STRAUSS: Scalable intent-driven industrial network service quality assurance with asset administration shells

With the emergence of 6G, there is an increasing need for autonomous network service quality assurance. This process is particularly challenging at scale when: (i) requirements of tens of industrial components are to be considered; (ii) conflicting requirements are to be resolved; (iii) mapping needs to be done across industrial and 6G domains; and (iv) autonomous intent resolution is to be incorporated. In this paper, we propose STRAUSS, a scalable intent-driven framework for service quality assurance. We exploit the features of asset administration shells to effectively manage requirements towards the network in an interoperable manner. The intents are mapped effectively between domains using AI-driven techniques. A similar Artificial Intelligence (AI)-driven technique is used to decompose intents with end-to-end expectations to various resource level domains to enable autonomous network configuration management. The proposed system is demonstrated over a realistic use case with multiple picking robots and Autonomous Mobile Robots (AMRs).