A Study on Advanced Networking using Intelligent Systems Applications

With the rapid advances being made in the implementation of real-time networks such as IoT (Internet of Things) and vehicles, there is steady progress in the digitization of everyday tasks. This adoption has led to various advantages such as an increase in efficiency, automation, connectivity, and cost savings. However, IoT faces significant issues due to its low-power nature and underdeveloped security systems. As such, researchers have proposed to adopt SDN (Software-Defined Network) practices to handle the security aspects that threaten IoT infrastructure. The implementation of SDN allowed for IoT devices to function better due to aspects such as low-performance requirements, and better monitoring capabilities. This paper discusses the various advances and implementations of intelligent systems in SDN-based IoT architecture, in the domains of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). Furthermore, this paper presents the analysis and comparison of various applications for SDN-based IoT system using intelligent systems based on their accuracy, precision, f1-score, and recall score.