多个相互作用的故障的同时序贯检测
Simultaneous Sequential Detection of Multiple Interacting Faults
AI总结：
针对分布式系统中多个相互作用的故障，提出一种基于复合停止规则的序贯检测算法，并在贝叶斯框架下证明其渐近最优性。
摘要：
单故障序贯变点问题对于大型分布式系统（如传感器网络）中各种现象的建模变得重要。但在许多情况下，此类系统存在多个相互作用的故障。例如，网络中的单个传感器可能发生故障，通过比较传感器之间的测量值进行检测，导致故障之间存在统计依赖性。我们提出了分布式系统中多个相互作用故障的新公式。该公式包括组成大型系统的各个子系统可能故障的方式、这些子系统之间可以共享的信息以及故障之间的交互模式。然后，我们指定了一种新的序贯算法来检测这些故障。该算法的主要特点是它使用依赖于其他子系统决策的子系统复合停止规则。我们在贝叶斯设置下对该算法进行了渐近虚警和检测延迟分析，并表明在某些条件下该算法是最优的。分析方法依赖于停止时间之间新颖的详细比较技术。我们通过一些仿真验证了该方法。
英文摘要：
Single fault sequential change point problems have become important in modeling for various phenomena in large distributed systems, such as sensor networks. But such systems in many situations present multiple interacting faults. For example, individual sensors in a network may fail and detection is performed by comparing measurements between sensors, resulting in statistical dependency among faults. We present a new formulation for multiple interacting faults in a distributed system. The formulation includes specifications of how individual subsystems composing the large system may fail, the information that can be shared among these subsystems and the interaction pattern between faults. We then specify a new sequential algorithm for detecting these faults. The main feature of the algorithm is that it uses composite stopping rules for a subsystem that depend on the decision of other subsystems. We provide asymptotic false alarm and detection delay analysis for this algorithm in the Bayesian setting and show that under certain conditions the algorithm is optimal. The analysis methodology relies on novel detailed comparison techniques between stopping times. We validate the approach with some simulations.
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