It is assumed that a dedicated management service is used to manage the deterministic communication service assurance. It may also coordinate with other related management services to provide service assurance for deterministic communications when it is needed. Based on the Service based management architecture, Deterministic Communication Service Assurance (DCSA) MnS producer could reside on 3GPP cross domain, RAN domain or CN domain as shown in the following Figure. DCSA MnS producer in 3GPP cross domain coordinates with DCSA MnS producers in RAN domain and CN domain.
To investigate how to support deterministic communication service assurance from management aspects, the management framework of DCSA MnS producer is studied. The following Figure shows the functional framework of DCSA MnS producer, including processes of data collection, service requirement modeling, network preparation, service and network analysis, optimization and verification. The main functionalities of each process is described as follows:
Data collection: Collects network performance and alarm data, signaling-plane and user-plane measurement information and abnormal events, and collects service experience related network performance information. The collected data is used for as input for other processes.
Service requirement modeling: The three-layer model of service experience, service quality, network performance is used for service requirement modeling. The service experience and service quality targets are analysed to derive the network capability requirements.
Network preparation: Based on deterministic communication service requirements, the DCSA MnS producer prepares network capabilities to ensure the SLA, and provides the corresponding network deployment solution, e.g. deployment of network slice, RAN functions and CN functions related to URLLC, Industrial IoT, TSN integration with 5GS to support deterministic communication service.
Service and network analysis: The DCSA MnS producer evaluates and identifies service and network issues through monitoring and analysis, demarcates and analyses the issues, and provides analysis recommendation for further optimization if needed.
Optimization and verification: The optimization is targeted to improve the service and network performance. For example, the optimization may include latency related optimization for a network slice instance. The optimization solution is applied and verification conclusion is conducted. If the optimization result deviates from the SLA target, the optimization solution is adjusted accordingly and the iterative optimization process is performed.