中央计算平台混合关键系统模型研究

Theoretical Modeling Research on Mixed Criticality System for Central Computing Platforms

  • 摘要: 为解决不同关键级任务在中央计算平台上部署时因安全隔离需求所带来的资源浪费与共享原则所要求的高效资源利用的矛盾,基于混合关键系统理论提出了车辆多模式混合关键系统模型(AMMMCS)与车辆自适应混合关键系统模型(AAMCS)及其降级策略.AMMMCS方法保障行车安全的高关键级任务的执行情况下对低关键级任务的执行采取相对积极的调度,AAMCS方法保障车辆控制任务不超过阈值条件下保障所有任务的执行以最大程度提升效率. 在FreeRTOS系统上实现了SMC-NO、AMC、AMMMCS、AAMCS模型的部署并进行了硬件在环实验,结果表明所提方法能显著提升任务的履行率与处理器资源利用率.

     

    Abstract: To address the conflict between the resource waste caused by the necessity for safety isolation and the efficient resource utilization required by the principle of sharing when deploying tasks of different criticality on a central computing platform, an Automotive Multi Mode Mixed Criticality System (AMMMCS) and an Automotive Adaptive Mixed Criticality System (AAMCS), along with their respective degradation strategies, were proposed based on mixed-criticality theory. The AMMMCS was arranged for low-criticality tasks to adopt a relatively proactive scheduling during the high-criticality task executions for driving safety. The AAMCS was designed to ensure the execution of all tasks with maximize efficiency as long as vehicle control tasks within the threshold. The SMC-NO, AMC, AMMMCS, and AAMCS models were arranged on the FreeRTOS system and the Hardware-in-the-Loop experiments were carried out. The results show that the proposed methods can significantly improve task fulfillment rates and processor resource utilization.

     

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