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This paper identifies that existing industrial automation standards, such as IEC/IEEE 60802 and IEEE 802.1Q, often have inconsistent definitions of traffic types. In the context of utilizing time-sensitive networking (TSN) standards for future automation systems, clear and consistent traffic characteristics and use cases should be defined to benefit from TSN features. Besides that, to facilitate the integration of TSN into the automation systems, the current standards provide a recommendation for mapping the automation traffic to the TSN traffic classes. In this paper, we propose an alternative mapping methodology for automation traffic to TSN traffic classes after presenting the existing automation traffic and their characteristics. Finally, through a case study, we show the potential of the new mapping methodology compared to the standard mapping strategy.

Formal verification of robotic applications, particularly those based on ROS 2, is desirable for ensuring correctness and safety. However, the complexity of formal methods and the manual effort required for model creation and parameter extraction often hinder their adoption. This paper addresses these challenges by proposing a model-based methodology that automates the formal verification process using model-driven engineering techniques. We introduce a methodology which can be applied as a toolchain that automates the initialization of formal model templates in UPPAAL using system parameters derived from ROS 2 execution traces generated by the ROS2_tracing tool. The toolchain employs four model representations based on custom Eclipse Ecore metamodels to capture both structural and verification aspects of ROS 2 systems. The methodology supports both implemented and conceptual systems and enables iterative verification of timing and scheduling parameters through model-to-model and model-to-text transformations. A proof-of-concept implementation demonstrates the feasibility of the proposed approach. The designed toolchain supports verification using two types of UPPAAL models: one for individual node verification (e.g., callback latency and buffer overflow) and another for end-to-end latency analysis of ROS 2 processing chains. Experiments conducted on two implemented and one conceptual ROS 2 systems validate the correctness and adaptability of the toolchain. The results show that the toolchain can automate parameter extraction and model generation. The proposed methodology modularizes the verification process, allowing domain experts to focus on their areas of expertise. It targets to enhances traceability and reusability across different verification scenarios and formal models. The approach aims to make formal verification more accessible and practical to robotics developers.

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.

Time-Sensitive Networking (TSN) has emerged as a key technology for ensuring reliable and deterministic communication in vehicular networks. However, the complexity of evaluating, configuring, and analyzing TSN mechanisms has hindered its widespread adoption. This paper introduces CONAN-TSN, an integrated toolchain designed to address these challenges by providing a comprehensive solution for the configuration, analysis, and evaluation of TSN networks. CONAN-TSN includes tools for traffic generation, traffic mapping, scheduling, and timing analysis, enabling seamless integration and practical implementation of TSN in vehicular systems. The toolchain’s effectiveness is demonstrated through its application to an industrial use case, showcasing its ability to enhance network schedulability and performance. The results highlight CONAN-TSN’s potential to bridge the gap between theoretical benefits and real-world deployment of TSN, offering a valuable resource for researchers and practitioners in the field.

A hybrid cloud is an efficient solution to deal with the problem of insufficient resources of a private cloud when computing demands increase beyond its resource capacities. Cost-efficient workflow scheduling, considering security requirements and data dependency among tasks, is a prominent issue in the hybrid cloud. To address this problem, we propose a mathematical model that minimizes the monetary cost of executing a workflow and satisfies the security requirements of tasks under a deadline. The proposed model fulfills data dependency among tasks, and data transmission time is formulated with exact mathematical expressions. The derived model is a Mixed-integer linear programming problem. We evaluate the proposed model with real-world workflows over changes in the input variables of the model, such as the deadline and security requirements. This paper also presents a post-optimality analysis that investigates the stability of the assignment problem. The experimental results show that the proposed model minimizes the cost by decreasing inter-cloud communications for dependent tasks. However, the optimal solutions are affected by the limitations that are imposed by the problem constraints. 

The increasing complexity of modern embedded systems highlights the limitations of Controller Area Network (CAN) in terms of transmission speed and scalability. The IEEE Time-Sensitive Networking (TSN) task group developed a set of standards to enhance switched Ethernet with high bandwidth, low jitter, and deterministic communication. Despite these advances, CAN will likely co-exist with TSN in, e.g., the automotive industry due to factors such as cost-effectiveness and legacy of CAN. This paper presents an experimental evaluation of a CAN-toTSN gateway implementation, focusing on the impact of different forwarding and scheduling strategies on network performance. We analyze various queuing techniques and scheduling mechanisms in a realistic experimental setup and assess their impact on end-to-end delay and TSN bandwidth utilization. The evaluation results demonstrate that encapsulating only a single CAN frame within a TSN frame effectively minimizes the end-to-end delay of CAN frames, in particular when a high-speed TSN network is used. Furthermore, we perform a comparative evaluation of the Time-Aware Shaper (TAS) and Weighted Round Robin (WRR) mechanisms in the TSN network. Interestingly, WRR leads to lower delays for CAN frames in the TSN network compared to TAS, which we attribute to the lack of synchronization between CAN and TSN.

This paper proposes an approach to pattern-based modeling and Uppaal-based verification for ROS 2 applications. The proposed verification focuses on callback execution latencies and buffer overflow. We propose formal model templates to model the execution of ROS 2 system components, created using a pattern-based approach. The model templates simplify the formal modeling of an ROS 2 application. Using Uppaal, we model in Uppaal timed automata, allowing the description of computation chains of ROS 2-based applications. Our focus is on execution behavior, including two versions of the mainline single-threaded executor of ROS 2. System traces generated using the formal models are validated in multiple experiments. Furthermore, we compare two approaches to modeling the execution of nodes that are typically the core units of computation of ROS 2. The first approach is a holistic approach to model ROS 2 applications, including communication and execution in computation chains. The second is an approach for individual nodes only, at a higher abstraction level. Additionally, we show the application of the verification by model checking in two ROS 2 system scenarios where we compare generated model traces to actual system executions. Overall, through formal modeling and verification, we showcase the potential for uncovering errors in the execution of distributed robotic systems.

Industrial real-time embedded systems run complex software applications with strict timing constraints to ensure efficient operation. Increasing computational demands often strain device resources, leading to missed deadlines and disrupted task execution. This paper proposes a novel decision-making mechanism for offloading soft real-time tasks to edge or cloud servers. The mechanism contains two major components: (i) a monitoring agent to observe and collect task-level performance parameters during run-time, and (ii) a decision-making component to decide, based on the collected parameters, which tasks should be offloaded to improve the overall system performance. We implement the proposed mechanism in the FreeRTOS real-time operating system to provide evidence of its feasibility. We also perform a set of experiments to show performance of the proposed mechanism. The results demonstrate that the proposed mechanism ensures predictable execution of the system with minimal overhead, offering a scalable solution for resource-constrained soft real-time systems.

This paper presents the development and evolution of an educational module centered on collaborative problem-based learning, model-based software development, and end-to-end timing analysis for vehicular embedded systems, highlighting our experiences in integrating state-of-the-art research and industry practices over the years. For the past eight years, the module has been taught to both industry professionals and academic students. In the industry, it has been presented through seminars and workshops organized within the industrial settings of two vehicle manufacturers and a provider of vehicular software development tools. In an academic context, this module has been delivered as part of a PhD course. Furthermore, it has been incorporated into 11 instances of master's courses across four European universities. When offered in an industry context, the module is kept concise and more focused on hands-on activities and practical use cases. In contrast, when the module is delivered in an academic setting, it is supplemented with additional lectures and discussions on its topics. Interestingly, the feedback received from participants, especially those from the industry, has not only contributed to refining this educational module but has also advanced the state of the art in modeling and timing analysis of embedded software architectures.

In this paper, we present the Rubus tool suite, with a focus on its static (offline) real-time scheduler. The schedules generated by the scheduler are executed by a real-time operating system certified according to the ISO 26262 safety standard. The Rubus tool suite and its scheduler have been utilized in the vehicle industry for model- and component-based software development of resource-constrained embedded systems for over 25 years. Since its introduction in 1998, the scheduler has evolved significantly, transitioning from pure Earliest Deadline First (EDF) heuristics to incorporating priorities, data dependencies, and the ability to distribute the schedule over the entire hyperperiod of the software application, among other heuristics. We provide an in-depth discussion on the mechanisms and algorithms that constitute the Rubus offline scheduler. Moreover, we provide an example of its application in generating an offline schedule for a part of software architecture in an industrial setting.