AI-Driven Closed-Loop Service Assurance with Service Exposures

Artificial Intelligence (AI) is widely applied in mobile and wireless networks to enhance network operation and service management. Advanced AI mechanisms often require high level of network service exposure in order to access data from as many network elements as possible and execute the AI recommended outcomes into the networks. However, in practice, it is not always feasible to expose the network services to 3rd parties or customers with AI ambitions. Considering that service assurance (SA) is a major area to which AI is applied, this paper describes how a closed-loop SA architecture is associated with the service exposure model in the 5G networks with network slicing. Then we investigate the impact and implication of service exposure on SA. Finally, a set of experiment results are provided to demonstrate the trade-off relationship between the AI ambition and the exposure level in SA.