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A policy based framework for quality of service management in software defined networks

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Abstract

Growth in multimedia traffic over the Internet increases congestion in the network architecture. Software-Defined Networking (SDN) is a novel paradigm that solves the congestion problem and allows the network to be dynamic, intelligent, and it centrally controls the network devices. SDN has many advantages in comparison to traditional networks, such as separation of forwarding and control plane from devices, global centralized control, management of network traffic. We design a policy-based framework to enhance the Quality of Service (QoS) of multimedia traffic flows in a potential SDN environment. We phrase a max-flow-min-cost routing problem to determine the routing paths and presented a heuristic method to route the traffic flows in the network in polynomial time. The framework monitors the QoS parameters of traffic flows and identifies policy violations due to link congestion in the network. The introduced approach dynamically implements policy rules to SDN switches upon detection of policy violations and reroutes the traffic flows. The results illustrate that the framework achieves a reduction in end-to-end delay, average jitter, and QoS violated flows by 24%, 37%, and 25%, respectively, as compared to the Delay Minimization method. Furthermore, the proposed approach has achieved better results when compared to SDN without policy-based framework and reduced end-to-end delay, average jitter, and QoS violated flows by 51%, 62%, and 28%, respectively.

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Notes

  1. End-user and host are used interchangeably.

  2. A path define the route between the switches.

  3. https://github.com/noxrepo/.

References

  1. Al Breiki, M. S., Zhou, S. & Luo, Y. R. (2020). Development of openflow native capabilities to optimize QoS. In: Seventh international conference on software defined systems (SDS), IEEE, pp. 67–74.

  2. Al-Jawad, A., Shah, P., Gemikonakli, O. & Trestian, R. (2018). Policy-based QoS management framework for software-defined networks. In: International Symposium on Networks, Computers and Communications (ISNCC), IEEE, pp. 1–6.

  3. Bari, M. F., Chowdhury, S. R., Ahmed, R., Boutaba, R. (2013). Policycop: An autonomic QoS policy enforcement framework for software defined networks. In: IEEE SDN for Future Networks and Services (SDN4FNS), pp. 1–7, DOI https://doi.org/10.1109/SDN4FNS.2013.6702548

  4. Botta, A., Dainotti, A., & Pescap´e, A. (2012). A tool for the generation of realistic network workload for emerging networking scenarios. Computer Networks, 56(15), 3531–3547.

    Article  Google Scholar 

  5. Colakovi´c, A., & Hadˇziali´c, M. (2018). Internet of things (iot): A review of enabling technologies, challenges, and open research issues. Computer Networks, 144, 17–39.

    Article  Google Scholar 

  6. Huang, H., Guo, S., Li, P., Ye, B., & Stojmenovic, I. (2015). Joint optimization of rule placement and traffic engineering for QoS provisioning in software defined network. IEEE Transactions on Computers, 64(12), 3488–3499.

    Article  Google Scholar 

  7. Hussain, M., & Shah, N. (2018). Automatic rule installation in case of policy change in software defined networks. Telecommunication Systems, 68(3), 461–477.

    Article  Google Scholar 

  8. Hussain, M., Shah, N., & Tahir, A. (2019). Graph-based policy change detection and implementation in SDN. Electronics, 8(10), 1136.

    Article  Google Scholar 

  9. Jeong, S., Lee, D., Hyun, J., Li, J., Hong, J. W. K. (2017). Application-aware traffic engineering in software-defined network. In: 19th Asia-Pacific network operations and management symposium, IEEE, pp. 315–318.

  10. Jiawei, W., Xiuquan, Q., & Guoshun, N. (2018). Dynamic and adaptive multi-path routing algorithm based on software-defined network. International Journal of Distributed Sensor Networks, 14(10), 1550147718805689.

    Article  Google Scholar 

  11. Kamboj, P., Pal, S. (2019). QoS in software defined IoT network using Blockchain based Smart Contract: Poster abstract. In: Proceedings of the 17th conference on embedded networked sensor systems, ACM, SenSys’19, pp. 430–431, DOI https://doi.org/10.1145/3356250.3361954, URL http://doi.acm.org/https://doi.org/10.1145/3356250.3361954

  12. Kamboj, P. & Pal, S. (2020). QoS in SDN for content delivery using blockchain based smart contract.

  13. Kamboj, P. & Raj, G. (2016). Analysis of role-based access control in software-defined networking. In: Proceedings of fifth international conference on soft computing for problem solving, Springer, pp. 687–697.

  14. Karakus, M., & Durresi, A. (2017). Quality of service (QoS) in software defined networking (SDN): A survey. Journal of Network and Computer Applications, 80, 200–218.

    Article  Google Scholar 

  15. Keshari, S. K., Kansal, V. & Kumar, S. (2020). A systematic review of quality of services (QoS) in software defined networking (SDN). Wireless Personal Communications, pp. 1–22.

  16. Khan, A. A., Hussain, M., Zafrullah, M., Zia, M. S. (2017). A convergence time optimization paradigm for OSPF based networks through SDN SPF protocol computer communications and networks (CCN)/Delay Tolerant Networks. In: Proceedings of the International Conference on Future Networks and Distributed Systems, pp. 1–6

  17. Knight, S., Nguyen, H. X., Falkner, N., Bowden, R., & Roughan, M. (2011). The internet topology zoo. IEEE Journal on Selected Areas in Communications, 29(9), 1765–1775.

    Article  Google Scholar 

  18. Lantz, B., Heller, B., McKeown, N. (2010). A network in a laptop: rapid prototyping for software-defined networks. In: Proceedings of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks, pp. 1–6.

  19. Lee, S. S., & Chan, K. Y. (2019). A traffic meter based on a multicolor marker for bandwidth guarantee and priority differentiation in SDN virtual networks. IEEE Transactions on Network and Service Management, 16(3), 1046–1058.

    Article  Google Scholar 

  20. Lei, K., Liang, Y., & Li, W. (2020). Congestion control in SDN-based networks via multi-task deep reinforcement learning. IEEE Network, 34(4), 28–34.

    Article  Google Scholar 

  21. Liao, L. & Leung, V. C. (2016). LLDP based link latency monitoring in software defined networks. In: 12th International Conference on Network and Service Management, IEEE, pp. 330–335.

  22. Lin, S. C., Akyildiz, I. F., Wang, P. & Luo, M. (2016). QoS-aware adaptive routing in multi-layer hierarchical software defined networks: A reinforcement learning approach. In: IEEE International Conference on Services Computing (SCC), IEEE, pp. 25–33.

  23. Llopis, J., Pieczerak, J. & Janaszka, T. (2016). Minimizing latency of critical traffic through SDN. Architecture and Storage (NAS) pp. 420–423.

  24. Machado, C. C., Wickboldt, J. A., Granville, L. Z. & Schaeffer-Filho, A. (2015). Policy authoring for software-defined networking management. In: IFIP/IEEE International Symposium on Integrated Network Management, pp. 216–224, DOI https://doi.org/10.1109/INM.2015.7140295

  25. McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., & Turner, J. (2008). Openflow: Enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 38(2), 69–74.

    Article  Google Scholar 

  26. Mendiola, A., Astorga, J., Jacob, E., & Stamos, K. (2019). Enhancing network resources utilization and resiliency in multi-domain bandwidth on demand service provisioning using sdn. Telecommunication Systems, 71(3), 505–515.

    Article  Google Scholar 

  27. Mohammadi, R., Javidan, R., Keshtgari, M., & Akbari, R. (2018). A novel multicast traffic engineering technique in SDN using TLBO algorithm. Telecommunication Systems, 68(3), 583–592.

    Article  Google Scholar 

  28. Noce, L., Gwaza, L., Mangas-Sanjuan, V., & Garcia-Arieta, A. (2020). Comparison of free software platforms for the calculation of the 90% confidence interval of f2 similarity factor by bootstrap analysis. European Journal of Pharmaceutical Sciences, 146, 105259.

    Article  Google Scholar 

  29. Otoshi, T., Ohsita, Y., Murata, M., Takahashi, Y., Ishibashi, K., & Shiomoto, K. (2015). Traffic prediction for dynamic traffic engineering. Computer Networks, 85, 36–50.

    Article  Google Scholar 

  30. Pokhrel, S. R., Sood, K., Yu, S. & Nosouhi, M. R. (2019). Policy-based bigdata security and QoS framework for SDN/IoT: An analytic approach. In: IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE, pp. 73–78.

  31. Priya, B. & Malhotra, J. (2020). QAAs: QoS provisioned artificial intelligence framework for AP selection in next-generation wireless networks. Telecommunication Systems, pp. 1–17.

  32. Scheid, E. J., Machado, C. C., dos Santos, R. L., Schaeffer-Filho, A. E. & Granville, L. Z. (2016). Policy-based dynamic service chaining in Network Functions Virtualization. In: IEEE Symposium on Computers and Communication (ISCC), IEEE, pp. 340–345.

  33. Sharma, P., Banerjee, S., Tandel, S., Aguiar, R., Amorim, R. & Pinheiro, D. (2013) Enhancing network management frameworks with SDN-like control. In: IFIP/IEEE International Symposium on Integrated Network Management (IM 2013), IEEE, pp. 688–691.

  34. Singh, S., & Jha, R. K. (2017). A survey on software defined networking: Architecture for next generation network. Journal of Network and Systems Management, 25(2), 321–374.

    Article  Google Scholar 

  35. Sivanathan, A., Sherratt, D., Gharakheili, H. H., Radford, A., Wijenayake, C., Vishwanath, A. & Sivaraman, V. (2017). Characterizing and classifying IoT traffic in smart cities and campuses. In: IEEE conference on computer communications workshops (INFOCOM WKSHPS), IEEE, pp. 559–564.

  36. Sul´ak, V., Helebrandt, P. & Kotuliak, I. (2016) Performance analysis of openflow forwarders based on routing granularity in openflow 1.0 and 1.3. In: 19th conference of open innovations association (FRUCT), IEEE, pp 236–241

  37. Tajiki, M. M., Akbari, B. & Mokari, N. (2016). QRTP: QoS-aware resource reallocation based on traffic prediction in software defined cloud networks. In: 8th International Symposium on Telecommunications (IST), IEEE, pp. 527–532.

  38. Thi, M. T., Huynh, T., Hasegawa, M., & Hwang, W. J. (2017). A rate allocation framework for multi-class services in software-defined networks. Journal of Network and Systems Management, 25(1), 1–20.

    Article  Google Scholar 

  39. Tripathy, B. K., Sethy, A. G., Bera, P., Rahman, M. A. (2016). A novel secure and efficient policy management framework for software defined network. In: IEEE 40th annual computer software and applications conference, IEEE, 2: 423–430.

  40. Van Adrichem, N. L., Doerr, C. & Kuipers FA (2014) Opennetmon: Network monitoring in openflow software-defined networks. In: IEEE Network Operations and Management Symposium (NOMS), IEEE, pp. 1–8.

  41. Verma, S., Kawamoto, Y., Fadlullah, Z. M., Nishiyama, H., & Kato, N. (2017). A survey on network methodologies for real-time analytics of massive IoT data and open research issues. IEEE Communications Surveys and Tutorials, 19(3), 1457–1477.

    Article  Google Scholar 

  42. Yang, Z., & Yeung, K. L. (2020). Flow monitoring scheme design in SDN. Computer Networks, 167, 107007.

    Article  Google Scholar 

  43. Yen, J. Y. (1971). Finding the K shortest loopless paths in a network. Management Science, 17(11), 712–716.

    Article  Google Scholar 

  44. Zhang, Y., Cui, L., Wang, W., & Zhang, Y. (2018). A survey on software defined networking with multiple controllers. Journal of Network and Computer Applications, 103, 101–118.

    Article  Google Scholar 

  45. Zhong, H., Wu, F., Xu, Y., & Cui, J. (2020). QoS-aware multicast for scalable video streaming in software-defined networks. IEEE Transactions on Multimedia, 23, 982–994.

    Article  Google Scholar 

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  1. Department of Computer Science and Engineering, Indian Institute of Technology, Ropar, Punjab, 140001, India

    Priyanka Kamboj & Sujata Pal

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  1. Priyanka Kamboj
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Kamboj, P., Pal, S. A policy based framework for quality of service management in software defined networks. Telecommun Syst 78, 331–349 (2021). https://doi.org/10.1007/s11235-021-00816-8

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