13 research outputs found

    Incorporating Security Constraints into Mixed-Criticality Real-Time Scheduling

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    Task-Level Re-Execution Framework for Improving Fault Tolerance on Symmetry Multiprocessors

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    Hard real-time systems are employed in military, aeronautics, and astronautics fields where deployed systems are susceptible to software faults that can result in functional errors. Thus, there is a need to use fault-tolerant (FT) real-time scheduling. Among the various fault-tolerant real-time scheduling techniques, re-execution has been applied widely to existing real-time systems owing to its simplicity and applicability. However, re-execution requires multiple executions of every task, and some tasks miss their deadlines owing to the prolonged execution time; therefore, it has been found to be suitable for only soft real-time systems. In this paper, we propose an FT policy that can be incorporated into most (if not all) existing real-time scheduling algorithms on multiprocessor systems, which improves the reliability of the target system without a tradeoff against schedulability. As a case study, we apply the FT policy to existing fixed-priority scheduling and earliest deadline zero-laxity scheduling, and we demonstrate that it enhances reliability without schedulability loss

    Contention-Free Scheduling for Single Preemption Multiprocessor Platforms

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    The Contention-Free (CF) policy has been extensively researched in the realm of real-time multi-processor scheduling due to its wide applicability and the performance enhancement benefits it provides to existing scheduling algorithms. The CF policy improves the feasibility of executing other real-time tasks by assigning the lowest priority to a task at a moment when it is guaranteed not to miss its deadline during the remaining execution time. Despite its effectiveness, existing studies on the CF policy are largely confined to preemptive scheduling, leaving the efficiency and applicability of limited preemption scheduling unexplored. Limited preemption scheduling permits a job to execute to completion with a limited number of preemptions, setting it apart from preemptive scheduling. This type of scheduling is crucial when preemption or migration overheads are either excessively large or unpredictable. In this paper, we introduce SP-CF, a single preemption scheduling approach that incorporates the CF policy. SP-CF allows a preemption only once during each job’s execution, following a priority demotion under the CF policy. We also propose a new schedulability analysis method for SP-CF to determine whether each task is executed in a timely manner and without missing its deadline. Through simulation experiments, we demonstrate that SP-CF can significantly enhance the schedulability of the traditional rate-monotonic algorithm and the earliest deadline first algorithm

    An N-Modular Redundancy Framework Incorporating Response-Time Analysis on Multiprocessor Platforms

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    A timing constraint and a high level of reliability are the fundamental requirements for designing hard real-time systems. To support both requirements, the N modular redundancy (NMR) technique as a fault-tolerant real-time scheduling has been proposed, which executes identical copies for each task simultaneously on multiprocessor platforms, and a single correct one is voted on, if any. However, this technique can compromise the schedulability of the target system during improving reliability because it produces N identical copies of each job that execute in parallel on multiprocessor platforms, and some tasks may miss their deadlines due to the enlarged computing power required for completing their executions. In this paper, we propose task-level N modular redundancy (TL-NMR), which improves the system reliability of the target system of which tasks are scheduled by any fixed-priority (FP) scheduling without schedulability loss. Based on experimental results, we demonstrate that TL-NMR maintains the schedulability, while significantly improving average system safety compared to the existing NMR

    Scheduling Randomization Protocol to Improve Schedule Entropy for Multiprocessor Real-Time Systems

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    Because most tasks on real-time systems are conducted periodically, its execution pattern is highly predictable. While such a property of real-time systems allows developing the strong schedulability analysis tools providing high analytical capability, it also leads that security attackers could analyze the predictable execution patterns of real-time systems and use them as attack surfaces. Among the few approaches to foil such a timing-inference security attack, TaskShuffler as a schedule randomization protocol received considerable attention owing to its simplicity and applicability. However, the existing TaskShuffler is only applicable to uniprocessor platforms, where the task execution pattern is quite simple to analyze when compared to multiprocessor platforms. In this study, we propose a new schedule randomization protocol for real-time systems on symmetry multiprocessor platforms where all processors are composed of the same architecture, which extends the existing TaskShuffler initially designed for uniprocessor platforms

    A Task Parameter Inference Framework for Real-Time Embedded Systems

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    While recent studies addressed security attacks in real-time embedded systems, most of them assumed prior knowledge of parameters of periodic tasks, which is not realistic under many environments. In this paper, we address how to infer task parameters, from restricted information obtained by simple system monitoring. To this end, we first develop static properties that are independent of inference results and therefore applied only once in the beginning. We further develop dynamic properties each of which can tighten inference results by feeding an update of the inference results obtained by other properties. Our simulation results demonstrate that the proposed inference framework infers task parameters for RM (Rate Monotonic) with reasonable tightness; the ratio of exactly inferred task periods is 95.3% and 65.6%, respectively with low and high task set use. The results also discover that the inference performance varies with the monitoring interval length and the task set use

    Necessary Feasibility Analysis for Mixed-Criticality Real-Time Embedded Systems

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    As multiple software components with different safety-criticality levels are integrated on a shared computing platform, a real-time embedded system becomes a mixed-criticality (MC) system, which should provide timing guarantees at all different levels of assurance to software components with different criticality levels. In the real-time systems community, the concept of an MC system is regarded as a promising, emerging solution to solve an inherent challenge of real-time systems: pessimistic reservation of computing resources, which yields a low resource-utilization for the sake of guaranteeing timing requirements. Since a timing guarantee should be provided before a real-time system starts to operate, its feasibility has been extensively studied for single-criticality systems; however, the same cannot be said for MC systems. In this article, we develop necessary feasibility tests for MC real-time embedded systems, which is the first study that yields non-trivial results for MC necessary feasibility on both uniprocessor and multiprocessor platforms. To this end, we investigate characteristics of MC necessary feasibility conditions, and identify new challenges posed by the characteristics. By addressing those challenges, we develop two collective necessary feasibility tests and their simplified versions, which are able to exploit a tradeoff between capability in finding infeasible task sets and time-complexity. The simulation results demonstrate that the proposed tests find a number of additional infeasible task sets for both uniprocessor and multiprocessor platforms, which have been proven neither feasible nor infeasible by any existing studies. © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.FALS
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