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Execution Stack Management for Hard Real-Time Computation in a Component-Based OS

机译:在基于组件的OS中执行硬实时计算的执行堆栈管理

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In addition to predictability, both reliability and security constraints are increasingly important. Mixed criticality, and open real-time systems execute software of different certification and trust levels. To limit the scope of errant behavior in these systems, a common approach is to raise isolation barriers between software components. However, a thread that executes through multiple components computes on execution stacks spread across each component. As these stacks require backing memory, each component has a finite amount of execution stacks. In this paper, we treat these stacks as shared resources, and investigate the implementation of traditional resource sharing protocols in a real component-based system. We implement multi-resource versions of the Priority Inheritance Protocol (PIP) and Priority Ceiling Protocol (PCP) for these shared stacks and find -- surprisingly -- that neither provide better schedulability characteristics than the other for all system parameterizations. Additionally, we identify the relationship between allocating additional stacks to components, and system schedulability. Given this, we describe and evaluate algorithms to ensure system schedulability while seeking to minimize the amount of memory consumed for stacks.
机译:除了可预测性之外,可靠性和安全性约束也越来越重要。混合关键性和开放实时系统执行具有不同认证和信任级别的软件。为了限制这些系统中错误行为的范围,一种通用的方法是在软件组件之间增加隔离壁垒。但是,通过多个组件执行的线程在跨每个组件的执行堆栈上进行计算。由于这些堆栈需要后备内存,因此每个组件都具有有限数量的执行堆栈。在本文中,我们将这些堆栈视为共享资源,并研究了在实际的基于组件的系统中传统资源共享协议的实现。我们为这些共享堆栈实现了优先级继承协议(PIP)和优先级上限协议(PCP)的多资源版本,令人惊讶的是,对于所有系统参数化,它们都没有提供比其他方法更好的可调度性。此外,我们确定了向组件分配其他堆栈与系统可调度性之间的关系。鉴于此,我们描述并评估算法以确保系统可调度性,同时力求最大程度地减少堆栈消耗的内存量。

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