IFCSim: An IoT-Fog-Cloud Simulator for Analyzing Performance of Topologies
Sanjaya Kumar Panda, Aditi Bhagat · 2024
Nowadays, many real-life applications, namely healthcare, transportation, fire detection, and many more, rely on data collected from Internet of Things (IoT) devices. The collected data is too extensive and requires enormous processing for analysis. As cloud device provides massive computation and storage, IoT devices transmit data for analysis without considering the proximity, resulting in latency and network usage issues. Therefore, fog computing brings computation and storage closer to the IoT devices to resolve these issues. However, it still depends on cloud device for massive computation and storage. On the other hand, a simulation platform is essential to evaluate IoT, fog, and cloud environments effectively and show resource management techniques’ impact on latency and network usage. Recently, the iFogSim simulator was introduced to show the impact of resource management techniques. However, this tool can be extended by adding various components, namely sensors, actuators and fog devices, to solve more real-life problems. This paper introduced various components within the iFogSim tool and named the IoT-fog-cloud simulator (IFCSim) tool. IFCSim is more user-friendly for developing, simulating, and reviewing the results of different topologies. It can simulate more real-life applications, from factories to intelligent buildings, exploring fog computing to its fullest potential. We show how fog computing can make an efficient fire detection systems with reduced latency and network usage using IFCSim. We study how spreading the data from the edge devices can make detection faster and more reliable. Our simulator tool lets one create different network topologies for performing simulations.