Performance Analysis of SDN Controller

doi:10.23940/ijpe.22.08.p1.537544

Abstract

Abstract: Software Defined Networking (SDN) is aimed at rethinking network topologies and mitigating the limits that have emerged in traditional networks. It is a relatively new networking architecture that has become the most widely discussed networking technology in recent years and the latest development in the field of developing digital networks, which aims to break down the traditional connection between the control level and the infrastructure level surface. It allows you to fix a number of legacy mesh issues as well as add a whole host of new functionality to your existing networks. The goal of this separation is to make resources more manageable, secure, and controllable. As a result, many controllers such as Beacon, Floodlight, RYU, OpenDayLight (ODL), Open Network Operating System (ONOS), NOX, & POX have been developed. Selection of the finest-fit controller has altered to an application-contingent operation due to the large range of SDN applications and controllers. The data circulate allying the application level and the data level surface is managed by a network controller using Southbound Application Program Interfaces (APIs) and Northbound APIs. Before proceeding down to the switches and making logical judgements, the counteract determines the majority of the forwarding decisions. Advantages include worldwide control and observation of the entire network at once, useful for automating operations such as network operation, better server and network utilization, and so on. This paper discusses SDN, a new networking model in which the architectonics transitions from a completely distribution to a greater extent centralized form, and evaluates and contrasts the effects of various SDN controllers on SDN. The fundamental component of the control plane that oversees all data plane operations is the controller. As a result, its capabilities and performance (SDN controllers such as POX, Ryu, ONOS, ODL, etc.) are crucial in maintaining optimal performance. There are many controller suggestions available in the paper, and this study compares them to see which is the best overall it will be used by the SDN community as a reference for various SDN controllers. This paper presents performance analysis of various controllers and work done by different researchers in the last 9 years.

Key words: software defined networking, controller, data plane, application layer, control plane

Neelam Gupta, Sarvesh Tanwar, Sumit Badotra, and Sunny Behal. Performance Analysis of SDN Controller [J]. Int J Performability Eng, 2022, 18(8): 537-544.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References

1. Zhu L., Karim M.M., Sharif K., Li F., Du X., andGuizani M.SDN Controllers: Benchmarking & Performance Evaluation. arXiv preprint arXiv:1902.04491, 2019.
2. Badotra, S. and Panda, S.N.Evaluation and Comparison of Opendaylight and Open Networking Operating System in Software-defined Networking. Cluster Computing, vol. 23, no. 2, pp. 1281-1291, 2020.
3. Fares, N. and Askar, S.A Novel Semi-symmetric Encryption Algorithm for Internet Applications. Journal of University of Duhok, vol. 19, no. 1, pp. 1-9, 2016.
4. Askar S.K.Adaptive Load Balancing Scheme for Data Center Networks Using Software Defined Network. Science Journal of University of Zakho, vol. 4, no. 2, pp. 275-286, 2016.
5. Sulaiman, S.M. and Askar, S.K.Investigation of the Impact of DDoS Attack on Network Efficiency of the University of Zakho. Science Journal of University of Zakho, vol. 3, no. 2, pp. 275-280, 2015.
6. Cox J.H., Chung J., Donovan S., Ivey J., Clark R.J., Riley G. and Owen H.L.Advancing Software-Defined Networks: A Survey. IEEE Access, vol. 5, pp. 25487-25526, 2017.
7. Rao S.K.SDN and Its Use-cases-NV and NFV. Network, vol. 2, pp. H6, 2014.
8. Jarschel M., Zinner T., Hoßfeld T., Tran-Gia, P., and Kellerer, W. Interfaces, Attributes, and Use Cases: A Compass for SDN. IEEE Communications Magazine, vol. 52, no. 6, pp. 210-217, 2014.
9. Raza M.H., Sivakumar S.C., Nafarieh A., andRobertson B.A Comparison of Software Defined Network (SDN) Implementation Strategies. Procedia Computer Science, vol. 32, pp. 1050-1055, 2014.
10. Badotra, S. and Panda, S.N.Snort Based Early DDoS Detection System Using Opendaylight and Open Networking Operating System in Software Defined Networking. Cluster Computing, vol. 24, no. 1, pp. 501-513, 2021.
11. Shalimov A., Zuikov D., Zimarina D., Pashkov V., andSmeliansky R.Advanced Study of SDN/Openflow Controllers. In Proceedings of the 9th Central & Eastern European Software Engineering Conference in Russia, pp. 1-6, 2013.
12. Khattak Z.K., Awais M., andIqbal A. Performance Evaluation of Opendaylight SDN Controller. In2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS), IEEE, pp. 671-676, 2014.
13. Stancu A.L., Halunga S., Vulpe A., Suciu G., Fratu O., andPopovici, E.C. A Comparison between Several Software Defined Networking Controllers. In2015 12th International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS), IEEE, pp. 223-226, 2015.
14. Badotra, S. and Panda, S.N.Software-defined Networking: A Novel Approach to Networks. In Handbook of Computer Networks and Cyber Security, Springer, Cham, pp. 313-339, 2020.
15. Wang F., Wang H., Lei B., andMa, W. A Research on High-Performance SDN Controller. In2014 International Conference on Cloud Computing and Big Data, IEEE, pp. 168-174, 2014.
16. Arbettu R.K., Khondoker R., Bayarou K., andWeber, F. Security Analysis of Opendaylight, ONOS, Rosemary and Ryu SDN Controllers. In2016 17th International Telecommunications Network Strategy and Planning Symposium (Networks), IEEE, pp. 37-44, 2016.
17. Wang G., Li J., andChang X. Modeling and Performance Analysis of the Multiple Controllers’ Approach in Software Defined Networking. In2015 IEEE 23rd International Symposium on Quality of Service (IWQoS), IEEE, pp. 73-74, 2015.
18. Islam M., Islam N., andRefat M.Node to Node Performance Evaluation through RYU SDN Controller. Wireless Personal Communications, vol. 112, no. 1, pp. 555-570, 2020.
19. Gautam Y., Gautam B.P., andSato K. Experimental Security Analysis of SDN Network by Using Packet Sniffing and Spoofing Technique on POX and Ryu Controller. In2020 International Conference on Networking and Network Applications (NaNA), IEEE, pp. 394-399, 2020.
20. Tootoonchian A., Ghobadi M., andGanjali Y.Opentm: Traffic Matrix Estimator for Openflow Networks. In International Conference on Passive and Active Network Measurement, Springer, Berlin, Heidelberg, pp. 201-210, 2010.
21. Badotra, S. and Panda, S.N.A Review on Software-defined Networking Enabled IoT Cloud Computing. IIUM Engineering Journal, vol. 20, no. 2, pp. 105-126, 2019.
22. Bailey, J. and Stuart, S.Faucet: Deploying SDN in the Enterprise. Communications of the ACM, vol. 60, no. 1, pp. 45-49, 2016.
23. “NOX Controller”, http://www.Noxrepo.Org/Nox/About-Nox/, Accessed in June 2022.
24. Zhang X., Hou W.G., Han P.C., andGuo L.Design and Implementation of the Routing Function in the Nox Controller for Software-defined Networks. In Applied Mechanics and Materials, Trans Tech Publications Ltd, vol. 635, pp. 1540-1543, 2014.
25. “POX Controller”, http://www.Noxrepo.Org/Pox/About-Pox/, Accessed in June 2022.
26. Badotra, S. and Panda, S.N.Experimental Comparison and Evaluation of Various Openflow Software Defined Networking Controllers. International Journal of Applied Science and Engineering, vol. 17, no. 4, pp. 317-324, 2020.
27. Badotra, S. and Singh, J.Creating Firewall in Transport Layer and Application Layer Using Software Defined Networking. In Innovations in Computer Science and Engineering, Springer, Singapore, pp. 95-103, 2019.
28. Badotra S., Panda S.N., andDatta P.Detection and Prevention from DDoS Attack Using Software-defined Security. In Progress in Advanced Computing and Intelligent Engineering, Springer, Singapore, pp. 207-217, 2021.
29. Berde P., Gerola M., Hart J., Higuchi Y., Kobayashi M., Koide T., Lantz B., O'Connor, B., Radoslavov, P., Snow, W., and Parulkar, G. ONOS: Towards an Open, Distributed SDN OS. In Proceedings of the third workshop on Hot topics in software defined networking, pp. 1-6, 2014.
30. Badotra S., Nagpal D., Panda S.N., Tanwar S., andBajaj, S. IoT-enabled Healthcare Network with SDN. In2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), IEEE, pp. 38-42, 2020.
31. Rowshanrad S., Abdi V., andKeshtgari M.Performance Evaluation of SDN Controllers: Floodlight and Opendaylight. IIUM Engineering Journal, vol. 17, no. 2, pp. 47-57, 2016.
32. Badotra, S. and Singh, J.Open Daylight as a Controller for Software Defined Networking. International Journal of Advanced Research in Computer Science, vol. 8, no. 5, 2017.
33. Duque J.P., Beltrán D.D., andLeguizamón G.P.Opendaylight vs. Floodlight: Comparative Analysis of a Load Balancing Algorithm for Software Defined Networking. International Journal of Communication Networks and Information Security, vol. 10, no. 2, pp. 348-357, 2018.
34. Morales L.V., Murillo A.F., andRueda, S.J. Extending the Floodlight Controller. In2015 IEEE 14th International Symposium on Network Computing and Applications, IEEE, pp. 126-133, 2015.
35. Priyadarsini M., Bera P., andBampal, R. Performance Analysis of Software Defined Network Controller Architecture—A Simulation Based Survey. In2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), IEEE, pp. 1929-1935, 2017.
36. Asadollahi S., Goswami B., andSameer, M. Ryu Controller’s Scalability Experiment on Software Defined Networks. In2018 IEEE International Conference on Current Trends in Advanced Computing (ICCTAC), IEEE, pp. 1-5, 2018.
37. Badotra, S. and Panda, S.N.Experimental Comparison and Evaluation of Various Openflow Software Defined Networking Controllers. International Journal of Applied Science and Engineering, vol. 17, no. 4, pp. 317-324, 2020.
38. Zhu L., Karim M.M., Sharif K., Xu C., Li F., Du X., andGuizani M.SDN Controllers: A Comprehensive Analysis and Performance Evaluation Study. ACM Computing Surveys (CSUR), vol. 53, no. 6, pp. 1-40, 2020.

[1]	Harshvardhan Singh Chauhan, Himanshi Babbar, and Shalli Rani. D²PG: Deep Deterministic Policy Gradient-Based Vehicular Edge Caching Scheme for Digital Twin-Based Vehicular Networks [J]. Int J Performability Eng, 2023, 19(5): 350-358.
[2]	Snehashis Ghoshal, Sumit Banerjee, and Chandan Kumar Chanda. Modelling and Performance Evaluation of MPPT-based Solar PV System with Different Interfaces in MATLAB/Simulink Environment [J]. Int J Performability Eng, 2021, 17(12): 989-997.
[3]	Sumit Badotra, Sarvesh Tanwar, and Ajay Rana. DDoS Penetration Testing on OpenDayLight 3-Node in Software Defined Networking [J]. Int J Performability Eng, 2021, 17(10): 866-872.
[4]	Fei Lu, Qian Wang, Jingjie Teng, Yan Kang, and Bilian Liu. Analysis of the Features of Air Traffic Controllers' Eye Movements [J]. Int J Performability Eng, 2019, 15(12): 3262-3270.
[5]	Zhihui Zhuang, Jian Cen, and Shuai Liu. Control Method of Multi-Split Wireless Remote Monitoring System [J]. Int J Performability Eng, 2019, 15(12): 3279-3286.