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REDUCING THE MEMORY FOOTPRINT OF OSEK-BASED SYSTEMS VIA STACK SHARING AND LIGHT-WEIGHT READY QUEUES

机译:通过堆栈共享和轻量级就绪队列减少基于OSEK的系统的内存足迹

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摘要

OSEK OS (Offene Systeme und deren Schnittstellen fur die Elektronik in Kraftfahrzeugen Operating System) is an open, real-time operating system standard for ECU software in vehicles. Because it was originally designed to be used in an extremely resource-constrained environment, an OSEK-compliant operating system must incur low processing overhead and memory usage. Unfortunately, as OSEK OS has evolved over time, it now specifies nontrivial kernel features along with multiple conformance classes and application modes. This may lead to unwanted dynamic resource usage in a system using OSEK OS unless the standard is carefully interpreted and designed into an OSEK OS implementation. In this paper, we analyzed the various kernel features of OSEK OS and their interactions to identify areas in the standard that warrant further resource usage optimization. In particular, we attempted to reduce the run-time memory footprint. Based on our analyses, we present two kernel mechanisms: (1) stack sharing among tasks and (2) light-weight ready queue handling specialized for OSEK OS conformance classes. We also offer implementation methods for the proposed mechanisms by extending OIL and associated tools. Finally, we show the effectiveness of the proposed mechanisms via extensive experiments. Our mechanisms allow OSEK-based systems to use only 36% of the memory requirements of conventional OSEK-based systems on average.
机译:OSEK OS(Kraftfahrzeugen操作系统中的Offene Systeme and deren Schnittstellen fur Elektronik)是一种用于车辆ECU软件的开放实时操作系统标准。因为它最初被设计为在极其资源受限的环境中使用,所以符合OSEK的操作系统必须降低处理开销和内存使用率。不幸的是,随着OSEK OS的发展,它现在指定了重要的内核功能以及多个一致性类和应用程序模式。除非仔细地将标准解释并设计到OSEK OS实施中,否则这可能导致使用OSEK OS的系统中不必要的动态资源使用。在本文中,我们分析了OSEK OS的各种内核功能及其相互作用,以确定标准中需要进一步优化资源使用的区域。特别是,我们尝试减少运行时内存占用。基于我们的分析,我们提出了两种内核机制:(1)任务之间的堆栈共享;(2)专用于OSEK OS一致性类的轻量级就绪队列处理。我们还通过扩展OIL和相关工具,为所提出的机制提供了实现方法。最后,我们通过大量实验证明了所提出机制的有效性。我们的机制允许基于OSEK的系统平均仅使用常规基于OSEK的系统的36%的内存需求。

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