TypicalCPA - Typical Worst Case Compositional Performance Analysis

控制工程和通信技术中的许多应用程序对于有限数量的截止日期未命中是稳健的。这种稳健性可以被用于嵌入式系统的有效尺寸划分。但是，需要对计时行为进行正式验证，以检查最后期限未命中的最大频率。实现这一验证任务是当前项目的主题：对于具有异质组件的复杂嵌入式系统，需要形式化地推导出(m，k)-保证。(m，k)-保证表明，在k个连续执行中，不超过m个连续执行受到最后期限未命中的影响。在本项目中，我们致力于深入了解瞬时过载系统的行为。在第一个项目阶段，现有的单组件(m，k)验证方法在被集成到现有的组成性能分析(CPA)框架之前得到了显著的改进。为此，单个组件分析之间的耦合机制被逐步扩展为“典型的最坏情况组合性能分析(TypicalCPA)”。对于实际可用的系统分析，仍然缺乏的是具有过载的事件模型的有效传播和端到端度量的推导。然后，将结果用于开发(m，k)系统设计。在新阶段的第一步，应对耦合机构的计算进行优化，以提高(m，k)保证的精度。组件相关分析的耦合源于激活事件在系统中的流动。我们想要考虑这样一个事实，即激活事件的性质在通过系统传播时可以改变，从而根据时间和地点的不同，它是否是过载的原因。所得结果将有助于研究过载在系统中的时空传播。随后，提出了考虑各种激活语义的端到端系统指标的定义和计算。这包括计算系统中由于(m，k)损失引起的相对数据年龄的变化和相对数据年龄的离散度。此外，应优化系统设计，以实现要求的(m，k)保证。对所获得结果的总结详细评估应基于工业案例研究，并继续关注以太主干网络以及合成测试用例，其中应提供关于具有瞬时过载行为的测试系统的自动生成的新结果。

Numerous applications in control engineering and communication technology are robust towards a limited number of deadline misses. This robustness can be exploited for the efficient dimensioning of embedded systems. However, a formal verification of the timing behavior is required, which checks the maximum frequency of deadline misses. Realizing this verification task is subject of the current project: For complex embedded systems with heterogeneous components so called (m,k)-guarantees shall be formally derived. The (m,k)-guarantees indicate that no more than m out of k consecutive executions are affected by a deadline miss. In the current project, we strive to gain an in-depth understanding of the behavior of transiently overloaded systems.In the first project phase the available single component (m,k)-verification method was significantly improved before it was integrated in the existing Compositional Performance Analysis (CPA) framework. For this purpose, the coupling mechanisms between the individual component analyses were gradually extended to a „Typical Worst Case Compositional Performance Analysis (TypicalCPA)“.What is still missing towards a practically usable system analysis is the efficient propagation of event models with overload and the derivation of end-to-end metrics. The results shall, then, be used to develop an (m,k) system design. In the first step of the new phase, the computation of the coupling mechanisms shall be optimized, in order to increase the accuracy of the (m,k)-guarantees. The coupling of component-related analyses results from the flow of activation events through the system. We want to consider the fact that the nature of an activation event can change while being propagated through the system, such that - depending on time and place – it is cause of overload or not. The obtained results will allow investigating the spatial and temporal propagation of overload in the system. Subsequently, the definition and computation of end-to-end system metrics under consideration of various activation semantics shall be advanced. This includes computing the change of the relative data age and the dispersion of the relative data age in the system due to (m,k)-losses. Moreover, the system design shall be optimized, such that demanding (m,k)-guarantees can be realized.The concluding detailed evaluation of the obtained results shall be based on industrial case studies, with a continued focus on Ethernet-backbone networks, as well as on synthetic test cases, where new results shall be provided with respect to the automatic generation of test systems with transient overload behavior.