With recent advancements in Internet technologies and wireless communications, wireless sensor network (WSN)-based smart systems are gaining an enormous increase in use in various applications (eg, healthcare, smart home, smart manufacturing, smart power grids, and smart transportation). Due to the mission-critical or safety-critical nature of smart system applications, it is imperative that a smart system be reliable during its mission time. However, reliability analysis and design of smart systems are still open challenging research problems due to complicated dependencies existing in the WSN domain or the physical domain monitored by the WSN, and due to dependencies crossing the two domains. This paper proposes a new behavior-driven reliability modeling methodology for accurate and efficient reliability analysis of complex WSN-based smart systems, contributing toward their robust designs and operations. The suggested method can address effects of dependent behaviors affecting different domains of the smart system in a combinatorial manner. It also enables the use of efficient single-domain reliability methods to retain their efficiency. A case study of a smart home system is performed to demonstrate the application of the proposed method as well as its advantages in handling nonexponential time-to-failure distributions and in analyzing smart systems with complicated intradomain and cross-domain dependencies.

中文翻译：

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一种行为驱动的复杂智能系统可靠性建模方法

随着互联网技术和无线通信的最新进展，基于无线传感器网络 (WSN) 的智能系统在各种应用（例如，医疗保健、智能家居、智能制造、智能电网和智能交通）中的使用量大幅增加。由于智能系统应用程序的关键任务或安全关键性质，智能系统在其任务时间内必须可靠。然而，由于 WSN 域或 WSN 监控的物理域中存在复杂的依赖关系，以及由于跨越两个域的依赖关系，智能系统的可靠性分析和设计仍然是开放的具有挑战性的研究问题。本文提出了一种新的行为驱动的可靠性建模方法，用于对基于 WSN 的复杂智能系统进行准确有效的可靠性分析，有助于其稳健的设计和操作。建议的方法可以以组合方式解决影响智能系统不同领域的依赖行为的影响。它还允许使用高效的单域可靠性方法来保持其效率。对智能家居系统进行了案例研究，以证明所提出方法的应用及其在处理非指数故障时间分布和分析具有复杂域内和跨域依赖关系的智能系统方面的优势。建议的方法可以以组合方式解决影响智能系统不同领域的依赖行为的影响。它还允许使用高效的单域可靠性方法来保持其效率。对智能家居系统进行了案例研究，以证明所提出方法的应用及其在处理非指数故障时间分布和分析具有复杂域内和跨域依赖关系的智能系统方面的优势。建议的方法可以以组合方式解决影响智能系统不同领域的依赖行为的影响。它还允许使用高效的单域可靠性方法来保持其效率。对智能家居系统进行了案例研究，以证明所提出方法的应用及其在处理非指数故障时间分布和分析具有复杂域内和跨域依赖关系的智能系统方面的优势。