Compositional Mixed-Criticality Systems with Multiple Executions and Resource-Budgets Model
Compositional Mixed-Criticality Systems with Multiple Executions and Resource-Budgets Model
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DOI：
10.1109/rtas58335.2023.00013
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Abdullah Al Arafat;Sudharsan Vaidhun;Liangkai Liu;Kecheng Yang;Zhishan Guo
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文献类型：
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作者：
Abdullah Al Arafat;Sudharsan Vaidhun;Liangkai Liu;Kecheng Yang;Zhishan Guo
软件可重用性和系统模块化是现代自治系统的关键特征。因此，就像汽车领域的AUTOSAR和机器人领域的ROS2所证明的那样，分层和组合架构正在迅速转变。资源预算供给模型广泛应用于此类系统的实时分析。与此同时，具有多临界水平的实时系统也受到了学术界和工业界的广泛关注。这些系统为多个系统关键级别设计了多个执行预算。现有的混合临界系统研究考虑了专用的资源供应。本文研究了组合系统具有多重执行估计和资源预算供给的一种新的广义系统模型。提出了组合混合临界系统中基于edf调度程序的可调度性分析模型和基于需求约束函数的可调度性检验方法。导出了设置资源供应周期的范围，以确保在供应预算已知时工作负载的可调度性。利用综合工作负载和资源模型进一步论证和评估了调度框架的总体性能及其更广泛的适用性，其中综合工作负载参数是通过对自动驾驶系统的案例研究得出的。
Software reusability and system modularity are key features of modern autonomous systems. As a consequence, there is a rapid shift towards hierarchical and compositional architecture, as evidenced by AUTOSAR in automobiles and ROS2 in robotics. The resource-budget supply model is widely applied in the real-time analysis of such systems. Meanwhile, real-time systems with multiple critical levels have received significant attention from the research community and industry. These systems are designed with multiple execution budgets for multiple system-critical levels. Existing studies on mixedcriticality systems consider a dedicated resource supply. This paper considers a novel generalized system model with multiple execution estimations and resource-budget supplies for compositional systems. An analytical model and a demand-bound function-based schedulability test are presented for the EDFbased scheduler in the proposed compositional mixed-criticality system. A range for setting the resource supply period is derived to ensure the schedulability of workloads when supply budgets are known. The general performance of the scheduling framework and its wider applicability is further demonstrated and evaluated using synthetic workloads and resource models, where synthetic workload parameters are derived through a case study on an autonomous driving system.