Markov modeling of fault-tolerant wireless sensor networks

Technological advancements in communications and embedded systems have led to the proliferation of wireless sensor networks (WSNs) in a wide variety of application domains. One commonality across all WSN application domains is the need to meet application requirements (e.g., lifetime, reliability, etc.). Many application domains require that sensor nodes be deployed in harsh environments (e.g., ocean floor, active volcanoes), making these sensor nodes more prone to failures. Unfortunately, sensor node failures can be catastrophic for critical or safety related systems. To improve reliability in such systems, we propose a fault-tolerant sensor node model for applications with high reliability requirements. We develop Markov models for characterizing WSN reliability and MTTF (Mean Time to Failure) to facilitate WSN application-specific design. Results show that our proposed fault-tolerant model can result in as high as a 100% MTTF increase and approximately a 350% improvement in reliability over a non-fault-tolerant WSN. Results also highlight the significance of a robust fault detection algorithm to leverage the benefits of fault-tolerant WSNs.