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Distributed real-time systems often rely on clock synchronization. However, the achievement of precise synchronization in Wireless Sensor Networks (WSNs) is hampered by competing design challenges, which finally causes many WSN hardware platforms to rely on low frequency clock crystal for local timebase provision. Although this solution is inexpensive and with a remarkably low energy consumption, it limits the resolution at which time can be measured. The FLOPSYNC synchronization scheme was then introduced to compensate for possible quartz crystal imperfections. The main limitation of FLOPSYNC is that it does not account for the effects of quantization. In this paper we propose a switched control variant of the base FLOPSYNC scheme to address quantization explicitly in the compensator design, providing clock synchronization in cost-sensitive WSN node platforms with a minimal additional overhead. Experimental evidence is given that the approach reaches a synchronization error of at most 1 clock tick in a real WSN.

This paper presents an overview of the ECSEL project entitled “Safe Cooperating Cyber-Physical Systems using Wireless Communication” (SafeCOP), which runs during the period 2016–2019. SafeCOP targets safety-related Cooperating Cyber-Physical Systems (CO-CPS) characterised by use of wireless communication, multiple stakeholders, dynamic system definitions (openness), and unpredictable operating environments. SafeCOP will provide an approach to the safety assurance of CO-CPS, enabling thus their certification and development. The project will define a runtime manager architecture for runtime detection of abnormal behaviour, triggering if needed a safe degraded mode. SafeCOP will also develop methods and tools, which will be used to produce safety assurance evidence needed to certify cooperative functions. SafeCOP will extend current wireless technologies to ensure safe and secure cooperation, and also contribute to new standards and regulations, by providing certification authorities and standardization committees with the scientifically validated solutions needed to craft effective standards extended to also address cooperation and system-of-systems issues. The project has 28 partners from 6 European countries, and a budget of about 11 million Euros corresponding to about 1,300 person-months., SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless Communication

This paper presents an overview of the ECSEL project entitled “Safe Cooperating Cyber-Physical Systems using Wireless Communication” (SafeCOP), which runs during the period 2016–2019. SafeCOP targets safety-related Cooperating Cyber-Physical Systems (CO-CPS) characterised by use of wireless communication, multiple stakeholders, dynamic system definitions (openness), and unpredictable operating environments. SafeCOP will provide an approach to the safety assurance of CO-CPS, enabling thus their certification and development. The project will define a runtime manager architecture for runtime detection of abnormal behaviour, triggering if needed a safe degraded mode. SafeCOP will also develop methods and tools, which will be used to produce safety assurance evidence needed to certify cooperative functions. SafeCOP will extend current wireless technologies to ensure safe and secure cooperation, and also contribute to new standards and regulations, by providing certification authorities and standardization committees with the scientifically validated solutions needed to craft effective standards extended to also address cooperation and system-of-systems issues. The project has 28 partners from 6 European countries, and a budget of about 11 million Euros corresponding to about 1,300 person-months., SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless Communication

This paper presents an overview of the ECSEL project entitled “Safe Cooperating Cyber-Physical Systems using Wireless Communication” (SafeCOP), which runs during the period 2016–2019. SafeCOP targets safety-related Cooperating Cyber-Physical Systems (CO-CPS) characterised by use of wireless communication, multiple stakeholders, dynamic system definitions (openness), and unpredictable operating environments. SafeCOP will provide an approach to the safety assurance of CO-CPS, enabling thus their certification and development. The project will define a runtime manager architecture for runtime detection of abnormal behaviour, triggering if needed a safe degraded mode. SafeCOP will also develop methods and tools, which will be used to produce safety assurance evidence needed to certify cooperative functions. SafeCOP will extend current wireless technologies to ensure safe and secure cooperation, and also contribute to new standards and regulations, by providing certification authorities and standardization committees with the scientifically validated solutions needed to craft effective standards extended to also address cooperation and system-of-systems issues. The project has 28 partners from 6 European countries, and a budget of about 11 million Euros corresponding to about 1,300 person-months., SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless Communication

This paper presents an overview of the ECSEL project entitled “Safe Cooperating Cyber-Physical Systems using Wireless Communication” (SafeCOP), which runs during the period 2016–2019. SafeCOP targets safety-related Cooperating Cyber-Physical Systems (CO-CPS) characterised by use of wireless communication, multiple stakeholders, dynamic system definitions (openness), and unpredictable operating environments. SafeCOP will provide an approach to the safety assurance of CO-CPS, enabling thus their certification and development. The project will define a runtime manager architecture for runtime detection of abnormal behaviour, triggering if needed a safe degraded mode. SafeCOP will also develop methods and tools, which will be used to produce safety assurance evidence needed to certify cooperative functions. SafeCOP will extend current wireless technologies to ensure safe and secure cooperation, and also contribute to new standards and regulations, by providing certification authorities and standardization committees with the scientifically validated solutions needed to craft effective standards extended to also address cooperation and system-of-systems issues. The project has 28 partners from 6 European countries, and a budget of about 11 million Euros corresponding to about 1,300 person-months., SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless Communication

This paper presents an overview of the ECSEL project entitled “Safe Cooperating Cyber-Physical Systems using Wireless Communication” (SafeCOP), which runs during the period 2016–2019. SafeCOP targets safety-related Cooperating Cyber-Physical Systems (CO-CPS) characterised by use of wireless communication, multiple stakeholders, dynamic system definitions (openness), and unpredictable operating environments. SafeCOP will provide an approach to the safety assurance of CO-CPS, enabling thus their certification and development. The project will define a runtime manager architecture for runtime detection of abnormal behaviour, triggering if needed a safe degraded mode. SafeCOP will also develop methods and tools, which will be used to produce safety assurance evidence needed to certify cooperative functions. SafeCOP will extend current wireless technologies to ensure safe and secure cooperation, and also contribute to new standards and regulations, by providing certification authorities and standardization committees with the scientifically validated solutions needed to craft effective standards extended to also address cooperation and system-of-systems issues. The project has 28 partners from 6 European countries, and a budget of about 11 million Euros corresponding to about 1,300 person-months., SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless Communication

This paper presents an overview of the ECSEL project entitled “Safe Cooperating Cyber-Physical Systems using Wireless Communication” (SafeCOP), which runs during the period 2016–2019. SafeCOP targets safety-related Cooperating Cyber-Physical Systems (CO-CPS) characterised by use of wireless communication, multiple stakeholders, dynamic system definitions (openness), and unpredictable operating environments. SafeCOP will provide an approach to the safety assurance of CO-CPS, enabling thus their certification and development. The project will define a runtime manager architecture for runtime detection of abnormal behaviour, triggering if needed a safe degraded mode. SafeCOP will also develop methods and tools, which will be used to produce safety assurance evidence needed to certify cooperative functions. SafeCOP will extend current wireless technologies to ensure safe and secure cooperation, and also contribute to new standards and regulations, by providing certification authorities and standardization committees with the scientifically validated solutions needed to craft effective standards extended to also address cooperation and system-of-systems issues. The project has 28 partners from 6 European countries, and a budget of about 11 million Euros corresponding to about 1,300 person-months., SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless Communication

A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.

A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.

A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.

A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.

A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.

A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.

MegaM@Rt2 is a large European project dedicated to the provisioning of a model-based methodology and supporting tooling for system engineering at a wide scale. It notably targets the continuous development and runtime validation of such complex systems by developing a framework addressing a large set of engineering processes and application domains. This collaborative project involves 27 partners from 6 different countries, 9 industrial case studies as well as over 30 different software tools from project partners (and others). In the context of the MegaM@Rt2 project, we elaborated on a pragmatic model-driven approach to specify the case study requirements, design the high-level architecture of a framework, perform the gap analysis between the industrial needs and current state-of-the-art, and plan a first framework development roadmap accordingly. The present paper describes the generic tool-supported approach that came out as a result. It also details its concrete application in the MegaM@Rt2 project. In particular, we discuss the collaborative modeling process, the requirement definition tooling, the approach for components modeling, as well as the traceability and document generation. In addition, we show how we used the proposed solution to specify the MegaM@Rt2 framework's conceptual tool components centered around three complementary tool sets: the MegaM@Rt2 System Engineering Tool Set, the MegaM@Rt2 Runtime Analysis Tool Set and the MegaM@Rt2 Model & Traceability Management Tool Set. The paper ends with a discussion on the practical lessons we have learned from this work so far.

Robotic technology helps humans in different areas such as manufacturing, health care and education. Due to the ubiquitous revolution, today's focus is on mobile robots and their applications in a variety of cyber-physical systems. ROS is a wll-known and powerful middleware that facilitates software development for mobile robots. However, this middleware does not support assuring properties such as timeliness and safety of ROS-based software. In this paper we present an integration of Timed Rebeca modeling language with ROS to synthesize verified robotic software. First, a conceptual model of robotic programs is developed using Timed Rebeca. After verifying a set of user-defined correctness properties on this model, it is translated to a ROS program automatically. Experiments on some small-scale case studies illustrates the applicability of the proposed integration method.

Deep Neural Networks (DNNs) are compute-intensive learning models with growing applicability in a wide range of domains. Due to their computational complexity, DNNs benefit from implementations that utilize custom hardware accelerators to meet performance and response time as well as classification accuracy constraints. In this paper, we propose DeepMaker framework that aims to automatically design a set of highly robust DNN architectures for embedded devices as the closest processing unit to the sensors. DeepMaker explores and prunes the design space to find improved neural architectures. Our proposed framework takes advantage of a multi-objective evolutionary approach that exploits a pruned design space inspired by a dense architecture. DeepMaker considers the accuracy along with the network size factor as two objectives to build a highly optimized network fitting with limited computational resource budgets while delivers an acceptable accuracy level. In comparison with the best result on the CIFAR-10 dataset, a generated network by DeepMaker presents up to a 26.4x compression rate while loses only 4% accuracy. Besides, DeepMaker maps the generated CNN on the programmable commodity devices, including ARM Processor, High-Performance CPU, GPU, and FPGA.

Development of critical systems nowadays is hardly achievable without reuse of previous knowledge. Design patterns have an important role in the design of such systems as they define and document common solutions to recurring design problems. However, critical systems such as those that are safety or security related, often require specific assurances that the system is adequate to operate in a given environment. Just as with any other reused knowledge in such systems, the reuse via application of design patterns needs to be assured every time. In this paper, we present a methodology for assuring the application of design patterns in critical domains. In particular, we enrich the design patterns template to support their further assurance. We define the aspects that should be tackled during the assurance of a design pattern application. We use the information specified in the design pattern template to guide the automated instantiation of the argumentation for each design pattern application in the system. We provide tool-support for our methodology in the context of the AMASS tool-platform and evaluate it in an automotive case study.

This paper identifies a limitation in the frame preemption model in the TSN standard (IEEE 802.1Q-2018), due to which high priority frames can experience significantly long blocking delays, thereby exacerbating their worst-case response times. This limitation can have a considerable impact on the design, analysis and performance of TSN-based systems. To address this limitation, the paper presents a novel and more efficient frame preemption model in the TSN standard that allows over 90% reduction in the maximum blocking delay leading to lower worst-case response times of high priority frames compared to the frame preemption model used in the existing works. The paper also shows that the improvement becomes even more significant in multi-switch TSN networks. In order to evaluate the effects of preemption, the paper performs simulations by enabling and disabling preemptions as well as enabling and disabling the Hold/Release mechanism supported by TSN. Furthermore, the paper performs a comparative evaluation of the two models of frame preemption in TSN using simulations. The evaluation shows that the maximum response times of high priority frames can be significantly reduced with very small impact on the response times of lower priority frames. The paper also shows the improvement in the maximum response times of higher priority frames using an automotive industrial use case that employs a multi-hop TSN network for on-board communication.

A safety case is a hierarchical argument supported by evidence, whose scope is defined by contextual information. The goal is to show that the conclusion of such argument, typically “the system is acceptably safe”, is true. However, because the knowledge about systems is always imperfect, the value true cannot be assigned with absolute certainty. Instead, researchers have proposed to assess the belief that a conclusion is true, which should be high for a safe system. Existing methods for belief calculations were shown to suffer from various limitations that lead to unrealistic belief values. This paper presents a novel method, underlined by formal definitions of concepts such as conclusion being true, or context defining the scope. Given these definitions, a general, probabilistic model for the calculation of belief in a conclusion of an arbitrary argument is derived. Because the derived probabilistic model is independent of any safety-case notation, the elements of a commonly used notation are mapped to the formal definitions, and the corresponding probabilistic model is represented as a Bayesian Network to enable large-scale calculations. Finally, the method is applied to scenarios where previous methods produce unrealistic values, and it is shown that the presented method produces belief values as expected.

This paper proposes a systematic three-stage methodology for migrating complex real-time industrial software systems from single-core to multi-core computing platforms. Single-core platforms have limited computational capabilities that prevent integration of computationally demanding applications such as image processing within the existing system. Modern multi-core processors offer a promising solution to address these limitations by providing increased computational power and allowing parallel execution of different applications within the system. However, the transition from traditional single-core to contemporary multi-core computing platforms is non-trivial and requires a systematic and well-defined migration process. This paper reviews some of the existing migration methods and provides a systematic multi-phase migration process with emphasis on software architecture recovery and transformation to explicitly address the timing and dependability attributes expected of industrial software systems. The methodology was evaluated using a survey-based approach and the results indicate that the presented methodology is feasible, useable and useful for real-time industrial software systems.

This paper presents a vision for a much-needed paradigm shift in Life Cycle Engineering (LCE), which is termed Adaptive and Intelligent Life Cycle Engineering (AI-LCE). To do so, interdisciplinary analysis of literature in domains of AI and LCE is performed. Needed concepts and methods are described: key enabling technologies are Artificial Intelligence (AI), the Internet of Things, and data lakes, which are becoming cost-effective and increasingly implemented in industry. Both artificial and human intelligence are used in combination. Its advantages compared with the conventional LCE include shorter time for changing activities in the lifecycle and the accuracy of changes made.

The relevance of context is particularly stressed in case studies, where it is said that “case study is an empirical method aimed at investigating contemporary phenomena in their context”. In this research, we classify context information and provide a context checklist for industrial software engineering. The checklist serves the purpose of (a) supporting researchers and practitioners in characterizing the context in which they are working; (b) supporting researchers with a checklist to identify relevant contextual information to elicit and report during primary and secondary studies. We utilized a systematic approach for constructing the classification of context information and provided a detailed definition for each item. We collected feedback from researchers as well as practitioners. The usefulness of the checklist was perceived more positively by researchers than practitioners, though they highlighted benefits (raising awareness of the importance of context and usefulness for management). The understandability was perceived positively by both practitioners and researchers. The checklist may serve as a “meta-model”, forming the basis for specific adaptations for different research areas, and as input for researchers deciding which context information to extract in systematic reviews. The checklist may also help researchers in reporting context in research papers.

Unlike what is common in the traditional manufacturing industry, the structures in the construction industry are often one of a kind. The goal of this work is to provide a real-world compatible fully automated gantry-robot system for flexible serial production of custom-made reinforcement cages. This can lead to increased efficiency, productivity, and sustainability, not to mention the positive impact on labour safety as well as decreased environmental impact. In this paper, we present a solution utilizing three industrial robots mounted on a gantry structure for automatic generation of robot paths for moving, placing, and tying rebars. Moreover, we present how a 3D BIM-model of a rebar cage, along with installation instructions such as the order in which the bars should be installed, are transferred into CoppeliaSim. This proof-of-concept implementation is an important milestone indicating the feasibility of our proposed robotic solution for the automated fabrication of one-of-a-kind reinforcement cages.

Scheduling of real-time applications modelled according to the periodic and the sporadic task model under hierarchical and compositional real-time systems has been widely studied to provide temporal isolation among independent applications running on shared resources. However, for some real-time applications which are amenable to variation in their timing behaviour, usage of these tasks models can result in pessimistic solutions. The elastic task model addresses this pessimism by allowing the timing requirements of an application's tasks to be specified as a range of values instead of a single value. Although the scheduling of elastic applications on dedicated resources has received considerable attention, there is limited work on scheduling of such applications in hierarchical and compositional settings. In this paper, we evaluate different earliest deadline first scheduling algorithms to schedule elastic applications in a minimum parallelism supply form reservation on a multiprocessor system. Our evaluation indicates that the proposed approach provides performance comparable to the current state-of-art algorithms for scheduling elastic applications on dedicated processors in terms of schedulability.