Stochastic Fault Trees for cross-layer power management of WSN monitoring systems

Critical systems require supervising infrastructures to keep their unreliability under control. We propose safety-critical systems to be modeled through a fault-tolerant architecture based on Stochastic Fault Trees (SFTs) and we refer to a scenario where the monitoring infrastructure is a Wireless Sensor Network (WSN). SFTs associate the failure time of leaf events with a non-Markovian (GEN) cumulative distribution function (CDF) and support the evaluation of system unreliability over time. In the reference scenario, the SFT model dynamically updates system unreliability according to samples delivered by the WSN, it maintains a dynamic measure of the safe time-horizon within which the system is expected to operate under a given threshold of unreliability, and it also provides the WSN with a measure of the contribution of each basic event to system unreliability.

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