. Goransson, P., Black, C., & Culver, T. (2016). Software defined networks: a comprehensive approach. Morgan Kaufmann

  21. Abdullah, M. Z., Al-Awad, N. A., & Hussein, F. W. (2018). “Performance Evaluation and Comparison of Software Defined Networks Controllers,“. International Journal of Scientific Engineering and Science, 2, 45–50

    Google Scholar 

  22. Wang, C., Zhang, G., Xu, H., & Chen, H. (2016). “An ACO-based link load- balancing algorithm in SDN,“ in 7th International Conference on Cloud Computing and Big Data (CCBD), pp. 214–218,

  23. Kaur, K., Kaur, S., & Gupta, V. (2016). “Least time based weighted load balancing using software defined networking,“ in International Conference on Advances in Computing and Data Sciences, pp. 309–314,

  24. Duque, J. P., Beltrán, D. D., & Leguizamón, G. P. (2018). “OpenDaylight vs. Floodlight: Comparative Analysis of a Load Balancing Algorithm for Software Defined Networking,“. International Journal of Communication Networks and Information Security, 10, 348–357

    Google Scholar 

  25. Joshi, & Gupta, D. (2019). “A Comparative Study on Load Balancing Algorithms in Software Defined Networking,“ in International Conference on Ubiquitous Communications and Network Computing, pp. 142–150,

  26. Sajid, A. S., Niloy, S. F. N., Hossain, K., & Rahman, T. (2018). “Comprehensive evaluation of shortest path algorithms and highest bottleneck bandwidth algorithm in software defined networks,“. BRAC University

  27. Jarraya, Y., Madi, T., & Debbabi, M. (2014). “A survey and a layered taxonomy of software-defined networking,“. IEEE communications surveys & tutorials, 16, 1955–1980

    Article  Google Scholar 

  28. Jain, S. (2018). “Performance Evaluation of Multi Hop Routing Using Software Defined Network,“ in Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), pp. 1–5, 2018

  29. Satre, S. M., Patil, N. S., Khot, S. V., & Saroj, A. A. (2020). “Network Performance Evaluation in Software-Defined Networking,“ presented at the International Conference on Information and Communication Technology for Intelligent Systems,

  30. Ryu, S., “Framework Community,“Ryu Controller.”,“ ed

  31. Ryu, S., “Framework (sd),“ Récupéré sur https://osrg.github.io/ryu

  32. Sufiev, H., & Haddad, Y. (2016). “A dynamic load balancing architecture for SDN,“ in IEEE International Conference on the Science of Electrical Engineering (ICSEE), pp. 1–3, 2016

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mengji Chen.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Chen, M. Performance evaluation of Software-Defined Network (SDN) controllers using Dijkstra’s algorithm. Wireless Netw 28, 3787–3800 (2022). https://doi.org/10.1007/s11276-022-03044-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-022-03044-3

Keywords

Navigation