混合临界系统中多规划的混合调度机制

Mohammad Bawatna, Behnaz Ranjbar, Akash Kumar
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引用次数: 0

摘要

在过去的十年中,商用现货(COTS)平台的快速发展导致安全关键系统朝着在共享硬件平台中集成具有不同临界级别的任务和应用程序的方向发展,即混合临界系统(MCS)。因此,基于一种常用的模型,即Vestal模型,提出了几种调度算法和方法。然而,在符合认证要求的情况下,将软件功能整合到共享处理器上不能直接在实际应用程序和工业系统中实现。现有的调度方法并没有提供一种简单的解决方案来消除不同临界级别任务之间对共享处理资源的干扰影响。此外,系统模式切换保证了高临界任务的时间约束和低临界任务的终止。在本文中,我们开发了一种新的基于轮询技术的调度算法来解决这些挑战,提高了整体的可调度性。我们将提出的算法与学术界和工业界现有的调度算法进行了比较,并进行了大量的实验来评估它。我们的结果表明,与传统的最早截止日期优先与虚拟截止日期(EDF-VD)和固定优先级抢占(FPP)调度方法相比,可调度性分别从0.8%提高到14.0%和2.7%提高到10.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Scheduling Mechanism for Multi-programming in Mixed-Criticality Systems
In the last decade, the rapid evolution of the Commercial-Off-The-Shelf (COTS) platforms led safety-critical systems towards integrating tasks and applications with different criticality levels in a shared hardware platform, i.e., Mixed-Criticality Systems (MCS)s. Therefore, several scheduling algorithms and approaches have been proposed upon a commonly used model, i.e., Vestal's model. However, consolidating software functions onto shared processors cannot be implemented directly in real-life applications and industrial systems while complying with certification requirements. The existing scheduling approaches do not provide a simple solution for eliminating the interference effect among the tasks with different criticality levels on the shared processing resources. Moreover, the system mode switch guarantees the timing constraints of the high-criticality tasks throw the termination of the low-criticality tasks. In this paper, we developed a new scheduling algorithm that addresses these challenges based on the round-robin technique, which improves the overall schedulability. We compared the proposed algorithm against existing scheduling algorithms in both academia and industry using extensive experiments to evaluate it. Our results show improvements in the schedulability from 0.8% to 14.0% and from 2.7% to 10.7% compared to the conventional Earliest Deadline First with Virtual Deadline (EDF-VD) and Fixed Priority Preemptive (FPP) scheduling approaches, respectively.
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