Supporting Read/Write Applications in Embedded Real-time Systems via Suspension-aware Analysis

In many embedded real-time systems, applications often interact with I/O devices via read/write operations, which may incur considerable suspension delays. Unfortunately, prior analysis methods for validating timing correctness in embedded systems become quite pessimistic when suspension delays are present. In this paper, we consider the problem of supporting two common types of I/O applications in a multiprocessor system, that is, write-only applications and read-write applications. For the write-only application model, we present a much improved analysis technique that results in only O(m) suspension-related utilization loss, where m is the number of processors. For the second application model, we present a flexible I/O placement strategy and a corresponding new scheduling algorithm, which can completely circumvent the negative impact due to read- and write-induced suspension delays. We illustrate the feasibility of the proposed I/O-placement-based schedule via a case study implementation. Furthermore, experiments presented herein show that the improvement with respect to system utilization over prior methods is often significant

Timing Analysis of Fixed Priority SelfSuspending Sporadic Tasks

27th Euromicro Conference on Real-Time Systems (ECRTS 2015), Lund, Sweden.Many real-time systems include tasks that need to suspend their execution in order to externalize some of their operations or to wait for data, events or shared resources. Although commonly encountered in real-world systems, study of their timing analysis is still limited due to the problem complexity. In this paper, we invalidate a claim made in one of the earlier works [1], that led to the common belief that the timing analysis of one self-suspending task interacting with non-self-suspending sporadic tasks is much easier than in the periodic case. This work highlights the complexity of the problem and presents a method to compute the exact worst-case response time (WCRT) of a self-suspending task with one suspension region. However, as the complexity of the analysis might rapidly grow with the number of tasks, we also define an optimization formulation to compute an upper-bound on the WCRT for tasks with multiple suspendion regions. In the experiments, our optimization framework outperforms all previous analysis techniques and often finds the exact WCRT

Suspension-Aware Analysis for Hard Real-Time Multiprocessor Scheduling

In many computing systems, tasks may experience suspension delays when accessing external devices. The problem of analyzing task systems with such suspensions on multiprocessors has been relatively unexplored. The commonly used suspension-oblivious approach of treating all suspensions as computation can be quite pessimistic. As an alternative, this paper presents the first suspension-aware multiprocessor schedulability analysis for task systems with suspensions, under both global fixed-priority and global earliest-deadline-first scheduling. In experiments presented herein, the proposed schedulability tests proved to be superior to suspension-oblivious tests. Moreover, when applied to ordinary sporadic task systems with no suspensions, the proposed analysis for fixed-priority scheduling improves upon prior analysis. I

Many suspensions, many problems: a review of self-suspending tasks in real-time systems

In general computing systems, a job (process/task) may suspend itself whilst it is waiting for some activity to complete, e.g., an accelerator to return data. In real-time systems, such self-suspension can cause substantial performance/schedulability degradation. This observation, first made in 1988, has led to the investigation of the impact of self-suspension on timing predictability, and many relevant results have been published since. Unfortunately, as it has recently come to light, a number of the existing results are flawed. To provide a correct platform on which future research can be built, this paper reviews the state of the art in the design and analysis of scheduling algorithms and schedulability tests for self-suspending tasks in real-time systems. We provide (1) a systematic description of how self-suspending tasks can be handled in both soft and hard real-time systems; (2) an explanation of the existing misconceptions and their potential remedies; (3) an assessment of the influence of such flawed analyses on partitioned multiprocessor fixed-priority scheduling when tasks synchronize access to shared resources; and (4) a discussion of the computational complexity of analyses for different self-suspension task models

Integrating Pragmatic Constraints and Behaviors into Real-Time Scheduling Theory

Scheduling theory has been studied and developed extensively in prior research. In some existing scheduling theory results, the focus is primarily on demonstrating interesting theoretical properties, thus these results are not always cognizant of pragmatic constraints. We seek to determine how existing scheduling theory can be improved with respect to pragmatic constraints and behaviors. The goal of this research is to study and design scheduling algorithms for scheduling real-time workload under constraints and behaviors found in real-time systems. Based on our study we derive a scheduling algorithm for partitioning a collection of real-time tasks in a manner that is cognizant of multiple resource constraints. We apply the above scheduling algorithm for partitioning mixed-criticality tasks. In real-time systems the scheduling algorithm must schedule workload such that all timing constraints are met; we verify this using schedulability tests. We describe schedulability tests for each of the scheduling algorithms that we derive. We also propose a new schedulability test for an existing scheduling algorithm that is commonly used in real-time systems research for scheduling tasks with limited-preemptivity. Finally, we propose a scheduling algorithm and schedulability test for scheduling real-time workload on processors that allow dynamic overclocking.Doctor of Philosoph

A time-predictable parallel programing model for real-time systems

The recent technological advancements and market trends are causing an interesting phenomenon towards the convergence of the high-performance and the embedded computing domains. Critical real-time embedded systems are increasingly concerned with providing higher performance to implement advanced functionalities in a predictable way. OpenMP, the de-facto parallel programming model for shared memory architectures in the high-performance computing domain, is gaining the attention to be used in embedded platforms. The reason is that OpenMP is a mature language that allows to efficiently exploit the huge computational capabilities of parallel embedded architectures. Moreover, OpenMP allows to express parallelism on top of the current technologies used in embedded designs (e.g., C/C++ applications). At a lower level, OpenMP provides a powerful task-centric model that allows to define very sophisticated types of regular and irregular parallelism. While OpenMP provides relevant features for embedded systems, both the programming interface and the execution model are completely agnostic to the timing requirements of real-time systems. This thesis evaluates the use of OpenMP to develop future critical real-time embedded systems. The first contribution analyzes the OpenMP specification from a timing perspective. It proposes new features to be incorporated in the OpenMP standard and a set of guidelines to implement critical real-time systems with OpenMP. The second contribution develops new methods to analyze and predict the timing behavior of parallel applications, so that the notion of parallelism can be safely incorporated into critical real-time systems. Finally, the proposed techniques are evaluated with both synthetic applications and real use cases parallelized with OpenMP. With the above contributions, this thesis pushes the limits of the use of task-based parallel programming models in general, and OpenMP in particular, in critical real-time embedded domains.Los recientes avances tecnológicos y tendencias de mercado estan causando un interesante fenómeno hacia la convergencia de dos dominios: la computacion de altas prestaciones y la computacion embebida. Hay cada vez mas interés en que los sistemas embebidos criticos de tiempo real proporcionen un mayor rendimiento para implementar funcionalidades avanzadas de una manera predecible. OpenMP, el modelo de programación paralela estándar para arquitecturas de memoria compartida en el dominio de la computación de altas prestaciones, está ganando atención para ser utilizado en systemas embebidos. La razón es que OpenMP es un lenguaje asentado que permite explotar eficientemente las enormes capacidades computacionales de las arquitecturas paralelas embebidas. Además, OpenMP permite expresar paralelismo sobre las tecnologías actuales utilizadas en los diseños embebidos (por ejemplo, aplicaciones C/C++). A un nivel inferior, OpenMP proporciona un potente modelo centrado en tareas que permite expresar tipos muy sofisticados de paralelismo regular e irregular. Si bien OpenMP proporciona funciones relevantes para los sistemas embebidos, tanto la interfaz de programación como el modelo de ejecución son completamente ajenos a los requisitos temporales de los sistemas de tiempo real. Esta tesis evalúa el uso de OpenMP para desarrollar los futuros sistemas embebidos criticos de timepo real. La primera contribución analiza la especificación de OpenMP desde una perspectiva temporal. Se propone nuevas funcionalidades que podrian ser incorporadas en el estándar de OpenMP y un conjunto de pautas para implementar sistemas críticos de tiempo real con OpenMP. La segunda contribución desarrolla nuevos métodos para analizar y predecir el comportamiento temporal de las aplicaciones paralelas, de modo que la noción de paralelismo se pueda incorporar de manera segura en sistemas críticos de tiempo real. Finalmente, las técnicas propuestas se evaluan con aplicaciones sintéticas y casos de uso reales paralelizados con OpenMP. Con las mencionadas contribuciones, esta tesis amplía los límites en el uso de los modelos de programación paralela basados en tarea en general, y de OpenMP en particular, en dominios embebidos criticos de tiempo real

Sharing Non-Processor Resources in Multiprocessor Real-Time Systems

Computing devices are increasingly being leveraged in cyber-physical systems, in which computing devices sense, control, and interact with the physical world. Associated with many such real-world interactions are strict timing constraints, which if unsatisfied, can lead to catastrophic consequences. Modern examples of such timing constraints are prevalent in automotive systems, such as airbag controllers, anti-lock brakes, and new autonomous features. In all of these examples, a failure to correctly respond to an event in a timely fashion could lead to a crash, damage, injury and even loss of life. Systems with imperative timing constraints are called real-time systems, and are broadly the subject of this dissertation. Much previous work on real-time systems and scheduling theory assumes that computing tasks are independent, i.e., the only resource they share is the platform upon which they are executed. In practice, however, tasks share many resources, ranging from more overt resources such as shared memory objects, to less overt ones, including data buses and other hardware and I/O devices. Accesses to some such resources must be synchronized to ensure safety, i.e., logical correctness, while other resources may exhibit better run-time performance if accesses are explicitly synchronized. The goal of this dissertation was to develop new synchronization algorithms and associated analysis techniques that can be used to synchronize access to many classes of resources, while improving the overall resource utilization, specifically as measured by real-time schedulability. Towards that goal, the Real-Time Nested Locking Protocol (RNLP), the first multiprocessor real-time locking protocol that supports lock nesting or fine-grained locking is proposed and analyzed. Furthermore, the RNLP is extended to support reader/writer locking, as well as k-exclusion locking. All presented RNLP variants are proven optimal. Furthermore, experimental results demonstrate the schedulability-related benefits of the RNLP. Additionally, three new synchronization algorithms are presented, which are specifically motivated by the need to manage shared hardware resources to improve real-time predictability. Furthermore, two new classes of shared resources are defined, and the first synchronization algorithms for them are proposed. To analyze these new algorithms, a novel analysis technique called idleness analysis is presented, which can be used to incorporate the effects of blocking into schedulability analysis.Doctor of Philosoph