End-to-End Timing Analysis of Sporadic Cause-Effect Chains in Distributed Systems
End-to-End Timing Analysis of Sporadic Cause-Effect Chains in Distributed Systems
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DOI：
10.1145/3358181
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
M. Dürr;G. V. D. Brüggen;Kuan-Hsun Chen;Jian-Jia Chen
中科院分区：
文献类型：
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作者：
M. Dürr;G. V. D. Brüggen;Kuan-Hsun Chen;Jian-Jia Chen
因果链用于定义依赖于数据的任务的逻辑顺序，该顺序独立于（周期性/零星）任务的作业的执行顺序。在嵌入式控制系统中，分析与因果链相关的最坏端到端时序行为是一个重要问题。例如，现代汽车系统的详细定时特性在AUTOSAR定时扩展中规定。在本文中，我们提出了一个正式的分布式系统的端到端时序分析。我们考虑两个最重要的端到端时序语义，即，按钮到动作的延迟（称为最大反应时间）和最坏情况下的数据新鲜度（称为最大数据年龄）。由于考虑了工作激活的零星行为，我们的贡献是重要的，而文献中的结果大多局限于周期性激活。证明策略显示了（以前未探索的）反应时间（分别为数据时代）和直接向前（分别为向后）作业链之间的联系。我们的分析结果主导了分布式系统中零星任务激活的最新技术，并且评估显示了合成任务系统以及真实世界汽车基准设置的明显改进。
A cause-effect chain is used to define the logical order of data dependent tasks, which is independent from the execution order of the jobs of the (periodic/sporadic) tasks. Analyzing the worst-case End-to-End timing behavior, associated to a cause-effect chain, is an important problem in embedded control systems. For example, the detailed timing properties of modern automotive systems are specified in the AUTOSAR Timing Extensions. In this paper, we present a formal End-to-End timing analysis for distributed systems. We consider the two most important End-to-End timing semantics, i.e., the button-to-action delay (termed as the maximum reaction time) and the worst-case data freshness (termed as the maximum data age). Our contribution is significant due to the consideration of the sporadic behavior of job activations, whilst the results in the literature have been mostly limited to periodic activations. The proof strategy shows the (previously unexplored) connection between the reaction time (data age, respectively) and immediate forward (backward, respectively) job chains. Our analytical results dominate the state of the art for sporadic task activations in distributed systems and the evaluations show a clear improvement for synthesized task systems as well as for a real world automotive benchmark setting.