Sensitivity analysis of complex embedded real-time systems
Sensitivity analysis of complex embedded real-time systems
复制标题
复杂嵌入式实时系统的灵敏度分析
DOI：
10.1007/s11241-007-9039-9
复制
发表时间：
2008
影响因子：
1.3
通讯作者：
R. Ernst
中科院分区：
文献类型：
--
作者：
R. Racu;A. Hamann;R. Ernst
摘要
体系结构对变化的健壮性是设计高效可靠的最先进的嵌入式实时系统的主要考虑因素。健壮性在设计过程中很重要，可以确定系统是否能够适应以后的更改或更新，以及在多大程度上可以适应，或者它是否可以在下一代产品中重复使用。在产品生命周期中，健壮性帮助设计人员执行因产品更新、新组件和子系统的集成或环境修改而产生的更改。在本文中，我们将健壮性定义为性能储备，即在系统无法满足时间要求之前的性能松弛。这是以设计灵敏度来衡量的。由于复杂的部件交互、资源共享和功能依赖，一维灵敏度分析可能不能涵盖一个系统属性的修改对系统性能的所有影响。一个原因是，一个属性的变化也会影响其他系统属性的值，因此需要新的方法来跟踪同时发生的参数更改。本文提出了一个实时系统一维和多维灵敏度分析的框架。该框架基于可扩展到大型系统的组成分析。一维灵敏度分析结合了二进制搜索技术和从实时调度理论导出的一组形式方程。多维敏感度分析引擎由扩展一维方法的精确算法和基于进化搜索技术的随机算法组成。
Abstract
The robustness of an architecture to changes is a major concern in the design of efficient and reliable state-of-the-art embedded real-time systems. Robustness is important during design process to identify if and in how far a system can accommodate later changes or updates, or whether it can be reused in a next generation product. In the product life-cycle, robustness helps the designer to perform changes as a result of product updates, integration of new components and subsystems, or modifications of the environment. In this paper we determine robustness as a performance reserve, the slack in performance before a system fails to meet timing requirements. This is measured as design sensitivity. Due to complex component interactions, resource sharing and functional dependencies, one-dimensional sensitivity analysis might not cover all effects that modifications of one system property may have on system performance. One reason is that the variation of one property can also affect the values of other system properties requiring new approaches to keep track of simultaneous parameter changes. In this paper we present a framework for one-dimensional and multi-dimensional sensitivity analysis of real-time systems. The framework is based on compositional analysis that is scalable to large systems. The one-dimensional sensitivity analysis combines a binary search technique with a set of formal equations derived from the real-time scheduling theory. The multi-dimensional sensitivity analysis engine consists of an exact algorithm that extends the one-dimensional approach, and a stochastic algorithm based on evolutionary search techniques.