IoT systems modeling and performance evaluation

Abstract

The continuous increase of IoT applications leads to a vast amount of data that needs to be transmitted, stored, and processed. Many IoT applications rely on the Cloud infrastructure to handle these specific application demands. However, the integration of IoT and Cloud poses challenges such as network delays, throughput, energy consumption, reliability, etc. Therefore, a new computing concept is required to support emerging IoT applications. These new concepts include fog computing, edge computing, mobile edge computing, mobile cloud computing, and cloudlets. They use various approaches to distribute resources, processes, and services among IoT system architecture layers. The challenge is to decide which offloading system is the best for a specific use case that emphasizes the IoT system modeling issue. In this paper, a model for the formal description of IoT systems is presented. In addition, an analytical evaluation method was proposed to design these systems using the corresponding architecture, technologies, protocols, and integration model to optimize performance. The proposed approach facilitates and simplifies the selection of the corresponding model for the system architecture. This approach enables an efficient method for performance optimization based on offloading processes (load balancing). Also, this paper provides some insights into specific emerging issues and ideas to be addressed by future research.