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Automatic Software Defined Network (SDN) Performance Management Using TOPSIS Decision-Making Algorithm

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Abstract

Software Defined Network (SDN) is an architecture and its main idea is data and control traffic separating which has amended the network flexibility, programmability, and manageability. The SDN-based network contains a physical or conceptual centeralized controller with a global view of the network. The centeralized controller is responsible for decision-making in the network. One of the most effective tasks in network performance is flow routing. In this paper, the network performance is measured by delay, jitter, packet loss ratio (PLR), and network utilization. The main idea of this paper is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which is used for decision-making in the controller for the proper path allocation to the flows of the network from the performance perspectives. In this paper, we implement the proposed algorithm in the Floodlight controller and compare it with the commonly used path allocation shortest path (SP), the greedy algorithm for path allocation and weighted Equal Cost Multi-Path (ECMP) to show the amelioration of the proposed algorithm. The simulation results show that the proposed algorithm improves the network performance metrics simultaneously.

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References

  1. Index, V.N., Vni, C., Vni, C., Cisco visual networking index: forecast and trends, 2017–2022, (2019)

  2. Cisco, T., Internet, A.: Cisco annual internet report, (2020)

  3. Pan, J., Paul, S., Jain, R.: A survey of the research on future internet architectures. Commun. Mag. IEEE. 49(7), 26–36 (2011)

    Article  Google Scholar 

  4. Hakiri, A., Gokhale, A., Berthou, P., Schmidt, D.C., Gayraud, T.: Software-defined networking: challenges and research opportunities for future internet. Comput. Netw. 75, 453–471 (2014)

    Article  Google Scholar 

  5. Masoudi, R., Ghaffari, A.: Software defined networks: a survey. J. Netw. Comput. Appl. 67, 1–25 (2016)

    Article  Google Scholar 

  6. Bera, S., Misra, S., Vasilakos, A.V.: Software-defined networking for Internet of things: a survey. IEEE Internet Things J. 4662, 1–1 (2017)

    Google Scholar 

  7. Maksymyuk, T., Jo, M.: An IoT based monitoring framework for software defined 5G Mobile networks. ACM. 7–10 (2017)

  8. Son, J., Buyya, R.: A taxonomy of software-defined networking (SDN)-enabled cloud computing. ACM Comput. Surv. 51(3), 1–36 (2018)

    Article  Google Scholar 

  9. Hoffmann, M., et al.: SDN and NFV as enabler for the distributed network cloud. Mob. Networks Appl. 1–88 (2017)

  10. Jain, R., Paul, S.: Network virtualization and software defined networking for cloud computing: a survey. IEEE Commun. Mag. 51(11), 24–31 (2013)

    Article  Google Scholar 

  11. Shirmarz, A., Ghaffari, A.: An autonomic software defined network (SDN) architecture with performance improvement considering. J. Inf. Syst. Telecommun. 8(2), 1–9 (2020)

    Google Scholar 

  12. Ieee, F., et al.: Software-defined networking : a comprehensive survey. Proc. IEEE. 103(1), 14–76 (2015)

    Article  Google Scholar 

  13. Karakus, M., Durresi, A.: A survey: control plane scalability issues and approaches in software-defined networking (SDN). Comput. Netw. 112, 279–293 (2017)

    Article  Google Scholar 

  14. Bannour, F., Souihi, S., Mellouk, A.: Distributed SDN control: survey, taxonomy, and challenges. IEEE Commun. Surv. Tutorials. 20(1), 333–354 (2018)

    Article  Google Scholar 

  15. Shirmarz, A., Ghaffari, A.: Performance issues and solutions in SDN-based data center: a survey. J. Supercomput (2020)

  16. Shirmarz, A., Ghaffari, A.: Taxonomy of controller placement problem (CPP) optimization in Software Defined Network (SDN): a survey. J. Ambient Intell. Humaniz. Comput., no. 0123456789, (2021)

  17. Hedrick, C.:, RFC 1058 (RIP1), (1988)

  18. Malkin G: RFC 2453 (rip 2), (1998)

  19. Moy J: RFC 2328 (OSPF 2), (1998)

  20. D. Oran and D. Oran, “RFC 1142 (IS-IS Protocol),” 1990

    Google Scholar 

  21. Y. Rekhter, T. Li, and S. Hares, “RFC 4271 (BGP-4),” 2006

    Google Scholar 

  22. D. Meyer, “RFC 4274 (BGP-4 Protocol Analysis),” 2006

    Google Scholar 

  23. Banihabib, M.E., Hashemi-Madani, F.S., Forghani, A.: Comparison of compensatory and non-compensatory multi-criteria decision making models in water resources strategic management. Water Resour. Manag. 31(12), 3745–3759 (2017)

    Article  Google Scholar 

  24. Krohling, R.A., Pacheco, A.G.C.: A-TOPSIS - an approach based on TOPSIS for ranking evolutionary algorithms. Procedia Comput. Sci. 55, 308–317 (2015)

    Article  Google Scholar 

  25. Li, Z.: Solving the multi-constrained path selection problem by using depth first search 1. In: 2nd Int’l Conf. on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

    Google Scholar 

  26. Wang, Z., Crowcroft, J., Criterion, A.S.: Quality-of-service routing for supporting multimedia applications. 1228 IEEE J. Sel. AREAS Commun. 14(7), 1228–1234 (1996)

    Article  Google Scholar 

  27. Analysis, T.: Lagrange relaxation based method for the QoS routing problem. IEEE INFOCOM. 2, 859–868 (2001)

    Google Scholar 

  28. Chen, S., Song, M., Sahni, S.: Two techniques for fast computation of constrained shortest paths. IEEE/ACMTRANSACTIONS Netw. 16(1), 105–115 (2008)

    Google Scholar 

  29. Hilmi, A.M.T., Egilmez, E., Civanlar, S.: An optimization framework for QoS-enabled adaptive video streaming over OpenFlow networks. IEEE Trans. ONMULTIMEDIA. 15(3), 710–715 (2013)

    Article  Google Scholar 

  30. M. Beshley, M. Seliuchenko, O. Panchenko, and A. Polishuk, “Adaptive flow routing model in SDN, in IEEE CADSM, pp. 21–25 (2017)

  31. Mehboob, U., Qadir, J., Ali, S., Vasilakos, A.: Genetic Algorithms in Wireless Networking: Techniques, Applications, and Issues. Soft Comput (2017)

  32. Zhoulaian, E., Mirabedini, S.J., Sadeghzadeh, M.: Multi-objective routing by using non -dominated sorting genetic algorithm in computer networks. Int. J. Comput. Sci. Netw. Solut. 2(7), 29–41 (2014)

    Google Scholar 

  33. Karakus, M., Durresi, A.: Quality of service (QoS) in software defined networking (SDN): a survey. J. Netw. Comput. Appl. 80, 200–218 (2017)

    Article  Google Scholar 

  34. Guck, J.W., Van Bemten, A., Reisslein, M., Kellerer, W.: Unicast QoS routing algorithms for SDN: a comprehensive survey and performance evaluation. IEEE Commun. Surv. Tutorials. 20(1), 388–418 (2018)

    Article  Google Scholar 

  35. S. Oh, J. Lee, K. Lee, and I. Shin: RT-SDN: adaptive routing and priority ordering for software-defined real-time networking, Springer Int. Publ. AG, part Springer Nat., (2018)

  36. Zhao, Z., Wu, B., Xiao, J., Hu, Z.: Joint optimization of flow entry aggregation and routing selection in software defined wireless access networks. Springer Int. Publ. AG. 834–839 (2018)

  37. Feng, H., Member, S., Llorca, J., Tulino, A.M., Molisch, A.F.: Optimal dynamic cloud network control. IEEE/ACM Trans. Netw. pp. 1–14, (2018)

    Google Scholar 

  38. Ali, T.E., Morad, A.H., Abdala, M.A.: Load balance in data center SDN networks. Int. J. Electr. Comput. Eng. 8(5), 3084–3091 (2018)

    Google Scholar 

  39. Bagci, K.T., Member, S., Tekalp, A.M.: Dynamic resource allocation by batch-optimization for value-added video services over SDN. IEEE Trans. Multimed. 20(11), 3084–3096 (2018)

    Article  Google Scholar 

  40. R. Lin: A bat algorithm for SDN network scheduling, EURASIP J. Wirel. Commun. Netw., no. 1687–1499, pp. 1–9, (2018)

  41. A. Shirmarz and A. Ghaffari: An adaptive greedy flow routing algorithm for performance improvement in a software-defined network, Int. Numer. Model. Electron. networks, Devices, Fields-Wiley online Libr., no. March, pp. 1–21, (2019)

  42. Wang, X., Zhang, Q., Ren, J., Xu, S., Wang, S., Yu, S.: Toward efficient parallel routing optimization for large-scale SDN networks using GPGPU. J. Netw. Comput. Appl. 113, 1–13 (2018)

    Article  Google Scholar 

  43. Amiri, E., Alizadeh, E., Rezvani, M.H.: Controller selection in software defined networks using best-worst multi-criteria decision-making. Bull. Electr. Eng. Informatics. 9(4), 1506–1517 (2020)

    Article  Google Scholar 

  44. F. F. Zobary: Applying TOPSIS method for software defined networking (SDN) controllers comparison and selection, in Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2018, vol. 210, no. September, pp. 132–141

  45. Ali, J., Roh, B.-H.: An effective hierarchical control plane for software-defined networks leveraging TOPSIS for end-to-end QoS class-mapping. IEEE Access. 8, 1–1 (2020)

    Article  Google Scholar 

  46. J. L. Ye, C. Chen, and Y. Huang Chu: A weighted ECMP load balancing scheme for data centers using P4 switches. Proc. 2018 IEEE 7th Int. Conf. Cloud Networking, CloudNet 2018, pp. 57–60, (2018)

  47. F. Rhamdani, N. A. Suwastika, and M. A. Nugroho, “Equal-cost multipath routing in data center network based on software defined network,” 2018 6th Int. Conf. Inf. Commun. Technol. ICoICT 2018, pp. 222–226, (2018)

  48. Lee, G.: Data center networking standards. Cloud Netw. 87–102 (2014)

  49. J. Wu and M. Savoie: Network virtualization, in Optics InfoBase Conference Papers, pp. 121–137 (2009)

  50. A. Shirmarz: TOPSIS Algorithm, https://github.com/alirezashirmarz/TOPSISPathAllocation.

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Authors and Affiliations

  1. Department of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran

    Alireza Shirmarz

  2. Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran

    Ali Ghaffari

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  1. Alireza Shirmarz
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  2. Ali Ghaffari
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Correspondence to Alireza Shirmarz.

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Shirmarz, A., Ghaffari, A. Automatic Software Defined Network (SDN) Performance Management Using TOPSIS Decision-Making Algorithm. J Grid Computing 19, 16 (2021). https://doi.org/10.1007/s10723-021-09557-z

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