## 4 Fine-Grained Service Orchestration for EIS
The subsequently transitional color set represents the attributes of their respective services, so as to realize the fine-grained EIS orchestration mode, i.e., service/business \(\rightarrow\) DBaaS (database as a Service), CaaS (container as a Service) \(\rightarrow\) FaaS, such as CRUD, URL call, Lambda \(\rightarrow\) task process, such as start, stop, update, and message passing. The EIS service orchestration model is both a hierarchical (orchestration service in the cloud-strategy controller on the edge-strategy executor in the node) architecture and a process (data stream and business flow) pattern. The former realizes the hierarchical interface through substitution transitions and fusion-set places, while the latter is described by Kanban information flow, as shown in Figure 2:  
Figure 2: EIS Model with Kanban Information Flow. EIS with fine-grained service orchestration consists of a series of business processes. It's assumed that there are three work nodes (excluding input and output interfaces) in this model, which also provides the Kanban information flow in the opposite direction corresponding to each node to provide feedback on the service status. One of the working nodes is shown in Figure 2, whose structure and behavior are consistent, only relevant parameters are different, such as processing times, resources per work node, and Kanban in between work nodes. The performance and resources of service orchestration are optimized by configuring parameters. The rationality of CPN model behavior can be verified by SSA (state space analysis). DSE is realized through parameter configuration. Performance is evaluated by the monitor of CPN Tools 4.0 in timed color set tokens. Among them, although the color set processing times significantly affect the efficiency of service orchestration. However, the color set resources per work node have little impact, because the conflict between nodes is not fully considered. Kanban's mode tuning can reasonably arrange service orchestration. The EIS state behavior in the CPN model represented by the color set is verified by CPN Tools, and then its process instance is about to run on WISE-PaaS to evaluate the data stream engine performance and communication proxy QoS (quality of service). WISE-PaaS is built into EIS. Among them, WISE-Agent provides abundant interaction-friendly and intelligent interfaces. Its application is connected to the WISE-PaaS/RMM cloud server, which is not only used to communicate and exchange information between edge devices and cloud platforms but also has the function of a small database and lightweight computing and analysis. The plug-in with a special protocol is configured to meet the requirements of flexible and extended services. The instance of service orchestration with information flow on WISE-PaaS is shown in Figure 3:  
Figure 3: Instance of Service Orchestration Running on WISE-PaaS. A service consists of several businesses according to the verification model. The service instance is assumed to include five segments of businesses, whose performance (service delay) and QoS (communication queue) are measured on WISE-PaaS for EIS, service orchestration, and non-orchestration. The test platform supports the data stream design engine (Node-RED), message passing (MQTT), function and service management, and output visualization. Service orchestration is based on business loads and node resources, and tasks are dispatched via MQTT topics. The tests show that service orchestration achieves the best results. Only EIS results come in second place because of reduced communication overhead on a single EIS node. The result of non-orchestration warns that the result may deteriorate due to mismatches between nodes and tasks if node resources are not properly utilized for service orchestration. This also basically shows that service delay can be significantly reduced by EIS and its service orchestration compared with centralized cloud computing.