Quantitative Characterization of Event Streams in Analysis of Hard Real-Time Applications
Quantitative Characterization of Event Streams in Analysis of Hard Real-Time Applications
复制标题
硬实时应用分析中事件流的定量表征
DOI：
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发表时间：
2004
期刊：
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通讯作者：
L. Thiele
中科院分区：
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作者：
E. Wandeler;A. Maxiaguine;L. Thiele
许多实时嵌入式系统处理由有限数量的不同事件类型组成的事件流。流上的每个不同事件类型通常会对系统施加不同的工作负载，因此可以利用不同事件类型之间的可能相关性和依赖性的知识来获得完整系统的更严格的分析性能界限。我们提出了一个抽象的流模型来描述这样的事件流。该模型捕获了一类事件流的所有可能轨迹的所需信息。因此，它可以用来获得硬有界的最坏情况和最佳情况下的分析结果的系统。我们将展示如何从一个具体的流规范，以及它如何可以用于性能分析所提出的抽象流模型。我们的方法的适用性和传统的最坏情况下的性能分析的优势，在一个多媒体应用程序的案例研究。
Many real-time embedded systems process event streams that are composed of a finite number of different event types. Each different event type on the stream would typically impose a different workload to the system, and thus the knowledge of possible correlations and dependencies between the different event types could be exploited to get tighter analytic performance bounds of the complete system. We propose an abstract stream model to characterize such an event stream. The model captures the needed information of all possible traces of a class of event streams. Hence, it can be used to obtain hard bounded worst-case and best-case analysis results of a system. We show how the proposed abstract stream model can be obtained from a concrete stream specification, and how it can be used for performance analysis. The applicability of our approach and its advantages over traditional worst-case performance analysis are shown in a case study of a multimedia application.