An optimal fixed-priority assignment algorithm for supporting fault-tolerant hard real-time systems

The main contribution of this paper is twofold. First, we present an appropriate schedulability analysis, based on response time analysis, for supporting fault-tolerant hard real-time systems. We consider systems that make use of error-recovery techniques to carry out fault tolerance. Second, we propose a new priority assignment algorithm which can be used, together with the schedulability analysis, to improve system fault resilience. These achievements come from the observation that traditional priority assignment policies may no longer be appropriate when faults are being considered. The proposed schedulability analysis takes into account the fact that the recoveries of tasks may be executed at higher priority levels. This characteristic is very important since, after an error, a task certainly has a shorter period of time to meet its deadline. The proposed priority assignment algorithm, which uses some properties of the analysis, is very efficient. We show that the method used to find out an appropriate priority assignment reduces the search space from O(n!) to O(n/sup 2/), where n is the number of task recovery procedures. Also, we show that the priority assignment algorithm is optimal in the sense that the fault resilience of task sets is maximized as for the proposed analysis. The effectiveness of the proposed approach is evaluated by simulation

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

k2U: A General Framework from k-Point Effective Schedulability Analysis to Utilization-Based Tests

To deal with a large variety of workloads in different application domains in real-time embedded systems, a number of expressive task models have been developed. For each individual task model, researchers tend to develop different types of techniques for deriving schedulability tests with different computation complexity and performance. In this paper, we present a general schedulability analysis framework, namely the k2U framework, that can be potentially applied to analyze a large set of real-time task models under any fixed-priority scheduling algorithm, on both uniprocessor and multiprocessor scheduling. The key to k2U is a k-point effective schedulability test, which can be viewed as a "blackbox" interface. For any task model, if a corresponding k-point effective schedulability test can be constructed, then a sufficient utilization-based test can be automatically derived. We show the generality of k2U by applying it to different task models, which results in new and improved tests compared to the state-of-the-art. Analogously, a similar concept by testing only k points with a different formulation has been studied by us in another framework, called k2Q, which provides quadratic bounds or utilization bounds based on a different formulation of schedulability test. With the quadratic and hyperbolic forms, k2Q and k2U frameworks can be used to provide many quantitive features to be measured, like the total utilization bounds, speed-up factors, etc., not only for uniprocessor scheduling but also for multiprocessor scheduling. These frameworks can be viewed as a "blackbox" interface for schedulability tests and response-time analysis

A C-DAG task model for scheduling complex real-time tasks on heterogeneous platforms: preemption matters

Recent commercial hardware platforms for embedded real-time systems feature heterogeneous processing units and computing accelerators on the same System-on-Chip. When designing complex real-time application for such architectures, the designer needs to make a number of difficult choices: on which processor should a certain task be implemented? Should a component be implemented in parallel or sequentially? These choices may have a great impact on feasibility, as the difference in the processor internal architectures impact on the tasks' execution time and preemption cost. To help the designer explore the wide space of design choices and tune the scheduling parameters, in this paper we propose a novel real-time application model, called C-DAG, specifically conceived for heterogeneous platforms. A C-DAG allows to specify alternative implementations of the same component of an application for different processing engines to be selected off-line, as well as conditional branches to model if-then-else statements to be selected at run-time. We also propose a schedulability analysis for the C-DAG model and a heuristic allocation algorithm so that all deadlines are respected. Our analysis takes into account the cost of preempting a task, which can be non-negligible on certain processors. We demonstrate the effectiveness of our approach on a large set of synthetic experiments by comparing with state of the art algorithms in the literature