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.

物联网应用的不断增长导致大量数据需要传输、存储和处理。许多物联网应用程序依赖云基础设施来处理这些特定的应用程序需求。然而，物联网和云的融合带来了网络延迟、吞吐量、能耗、可靠性等挑战。因此，需要一种新的计算概念来支持新兴的物联网应用。这些新概念包括雾计算、边缘计算、移动边缘计算、移动云计算和cloudlet。他们使用各种方法在物联网系统架构层之间分配资源、流程和服务。面临的挑战是确定哪种卸载系统最适合强调物联网系统建模问题的特定用例。本文提出了物联网系统形式化描述的模型。此外，还提出了一种分析评估方法，使用相应的架构、技术、协议和集成模型来设计这些系统，以优化性能。所提出的方法促进并简化了系统架构相应模型的选择。这种方法提供了一种基于卸载进程（负载平衡）的有效性能优化方法。此外，本文还对未来研究要解决的具体新问题和想法提供了一些见解。