Closed loops are key enablers for automation that have been successfully used in many industries for long, and more recently for computing and networking applications. The Zero-touch network and service management (ZSM) framework introduced standardized components that allow the creation, execution, and governance of multiple closed loops, enabling zero-touch management of end-to-end services across different management domains. However, the coordinated and optimal instantiation and operation of multiple closed loops is an open question that is left for implementation by the ZSM specifications. In this paper, we propose a methodology that uses intents as a way of communicating requirements to be considered by autonomous management domains to coordinate hierarchies of closed loops. The intent-driven methodology facilitates hierarchical and peer interactions for delegation and escalation of intents. Furthermore, it extends the existing management capabilities of the ZSM framework and facilitates conflict-free integration of closed loops by setting optimal (and non-conflicting) goals that each closed loop in the hierarchy needs to account for. We show an example of the application of the proposed methodology in a network slicing assurance use case. The new capabilities introduced in this paper can be considered as an extension of the ZSM framework to be used in scenarios where multiple intent-driven closed loops exist.

Digitalization and networking are taking on an increasingly important role in manufacturing. Fifth Generation mobile networks (5G) allow us to wirelessly connect multiple assets in factories with guaranteed quality of service (QoS). A 5G non-public network (5G-NPN) realizes a dedicated network with secure communication within the factory. Time-sensitive networking (TSN) provides deterministic connectivity and reliability in local networks. Edge computing moves computing power near factory locations, reducing the latency of edge applications. Making production processes more flexible, more robust, and resilient induces a great challenge for integrating these technologies. This paper presents the benefits of the joint use of 5G-NPN, TSN, and edge computing in manufacturing. To that end, first, the characteristics of the technologies are analyzed. Then, the integration of different 5G-NPN deployment options with edge (and cloud) computing is presented to provide end-to-end services. For enhanced reliability, ways of interworking between TSN and edge computing domains are proposed. Afterward, as an example realization of edge computing, the investigation on the capabilities of the Kubernetes container orchestration platform is presented together with the gap analysis for smart manufacturing requirements. Finally, the different integration options, interworking models, and Kubernetes-based edge computing are evaluated to assist smart factories to use these new technologies in combination in the future.

The importance of time- and mission-critical applications is increasing as industries and society are advancing in their digitalization. As such applications introduce stringent quality of service (QoS) requirements on the underlying network infrastructure, open standards like TSN and DetNet are being developed to provide dependable and time-sensitive communication in bridged LAN networks and IP networks, respectively. More recently, the extension to support wireless time-sensitive connectivity has received special interest due to improved network deployment flexibility with mobile devices. These efforts have led to the standardized support of TSN/DetNet in 5G, allowing the 5G system and its mobile devices to be integrated transparently into TSN/DetNet networks while conforming to their user and control plane protocols. Nevertheless, the induced packet delays – and in particular the packet delay variations (PDVs) – of 5G are significantly larger than in their wired counterparts. In this work, we illustrate that established methods to configure TSN/DetNet networks insufficiently address major runtime uncertainties, and that they would consequently result in QoS impairments or scalability issues. We therefore advocate for two systematic approaches to improve traffic shaping in this setting: first, we propose Packet Delay Correction where the PDV is corrected within the 5G system. Second, we introduce “wireless-aware” TSN scheduling to account for the packet delay characteristics of 5G. We demonstrate that wireless-aware TSN scheduling and Packet Delay Correction are complementary in their design and can be combined to provide formal end-to-end reliability guarantees at scale. In addition, being a key aspect to support wireless-aware TSN scheduling in 5G and future 6G networks, we introduce a data-driven framework to predict the packet delay characteristics of the wireless systems over a finite time horizon. Finally, we identify open research questions in wireless-aware TSN engineering and call for action on future studies and standardizations.