Real-time and fault tolerance in distributed control software

Closed loop control systems typically contain multitude of spatially distributed sensors and actuators operated simultaneously. So those systems are parallel and distributed in their essence. But mapping this parallelism onto the given distributed hardware architecture, brings in some additional requirements: safe multithreading, optimal process allocation, real-time scheduling of bus and network resources. Nowadays, fault tolerance methods and fast even online reconfiguration are becoming increasingly important. All those often conflicting requirements, make design and implementation of real-time distributed control systems an extremely difficult task, that requires substantial knowledge in several areas of control and computer science. Although many design methods have been proposed so far, none of them had succeeded to cover all important aspects of the problem at hand. [1] Continuous increase of production in embedded market, makes a simple and natural design methodology for real-time systems needed more then ever

Compiler-Assisted Scheduling for Real-Time Applications: A Static Alternative to Low-Level Tuning

Developing a real-time system requires finding a balance between the timing constraints and the functional requirements. Achieving this balance often requires last-minute, low-level intervention in the code modules -- via intensive hardware-based instrumentation and manual program optimizations. In this dissertation we present an automated, static alternative to this kind of human-intensive work. Our approach is motivated by recent advances in compiler technologies, which we extend to two specific issues on real-time programming, that is, feasibility and schedulability. A task is infeasible if its execution time stretches over its deadline. To eliminate such faults, we have developed a synthesis method that (1) inspects all infeasible paths, and then (2) moves instructions out of those paths to shorten the execution time. On the other hand, schedulability of a task set denotes an ability to guarantee the deadlines of all tasks in the application. This property is affected by interactions between the tasks, as well as their individual execution times and deadlines. To address the schedulability problem, we have developed a task transformation method based on program slicing. The method decomposes a task into two subthreads: the IO-handler component that must meet the original deadline, and the state-update component that can be postponed past the deadline. This delayed-deadline approach contributes to the schedulability of the overall application. We also present a new fixed-priority preemptive scheduling strategy, which yields both a feasible priority ordering and a feasible task-slicing metric. (Also cross-referenced as UMIACS-TR-95-33

Languages and Tools for Real-Time Systems: Problems, Solutions and Opportunities

This report summarizes two talks I gave at the ACM SIGPLAN Workshop on Language, Compiler, and Tool Support for Real-Time Systems, which took place on June 21, 1994, in in Orlando, Florida. The workshop was held in concert with ACM SIGPLAN Conference on Programming Languages Design and Implementation. The first talk ("Statements about Real-Time: Truth or Bull?") was given in the early morning. At the behest of the workshop's organizers, its primary function was to seed the ongoing discourse and provoke some debate. Besides asking controversial questions, and positing opinions, the talk also identified some several fertile research areas that might interest PLDI attendees . The second talk ("Languages and Transformations: Some Solutions") was more technical, and it reviewed our research on program optimizations for real-time domains. However, I tried as much as possible to revisit the research problems raised in the morning talk, and present some possible approaches to them. The following paragraphs contain the text from my viewgraphs, laced with some commentary. Since so much work has been done in real-time systems - and even more in programming languages - my references are by necessity incomplete. (Also cross-referenced as UMIACS-TR-94-117

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

A software architecture for hard real-time execution of automatically synthesized plans or control laws

The design of a flexible, real-time software architecture for trajectory planning and automatic control of redundant manipulators is described. Emphasis is placed on a technique of designing control systems that are both flexible and robust yet have good real-time performance. The solution presented involves an artificial intelligence algorithm that dynamically reprograms the real-time control system while planning system behavior

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system

Sharing GPUs for Real-Time Autonomous-Driving Systems

Autonomous vehicles at mass-market scales are on the horizon. Cameras are the least expensive among common sensor types and can preserve features such as color and texture that other sensors cannot. Therefore, realizing full autonomy in vehicles at a reasonable cost is expected to entail computer-vision techniques. These computer-vision applications require massive parallelism provided by the underlying shared accelerators, such as graphics processing units, or GPUs, to function “in real time.” However, when computer-vision researchers and GPU vendors refer to “real time,” they usually mean “real fast”; in contrast, certifiable automotive systems must be “real time” in the sense of being predictable. This dissertation addresses the challenging problem of how GPUs can be shared predictably and efficiently for real-time autonomous-driving systems. We tackle this challenge in four steps. First, we investigate NVIDIA GPUs with respect to scheduling, synchronization, and execution. We conduct an extensive set of experiments to infer NVIDIA GPU scheduling rules, which are unfortunately undisclosed by NVIDIA and are beyond access owing to their closed-source software stack. We also expose a list of pitfalls pertaining to CPU-GPU synchronization that can result in unbounded response times of GPU-using applications. Lastly, we examine a fundamental trade-off for designing real-time tasks under different execution options. Overall, our investigation provides an essential understanding of NVIDIA GPUs, allowing us to further model and analyze GPU tasks. Second, we develop a new model and conduct schedulability analysis for GPU tasks. We extend the well-studied sporadic task model with additional parameters that characterize the parallel execution of GPU tasks. We show that NVIDIA scheduling rules are subject to fundamental capacity loss, which implies a necessary total utilization bound. We derive response-time bounds for GPU task systems that satisfy our schedulability conditions. Third, we address an industrial challenge of supplying the throughput performance of computer-vision frameworks to support adequate coverage and redundancy offered by an array of cameras. We re-think the design of convolution neural network (CNN) software to better utilize hardware resources and achieve increased throughput (number of simultaneous camera streams) without any appreciable increase in per-frame latency (camera to CNN output) or reduction of per-stream accuracy. Fourth, we apply our analysis to a finer-grained graph scheduling of a computer-vision standard, OpenVX, which explicitly targets embedded and real-time systems. We evaluate both the analytical and empirical real-time performance of our approach.Doctor of Philosoph