具有不可抢占区域的实时多模态fp调度系统分析

Masud Ahmed, P. Hettiarachchi, N. Fisher
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引用次数: 2

摘要

多年来,许多计算设备(如平板电脑、智能手机、GPS接收器)采用了多种硬件和软件操作模式,以有效地利用设备资源。在实时系统(RTS)中也有类似的优势,因为RTS必须及时响应可能偶尔变化的物理环境。一个高效的多模态系统(MMS)也是开发实时控制系统的先决条件,它可以在保证实时任务变化的同时保持稳定的系统行为。然而,对于具有软件/硬件模式的多模态系统,当前可用的固定优先级(FP)可调度性分析在计算上是昂贵的。此外,当前支持模式变化的系统的可调度性分析需要一个通常不适合网络物理系统(CPS)的假设:底层物理设备中的传感和驱动是可先发制人的活动。然而,像雷达发射器/接收器这样的传感器需要在发送和处理返回信号时不可抢占地访问处理器,然后处理返回信号以保证准确性。在本研究中,考虑到特定软硬件模型的优点和局限性,我们开发了一种基于FP算法的多模态RTS调度框架以及伪多项式复杂度的高效可调度性分析。以汽车系统自适应巡航控制为例,通过可调度性比较验证了可调度性分析的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of real-time multi-modal FP-scheduled systems with non-preemptible regions
Over the years, multiple hardware and software operating modes have been employed in many computing devices (e.g., tablets, smart-phones, GPS receivers) to efficiently utilize device resources. Similar advantages are also preferred in realtime systems (RTS) due to the requirement that a RTS must respond in a timely manner to a physical environment that may change sporadically. An efficient multi-modal system (MMS) is also a prerequisite for the development of real-time control systems which can maintain stable system behavior while ensuring timing guarantees for a changing set of real-time tasks. However, the currently-available fixed-priority (FP) schedulability analysis for multi-modal systems with both software/hardware modes is computationally expensive. In addition, current schedulability analysis for systems that support mode changes requires an assumption that is often not suitable for cyber-physical systems (CPS): sensing and actuation in the underlying physical plant are preemptible activities. However, sensors such as radar transmitter/ receiver requires non-preemptible access to the processor upon sending and then processing the return signal for accuracy. In this research, we develop a framework for multi-modal RTS scheduled by FP algorithm along with efficient schedulability analysis with pseudo-polynomial complexity considering the advantages and limitations of specific software/hardware model. Two simulations: a case study on adaptive cruise control in automotive systems, and schedulability comparison are included to corroborate the performance of the schedulability analysis.
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