Asian Journal of Computer Science and Technology (AJCST)
AI Based SDN Technology Integration with their Challenges and OpportunitiesAuthor : Shabana, Sallauddin Mohmmad, Kotha Shankar and Yerrolla Chanti
Volume 8 No.3 Special Issue:June 2019 pp 165-169
Software Defined Networking (SDN) is a new architecture that provides innovative set of tools for facing the network challenges. Using of software-based control plane and data plane, SDN is easily managing the adapted tradition network functions. In the real time scenario SDN is managing resources of different types of networks such as mobile networks, IoT and internet communication and data centers. To manage these all inter discipline functionalities from various networks SDN need of AI integration. Artificial intelligence (AI) is an extensive scientific revolution which enables SDN/NVF to solve problems by emulating complex network processes such as routing, dynamic configurations, bandwidth availability and domain name processing and transmission in communication etc. This paper presents a comprehensive review of the application of AI techniques for improving performance of SDN and NVF. The ML based AI techniques learn the data plane functionalities such as MAC, implementation of routing algorithms, firewall systems and load balance. AI-based ML techniques and also learn topology abstraction and NOS in the control plane in the network then monitoring the devices, reduce the non-linearity in network communication, create quality of transmission and finally deploy the autonomic controlling on systems. ML-based AI techniques can able to create SDN in autonomic and self-managing networks which allows SDN to learn about network subsequently take automatic decisions. This article describes on how to interpret the AI techniques and wide deployment of autonomic learns nature in the SDN also describes the opportunities and challenges in AI based SDN.
SDN, NVF, Artificial Intelligence, Machine Learning
 D. Kreutz, F. M. Ramos, and P. Verissimo, “Towards secure and dependable software-defined networks,” in Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking – HotSDN ’13. New York, New York, USA: ACM Press, 2013, pp. 55.
 M. Casado, T. Garfinkel, A. Akella, M. J. Freedman, D. Boneh, N. McKeown, and S. Shenker, “SANE: a protection architecture for enterprise networks,” 15th USENIX Security Symposium, pp. 137151, 2006.
 F. Hu, Q. Hao, and K. Bao, “A survey on software-defined network (SDN) and open flow: From concept to implementation,” IEEE Commun. Surveys & Tutorials, Vol. 16, No. 4, pp. 2181–2206, Fourth Quarter 2014.
 C. V. N. I. Forecast, “Cisco visual networking index: Global mobile data traffic forecast update 2016-2021,” Cisco Public Information, February, 2017.
 F. Tram`er, F. Zhang, F. E. Epfl, A. Juels, M. K. Reiter, and T. Ristenpart, “Stealing Machine Learning Models via Prediction APIs,” in Proceedings of the 25th USENIX Security Symposium, 2016.
 Indira Paudel, Jeevan Pokhrel, Bachar Wehbiy, Ana Cavalli and Badii Jouaber. “Estimation of video QoE from MAC parameters in wireless network: A Random Neural Network approach”. International Symposium on Communications and Information Technologies (ISCIT), 2014.
 Yaqian Kang, Huifang Chen, Lei Y.-J. Kim, K. He, M. Thottan and J. G.Deshpande, “Virtualized and self-configurable utility communications enabled by software-defined networks”. In Proceedings of 5th IEEE International Conference on Smart Grid Communications (SmartGridComm), 2014.
 Sallauddin Mohmmad, Shabana and Ranganath Kanakam, “Provisioning Elasticity on IoT’s Data In Shared-Nothing Nodes”, International Journal of Pure and Applied Mathematics, Vol. 117, No. 7, pp. 165-173, Oct. 2017.
 Sallauddin Mohmmad, Dr. M. Sheshikala and Shabana, “Software Defined Security (SDSec): Reliable centralized security system to decentralized applications in SDN and their challenges” Jour. of Adv. Research in Dynamical & Control Systems, Vol. 10, 10-Special Issue, pp. 147-152, 2018
 A´ ngel Leonardo Valdivieso Caraguay, Alberto Benito Peral, Lorena Isabel Barona L´opez, and Luis Javier Garc´ıa Villalba. “SDN: evolution and opportunities in the development IoT applications”. International Journal of Distributed Sensor Networks, 2014.
 Zhijing Qin, Luca Iannario, Carlo Giannelli, Paolo Bellavista, Grit Denker, and Nalini Venkatasubramanian, “Mina: A reflective middleware for managing dynamic multi network environments”. In 2014 IEEE Network Operations and Management Symposium (NOMS), pp. 1– 4, 2014.