The next generation of mobile broadband communication, 5G, is seen as a driver for the industrial Internet of things (IIoT). The expected 5G-increased performance spanning across different indicators, flexibility to tailor the network to the needs of specific use cases, and the inherent security that offers guarantees both in terms of performance and data isolation have triggered the emergence of the concept of public network integrated non-public network (PNI-NPN) 5G networks. These networks might be a flexible alternative for the well-known (albeit mostly proprietary) Ethernet wired connections and protocols commonly used in the industry setting. With that in mind, this paper presents a practical implementation of IIoT over 5G composed of different infrastructure and application components. From the infrastructure perspective, the implementation includes a 5G Internet of things (IoT) end device that collects sensing data from shop floor assets and the surrounding environment and makes these data available over an industrial 5G Network. Application-wise, the implementation includes an intelligent assistant that consumes such data to generate valuable insights that allow for the sustainable operation of assets. These components have been tested and validated in a real shop floor environment at Bosch Termotecnologia (Bosch TT). Results show the potential of 5G as an enhancer of IIoT towards smarter, more sustainable, green, and environmentally friendly factories.

5G has been heralded as a critical, decisive technology for verticals’ digital transformation. It targets innovative technical capabilities, allowing dedicated and improved communication mechanisms, going beyond the mere performance increase experienced by past generations’ evolution. Despite the literature already envisaging the application of 5G-enabled solutions in vertical-based deployments, there is still a lack of experimental insights shedding light on the actual feasibility of 5G capabilities in specific vertical deployments. This gap is particularly evident in verticals that did not traditionally rely on mobile network solutions for their communication needs, such as safety-related control signals in railway operations. This paper aims to fill this gap by delivering an extensive empirical analysis performed through a 5G-enabled railway deployment. We designed and implemented a joint testbed, which allows us to faithfully reproduce two important transportation railway use cases that leverage 5G communications involving the vertical, communication service solutions operator, and integration actors. There, we expose the necessary integration engineering behind the enablement of 5G capabilities in such scenarios, considering the highly safety-certified and standardized environment of railway vertical sector regulations (which never considered the utilization of mobile networks in their development). We empirically demonstrate the performance capability achieved by the 5G-enabled network using two different systems, a carrier-grade one and an open-development one, in light of the required key performance indicators. To the best of our knowledge, this is the very first field trial and empirical evaluation of the suitability of 5G with the implementation of a 5G-enabled railway cross-level scenario within the transportation context.

5G technologies are considered a cornerstone of the advent of the next industrial revolution. Promising performance improvements, along with advanced features and assurances in terms of reliability, flexibility and isolation, are expected to enable the realization of diverse and novel use cases, fostering industrial automation with optimized production lines and manufacturing systems. This document shares the experience and knowledge using a 5G SA network for industrial applications. Concretely, the paper examines whether and how the available technology could fulfil the demanding industry requirements, namely in terms of isolation, flexibility and performance. This gap analysis revealed 5G QoS mechanisms as a key driver towards 5G for industry. Thus, a comprehensive analysis of the existing mechanisms and their impact on the network performance are presented, serving as a reality check of 5G SA Release 15 technologies. Although results showed promising possibilities to support industrial deployments, there is still a gap between what’s achievable and what is expected from 5G that will be gradually filled by the introduction of novel features in the upcoming releases. In general, the contributions and insights presented in this paper are considered to be valuable for industry, standards development organizations, manufacturers, and the wider 5G ecosystem. Moreover, this paper serves as a foundational component within a larger endeavour of automating network slicing mechanisms for industrial applications.

5G network is expected to be highly flexible, enabling its adjustment according to user requirements. To achieve this, 5G leverages network slicing, allowing the division of the network infrastructure into different slices with completely different communication performances. However, this flexibility is not easily achieved, requiring the use of available 5G features, Quality of Service (QoS) parameters, and technologies to adapt the communication performance according to the user requirements. Furthermore, to foster wider adoption of 5G by verticals, it is crucial to simplify the network configuration process by providing common interfaces that accept attributes familiar to vertical users. In this line, having a vertical-oriented network slice manager capable of automating the deployment of slices in 5G networks is crucial. One of the key elements involved in creating such a system is a mapping between common communication attributes and available 5G configuration parameters and features. This mapping facilitates the adjustment of communication performance to meet vertical requirements. With this in mind, the document explores the realisation of such a mapping. First, it analyses the communication attributes defined by well-known organisations (e.g., 5G-ACIA, and 5GDNA); these attributes define the performance requirements of network slices or industrial use cases. Then, it maps these attributes to standardised R17 5G functionalities. The mapping is followed by a validation using the 5GAIner infrastructure (part of the IMAGINE-B5G experimental facilities), a real-world commercial-grade 5G Standalone (SA) network. The results showcase the feasibility of using this mapping to realize vertical slices.

The expansion of the autonomous mobility market has brought unprecedented challenges to Multi-access Edge Computing (MEC) servers, including the deterioration of latency and energy consumption performance, which falls into multi-objective and integer programming optimization problems for service instantiation among MECs. Additionally, feasible solutions to support service instantiation among MECs in Cooperative Driving Automation (CDA) overlook the interoperability issues by exposing MNOs’ (in general, Mobile Network Operators’ (MNOs’)) privacy sensitive data. Therefore, this paper proposes a novel fully-decentralized MEC network architecture for CDA, targeting overall latency and energy consumption minimization, simultaneously, while enhancing multi-MNO interoperability. This is achieved by introducing a novel network orchestration algorithm, which decentralizes the network orchestration decision-making to individual MECs, while avoiding the exposure of the MNOs’ privacy sensitive data. Simulation results show that the proposed algorithm achieves an overall average latency and energy consumption of 33.2ms and 8.1W for 5 MECs, outperforming the selected benchmarks by up to 86.7% and 88.1%, respectively. A prototype using carrier-grade and open-source 5G networks is further developed and evaluated with a moving developer-mode vehicle used for Vehicle-to-Everything (V2X) Research. Experimental results show an almost three-fold reduction in both latency and power consumption while proving the applicability of the proposed architecture for the considered case.