Improving the Schedulability and Quality of Service for Federated Scheduling of Parallel Mixed-Criticality Tasks on Multiprocessors

This paper presents federated scheduling algorithm, called MCFQ, for a set of parallel mixed-criticality tasks on multiprocessors. The main feature of MCFQ algorithm is that different alternatives to assign each high-utilization, high-critical task to the processors are computed. Given the different alternatives, we carefully select one alternative for each such task so that all the other tasks can be successfully assigned on the remaining processors. Such flexibility in choosing the right alternative has two benefits. First, it has higher likelihood to satisfy the total resource requirement of all the tasks while ensuring schedulability. Second, computational slack becomes available by intelligently selecting the alternative such that the total resource requirement of all the tasks is minimized. Such slack then can be used to improve the QoS of the system (i.e., never discard some low-critical tasks). Our experimental results using randomly-generated parallel mixed-critical tasksets show that MCFQ can schedule much higher number of tasksets and can improve the QoS of the system significantly in comparison to the state of the art

Parallel Real-Time Scheduling for Latency-Critical Applications

In order to provide safety guarantees or quality of service guarantees, many of today\u27s systems consist of latency-critical applications, e.g. applications with timing constraints. The problem of scheduling multiple latency-critical jobs on a multiprocessor or multicore machine has been extensively studied for sequential (non-parallizable) jobs and different system models and different objectives have been considered. However, the computational requirement of a single job is still limited by the capacity of a single core. To provide increasingly complex functionalities of applications and to complete their higher computational demands within the same or even more stringent timing constraints, we must exploit the internal parallelism of jobs, where individual jobs are parallel programs and can potentially utilize more than one core in parallel. However, there is little work considering scheduling multiple parallel jobs that are latency-critical. This dissertation focuses on developing new scheduling strategies, analysis tools, and practical platform design techniques to enable efficient and scalable parallel real-time scheduling for latency-critical applications on multicore systems. In particular, the research is focused on two types of systems: (1) static real-time systems for tasks with deadlines where the temporal properties of the tasks that need to execute is known a priori and the goal is to guarantee the temporal correctness of the tasks prior to their executions; and (2) online systems for latency-critical jobs where multiple jobs arrive over time and the goal to optimize for a performance objective of jobs during the execution. For static real-time systems for parallel tasks, several scheduling strategies, including global earliest deadline first, global rate monotonic and a novel federated scheduling, are proposed, analyzed and implemented. These scheduling strategies have the best known theoretical performance for parallel real-time tasks under any global strategy, any fixed priority scheduling and any scheduling strategy, respectively. In addition, federated scheduling is generalized to systems with multiple criticality levels and systems with stochastic tasks. Both numerical and empirical experiments show that federated scheduling and its variations have good schedulability performance and are efficient in practice. For online systems with multiple latency-critical jobs, different online scheduling strategies are proposed and analyzed for different objectives, including maximizing the number of jobs meeting a target latency, maximizing the profit of jobs, minimizing the maximum latency and minimizing the average latency. For example, a simple First-In-First-Out scheduler is proven to be scalable for minimizing the maximum latency. Based on this theoretical intuition, a more practical work-stealing scheduler is developed, analyzed and implemented. Empirical evaluations indicate that, on both real world and synthetic workloads, this work-stealing implementation performs almost as well as an optimal scheduler

Concurrency Platforms for Real-Time and Cyber-Physical Systems

Parallel processing is an important way to satisfy the increasingly demanding computational needs of modern real-time and cyber-physical systems, but existing parallel computing technologies primarily emphasize high-throughput and average-case performance metrics, which are largely unsuitable for direct application to real-time, safety-critical contexts. This work contrasts two concurrency platforms designed to achieve predictable worst case parallel performance for soft real-time workloads with millisecond periods and higher. One of these is then the basis for the CyberMech platform, which enables parallel real-time computing for a novel yet representative application called Real-Time Hybrid Simulation (RTHS). RTHS combines demanding parallel real-time computation with real-time simulation and control in an earthquake engineering laboratory environment, and results concerning RTHS characterize a reasonably comprehensive survey of parallel real-time computing in the static context, where the size, shape, timing constraints, and computational requirements of workloads are fixed prior to system runtime. Collectively, these contributions constitute the first published implementations and evaluations of general-purpose concurrency platforms for real-time and cyber-physical systems, explore two fundamentally different design spaces for such systems, and successfully demonstrate the utility and tradeoffs of parallel computing for statically determined real-time and cyber-physical systems

A Measurement-Based Model for Parallel Real-Time Tasks

Under the federated paradigm of multiprocessor scheduling, a set of processors is reserved for the exclusive use of each real-time task. If tasks are characterized very conservatively (as is typical in safety-critical systems), it is likely that most invocations of the task will have computational demand far below the worst-case characterization, and could have been scheduled correctly upon far fewer processors than were assigned to it assuming the worst-case characterization of its run-time behavior. Provided we could safely determine during run-time when all the processors are going to be needed, for the rest of the time the unneeded processors could be idled in low-energy "sleep" mode, or used for executing non-real time work in the background. In this paper we propose a model for representing parallelizable real-time tasks in a manner that permits us to do so. Our model does not require us to have fine-grained knowledge of the internal structure of the code represented by the task; rather, it characterizes each task by a few parameters that are obtained by repeatedly executing the code under different conditions and measuring the run-times

Development and certification of mixed-criticality embedded systems based on probabilistic timing analysis

An increasing variety of emerging systems relentlessly replaces or augments the functionality of mechanical subsystems with embedded electronics. For quantity, complexity, and use, the safety of such subsystems is an increasingly important matter. Accordingly, those systems are subject to safety certification to demonstrate system's safety by rigorous development processes and hardware/software constraints. The massive augment in embedded processors' complexity renders the arduous certification task significantly harder to achieve. The focus of this thesis is to address the certification challenges in multicore architectures: despite their potential to integrate several applications on a single platform, their inherent complexity imperils their timing predictability and certification. Recently, the Measurement-Based Probabilistic Timing Analysis (MBPTA) technique emerged as an alternative to deal with hardware/software complexity. The innovation that MBPTA brings about is, however, a major step from current certification procedures and standards. The particular contributions of this Thesis include: (i) the definition of certification arguments for mixed-criticality integration upon multicore processors. In particular we propose a set of safety mechanisms and procedures as required to comply with functional safety standards. For timing predictability, (ii) we present a quantitative approach to assess the likelihood of execution-time exceedance events with respect to the risk reduction requirements on safety standards. To this end, we build upon the MBPTA approach and we present the design of a safety-related source of randomization (SoR), that plays a key role in the platform-level randomization needed by MBPTA. And (iii) we evaluate current certification guidance with respect to emerging high performance design trends like caches. Overall, this Thesis pushes the certification limits in the use of multicore and MBPTA technology in Critical Real-Time Embedded Systems (CRTES) and paves the way towards their adoption in industry.Una creciente variedad de sistemas emergentes reemplazan o aumentan la funcionalidad de subsistemas mecánicos con componentes electrónicos embebidos. El aumento en la cantidad y complejidad de dichos subsistemas electrónicos así como su cometido, hacen de su seguridad una cuestión de creciente importancia. Tanto es así que la comercialización de estos sistemas críticos está sujeta a rigurosos procesos de certificación donde se garantiza la seguridad del sistema mediante estrictas restricciones en el proceso de desarrollo y diseño de su hardware y software. Esta tesis trata de abordar los nuevos retos y dificultades dadas por la introducción de procesadores multi-núcleo en dichos sistemas críticos: aunque su mayor rendimiento despierta el interés de la industria para integrar múltiples aplicaciones en una sola plataforma, suponen una mayor complejidad. Su arquitectura desafía su análisis temporal mediante los métodos tradicionales y, asimismo, su certificación es cada vez más compleja y costosa. Con el fin de lidiar con estas limitaciones, recientemente se ha desarrollado una novedosa técnica de análisis temporal probabilístico basado en medidas (MBPTA). La innovación de esta técnica, sin embargo, supone un gran cambio cultural respecto a los estándares y procedimientos tradicionales de certificación. En esta línea, las contribuciones de esta tesis están agrupadas en tres ejes principales: (i) definición de argumentos de seguridad para la certificación de aplicaciones de criticidad-mixta sobre plataformas multi-núcleo. Se definen, en particular, mecanismos de seguridad, técnicas de diagnóstico y reacción de faltas acorde con el estándar IEC 61508 sobre una arquitectura multi-núcleo de referencia. Respecto al análisis temporal, (ii) presentamos la cuantificación de la probabilidad de exceder un límite temporal y su relación con los requisitos de reducción de riesgos derivados de los estándares de seguridad funcional. Con este fin, nos basamos en la técnica MBPTA y presentamos el diseño de una fuente de números aleatorios segura; un componente clave para conseguir las propiedades aleatorias requeridas por MBPTA a nivel de plataforma. Por último, (iii) extrapolamos las guías actuales para la certificación de arquitecturas multi-núcleo a una solución comercial de 8 núcleos y las evaluamos con respecto a las tendencias emergentes de diseño de alto rendimiento (caches). Con estas contribuciones, esta tesis trata de abordar los retos que el uso de procesadores multi-núcleo y MBPTA implican en el proceso de certificación de sistemas críticos de tiempo real y facilita, de esta forma, su adopción por la industria.Postprint (published version

On the Pitfalls of Resource Augmentation Factors and Utilization Bounds in Real-Time Scheduling

In this paper, we take a careful look at speedup factors, utilization bounds, and capacity augmentation bounds. These three metrics have been widely adopted in real-time scheduling research as the de facto standard theoretical tools for assessing scheduling algorithms and schedulability tests. Despite that, it is not always clear how researchers and designers should interpret or use these metrics. In studying this area, we found a number of surprising results, and related to them, ways in which the metrics may be misinterpreted or misunderstood. In this paper, we provide a perspective on the use of these metrics, guiding researchers on their meaning and interpretation, and helping to avoid pitfalls in their use. Finally, we propose and demonstrate the use of parametric augmentation functions as a means of providing nuanced information that may be more relevant in practical settings

A Survey of Research into Mixed Criticality Systems

This survey covers research into mixed criticality systems that has been published since Vestal’s seminal paper in 2007, up until the end of 2016. The survey is organised along the lines of the major research areas within this topic. These include single processor analysis (including fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, realistic models, and systems issues. The survey also explores the relationship between research into mixed criticality systems and other topics such as hard and soft time constraints, fault tolerant scheduling, hierarchical scheduling, cyber physical systems, probabilistic real-time systems, and industrial safety standards