In light of the evolving landscape of future converged networks, heightened demands for scalability and performance have become paramount, particularly in the industrial context where enhanced flexibility, adaptability, time synchronization and deterministic low latency are key features. Time-Sensitive Networking (TSN) has been introduced to provide converged networks with determinism. To mitigate the complexities associated with cabling requirements, Wireless Time-Sensitive Networking (WTSN) emerges as a more suited solution in industrial applications that need mobility. This study presents an application in smart manufacturing that incorporates WTSN technology. Specifically, it focuses on a scenario where an Unmanned Ground Vehicle (UGV), under the control of an edge controller connected through a wireless link, operates within a critical environment subject to constraints such as to avoid obstacles and to build a real-time map of the surrounding area. The mapping outcome performed by the edge controller demonstrates the effectiveness of the WTSN capabilities.

Resilient systems are crucial for modern interconnected applications, especially those with autonomous machine-to-machine communication. Standard network protocols can exhibit unacceptable recovery times for time-critical operations, and systems must withstand various disruptions beyond just connection failures.This paper addresses these vulnerabilities by proposing a robust communication architecture based on an adapted MQTT protocol employing duplicated packet transmission over parallel pathways. The approach, based on redundancy, employs a smart algorithm for selecting the best communication path to rely on. This strategy aims to ensure reliable data delivery and mitigate service interruptions, particularly for demanding industrial applications, while limiting resources and bandwidth consumption. The effectiveness of this architecture is validated through a real testbed implementation and online testing.

The demand for precise time synchronization is of great interest in contemporary networked systems, especially in the context of converged networks where seamless communication among devices, actuators, and sensors is imperative. This has led to the development and adoption of Time-Sensitive Networking (TSN) and Wireless TSN (WTSN) technologies, with a particular attention to the IEEE 802.1AS Generalized Precision Time Protocol (gPTP) standard. In this work, we explore the role of time synchronization in a wireless network scenario involving an Unmanned Ground Vehicle (UGV) that has to track a desired time dependent trajectory. The UGV receives trajectory waypoints from a secondary station, emphasizing the importance of precise timing in trajectory tracking. Utilizing the IEEE 802.1AS standard for wireless time synchronization, this study investigates the impact of clock synchronization errors and latency on trajectory tracking. Hence, it demonstrates the capability and benefits of IEEE 802.1AS in managing device clocks and facilitating time correction to ensure precise trajectory tracking despite synchronization errors and latency.

The extension of Time Sensitive Networking (TSN) to wireless domains is a key enabler for the realization of Industry 4.0 and 5.0 applications. Thanks to their characteristics in terms of latency and bandwidth, and the seamless integration with Ethernet TSN, 5G New Radio (NR) and 802.11 (WiFi) are the primary candidates for enabling wireless TSN applications. In the TSN context, precise time synchronization represents a funda-mental building block. In this paper, we focus on the assessment of the synchronization accuracy of IEEE 1588 (PTP) over 5G NR networks by considering different network configurations and traffic loads. The results provide preliminary insights into the performance of PTP over 5G NR and its suitability for TSN applications.

Object detection is a critical task in various real-time applications, including surveillance, autonomous vehicles, and industrial automation, especially within the emerging paradigms of Industry 5.0 and Industrial Internet of Things (IIoT). However, deploying such algorithms on resource-constrained embedded devices poses significant challenges due to their limited computational power and memory resources. This paper presents a comparative evaluation of YOLOv5 and YOLOv8, two state-of-the-art object detection algorithms, on different embedded hardware platforms. Leveraging insights from existing research, we aim to address this work by conducting comprehensive experiments to assess the performance of the proposed algorithm in terms of detection precision and inference speed on each hardware platform. The analysis provided encouraging results and revealed different behaviors, showing the importance of GPUs also for embedded systems.

Critical infrastructure, utilities, and large enter-prises are increasingly complex. These sprawling systems, often geographically dispersed, rely on seamless coordination across vast networks. Typically, they use the internet and TCPIIP proto-cols for communication. However, ensuring system-level resilience requires exceptionally dependable network infrastructure. This paper proposes a solution built on a redundant version of the MQTT protocol, implemented directly at the network's endpoints. This approach ensures reliable communication even in the face of potential network issues. Additionally, the paper explores the potential for a future solution that analyzes multi-publisher/subscriber scenarios and, for this purpose, a prelimi-nary research on synchronizing communication among a larger number of devices within the network. The paper concludes by detailing the proposed solution, evaluating its effectiveness, and validating its practicality through experimentation.

The ever more used and widespread Time-Sensitive Networking (TSN) has changed real-time networks, enabling reliable communication for time-critical applications. At the same time Software-Defined Networking (SDN) has emerged as a solution to ensure proper quality of service for managing dynamic network configurations even in evolving topologies. This paper investigates the integration between TSN and SDN to enable dynamic network re-configuration and improve performance for time-critical applications. We present an experimental setup designed to evaluate this approach. The setup focuses on scenarios where an SDN controller can dynamically reroute critical data flows across different TSN network devices to avoid interference and maintain consistent Quality-of-Service (QoS).

The introduction of Time-Sensitive Networking (TSN) is revolutionizing real-time networks and time-critical applications. Recent advancements in this field extended the TSN capabilities to wireless technologies, giving rise to the concept of wireless TSN (WTSN). This paper focuses on the integration of wireless TSN with Software-Defined Networking (SDN) to enable dynamic network configuration and improve the performance of time-sensitive applications. We present a practical test environment that uses a hybrid network configuration consisting of wireless and wired TSN links. The primary objective is to evaluate the effectiveness of combining a TSN-capable network with an SDN controller. This setup enables dynamic configuration and routing within the system, allowing for prompt actions to address network issues, such as seamlessly re-routing data paths between the two links due to an increase in latency or packet loss. A measurement setup using OpenVSwitch in the wireless TSN domain is presented, along with the evaluation of time synchronization and dynamic route selection capabilities.

The introduction of the Industrial Internet of Things (IIoT) is dramatically changing the concept of manufacturing, ensuring better production flexibility, efficiency, safety and security. In this scenario, Functional Safety Networks are ever more deployed, being networks that allow to implement functional safety systems, integrated and cooperating with factory communication infrastructures that are ever more characterized by the deployment of wireless communication systems. Unfortunately, nowadays, the lack of safety protocols targeted for wireless networks represents a bottleneck in the novel smart factory development process. Thus, functional safety over wireless is becoming a hot research topic. In this paper, we address the adoption of Wi-Fi to implement functional safety networks by exploiting the black channel approach, which is at the basis of the most popular functional safety protocols designed for wired networks. In practice, with such an approach, the safety protocol is not aware of the underlying communication system. We focus on a specific protocol, namely FailSafe over EtherCAT (FSoE) and investigate its behavior over Wi-Fi. To this aim, we developed an experimental set-up and conducted several tests to adequately assess safety, reliability and timing performance. Specifically, we addressed the achievable Safety Integrated Level (SIL), the number of network re-initializations and the message delivery times. The analysis provided encouraging results and revealed different behaviors concerned with the use of different transport layer protocols (TCP and UDP) that suggest interesting future activities.

In recent years, Factory Automation is evolving towards the so-called Industry 4.0, and the creation of a smart factory ecosystem comprising of ubiquitously interconnected objects, namely the Industrial Internet of Things (IIoT), is gaining much research interest. This paradigm aims at developing new smart technological equipment and protocols, thus providing interconnection among "factory objects" anywhere and at any time. In this context, people and machines have to safely cooperate and a high level of protection needs to be guaranteed for both operators and the surrounding environment. For this reason, safety systems, aiming at decreasing risks and failure probabilities, are nowadays of uttermost importance. Several Functional Safety communication protocols have been developed during these years pointing to increase data integrity and guarantee protection in a safety system. Popular examples are Fail Safe over EtherCAT (FSoE), ProfiSAFE, and OPC-UA Safety. These protocols, al-though conceived for wired networks, can be in principle adopted also by wireless communication, as they are developed by using a black channel approach. Nevertheless, the implementation of these protocols over different wireless networks is challenging as they might not ensure the required Safety Integrated Level (SIL). This paper, moving from the aforementioned observations and the need for wireless solutions in the IIoT context, focuses on proposing a possible implementation of FSOE over Wi-Fi, running UDP at the transport layer. In particular, by using suitable experimental outcomes, an OMNeT++ simulator has been calibrated, thus enabling the possibility to analyze the proposed protocol in wide industrial systems.

Modern industrial manufacturing plants, especially those using coordinated electrical drives with strict timing requirements, make extensive use of real-time communication networks. These systems, typically, are based on various topologies, include diverse protocols, and connect devices from different manufacturers, which may make them difficult to study, plan and optimize. As a solution, the adoption of digital twins allows to simulate such systems under various operating conditions in a low-cost and zero-risk environment. In this paper we address the digital twin of a networked electrical drive system, focusing on the real-time communication network used to connect the drives. In particular, we describe the simulation model of Profinet IO RT Class 1, implemented as an extension of the INET library of OMNeT++. Moreover, we present the outcomes of the tests carried out on a prototype simulated network and compare them with those of the equivalent real one.

Wireless technologies play a key role in the Industrial Internet of Things (IIoT) scenario, for the development of increasingly flexible and interconnected factory systems. Wi-Fi remains particularly attracting due to its pervasiveness and high achievable data rates. Furthermore, its Rate Adaptation (RA) capabilities make it suitable to the harsh industrial environments, provided that specifically designed RA algorithms are deployed. To this aim, this paper proposes to exploit Reinforcement Learning (RL) techniques to design an industry-specific RA algorithm. The RL is spreading in many fields since it allows to design intelligent systems by means of a stochastic discrete-time system based approach. In this work we propose to enhance the Robust Rate Adaptation Algorithm (RRAA) by means of a RL approach. The preliminary assessment of the designed RA algorithm is carried out through meaningful OMNeT++ simulations, that allow to recognize the beneficial impact of the introduction of RL with respect to several industry-specific performance indicators.

In this paper we consider an Industrial Internet of Things (IIoT) system, based on the production of 3D-printed artifacts that are equipped with embedded sensors to monitor some environmental variables such as temperature, humidity, etc. These sensors allow to gather information during the production phase of the artifacts, as well as while they are deployed in their final locations, so that diverse operations (e.g. tuning of the production parameters, predictive maintenance, environmental monitoring) can be undertaken. Monitoring is implemented via LoRaWAN, a Low Power Wide Area Network (LPWAN) that allows to acquire data from the sensors embedded in the artifacts. After a description of the IIoT system, we provide the description of some experimental tests we carried out in this challenging context, aimed at investigating both the reliability of the transmission and the battery life time. The outcomes of such experiments indicate the actual feasibility of the proposed technique.

Wireless networks are ever more deployed in industrial automation systems in various types of applications. A significant example in this context is represented by the transmission of safety data that, traditionally, was accomplished by wired systems. In this paper we propose an implementation of the Fail Safe over EtherCAT (FSoE) protocol on the top of IEEE 802.11 WLAN. The paper, after a general introduction of FSoE, focuses on the implementation of such protocol on commercial devices running UDP at the transport layer and connected via the IEEE 802.11 Wireless LAN. Then the paper presents some experimental setups and the tests that have been carried out on them. The obtained results are encouraging, since they show that good safety performance can be achieved even in the presence of wireless transmission media.

In this paper we address the safety strategies for networked electrical drive systems, in the context of industrial automation. Specifically, it is considered the handling of errors and faults that may occur during the execution of safety related functions, on a set of electrical drives. Such devices, which operate in a coordinated way, are connected via an industrial communication network and use a safety industrial protocol. In this respect, a novel approach that exploits a distributed consensus algorithm to identify and possibly recover the aforementioned errors is devised and discussed in comparison with a traditional safe shut-down strategy. The theoretical performance figures and the effectiveness of the proposed approach are evaluated in a real industrial case study considering two different widespread network topologies.