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Embedded System Design: Embedded Systems Foundations of Cyber-Physical Systems, and the Internet of Things
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  • Title: Embedded System Design: Embedded Systems Foundations of Cyber-Physical Systems, and the Internet of Things
  • Author(s) Peter Marwedel
  • Publisher: Springer; 4th ed. 2021 edition (January 26, 2021); eBook (Open Access Edition)
  • License(s): CC BY 4.0
  • Hardcover: 455 pages
  • eBook: PDF (446 pages) and ePub
  • Language: English
  • ISBN-10: 303060909X
  • ISBN-13: 978-3030609092
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Book Description

A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things (IoT).

It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems.

The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms.

Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing.

This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues.

About the Authors
  • Dr. Peter Marwedel studied physics at the University of Kiel, Germany. He received his PhD in that subject in 1974. Since 2011, he is the vice-chair of the collaborative research center SFB 876, aiming at resource-efficient analysis of large data sets. Dr. Marwedel is an IEEE Fellow.
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