Teacher Learning Based IOT Wireless Network Optimization Models And Techniques

Authors: Sidra Khan, Sujeet Gautam

Abstract: Wireless Sensor Networks (WSNs) and Internet of Things (IoT) systems play a crucial role in modern smart applications such as smart cities, healthcare, industrial automation, and precision agriculture. Despite rapid advances in communication, cloud, and edge computing technologies, energy efficiency remains a fundamental challenge due to the limited power resources of sensor nodes. This work has proposed a IOT network optimization model that cluster nodes into cluster and further transfer packets from sensing ITO device to the base station. Clustering of model was done by teacher learning model as without prior knowledge algorithm cluster nodes in dynamic situations of WSN. Use of linear routing algorithm energy utilization was highly dropped. Experiment was done on various virtual environment of nodes and region. Result shows that Teacher Learning based Optimize Cluster Center (TLOCC) algorithm work has improves the life span of the ITO network.