Non-Preemptive Scheduling for Mixed-Criticality Real-Time Multiprocessor Systems

Baek, Hyeongboo; Jung, Namyong; Chwa, Hoon Sung; Shin, Insik; Lee, Jinkyu

doi:10.1109/tpds.2018.2806443

Cited by 14 publications

(5 citation statements)

References 22 publications

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“…Based on the simulation results, we investigated the effect of our approach on various factors. Non-preemptive [29] or partitioned [2] scheduling will be considered in our future work.…”

Section: Discussionmentioning

confidence: 99%

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

Baek

Kang

2020

Symmetry

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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.

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“…Based on the simulation results, we investigated the effect of our approach on various factors. Non-preemptive [29] or partitioned [2] scheduling will be considered in our future work.…”

Section: Discussionmentioning

confidence: 99%

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

Baek

Kang

2020

Symmetry

Self Cite

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“…Till recently, this classical scheduling problem is deemed to be practically resolved as a heuristic-based algorithm is shown to be able to achieve a rather high runtime schedulability considering real system overheads [10]. Besides this basic system model (i.e., sporadic workloads preemptively scheduled on homogeneous multiprocessor), extensive efforts have been made to handle increasing complexities seen in the task model, such as non-preemptive execution [2], [3], [4], precedence constraints [11], [12], [13], [14], selfsuspensions [15], [16], and mixed-criticality [17], [18], [19], [20], as well as those seen in the hardware platform, such as heterogeneous multiprocessors [21], [22], computing accelerators [23], [24], [25], and shared resources [26], [27], [28]. Unfortunately, although promising progress has been made for dealing with various complexities, many such complexities yield rather pessimistic results.…”

Section: A Real-time Schedulingmentioning

confidence: 99%

“…Unfortunately, although promising progress has been made for dealing with various complexities, many such complexities yield rather pessimistic results. For instance, the non-preemptive scheduling of sporadic task systems on a homogeneous multiprocessor, which merely adds the complexity of non-preemptive execution into the scheduling context, remains largely as an open problem since the state-of-theart schedulability tests [2], [3], [4] may cause significant utilization loss under many settings. When facing a system environment where multiple such complexities are presented, the real-time scheduling problem may become significantly difficult.…”

Section: A Real-time Schedulingmentioning

confidence: 99%

“…Any tiny piece of complexity in either workload (e.g., non-preemption or data dependency) or hardware (e.g., resource heterogeneity) would cause significant pessimism in using existing scheduling disciplines. For instance, the non-preemptive scheduling of sporadic task systems on a homogeneous multiprocessor has shown to be hard [2], [3], [4], where using existing scheduling algorithms may result in unacceptable utilization loss under various scenarios. Adding multiple complexity elements into the real-time scheduling context would make most existing rule-based scheduler design fail.…”

Section: Introductionmentioning

confidence: 99%

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LINTS^RT: A Learning-driven Testbed for Intelligent Scheduling in Embedded Systems

Kong,

Yadlapalli,

Bateni

et al. 2020

Preprint

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Due to the increasing complexity seen in both workloads and hardware resources in state-of-the-art embedded systems, developing efficient real-time schedulers and the corresponding schedulability tests becomes rather challenging. Although close to optimal schedulability performance can be achieved for supporting simple system models in practice, adding any small complexity element into the problem context such as non-preemption or resource heterogeneity would cause significant pessimism, which may not be eliminated by any existing scheduling technique. In this paper, we present LINTS RT , a learning-based testbed for intelligent real-time scheduling, which has the potential to handle various complexities seen in practice. The design of LINTS RT is fundamentally motivated by AlphaGo Zero for playing the board game Go, and specifically addresses several critical challenges due to the real-time scheduling context. We first present a clean design of LINTS RT for supporting the basic case: scheduling sporadic workloads on a homogeneous multiprocessor, and then demonstrate how to easily extend the framework to handle further complexities such as nonpreemption and resource heterogeneity. Both application and OSlevel implementation and evaluation demonstrate that LINTS RT is able to achieve significantly higher runtime schedulability under different settings compared to perhaps the most commonly applied schedulers, global EDF, and RM. To our knowledge, this work is the first attempt to design and implement an extensible learning-based testbed for autonomously making realtime scheduling decisions.

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“…For example, modern automotive systems conduct safety-critical tasks (e.g., wheel steering and breaking systems) as well as mission-critical ones (e.g., the camera and various sensing systems), the various criticalities of which are explicitly categorized in the ISO 26262 standard [7]. Although a mixed-criticality (MC) system should support different criticalities with high CPU utilization, relatively few approaches have been proposed [8][9][10] compared to those for single-criticality (SC) systems.…”

Section: Introductionmentioning

confidence: 99%

Contention-Free Scheduling for Mixed-Criticality Multiprocessor Real-Time System

Baek

Lee

2020

Symmetry

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Zero-laxity (ZL) and contention-free (CF) policies have received considerable attention owing to their simplicity and applicability to real-time systems equipped with symmetry multiprocessors. Recently, the ZL policy for mixed-criticality (MC) systems has been proposed and studied, but the applicability to and performance of the CF policy for MC systems have not been investigated yet. In this paper, we propose the CF policy (as a scheduling policy) for MC symmetry multiprocessor systems, referred to as the MC systems tailored CF policy (MC-CF), and a schedulability analysis in support thereof. We define the notion of contention-free slots for two different criticalities (of MC systems) of tasks, propose a technique to limit the amount to be utilized for each task by defining an upper bound, and subsequently explain the way in which the contention-free slots are systematically utilized to improve the schedulability of MC symmetry multiprocessor systems. Following this, we develop a deadline analysis (DA) for MC-CF. Using our experimental results under various environmental settings, we demonstrate that MC-CF can significantly improve the schedulability of fixed-priority scheduling.

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Non-Preemptive Scheduling for Mixed-Criticality Real-Time Multiprocessor Systems

Cited by 14 publications

References 22 publications

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

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

LINTS^RT: A Learning-driven Testbed for Intelligent Scheduling in Embedded Systems

Contention-Free Scheduling for Mixed-Criticality Multiprocessor Real-Time System

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