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This work explores how to leverage two novel features provided by the IEEE 802.11be (Wi-Fi 7) standard, such as the Restricted Target Wake Time and Multi-Link Operation, to offer support to real-time periodic flows. In fact, the standard does not define mechanisms to effectively integrate these features in admission control and scheduling policies for real-time flows. The work first addresses the design challenges behind providing bounded latency guarantees and efficient link utilization to realtime uplink flows and then outlines two strategies, called Dedicated and Shared R-TWT. Finally, the work compares the results of a preliminary analytical assessment of the proposed strategies.

Increasing market uncertainties and the growing demand for customized products from end-users are creating major challenges for manufacturing companies, driving the need for a production system automation that offers greater flexibility and adaptability to remain competitive and sustainable. However, current highly automated production systems are typically designed to be static, hardware-centric and difficult to scale and reconfigure quickly. Consequently, it affects the ability of manufacturing companies to continuously adapt to changing customer requirements. Using a case study method, this paper identifies the challenges of traditional hardware-centric automation and analyzes the key drivers for the adoption of software-defined automation (SDA) in production systems. The study identifies system rigidity, hardware constraints, and vendor lock-in as critical challenges of hardware-centric automation. The research reveals that the key drivers for transitioning towards software-defined automation are system flexibility and technological integration, operational efficiency and cost reduction, and enhanced sustainability and cybersecurity. This study contributes to existing literature on SDA in industrial production by providing empirical evidence and identifying SDA as a potential approach to mitigate the challenges of hardware-centric automation.

Integrating Time-Sensitive Networking (TSN) with 5G cellular networks facilitates high-bandwidth, low-latency end-to-end communication in networked embedded systems. An integrated TSN-5G network has the potential to support predictable and deterministic end-to-end communication, as well as to significantly enhance scalability, particularly in industrial automation, by providing flexibility, efficiency, and responsiveness. This paper aims to facilitate the end-to-end (E2E) communication over the integrated TSN-5G networks, by addressing two of the main challenges: (1) design and implementation of an effective TSN-5G gateway that not only ensures an effective forwarding mechanism to translate the traffic among both networks, but also maps the TSN traffic to the corresponding 5G quality-of-service profiles to ensure the timing requirements of highly critical traffic, and (2) establishment of clock synchronization across all network components to support the E2E communication in TSN-5G networks. The paper outlines the design and implementation of a robust TSN-5G gateway that bridges TSN and 5G network architectures, ensuring seamless interoperability between them. We utilize a standalone private 5G network within a controlled lab environment to establish the E2E communication for the TSN-5G network, with a particular emphasizes on analyzing latencies and jitter to provide valuable insights for industrial implementation. Moreover, the gateway facilitates a time synchronization approach, to enable time coordination between network components that supports E2E communication on TSN-5G networks considering the hardware limitation. Our findings indicate that achieving latencies below 20 ms is feasible in an integrated TSN-5G network using the proposed configuration of a private 5G setup with a channel bandwidth of 40 MHz.

The rising demand for real-time applications with ultra-low end-to-end network latency has driven advancements in communication technologies. The IEEE 802.1 Time-Sensitive Networking (TSN) is a set of standards that enable low-latency wired communication, meeting the stringent timing requirements of real-time applications. TSN uses wired communication and lacks the mobility of wireless networks. To overcome this limitation and broaden the applicability of TSN across diverse use cases, the integration of TSN with wireless technologies is essential. The fifth generation of cellular networks (5G) supports real-time applications by providing reliable communication with latencies as low as 1~ms. Seamless integration of TSN and 5G is needed to fully utilize the potential of these technologies in many contemporary and future industrial applications. However, achieving this integration presents significant challenges due to the fundamental differences between TSN and 5G, particularly in ensuring the applications requirements on end-to-end Quality of Services (QoS).

This thesis addresses the challenges of integrated TSN-5G networks, focusing on ensuring end-to-end QoS, traffic forwarding, and real-time scheduling. It presents a systematic literature survey of the existing research on TSN-5G integration that identifies gaps in the current research, including the need of a dedicated TSN-5G gateway to ensure seamless integration. To bridge this gap, the thesis proposes novel techniques to ensure end-to-end QoS and traffic forwarding, validated through a proof-of-concept implementation in a private 5G setup. Moreover, the thesis tackles the challenge of scheduling 5G radio resources for real-time TSN flows with diverse timing requirements. It introduces flow-based radio resource scheduling approaches that adapt to dynamic channel conditions and ensure latency guarantees for the transmission of TSN flows over 5G. These contributions enable real-time communication in integrated TSN-5G networks, paving the way for advanced real-time applications across various industrial domains.

This paper explores the integration of Time-Sensitive Networking (TSN) with 5G cellular networks to support high-bandwidth and low-latency end-to-end communication in networked embedded systems. Integrating TSN with 5G has the potential to support predictable and deterministic end-to-end communication, as well as to significantly enhance scalability, particularly in industrial automation, by providing flexibility, efficiency, and responsiveness. To ensure smooth integration while preserving TSN's Quality of Service (QoS) requirements, effective traffic translation and forwarding within the network are crucial. In this regard, this paper addresses key challenges related to traffic translation, QoS implementation, and latency in both TSN and private 5G networks on a realistic scenario. Through experiments, measurements, and evaluation, this paper thoroughly assesses latency and network capabilities in the integrated networks. Understanding these metrics is essential for devising effective integration strategies. Our findings indicate that it is possible to achieve latencies under 20 ms in an integrated TSN-5G network, given our specific configuration of a private 5G setup with a channel bandwidth of 40 MHz. We also identify an urgent need for the implementation of a proper QoS mechanism in the Open Air Interface software to enable the prioritization of high-critical data transmission.

Many industrial real-time applications in various domains, e.g., automotive, industrial automation, industrial IoT, and industry 4.0, require ultra-low end-to-end network latency, often in the order of 10 milliseconds or less. The IEEE 802.1 time-sensitive networking (TSN) is a set of standards that supports the required low-latency wired communication with ultra-low jitter. The flexibility of such a wired connection can be increased if it is integrated with a mobile wireless network. The fifth generation of cellular networks (5G) is capable of supporting the required levels of network latency with the Ultra-Reliable Low Latency Communication (URLLC) service. To fully utilize the potential of these two technologies (TSN and 5G) in industrial applications, seamless integration of the TSN wired-based network with the 5G wireless-based network is needed. In this article, we provide a comprehensive and well-structured snapshot of the existing research on TSN-5G integration. In this regard, we present the planning, execution, and analysis results of the systematic review. We also identify the trends, technical characteristics, and potential gaps in the state of the art, thus highlighting future research directions in the integration of TSN and 5G communication technologies. We notice that 73% of the primary studies address the time synchronization in the integration of TSN and 5G technologies, introducing approaches with an accuracy starting from the levels of hundred nanoseconds to one microsecond. Majority of primary studies aim at optimizing communication latency in their approach, which is a key quality attribute in automotive and industrial automation applications today.

The advancement of technology has led to an increase in the demand for ultra-low end-to-end network latency in real-time applications with a target of below 10ms. The IEEE 802.1 Time-Sensitive Networking (TSN) is a set of standards that supports the required low-latency wired communication with ultra-low jitter for real-time applications. TSN is designed for fixed networks thus it misses the flexibility of wireless networks.To overcome this limitation and to increase its applicability in different applications, an integration of TSN with other wireless technologies is needed. The fifth generation of cellular networks (5G) supports real-time applications with its Ultra-Reliable Low Latency Communication (URLLC) service. 5G URLLC is designed to meet the stringent timing requirements of these applications, such as providing reliable communication with latencies as low as 1ms. Seamless integration of TSN and 5G is needed to fully utilize the potential of these technologies in contemporary and future industrial applications. However, to achieve the end-to-end Quality of Service (QoS) requirements of a TSN-5G network, a significant effort is required due to the large dissimilarity between these technologies.

This thesis presents a comprehensive and well-structured snapshot of the existing research on TSN-5G integration that identifies gaps in the current research and highlights the opportunities for further research in the area of TSN-5G integration. In particular, the thesis identifies that the state of the art lacks an end-to-end mapping of QoS requirements and traffic forwarding mechanisms for a converged TSN-5G network. This lack of knowledge and tool support hampers the utilisation of ground-breaking technologies like TSN and 5G. Hence, the thesis develops novel techniques to support the end-to-end QoS mapping and traffic forwarding of a converged TSN-5G network for predictable communication.Furthermore, the thesis presents a translation technique between TSN and 5G with a proof-of-concept implementation in a well-known TSN network simulator. Moreover, a novel QoS mapping algorithm is proposed to support the systematic mapping of QoS characteristics and integration of traffic flows in a converged TSN-5G network.

Wireless Time-Sensitive Networks (TSN) are needed to fulfill the requirements of real-time applications in areas where wired connections are not feasible. Wireless TSN combines the real-time capabilities of TSN with the flexibility of wireless connectivity opening a path for new use cases while providing determinism to time-critical scenarios such as autonomous vehicles. Industrial automation is integrating TSN with various wireless technologies such as WiFi, 4G, and 5G. This paper presents an ongoing work which aim is to experimentally analyze the performance of TSN when integrated with 4G, 5G, and WiFi in real-world scenarios. This will help both the researchers and industries to have a clear view of the network performance regarding the end-to-end latency requirements when designing their applications and use cases.

Time Sensitive Networking (TSN) is a set of IEEE standards based on switched Ethernet that aim at meeting high-bandwidth and low-latency requirements in wired communication. TSN implementations typically do not support integration of wireless networks, which limits their applicability to many industrial applications that need both wired and wire-less communication. The development of 5G and its promised Ultra-Reliable and Low-Latency Communication (URLLC) in-tegrated with TSN would offer a promising solution to meet the bandwidth, latency and reliability requirements in these industrial applications. In order to support such an integration, we propose a technique to translate the traffic between TSN and 5G communication technologies. As a proof of concept, we implement the translation technique in a well-known TSN simulator, namely NeSTiNg, that is based on the OMNeT ++ tool. Furthermore, we evaluate the proposed technique using an automotive industrial use case. 

Integrating wired Ethernet networks, such as Time-Sensitive Networks (TSN), to 5G cellular network requires a flow management technique to efficiently map TSN traffic to 5G Quality-of-Service (QoS) flows. The 3GPP Release 16 provides a set of predefined QoS characteristics, such as priority level, packet delay budget, and maximum data burst volume, which can be used for the 5G QoS flows. Within this context, mapping TSN traffic flows to 5G QoS flows in an integrated TSN-5G network is of paramount importance as the mapping can significantly impact on the end-to-end QoS in the integrated network. In this paper, we present a novel and efficient mapping algorithm to map different TSN traffic flows to 5G QoS flows. To the best of our knowledge, this is the first QoS-aware mapping algorithm based on the application constraints used to exchange flows between TSN and 5G network domains. We evaluate the proposed mapping algorithm on synthetic scenarios with random sets of constraints on deadline, jitter, bandwidth, and packet loss rate. The evaluation results show that the proposed mapping algorithm can fulfill over 90% of the applications' constraints.