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Resilient monitoring in self-adaptive systems through behavioral parameter estimation
Journal of Systems Architecture ( IF 3.7 ) Pub Date : 2021-05-24 , DOI: 10.1016/j.sysarc.2021.102177
Mehran Alidoost Nia , Mehdi Kargahi , Alessandro Abate

Cyber-physical systems need self-adaptation as a mean to autonomously deal with changes. For runtime adaptation, a cyber-physical system repeatedly monitors the environment for detecting possible changes. Faults in the monitoring devices due to the dynamic and uncertain environment is very likely, necessitating resilient monitoring. In this paper, we discuss imperfect monitoring in self-adaptive systems, and propose a model-driven methodology to represent the self-adaptive system using a parametric Markov decision process, where the changes are reflected by a set of model parameters. Fault in the monitoring device may result in some parameter valuation miss. We propose a comprehensive framework for parameter estimation using behavioral patterns of the system implemented by a pattern-matching component. The proposed method simulates the current behavior of the system using random walk patterns, and matches it to a history of patterns for estimating the valuation of the omitted data. The results show that the accuracy of the framework is evaluated about 96% under imperfect monitoring. In addition, we elaborate a set of theoretical proofs to support rigorous error analysis, and determine a certain upper-bound of errors to guarantee an accurate decision-making outcome. We establish a logical connection between the error and the accuracy of decisions, and introduce tolerable error metric that is used to guarantee the accuracy of decisions under estimation.



中文翻译:

通过行为参数估计在自适应系统中进行弹性监控

信息物理系统需要自适应作为自主处理变化的手段。对于运行时适应,网络物理系统反复监视环境以检测可能的变化。由于动态和不确定的环境,监控设备很可能出现故障,需要弹性监控。在本文中,我们讨论了自适应系统中的不完善监控,并提出了一种模型驱动的方法来使用参数马尔可夫决策过程来表示自适应系统,其中的变化由一组模型参数反映。监控设备中的故障可能会导致某些参数评估丢失。我们提出了一个使用由模式匹配组件实现的系统行为模式的参数估计综合框架。所提出的方法使用随机游走模式模拟系统的当前行为,并将其与模式历史相匹配,以估计遗漏数据的估值。结果表明,在不完善的监测下,评估框架的准确率约为 96%。此外,我们阐述了一套理论证明来支持严格的误差分析,并确定一定的误差上限以保证准确的决策结果。我们在误差和决策准确性之间建立逻辑联系,并引入可容忍误差度量,用于保证估计决策的准确性。结果表明,在不完善的监测下,评估框架的准确率约为 96%。此外,我们阐述了一套理论证明来支持严格的误差分析,并确定一定的误差上限以保证准确的决策结果。我们在误差和决策准确性之间建立了逻辑联系,并引入了用于保证估计决策准确性的可容忍误差度量。结果表明,在不完善的监测下,评估框架的准确率约为 96%。此外,我们阐述了一套理论证明来支持严格的误差分析,并确定一定的误差上限以保证准确的决策结果。我们在误差和决策准确性之间建立了逻辑联系,并引入了用于保证估计决策准确性的可容忍误差度量。

更新日期:2021-06-30
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