Safety-critical Java for embedded systems

This paper presents the motivation for and outcomes of an engineering research project on certifiable Java for embedded systems. The project supports the upcoming standard for safety-critical Java, which defines a subset of Java and libraries aiming for development of high criticality systems. The outcome of this project include prototype safety-critical Java implementations, a time-predictable Java processor, analysis tools for memory safety, and example applications to explore the usability of safety-critical Java for this application area. The text summarizes developments and key contributions and concludes with the lessons learned

Analyses and optimizations of timing-constrained embedded systems considering resource synchronization and machine learning approaches

Nowadays, embedded systems have become ubiquitous, powering a vast array of applications from consumer electronics to industrial automation. Concurrently, statistical and machine learning algorithms are being increasingly adopted across various application domains, such as medical diagnosis, autonomous driving, and environmental analysis, offering sophisticated data analysis and decision-making capabilities. As the demand for intelligent and time-sensitive applications continues to surge, accompanied by growing concerns regarding data privacy, the deployment of machine learning models on embedded devices has emerged as an indispensable requirement. However, this integration introduces both significant opportunities for performance enhancement and complex challenges in deployment optimization. On the one hand, deploying machine learning models on embedded systems with limited computational capacity, power budgets, and stringent timing requirements necessitates additional adjustments to ensure optimal performance and meet the imposed timing constraints. On the other hand, the inherent capabilities of machine learning, such as self-adaptation during runtime, prove invaluable in addressing challenges encountered in embedded systems, aiding in optimization and decision-making processes. This dissertation introduces two primary modifications for the analyses and optimizations of timing-constrained embedded systems. For one thing, it addresses the relatively long access times required for shared resources of machine learning tasks. For another, it considers the limited communication resources and data privacy concerns in distributed embedded systems when deploying machine learning models. Additionally, this work provides a use case that employs a machine learning method to tackle challenges specific to embedded systems. By addressing these key aspects, this dissertation contributes to the analysis and optimization of timing-constrained embedded systems, considering resource synchronization and machine learning models to enable improved performance and efficiency in real-time applications with stringent constraints

Embedded System Design

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. 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

Embedded System Design

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. 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

Scheduling and locking in multiprocessor real-time operating systems

With the widespread adoption of multicore architectures, multiprocessors are now a standard deployment platform for (soft) real-time applications. This dissertation addresses two questions fundamental to the design of multicore-ready real-time operating systems: (1) Which scheduling policies offer the greatest flexibility in satisfying temporal constraints; and (2) which locking algorithms should be used to avoid unpredictable delays? With regard to Question 1, LITMUSRT, a real-time extension of the Linux kernel, is presented and its design is discussed in detail. Notably, LITMUSRT implements link-based scheduling, a novel approach to controlling blocking due to non-preemptive sections. Each implemented scheduler (22 configurations in total) is evaluated under consideration of overheads on a 24-core Intel Xeon platform. The experiments show that partitioned earliest-deadline first (EDF) scheduling is generally preferable in a hard real-time setting, whereas global and clustered EDF scheduling are effective in a soft real-time setting. With regard to Question 2, real-time locking protocols are required to ensure that the maximum delay due to priority inversion can be bounded a priori. Several spinlock- and semaphore-based multiprocessor real-time locking protocols for mutual exclusion (mutex), reader-writer (RW) exclusion, and k-exclusion are proposed and analyzed. A new category of RW locks suited to worst-case analysis, termed phase-fair locks, is proposed and three efficient phase-fair spinlock implementations are provided (one with few atomic operations, one with low space requirements, and one with constant RMR complexity). Maximum priority-inversion blocking is proposed as a natural complexity measure for semaphore protocols. It is shown that there are two classes of schedulability analysis, namely suspension-oblivious and suspension-aware analysis, that yield two different lower bounds on blocking. Five asymptotically optimal locking protocols are designed and analyzed: a family of mutex, RW, and k-exclusion protocols for global, partitioned, and clustered scheduling that are asymptotically optimal in the suspension-oblivious case, and a mutex protocol for partitioned scheduling that is asymptotically optimal in the suspension-aware case. A LITMUSRT-based empirical evaluation is presented that shows these protocols to be practical

A framework for flexible scheduling in real-time middleware

The traditional vehicle for the deployment of a real-time system has been a real-time operating system (RTOS). In recent years another programming approach has increasingly found its way into the real-time systems domain: the use of middleware. Examples are the so called pervasive systems (embedded, interactive but not mobile), and ubiquitous systems (embedded, interactive and mobile), e.g. hand-held devices. These tend to be dynamic systems that often exhibit a need for flexible scheduling because of their operating requirement; or their execution environment. Thus, today there is a true need in many realtime applications for more flexible scheduling than what is currently the stateof- prac'tice. By flexible scheduling we mean the ability of the program execution platform to provide a range of scheduling policies, all the way from hard real-time to soft real-time policies, from which an application can choose one most suited to its needs. Furthermore, some applications may need to be scheduled by one policy while others may need a different policy, e.g. fi'Ced priority or earliest deadline first (EDF) for hard real-time tasks, least slack time first (LST) or shortest remaining time for soft real-time tasks. It would be difficult for the middleware to expect this functionality from the RTOS. This would require a fine balance to be struck in the RTOS between flexibility and usability, and many years will probably pass until such approaches become mainstream and usable. 'This thesis maintains that this flexibility can be introduced into the middleware. It presents a viable solution to introducing flexible scheduling in real-time program execution middleware in the form of a flexible scheduling framework. Such a framework allows use of the same program execution middleware for a variety of applications - soft, firm and hard. In particular, the framework allows different scheduling policies to co-exist in the system and their tasks to share common resources. The thesis describes tlle framework's protocol, examines the different types of scheduling policies that can be supported, tests its correctness through the use of a model checker and evaluates the proposed framework by measuring its execution cost overhead. The framework is deemed appropriate for the types of real-time applications that need the services of flexible scheduling

Multiprocessor-safe Wait-free Queue in RTSJ

Currently, most computer systems are running on multiprocessors (or multicores). Moreover, the number of cores inside the processor are expected to increase. To be able to utilise the increased computational power in these systems, developers are enforced to expose more parallelism within their applications. Multi-threading is one of the common techniques that are used to introduce parallelism within computer applications. Shared data structures are in the core of multi-threaded applications; these data structures facilitate the communication between the different threads to help in completing the designed tasks within the application. A control mechanism should be provided such that the access of any thread will not compromise the consistency and correctness of the data structure contents. The increased number of threads will result in an increased competition, this will lead to inevitable difficulties in understanding the interleaving scenarios at runtime, hence, the time analysis will be a very complex task. The Real-Time Specification for Java (RTSJ) introduces different shared queues that can facilitate communication between different threads within the application. However, these queues are uni-directional enabling communication between standard Java threads and the realtime thread classes, which the RTSJ introduces. The work presented in this thesis introduces a novel algorithm for concurrently accessing shared data structures in a shared memory multi-processor (or multi-core) systems. The proposed algorithm is implemented as an arraybased First-In-First-Out (FIFO) queue, which improves the scalability and time predictability in multi-threaded applications. The algorithm utilises the different features that the RTSJ introduces to ensure the time predictability