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Verifying network performance of cyber-physical systems with multiple runtime configurations

机译:使用多个运行时配置验证网络 - 物理系统的网络性能

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Modern Cyber-Physical Systems (CPS) must increasingly adapt to changing contexts, like smart cars to changing driving conditions. Thus, design approaches are facing a rapidly growing number of network runtime configurations. With recent approaches this problem can be solved for design space exploration (DSE) by analyzing the network performance of single configurations which are intended to represent the entire runtime variability space. This technique can be applied for DSE since the latter only intends to find an optimized system setup. Yet it does not meet the requirements of network verification, since it does not necessarily find the worst-case for all applications. To solve this, we developed an integrated model, which allows describing runtime variability in the network performance model with a 0-1 linear-fractional program. Thus, we can cover entire runtime variability spaces without analyzing every single network runtime configuration. Although the approach utilizes heuristics, it still guarantees worst-case results. We can show that in comparison to state-of-the-art methods our approach scales for large automotive systems with multiple network configurations. Moreover, our evaluation results highlight the superior capabilities of our method with respect to accuracy and computation time.
机译:现代网络物理系统(CPS)必须越来越适应改变上下文,如智能汽车,以改变驾驶条件。因此,设计方法面临着快速越来越多的网络运行时配置。随着最近的方法,可以通过分析旨在表示整个运行时可变性空间的单个配置的网络性能来解决这个问题的解决方案探索(DSE)。这种技术可以应用于DSE,因为后者仅打算找到优化的系统设置。然而,它不符合网络验证的要求,因为它不一定找到所有应用程序的最坏情况。为了解决这个问题,我们开发了一个集成模型,它允许使用0-1线性分数程序描述网络性能模型中的运行时变异性。因此,我们可以介绍整个运行时变化空间,而无需分析每个网络运行时配置。虽然该方法采用启发式,但它仍然可以保证最坏情况的结果。我们可以表明与最先进的方法相比,我们的方法为具有多个网络配置的大型汽车系统的方法。此外,我们的评估结果突出了我们对准确性和计算时间的方法的优越功能。

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