Improvement of Software-Defined Network Performance Using Queueing Theory: A Survey

Majlesi Journal of Telecommunication Devices

مقاله 5، دوره 10، شماره 1، خرداد 2021، صفحه 33-43   

نوع مقاله: Articles

شناسه دیجیتال (DOI): 10.52547/mjtd.10.1.33

نویسندگان

Ava Tahmasebi¹؛ Ahmad Salahi^{* 2}؛ Mohammad Ali Pourmina³

¹Faculty of Mechanical, Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Tehranran, Iran.

²Communications Technology Institute, Iran Telecommunication Research Center, Tehran, Iran

³Faculty of Mechanical, Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

چکیده

Software-Defined Networking (SDN) is a growing network technology that has brought significant benefits to a wide range of disciplines, from science to technology to various fields. This structure can be used in network-based environments, data centers and various research sites. OpenFlow is one of the most widely used protocols for interaction between a controller and a switch in a Software-Defined Networking. Understanding the performance and limitations of the network defined by open source software, including bottlenecks and security vulnerabilities due to the centralized network structure, are important prerequisites for the efficient deployment of these systems. These points of view led researchers to examine various related mathematical models to address these issues. Queueing theory provides the most important and accurate model for evaluating the performance of the SDN networks affected by these restrictions, which has attracted the attention of researchers recently. Regarding to extensive mathematical modeling, this theory has also been used to improve network efficiency. Researchers have used this theory to investigate operational power and improve time consumption and control of data planes due to the nature of classification and storage of packets in SDN buffers. These methods overcome controller performance bottlenecks and increase SDN control capacity, especially for large distributed networks. In this paper, we examine the queueing models for different applications in different layers of SDN, in which researchers use these methods to monitor network loads, evaluate and predict performance changes due to diversity in network traffic. We introduce and review a collection of articles that explore, different applications of Queueing theory in SDN networks. In addition, in order to increase the efficiency of this research, detailed comparisons are performed in terms of structure, mathematical models and the final simulation results.

کلیدواژه‌ها

Queueing Theory؛ OpenFlow؛ Performance Enhancement

مراجع

1. Hakiri A., Aniruddha G., Pascal B., Douglas C, Gayraud T, Software-Defined Networking: Challenges and research opportunities for future internet. Computer Networks, 2014. 75: p. 453-471.

2. Pan, J., S. Paul, and R. Jain, A survey of the research on future internet architectures. IEEE Communications Magazine, 2011. 49(7): p. 26-36.

3. Rowshanrad S., Yonggang W, Chuan H, A survey on SDN, the future of networking. Journal of Advanced Computer Science & Technology, 2014. 3(2): p. 232-248.

4. Lara A., A. Kolasani, Ramamurthy B.,, Network innovation using OpenFlow: A survey. IEEE communications surveys & tutorials, 2013. 16(1): p. 493-512.

5. McKeown, N., Anderson T., Balakrishnan H., OpenFlow: enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 2008. 38(2): p. 69-74.

6. Feamster, N., J. Rexford, and E. Zegura, The road to SDN: an intellectual history of programmable networks. ACM SIGCOMM Computer Communication Review, 2014. 44(2): p. 87-98.

7. Nunes, B., Mendonca M., Nguyen X., Obraczka K., Turlett T., A survey of Software-Defined Networking: Past, present, and future of programmable networks. IEEE Communications Surveys & Tutorials, 2014. 16(3): p. 1617-1634.

8. Bozakov, Z. and A. Rizk. Taming SDN controllers in heterogeneous hardware environments. 2013 Second European Workshop on Software-Defined Networks. 2013.

9. Xiong, B., Yang K., Zhaoc J., Keqin L., Performance evaluation of OpenFlow-based Software-Defined Networks based on queueing model. Computer Networks, 2016. 102: p. 172-185.

10. Zuo, Q., M. Chen, and P. Jiang, Delay evaluation of OpenFlowcontrol plane by queueing model. J. Huazhong Univ. Sci. Technol.(Nat. Sci. Ed.), 2013. 8(1): p. 44-49.

11. Alsmadi, I., Alzam I., Akour M., A systematic literature review on Software-Defined Networking, in Information Fusion for Cyber-Security Analytics. 2017, Springer. p. 333-369.

12. Xia W., Wen H., Heng C., A survey on Software-Defined Networking. IEEE Communications Surveys & Tutorials, 2014. 17(1): p. 27-51.

13. Yan Q., Yu F., Gong Q., Li J., Software-Defined Networking (SDN) and distributed denial of service (DDoS) attacks in cloud computing environments: A survey, some research issues, and challenges. IEEE Communications Surveys & Tutorials, 2015. 18(1): p. 602-622.

14. Gude, N., NOX: towards an operating system for networks. ACM SIGCOMM Computer Communication Review, 2008. 38(3): p. 105-110.

15. Hassas Yeganeh, S. and Y. Ganjali. Kandoo: a framework for efficient and scalable offloading of control applications. Proceedings of the first workshop on hot topics in Software-Defined Networks. 2012. ACM.

16. Tootoonchian A., Gorbunov S., Ganjali Y., On Controller Performance in Software-Defined Networks. The 2nd {USENIX} Workshop on Hot Topics in Management of Internet, Cloud, and Enterprise Networks and Services. 2012. p. 10-16.

17. Goto, Y., Masuyama H., Bryan N., Winston K. Seah G., Yutaka Takahashi. Queueing analysis of Software-Defined Networking with realistic OpenFlow–based switch model. IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS). 2016.

18. Hu J, Lin C, Li X, Huang J. Scalability of control planes for Software-Defined Networks: Modeling and evaluation. In2014 IEEE 22nd International Symposium of Quality of Service (IWQoS), p. 147-152. 2014.

19. Farhady, H., H. Lee, and A. Nakao, Software-Defined Networking: A survey. Computer Networks, 2015. 81: p. 79-95.

20. Hu, F., Q. Hao, and K. Bao, A survey on Software-Defined Networking and OpenFlow: From concept to implementation. IEEE Communications Surveys & Tutorials, 2014. 16(4): p. 2181-2206.

21. Alencar F, Santos M, Santana M, Fernandes S. How Software Aging affects SDN: A view on the controllers. 2014 Global Information Infrastructure and Networking Symposium (GIIS). p. 1-6, 2014.

22. Zhu L, Karim M, Li F, Du X, Guizani M. SDN Controllers: Benchmarking & Performance Evaluation. arXiv preprint arXiv:1902.04491. 2019 Feb 12.

23. Shalimov A, Zuikov D, Zimarina D, Pashkov V, Smeliansky R. Advanced study of SDN/OpenFlow controllers. in Proceedings of the 9th central & eastern european software engineering conference in russia. P. 1-6, 2013.

24. Osgouei AG, Koohanestani AK, Saidi H, Fanian A. Analytical performance model of virtualized SDNs using network calculus. In 2015 23rd Iranian Conference on Electrical Engineering. p. 770-774, 2015.

25. Mahmood K, Chilwan A, Østerbø O, Jarschel M. Modelling of OpenFlow-based Software-Defined Networks: the multiple node case. IET Networks, 4(5): p. 278-284. 2015.

26. Y. Fu, J.B., J. Wu, Z. Chen, K. Wang, and M. Luo, “A dormant multicontroller model for Software-Defined Networking,” China Communications, 2014. 11(no. 3,): p. 44-45.

27. Kobayashi M, Seetharaman S, Parulkar G, Appenzeller G, Maturing of OpenFlow and Software-Defined Networking through deployments. Computer Networks, 2014. 61: p. 151-175.

28. S. H. Yeganeh, A.T., and Y. Ganjali, On Scalability of Software-Defined Networking. IEEE

Communications Magazine, 2013. 51(no. 2,): p. 136-141.

29. Sezer S, Scott-Hayward S, Chouhan PK, Fraser B, Are we ready for SDN? Implementation challenges for Software-Defined Networks. IEEE Communications Magazine, 2013. 51(7): p. 36-43.

30. Jiang G, Fu B, Chen M, Zhang LX., The survey and quantitative analysis of SDN controller. Frontiers of Computer Science and Technology, 2014. 8(6): p. 653-664.

31. Singh D, Ng B, Lai YC, Lin YD, Seah WK. Modelling Software-Defined Networking: switch design with finite buffer and priority queueing. 2017 IEEE 42nd Conference on Local Computer Networks (LCN). 2017.

32. Choi BD, Choi DI, Lee Y, Sung DK, Priority queueing system with fixed-length packet-train arrivals. IEE Proceedings-Communications, 1998. 145(5): p. 331-336.

33. Jain, R. and S. Routhier, Packet trains--measurements and a new model for computer network traffic. IEEE journal on selected areas in Communications, 1986. 4(6): p. 986-995.

34. Okamura, H., T. Dohi, and K.S. Trivedi, Markovian arrival process parameter estimation with group data. IEEE/ACM Transactions on Networking (TON), 2009. 17(4): p. 1326-1339.

35. Wang Z, Zhao S, Fan Z, Wan X. Performance Modeling and Analysis of Control Plane for SDN Based on Queueing Theory. Wireless Personal Communications, 2017. 97(1): p. 591-601.

36. Jarschel M, Zinner T, Hoßfeld T, Tran-Gia P, Kellerer W, Interfaces, attributes, and use cases: A compass for SDN. IEEE Communications Magazine, 2014. 52(6): p. 210-217.

37. Yonghong F, Jun B, Jianping W, Ze C, Ke W, Min L. A dormant multi-controller model for Software-Defined Networking. China Communications. 2014, 11(3): p. 45-55.

38. Chamola V, Tham CK, Gurunarayanan S, Ansari N. An optimal delay aware task assignment scheme for wireless SDN networked edge cloudlets. Future Generation Computer Systems. 2020. 102, p. 862-875.

39. Li G, Wang X, Zhang Z. SDN-based load balancing scheme for multi-controller deployment. IEEE Access. 2019, 7, p. 312-322.

40. Hu J, Lin C, Zhang P. Performance evaluation and optimization of hierarchical routing in SDN control plane. Chinese Journal of Electronics. 2018, 27(2), p. 342-350.

41. Ansell J, Seah WK, Ng B, Marshall S. Making Queueing theory more palatable to SDN/OpenFlow-based network practitioners. InNOMS 2016-2016 IEEE/IFIP Network Operations and Management Symposium. 2016, p. 1119-1124.

42. Sood K, Yu S, Xiang Y. Performance analysis of Software-Defined Networking switch using $ M/Geo/1$ model. IEEE Communications Letters. 2016, 20(12). p. 22-25.

43. Tuysuz, M.F., Z.K. Ankarali, and D. Gözüpek, A survey on energy efficiency in Software-Defined Networks. Computer Networks, 2017. 113: p. 188-204.

44. Newport, C. and W. Zhou. The (surprising) computational power of the SDN data plane. 2015 IEEE Conference on Computer Communications (INFOCOM). 2015.

45. Xie K, Huang X, Hao S, Ma M., Distributed power saving for large-scale software-defined data center networks. IEEE Access, 2018. 6: p. 5897-5909.

46. Shen G, Li Q, Ai S, Jiang Y, Xu M, Jia X. How powerful switches should be deployed: A precise estimation based on queueing theory. IEEE Conference on Computer Communications, 2019, p. 811-819.

47. Hammadi, A. and L. Mhamdi, A survey on architectures and energy efficiency in data center networks. Computer Communications, 2014. 40, p. 1-21.

48. Qiu T, Zhang Y, Qiao D, Zhang X, Wymore ML, Sangaiah AK. A robust time synchronization scheme for industrial internet of things. IEEE Transactions on Industrial Informatics, 2017. 14(8): p. 3570-3580.

49. Huang X, Li F, Cao K, Cong P, Wei T, Hu S, Queueing Theoretic Approach for Performance-Aware Modeling of Sustainable SDN Control Planes. 2018.

50. Kaup, F., S. Melnikowitsch, and D. Hausheer. Measuring and modeling the power consumption of OpenFlow switches. 10th International Conference on Network and Service Management (CNSM) and Workshop. 2014.

51. Faraci, G. and G. Schembra, An analytical model to design and manage a green SDN/NFV CPE node. IEEE Transactions on Network and Service Management, 2015. 12(3): p. 435-450.

52. Ansell J, Seah WK, Ng B, Marshall S. Making Queueing theory more palatable to SDN/OpenFlow-based network practitioners. IEEE/IFIP Network Operations and Management Symposium. 2016.

53. Wei L, Fung C. FlowRanger: A request prioritizing algorithm for controller DoS attacks in Software-Defined Networks. In2015 IEEE International Conference on Communications (ICC) 2015, p. 5254-5259.

54. Zhang P, Wang H, Hu C, Lin C. On denial of service attacks in Software-Defined Networks. IEEE Network. 2016, 30(6), p.28-33.

55. Yan Q, Gong Q, Yu FR. Effective Software-Defined Networking controller scheduling method to mitigate DDoS attacks. Electronics Letters. 2017, 53(7), p. 469-471.

56. Eom, T., Hong, J.B., An, S., Park, J.S. and Kim, D.S., 2019, August. Security and Performance Modeling and Optimization for Software-Defined Networking. In 2019 18th IEEE International Conference on Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), 2019, p. 610-617.

57. Wang T, Guo Z, Chen H, Liu W. BWManager: Mitigating denial of service attacks in Software-Defined Networks through bandwidth prediction. IEEE Transactions on Network and Service Management. 2018, 15(4), p. 1235-1248.