Wireless sensor networks (WSNs) have been used widely across various industries and business fields that require the coverage of large geographical regions that are difficult for humans to reach. It is therefore important to be able to model, assess, and predict the reliability of WSNs. Masked data is a type of missing data used to represent system failure when the exact cause of the failure is unknown. This paper proposed a novel additive reliability model for a cluster-based WSN system using general masked data and uses the expectation maximization (EM) algorithm to solve the problem of the maximum likelihood estimation (MLE). Moreover, the proposed model assumes that a WSN comprises several clusters, and the failure processes of these clusters are independent. The probability characteristics of the system are determined according to the topology of the WSN system to evaluate the system reliability. Finally, the proposed model is demonstrated to be powerful for estimating WSN system reliability using a simulated dataset.

中文翻译：

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基于期望最大化算法的新型基于集群的无线传感器网络可靠性模型

无线传感器网络（WSN）已广泛用于需要覆盖人类难以到达的较大地理区域的各个行业和商业领域。因此，重要的是能够建模，评估和预测WSN的可靠性。屏蔽数据是一种丢失的数据，用于在故障的确切原因未知的情况下表示系统故障。本文提出了一种基于通用屏蔽数据的基于集群的无线传感器网络的加性可靠性模型，并采用期望最大化算法解决了最大似然估计问题。此外，所提出的模型假设WSN包含多个群集，并且这些群集的故障过程是独立的。根据WSN系统的拓扑确定系统的概率特性，以评估系统的可靠性。最后，证明了所提出的模型对于使用模拟数据集估计WSN系统可靠性具有强大的功能。