Model Based Engineering Of Collaborative Embedded Systems


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Model-Based Engineering of Collaborative Embedded Systems


Model-Based Engineering of Collaborative Embedded Systems

Author: Wolfgang Böhm

language: en

Publisher: Springer Nature

Release Date: 2020-12-14


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This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years.

Model-Based Engineering of Embedded Systems


Model-Based Engineering of Embedded Systems

Author: Klaus Pohl

language: en

Publisher: Springer Science & Business Media

Release Date: 2012-11-08


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Embedded systems have long become essential in application areas in which human control is impossible or infeasible. The development of modern embedded systems is becoming increasingly difficult and challenging because of their overall system complexity, their tighter and cross-functional integration, the increasing requirements concerning safety and real-time behavior, and the need to reduce development and operation costs. This book provides a comprehensive overview of the Software Platform Embedded Systems (SPES) modeling framework and demonstrates its applicability in embedded system development in various industry domains such as automation, automotive, avionics, energy, and healthcare. In SPES 2020, twenty-one partners from academia and industry have joined forces in order to develop and evaluate in different industrial domains a modeling framework that reflects the current state of the art in embedded systems engineering. The content of this book is structured in four parts. Part I “Starting Point” discusses the status quo of embedded systems development and model-based engineering, and summarizes the key requirements faced when developing embedded systems in different application domains. Part II “The SPES Modeling Framework” describes the SPES modeling framework. Part III “Application and Evaluation of the SPES Modeling Framework” reports on the validation steps taken to ensure that the framework met the requirements discussed in Part I. Finally, Part IV “Impact of the SPES Modeling Framework” summarizes the results achieved and provides an outlook on future work. The book is mainly aimed at professionals and practitioners who deal with the development of embedded systems on a daily basis. Researchers in academia and industry may use it as a compendium for the requirements and state-of-the-art solution concepts for embedded systems development.

Collaborative Design for Embedded Systems


Collaborative Design for Embedded Systems

Author: John Fitzgerald

language: en

Publisher: Springer Science & Business

Release Date: 2014-04-23


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One of the most significant challenges in the development of embedded and cyber-physical systems is the gap between the disciplines of software and control engineering. In a marketplace, where rapid innovation is essential, engineers from both disciplines need to be able to explore system designs collaboratively, allocating responsibilities to software and physical elements, and analyzing trade-offs between them. To this end, this book presents a framework that allows the very different kinds of design models – discrete-event (DE) models of software and continuous time (CT) models of the physical environment – to be analyzed and simulated jointly, based on common scenarios. The individual chapters provide introductions to both sides of this co-simulation technology, and give a step-by-step guide to the methodology for designing and analyzing co-models. They are grouped into three parts: Part I introduces the technical basis for collaborative modeling and simulation with the Crescendo technology. Part II continues with different methodological guidelines for creating co-models and analyzing them in different ways using case studies. Part III then delves into more advanced topics and looks into the potential future of this technology in the area of cyber-physical systems. Finally various appendices provide summaries of the VDM and 20-sim technologies, a number of valuable design patterns applicable for co-models, and an acronym list along with indices and references to other literature. By combining descriptions of the underlying theory with records of real engineers’ experience in using the framework on a series of case studies the book appeals to scientists and practitioners alike. It is complemented by tools, examples, videos, and other material on www.crescendotool.org. Scientists/researchers and graduate students working in embedded and cyber-physical systems will learn the semantic foundations for collaborative modeling and simulation, as well as the current capabilities and limitations of methods and tools in this field. Practitioners will be able to develop an appreciation of the capabilities of the co-modeling techniques, to assess the benefits of more collaborative approaches to modeling and simulation, and will benefit from the included guidelines and modeling patterns.