## 3 Intelligent Cloud-Edge Model  
Following the design methodology of \"description-synthesis-verification-optimization\", the intelligent cloud-edge architecture was built at first, and the corresponding using-view and deployment view were explained to ensure the implementation of the system. Based on this, the model in CPN is described, which focuses on the hierarchical interface and highlights cloud-edge collaboration and intelligent services. It supports the executable design specifications using CPN Tools. The model simulation verification and its instance activity combined with typical services are presented in the following two sections. Edge computing is a distributed IT architecture [41], and the platform services are mainly based on EIS and cloud component services. Cloud-edge intelligent service has the ability to bridge and coordinate the two (cloud, edge) to guide the partition and execution of tasks, so that time-sensitive data can be preprocessed by the local or nearest EIS, and time-insensitive data can be sent to the cloud for big data intelligence analysis and global long-term storage. It also manages and optimizes the network from the overall view, and has a certain openness to flexibly deploy new applications and services. Intelligent cloud-edge architecture is mainly composed of three parts: 1 edge layer: As PaaS in cloud-edge cooperation, it is composed of many edge domain environments such as virtualization, data storage, edge device management, and data processing. For each domain, EIS local resources are defined by software, and SDN is enabled to solve the heterogeneity and scalability of edge devices, so as to schedule edge computing network resources more effectively; 2 cloud center: It is responsible for managing, scheduling, integrating, and optimizing various resources distributed on the network by cloud computing technology. The dynamic network system based on SDN enables real-time programming and large-scale management for a value-added cloud computing network, to further enhance its scalability and dynamics and provide new IT service; 3 Hub/Gateway: based on the idea of step-by-step control and global/local control, it ensures the overall consistency to realize the reasonable access to computing tasks and the optimal allocation of computing resources, quickly responding to computing requests and feedback, computing results in real-time, and building a service-oriented network open capability interface to meet the different requirements of services. Intelligent cloud-edge service involves the following elements: infrastructure, Hub/Gateway, SDN/MQTT, data center, AIFS (AI framework service), service management, orchestration, security, etc. Its architecture is shown in Figure 1:  
Using view describes the activities that need to be coordinated between different elements involved in edge computing to guide the implementation of reliable and complex applications, which give the key in each stage of system design, implementation, deployment, operation, and development. The function module and implementation module among using-view provide the basis for the subsequent stage of detailed function design and implementation. The executable module tasks realize the business logic, which has two ways: service orchestration and simple business invocation. User roles involve a variety of user types in the whole life cycle of edge applications, which have corresponding access permissions to ensure the security and reliability of the system. The core elements emphasized in the edge computing scenario include time, space, trigger conditions, results, and constraints.