Nowadays, the Internet of Things (IoT) allows monitoring and automation in diverse contexts, such as hospitals, homes, or even smart cities, just to name a few examples. IoT data processing may occur, at the edge of the network or in the cloud, but frequently the processing must be divided between the two layers. Aiming to guarantee that the IoT systems works efficiently, it is essential to evaluate the system even in initial design stages. However, evaluating hybrid systems composed by multiple layers is not an easy task as a myriad of parameters are involved in the process. Thus, this paper presents two SPN models (one base and extended one) that can represent an abstract distributed system composed of IoT, edge and cloud layers. The models are highly configurable to be used in diverse simulation scenarios. Besides a sensitivity analysis evidenced the most impacting components in the studied architecture and made it possible to optimize the base SPN model. Finally a case study explores multiple metrics of interest concurrently and works as a guide of the model utilization. Ultimately, the proposed approach can assist system designers to avoid unnecessary investment in original equipment.

如今，仅举几个例子，物联网（IoT）允许在多种环境中进行监视和自动化，例如医院，家庭甚至智能城市。物联网数据处理可能发生在网络边缘或云中，但是经常必须在两层之间划分处理。为了确保物联网系统高效运行，即使在初始设计阶段，也必须对系统进行评估。但是，评估由多层组成的混合系统并非易事，因为该过程涉及许多参数。因此，本文提出了两个SPN模型（一个基础模型和一个扩展模型），它们可以表示由物联网，边缘和云层组成的抽象分布式系统。这些模型是高度可配置的，可用于各种模拟场景。此外，敏感性分析还证明了所研究体系结构中影响最大的组件，并使优化基础SPN模型成为可能。最后，一个案例研究同时探索了多个关注指标，并作为模型利用的指南。最终，所提出的方法可以帮助系统设计人员避免对原始设备进行不必要的投资。