573 research outputs found

    TASKers: A Whole-System Generator for Benchmarking Real-Time-System Analyses

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    Implementation-based benchmarking of timing and schedulability analyses requires system code that can be executed on real hardware and has defined properties, for example, known worst-case execution times (WCETs) of tasks. Traditional approaches for creating benchmarks with such characteristics often result in implementations that do not resemble real-world systems, either due to work only being simulated by means of busy waiting, or because tasks have no control-flow dependencies between each other. In this paper, we address this problem with TASKers, a generator that constructs realistic benchmark systems with predefined properties. To achieve this, TASKers composes patterns of real-world programs to generate tasks that produce known outputs and exhibit preconfigured WCETs when being executed with certain inputs. Using this knowledge during the generation process, TASKers is able to specifically introduce inter-task control-flow dependencies by mapping the output of one task to the input of another

    Validate implementation correctness using simulation: the TASTE approach

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    High-integrity systems operate in hostile environment and must guarantee a continuous operational state, even if unexpected events happen. In addition, these systems have stringent requirements that must be validated and correctly translated from high-level specifications down to code. All these constraints make the overall development process more time-consuming. This becomes especially complex because the number of system functions keeps increasing over the years. As a result, engineers must validate system implementation and check that its execution conforms to the specifications. To do so, a traditional approach consists in a manual instrumentation of the implementation code to trace system activity while operating. However, this might be error-prone because modifications are not automatic and still made manually. Furthermore, such modifications may have an impact on the actual behavior of the system. In this paper, we present an approach to validate a system implementation by comparing execution against simulation. In that purpose, we adapt TASTE, a set of tools that eases system development by automating each step as much as possible. In particular, TASTE automates system implementation from functional (system functions description with their properties – period, deadline, priority, etc.) and deployment(processors, buses, devices to be used) models. We tailored this tool-chain to create traces during system execution. Generated output shows activation time of each task, usage of communication ports (size of the queues, instant of events pushed/pulled, etc.) and other relevant execution metrics to be monitored. As a consequence, system engineers can check implementation correctness by comparing simulation and execution metrics

    MORA: an Energy-Aware Slack Reclamation Scheme for Scheduling Sporadic Real-Time Tasks upon Multiprocessor Platforms

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    In this paper, we address the global and preemptive energy-aware scheduling problem of sporadic constrained-deadline tasks on DVFS-identical multiprocessor platforms. We propose an online slack reclamation scheme which profits from the discrepancy between the worst- and actual-case execution time of the tasks by slowing down the speed of the processors in order to save energy. Our algorithm called MORA takes into account the application-specific consumption profile of the tasks. We demonstrate that MORA does not jeopardize the system schedulability and we show by performing simulations that it can save up to 32% of energy (in average) compared to execution without using any energy-aware algorithm.Comment: 11 page

    A Lazy Bailout Approach for Dual-Criticality Systems on Uniprocessor Platforms

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    © 2019 by the authors. Licensee MDPI, Basel, Switzerland.A challenge in the design of cyber-physical systems is to integrate the scheduling of tasks of different criticality, while still providing service guarantees for the higher critical tasks in case of resource-shortages caused by faults. While standard real-time scheduling is agnostic to the criticality of tasks, the scheduling of tasks with different criticalities is called mixed-criticality scheduling. In this paper we present the Lazy Bailout Protocol (LBP), a mixed-criticality scheduling method where low-criticality jobs overrunning their time budget cannot threaten the timeliness of high-criticality jobs while at the same time the method tries to complete as many low-criticality jobs as possible. The key principle of LBP is instead of immediately abandoning low-criticality jobs when a high-criticality job overruns its optimistic WCET estimate, to put them in a low-priority queue for later execution. To compare mixed-criticality scheduling methods we introduce a formal quality criterion for mixed-criticality scheduling, which, above all else, compares schedulability of high-criticality jobs and only afterwards the schedulability of low-criticality jobs. Based on this criterion we prove that LBP behaves better than the original {\em Bailout Protocol} (BP). We show that LBP can be further improved by slack time exploitation and by gain time collection at runtime, resulting in LBPSG. We also show that these improvements of LBP perform better than the analogous improvements based on BP.Peer reviewedFinal Published versio

    Schedulability-driven scratchpad memory swapping for resource-constrained real-time embedded systems

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    In resource-constrained real-time embedded systems, scratchpad memory (SPM) is utilized in place of cache to increase performance and enforce consistent behavior of both hard and soft real-time tasks via software-controlled SPM management techniques (SPMMTs). Real-time systems depend on time critical (hard) tasks to complete execution before their deadline times. Many real-time systems also depend on the execution of soft tasks that do not have to complete by hard deadlines. This thesis evaluates a new SPMMT that increases both worst-case task slack time (TST) and soft task processing capabilities, by combining two existing SPMMTs. The schedulability-driven ACETRB / WCETRB swapping (SDAWS) SPMMT of this thesis uses task schedulability characteristics to control the selection of either the average-case execution time reduction based (ACETRB) SPMMT or the worst-case execution time reduction based (WCETRB) SPMMT. While the literature contains examples of combined management techniques, until now there have been none that combine both WCETRB and ACETRB SPMMTs. The advantage of combining them is to achieve WCET reduction comparable to what can be achieved with the WCETRB SPMMT, while achieving significantly reduced ACET relative to the WCETRB SPMMT. Using a stripped-down RTOS and an SPMMT simulator implemented for this work, evaluated resource-constrained scenarios show a reduction in task slack time from the SDAWS SPMMT relative to the WCETRB SPMMT between 20% and 45%. However, the evaluated scenarios also conservatively show that SDAWS can reduce ACET relative to the WCETRB SPMMT by up to 60%

    Response-time analysis for fixed-priority systems with a write-back cache

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    This paper introduces analyses of write-back caches integrated into response-time analysis for fixed-priority preemptive and non-preemptive scheduling. For each scheduling paradigm, we derive four different approaches to computing the additional costs incurred due to write backs. We show the dominance relationships between these different approaches and note how they can be combined to form a single state-of-the-art approach in each case. The evaluation explores the relative performance of the different methods using a set of benchmarks, as well as making comparisons with no cache and a write-through cache. We also explore the effect of write buffers used to hide the latency of write-through caches. We show that depending upon the depth of the buffer used and the policies employed, such buffers can result in domino effects. Our evaluation shows that even ignoring domino effects, a substantial write buffer is needed to match the guaranteed performance of write-back caches

    Towards an HLA Run-time Infrastructure with Hard Real-time Capabilities

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    Our work takes place in the context of the HLA standard and its application in real-time systems context. The HLA standard is inadequate for taking into consideration the different constraints involved in real-time computer systems. Many works have been invested in order to providing real-time capabilities to Run Time Infrastructures (RTI) to run real time simulation. Most of these initiatives focus on major issues including QoS guarantee, Worst Case Transit Time (WCTT) knowledge and scheduling services provided by the underlying operating systems. Even if our ultimate objective is to achieve real-time capabilities for distributed HLA federations executions, this paper describes a preliminary work focusing on achieving hard real-time properties for HLA federations running on a single computer under Linux operating systems. Our paper proposes a novel global bottom up approach for designing real-time Run time Infrastructures and a formal model for validation of uni processor to (then) distributed real-time simulation with CERTI

    Effective And Efficient Preemption Placement For Cache Overhead Minimization In Hard Real-Time Systems

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    Schedulability analysis for real-time systems has been the subject of prominent research over the past several decades. One of the key foundations of schedulability analysis is an accurate worst case execution time (WCET) for each task. In preemption based real-time systems, the CRPD can represent a significant component (up to 44% as documented in research literature) of variability to overall task WCET. Several methods have been employed to calculate CRPD with significant levels of pessimism that may result in a task set erroneously declared as non-schedulable. Furthermore, they do not take into account that CRPD cost is inherently a function of where preemptions actually occur. Our approach for computing CRPD via loaded cache blocks (LCBs) is more accurate in the sense that cache state reflects which cache blocks and the specific program locations where they are reloaded. Limited preemption models attempt to minimize preemption overhead (CRPD) by reducing the number of allowed preemptions and/or allowing preemption at program locations where the CRPD effect is minimized. These algorithms rely heavily on accurate CRPD measurements or estimation models in order to identify an optimal set of preemption points. Our approach improves the effectiveness of limited optimal preemption point placement algorithms by calculating the LCBs for each pair of adjacent preemptions to more accurately model task WCET and maximize schedulability as compared to existing preemption point placement approaches. We utilize dynamic programming technique to develop an optimal preemption point placement algorithm. Lastly, we will demonstrate, using a case study, improved task set schedulability and optimal preemption point placement via our new LCB characterization. We propose a new CRPD metric, called loaded cache blocks (LCB) which accurately characterizes the CRPD a real-time task may be subjected to due to the preemptive execution of higher priority tasks. We show how to integrate our new LCB metric into our newly developed algorithms that automatically place preemption points supporting linear control flow graphs (CFGs) for limited preemption scheduling applications. We extend the derivation of loaded cache blocks (LCB), that was proposed for linear control flow graphs (CFGs) to conditional CFGs. We show how to integrate our revised LCB metric into our newly developed algorithms that automatically place preemption points supporting conditional control flow graphs (CFGs) for limited preemption scheduling applications. For future work, we will verify the correctness of our framework through other measurable physical and hardware constraints. Also, we plan to complete our work on developing a generalized framework that can be seamlessly integrated into real-time schedulability analysis
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