7 research outputs found

    A Survey of Research into Mixed Criticality Systems

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    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

    Analysis and simulation of scheduling techniques for real-time embedded multi-core architectures

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    In this modern era of technological progress, multi-core processors have brought significant and consequential improvements in the available processing potential to the world of real-time embedded systems. These improvements impose a rapid increment of software complexity as well as processing demand placed on the underlying hardware. As a consequence, the need for efficient yet predictable multi-core scheduling techniques is on the rise. As part of this thesis, in-depth research of currently available multi-core scheduling techniques, belonging to both partitioned and global approaches, is done in the context of real-time embedded systems. The emphasis is on the degree of their usability on hard real-time systems, focusing on the scheduling techniques offering better processor affinity and the lower number of context switching. Also, an extensive research of currently available real-time test-beds as well as real-time operating systems is performed. Finally, a subset of the analyzed multi-core scheduling techniques comprising PSN-EDF, GSN-EDF, PD2^{2} and PD2∗^{2*} is simulated on the real-time test-bed LITMUSRT^{RT}

    Resource-Efficient Scheduling Of Multiprocessor Mixed-Criticality Real-Time Systems

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    Timing guarantee is critical to ensure the correctness of embedded software systems that interact with the physical environment. As modern embedded real-time systems evolves, they face three challenges: resource constraints, mixed-criticality, and multiprocessors. This dissertation focuses on resource-efficient scheduling techniques for mixed-criticality systems on multiprocessor platforms. While Mixed-Criticality (MC) scheduling has been extensively studied on uniprocessor plat- forms, the problem on multiprocessor platforms has been largely open. Multiprocessor al- gorithms are broadly classified into two categories: global and partitioned. Global schedul- ing approaches use a global run-queue and migrate tasks among processors for improved schedulability. Partitioned scheduling approaches use per processor run-queues and can reduce preemption/migration overheads in real implementation. Existing global scheduling schemes for MC systems have suffered from low schedulability. Our goal in the first work is to improve the schedulability of MC scheduling algorithms. Inspired by the fluid scheduling model in a regular (non-MC) domain, we have developed the MC-Fluid scheduling algo- rithm that executes a task with criticality-dependent rates. We have evaluated MC-Fluid in terms of the processor speedup factor: MC-Fluid is a multiprocessor MC scheduling algo- rithm with a speed factor of 4/3, which is known to be optimal. In other words, MC-Fluid can schedule any feasible mixed-criticality task system if each processor is sped up by a factor of 4/3. Although MC-Fluid is speedup-optimal, it is not directly implementable on multiprocessor platforms of real processors due to the fractional processor assumption where multiple task can be executed on one processor at the same time. In the second work, we have considered the characteristic of a real processor (executing only one task at a time) and have developed the MC-Discrete scheduling algorithm for regular (non-fluid) scheduling platforms. We have shown that MC-Discrete is also speedup-optimal. While our previous two works consider global scheduling approaches, our last work con- siders partitioned scheduling approaches, which are widely used in practice because of low implementation overheads. In addition to partitioned scheduling, the work consid- ers the limitation of conventional MC scheduling algorithms that drops all low-criticality tasks when violating a certain threshold of actual execution times. In practice, the system designer wants to execute the tasks as much as possible. To address the issue, we have de- veloped the MC-ADAPT scheduling framework under uniprocessor platforms to drop as few low-criticality tasks as possible. Extending the framework with partitioned multiprocessor platforms, we further reduce the dropping of low-criticality tasks by allowing migration of low-criticality tasks at the moment of a criticality switch. We have evaluated the quality of task dropping solution in terms of speedup factor. In existing work, the speedup factor has been used to evaluate MC scheduling algorithms in terms of schedulability under the worst-case scheduling scenario. In this work, we apply the speedup factor to evaluate MC scheduling algorithms in terms of the quality of their task dropping solution under various MC scheduling scenarios. We have derived that MC-ADAPT has a speedup factor of 1.618 for task dropping solution

    Adapting Pfair Scheduling for Symmetric Multiprocessors

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    Abstract — We consider the implementation of a Pfair realtime scheduler on a symmetric multiprocessor (SMP). Although SMPs are in many ways well-suited for Pfair scheduling, experimental results presented herein suggest that bus contention resulting from the simultaneous scheduling of all processors can substantially degrade performance. To correct this problem, we propose a staggered model for Pfair scheduling that strives to improve performance by more evenly distributing bus traffic over time. Additional simulations and experiments with a scheduler prototype are presented to demonstrate the effectiveness of the staggering approach. In addition, we discuss other techniques for improving performance while maintaining worst-case predictability. Finally, we present an efficient scheduling algorithm to support the proposed model and briefly explain how existing Pfair results apply to staggered scheduling

    SCHEDULING REAL-TIME GRAPH-BASED WORKLOADS

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    Developments in the semiconductor industry in the previous decades have made possible computing platforms with very large computing capacities that, in turn, have stimulated the rapid progress of computationally intensive computer vision (CV) algorithms with highly parallelizable structure (often represented as graphs). Applications using such algorithms are the foundation for the transformation of semi-autonomous systems (e.g., advanced driver-assist systems) to future fully-autonomous systems (e.g., self-driving cars). Enabling mass-produced safety-critical systems with full autonomy requires real-time execution guarantees as a part of system certification.Since multiple CV applications may need to share the same hardware platform due to size, weight, power, and cost constraints, system component isolation is necessary to avoid explosive interference growth that breaks all execution guarantees. Existing software certification processes achieve component isolation through time partitioning, which can be broken by accelerator usage, which is essential for high-efficacy CV algorithms.The goal of this dissertation is to make a first step towards providing real-time guarantees for safety-critical systems by analyzing the scheduling of highly parallel accelerator-using workloads isolated in system components. The specific contributions are threefold.First, a general method for graph-based workloads’ response-time-bound reduction through graph structure modifications is introduced, leading to significant response-time-bound reductions. Second, a generalized real-time task model is introduced that enables real-time response-time bounds for a wider range of graph-based workloads. A proposed response-time analysis for the introduced model accounts for potential accelerator usage within tasks. Third, a scheduling approach for graph-based workloads in a single system component is proposed that ensures the temporal isolation of system components. A response-time analysis for workloads with accelerator usage is presented alongside a non-mandatory schedulability-improvement step. This approach can help to enable component-wise certification in the considered systems.Doctor of Philosoph

    Adapting Pfair Scheduling for Symmetric Multiprocessors

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    Abstract — We consider the implementation of a Pfair realtime scheduler on a symmetric multiprocessor (SMP). Although SMPs are in many ways well-suited for Pfair scheduling, experimental results presented herein suggest that bus contention resulting from the simultaneous scheduling of all processors can substantially degrade performance. To correct this problem, we propose a staggered model for Pfair scheduling that strives to improve performance by more evenly distributing bus traffic over time. Additional simulations and experiments with a scheduler prototype are presented to demonstrate the effectiveness of the staggering approach. In addition, we discuss other techniques for improving performance while maintaining worst-case predictability. Finally, we present an efficient scheduling algorithm to support the proposed model and briefly explain how existing Pfair results apply to staggered scheduling

    Scheduling and locking in multiprocessor real-time operating systems

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    With the widespread adoption of multicore architectures, multiprocessors are now a standard deployment platform for (soft) real-time applications. This dissertation addresses two questions fundamental to the design of multicore-ready real-time operating systems: (1) Which scheduling policies offer the greatest flexibility in satisfying temporal constraints; and (2) which locking algorithms should be used to avoid unpredictable delays? With regard to Question 1, LITMUSRT, a real-time extension of the Linux kernel, is presented and its design is discussed in detail. Notably, LITMUSRT implements link-based scheduling, a novel approach to controlling blocking due to non-preemptive sections. Each implemented scheduler (22 configurations in total) is evaluated under consideration of overheads on a 24-core Intel Xeon platform. The experiments show that partitioned earliest-deadline first (EDF) scheduling is generally preferable in a hard real-time setting, whereas global and clustered EDF scheduling are effective in a soft real-time setting. With regard to Question 2, real-time locking protocols are required to ensure that the maximum delay due to priority inversion can be bounded a priori. Several spinlock- and semaphore-based multiprocessor real-time locking protocols for mutual exclusion (mutex), reader-writer (RW) exclusion, and k-exclusion are proposed and analyzed. A new category of RW locks suited to worst-case analysis, termed phase-fair locks, is proposed and three efficient phase-fair spinlock implementations are provided (one with few atomic operations, one with low space requirements, and one with constant RMR complexity). Maximum priority-inversion blocking is proposed as a natural complexity measure for semaphore protocols. It is shown that there are two classes of schedulability analysis, namely suspension-oblivious and suspension-aware analysis, that yield two different lower bounds on blocking. Five asymptotically optimal locking protocols are designed and analyzed: a family of mutex, RW, and k-exclusion protocols for global, partitioned, and clustered scheduling that are asymptotically optimal in the suspension-oblivious case, and a mutex protocol for partitioned scheduling that is asymptotically optimal in the suspension-aware case. A LITMUSRT-based empirical evaluation is presented that shows these protocols to be practical
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