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Modeling structured event streams in system level performance analysis

机译:在系统级性能分析中对结构化事件流建模

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This paper extends the methodology of analytic real-time analysis of distributed embedded systems towards merging and extracting sub-streams based on event type information. For example, one may first merge a set of given event streams, then process them jointly and finally decompose them into separate streams again. In other words, data streams can be hierarchically composed into higher level event streams and decomposed later on again. The proposed technique is strictly compositional, hence highly suited for being embedded into well known performance evaluation frameworks such as Symta/S and MPA (Modular Performance Analysis). It is based on a novel characterization of structured event streams which we denote as Event Count Curves. They characterize the structure of event streams in which the individual events belong to a finite number of classes. This new concept avoids the explicit maintenance of streamindividual information when routing a composed stream through a network of system components. Nevertheless it allows an arbitrary composition and decomposition of sub-streams at any stage of the distributed event processing. For evaluating our approach we analyze a realistic case-study and compare the obtained results with other existing techniques.
机译:本文将分布式嵌入式系统的实时分析性分析方法扩展为基于事件类型信息合并和提取子流。例如,可以先合并一组给定的事件流,然后对其进行联合处理,最后再次将其分解为单独的流。换句话说,数据流可以按层次结构组合成更高级别的事件流,并在以后再次分解。所提出的技术严格地是组成性的,因此非常适合嵌入到众所周知的性能评估框架中,例如Symta / S和MPA(模块化性能分析)。它基于结构化事件流的新颖特征,我们将其表示为事件计数曲线。它们描述了事件流的结构,其中各个事件属于有限数量的类。当通过系统组件网络路由组成的流时,此新概念避免了显式维护流个体信息。但是,它允许在分布式事件处理的任何阶段任意组合和分解子流。为了评估我们的方法,我们分析了一个实际的案例研究,并将获得的结果与其他现有技术进行了比较。

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