ABSTRACT
This chapter deals with intelligent IoT (Internet of Things) architecture comprised of a hybrid wired and wireless based network architecture with a smart gateway capable of link selection and switching in the hybrid network. Sensor network based IoT architectures are challenged with limited bandwidth and power. For such constrained IoT networks, the chapter presents an intelligent gateway based hybridized (integrated wired and wireless) IoT network. Such a gateway is capable of incoming traffic classification and intelligent link selection based upon the user traffic requirements. The gateway utilizes machine learning algorithms for user task (traffic) classification and decision making on link selection. The chapter presents two machine learning algorithms: kNN (k-Nearest Neighbors) and SVM (Support Vector Machine) for this purpose. A comparative analysis has been presented between the two machine learning techniques using MATLAB R2021b. Further, transmission reliability analysis has been given for the hybrid IoT model. Finally, the chapter is concluded followed by references.
