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A Unified Framework for Period and Priority Optimization in Distributed Hard Real-Time Systems

机译:分布式硬实时系统中时间和优先级优化的统一框架

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摘要

Modern embedded systems, such as automotive, are physically distributed with an increasing number of microcontrollers and buses. They support complex functions such as active safety and autonomous driving features with a high degree of data dependencies. The most common configuration uses periodic activation of tasks and messages coupled with priority-based scheduling. Selecting task and message parameters so that end-to-end deadlines are met can be very challenging, since such deadlines are enforced across a set of microcontrollers and buses. In this paper, we address the problem of optimal selection of task and message activation periods and priorities. Existing approaches cannot scale to large designs and have to settle to optimize period or priority separately, largely due to the complexity of response time analysis techniques. Instead, we present a new, unified framework that simultaneously optimizes period and priority assignment. It avoids the pitfalls of existing approaches by abstracting the response time calculation with the new concept of maximal unschedulable period and deadline assignment. We demonstrate with two industrial case studies that our approach runs magnitudes faster than existing approach on period optimization, while providing substantially better solutions.
机译:现代的嵌入式系统(例如汽车)在物理上分布着越来越多的微控制器和总线。它们支持复杂的功能,例如主动安全性和具有高度数据依赖性的自动驾驶功能。最常见的配置使用定期激活任务和消息以及基于优先级的计划。选择任务和消息参数以便满足端到端的期限可能是非常具有挑战性的,因为此类期限是在一组微控制器和总线上强制执行的。在本文中,我们解决了任务和消息激活周期以及优先级的最佳选择问题。由于响应时间分析技术的复杂性,现有方法无法扩展到大型设计,而必须单独解决以优化周期或优先级。相反,我们提出了一个新的统一框架,该框架可以同时优化期限和优先级分配。它通过使用最大不可计划的期限和期限分配的新概念来抽象响应时间计算,从而避免了现有方法的陷阱。我们通过两个工业案例研究证明,在周期优化方面,我们的方法比现有方法运行速度更快,同时提供了更好的解决方案。

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