Reliability analysis of IoV-based vehicle monitoring systems subject to cascading probabilistic common cause failures
研究了车联网车辆监控系统在级联概率共因失效下的可靠性，提出了两种组合方法处理有向无环图和哈密顿环结构的级联效应，并通过实例和蒙特卡洛仿真验证了方法的正确性。
As an important application of the Internet of Things (IoT), Internet of Vehicles (IoV)-based vehicle monitoring systems (IVMSs), gathering, processing and communicating traffic and vehicle data, are installed in vehicles and deployed to avoid traffic accidents and ensure road safety. In this paper, the reliability of IVMSs subject to cascading probabilistic common cause failures (CPCCFs) is studied where a common cause (CC) may cause multiple system devices to fail probabilistically and the failures of some devices may further trigger failures of other system devices in a domino manner. Two combinatorial methods are proposed to handle complex cascading effects of directed acyclic graph structure and Hamilton loop structure, respectively. The proposed methods are applicable to any arbitrary time-to-failure distribution of devices and both external and internal CCs are considered. The applications and advantages of the proposed methods are illustrated through an IVMS example. The correctness of the methods is proved by Monte Carlo simulation. The time and space complexity of the methods is also analyzed.