OPTIMAL TRANSMISSION SUPPORT FOR REAL TIME APPLICATIONS USING FOGEDGE COMPUTING

Abstract

Internet of Things (IoT) services have gained unprecedented recognition in the past few years and become critical to support real-time high data rate applications. This will introduce new challenges to supporting application in terms of latency, bandwidth, and sustained connectivity, etc. Due to these constraints, it is challenging for the existing centralized cloudcomputing model to supports real-time applications. To cater these challenges, it is necessary that the data is processed near the end devices. Therefore, in this research, we present a new Fog computing based 4-tier architecture for the efficient data processing generated by the IoT devices specifically targeting real-time applications. Under this architecture, the desired data coming from the cloud is cached at fog nodes and the data generated by the IoT nodes is processed near the edge devices. We erected a predictive model for fog nodes selection focus on minimizing the latency and hit-miss ratio by the use of machine learning. Our architecture achieved better performance in terms of throughput, delay and hit-miss ratios.