AI Based SDN Technology Integration with their Challenges and Opportunities
Author : Shabana, Sallauddin Mohmmad, Kotha Shankar and Yerrolla ChantiVolume 8 No.3 Special Issue:June 2019 pp 165-169
Abstract
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.
Keywords
SDN, NVF, Artificial Intelligence, Machine Learning
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