用于硬实时任务执行的细粒度定时和控制流错误检查

Julian Wolf, Bernhard Fechner, S. Uhrig, T. Ungerer
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引用次数: 10

摘要

健壮性和可靠性是当今嵌入式系统的基本要求。特别是程序控制流程中的错误,例如由瞬态错误引起的错误,可能导致系统行为错误,并可能造成灾难性后果。在过去的几十年里,已经提出了几种控制流检查方法。然而,这些技术主要关注应用程序部分的正确顺序,而不是控制流的正确定时行为,这对于硬实时系统至关重要。在本文中,我们提出了一种新的方法,该方法结合轻量级控制流监测技术,为硬实时系统引入了细粒度在线定时检查。所建议的方法是一种混合硬件软件技术:我们通过添加检查点在编译时检测应用程序代码,检查点包含控制流的时间和逻辑信息。在运行期间,连接到内核的一个小型硬件检查单元读取仪器化的数据,以验证应用程序的控制流和计时行为的正确性。我们机制的细粒度功能允许检测许多瞬态错误,并且具有非常低的检测延迟。不再需要为了监视异常而冗余地执行代码。硬件开销被限制在一个小的检查单元(与处理器核心相比,仅占芯片空间的0.5%);根据实验结果,在平均情况下,执行时间开销仅为10.6%,而内存开销为12.3%。
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Fine-grained timing and control flow error checking for hard real-time task execution
Robustness and reliability are essential requirements of today's embedded systems. Especially errors in the control flow of a program, e.g. caused by transient errors, may lead to a faulty system behavior potentially with catastrophic consequences. Several methods for control flow checking have been proposed during the last decades. However, these techniques mostly focus on a correct sequence of application parts but not on the correct timing behavior of the control flow, which is essential for hard real-time systems. In this paper, we present a new approach which introduces fine-grained on-line timing checks for hard real-time systems combined with a lightweight control flow monitoring technique. The proposed approach is a hybrid hardware-software technique: We instrument the application code at compile-time by adding checkpoints, which contain temporal and logical information of the control flow. During run-time, a small hardware check unit connected to the core reads the instrumented data in order to verify the correctness of the application's control flow and timing behavior. The finegrained functionality of our mechanism allows a detection of many transient errors, associated with very low detection latency. It is no longer necessary to redundantly execute code in order to monitor anomalies. The hardware overhead is limited to a small check unit (only 0.5 % of chip space compared to the processor core); according to experimental results, the execution time overhead is only 10.6 % in the average case while the memory overhead is 12.3 %.
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