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• W1121554985 abstract "This paper studies the reliability modelling of wireless sensor networks (WSNs) with the masked data that are often observed in practice. The masked data are the system failure data when exact subsystems or components causing system failures cannot be identified. When the masked data are observed, however, it is difficult to estimate the WSN reliability since the failure processes of the subnets cannot be decomposed into simple subsystem processes. In this paper, an additive non-homogeneous poisson process (NHPP) model is proposed to describe the failure process of the WSN with subnets. The maximum likelihood estimation (MLE) procedure is developed to estimate the parameters in the proposed model. By applying the given procedure, the WSN reliability estimate can be relatively easy to obtain. A numerical example based on simulation data with random masking is also provided to illustrate the applicability of the methodology." @default.
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• W1121554985 date "2015-01-01" @default.
• W1121554985 modified "2023-10-16" @default.
• W1121554985 title "Wireless sensor network reliability modelling based on masked data" @default.
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• W1121554985 doi "https://doi.org/10.1504/ijsnet.2015.069584" @default.
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