Performance Evaluation of IoT-Fog-Cloud System for Data Storage, Analysis and Visualisations Using Retrial Queues Approach

The significance of the Internet of Things (IoT) is growing in the contemporary information age due to its quick acquisition of diverse data. Both the IoT and cloud computing systems generate vast quantities of data. Fog computing, a technique that employs leveraging, is utilised to process substantial volumes of data. Subsequently, the processed data are transmitted to a cloud storage system using fog nodes. The installation of an IoT-Fog-Cloud system leads to enhancements in both latency and throughput. The primary responsibility of the fog nodes inside the IoT-Fog-Cloud system is to perform localised collection, monitoring, and storage of IoT workload and data. This function serves to enhance efficiency and availability within the system. The discussion of compliance with Quality of Service (QoS) standards constitutes the pertinent subjects and challenges that necessitate attention in fog computing. The present article employs an M/M/1 retrial queueing model and analytical methodology to assess and examine the performance of the IoT-Fog-Cloud system, thereby offering a solution to the problem at hand. The mathematical methods employed in this study enable the determination of the service arrival required to meet the QoS criteria in IoT layer. It also provides mathematical expressions for various performance metrics of the system, including the arrival rate, service rate, retrial rate, and the average waiting time for requests in the system.