On distributed fault-tolerant detection in wireless sensor networks

TLDR

The paper addresses simultaneous noise‑related measurement error and sensor fault mitigation in fault‑tolerant detection, and determines an optimal neighborhood size to conserve energy. It introduces sensor fault probability into the optimal event detection process to form a fault‑tolerant detection scheme. Mathematically, the optimal detection error decreases exponentially with neighborhood size, and experiments using Bayesian and Neyman‑Pearson methods show the algorithm improves detection accuracy while balancing energy usage, enabling energy‑efficient fault‑tolerant detection in wireless sensor networks.

Abstract

In this paper, we consider two important problems for distributed fault-tolerant detection in wireless sensor networks: 1) how to address both the noise-related measurement error and sensor fault simultaneously in fault-tolerant detection and 2) how to choose a proper neighborhood size n for a sensor node in fault correction such that the energy could be conserved. We propose a fault-tolerant detection scheme that explicitly introduces the sensor fault probability into the optimal event detection process. We mathematically show that the optimal detection error decreases exponentially with the increase of the neighborhood size. Experiments with both Bayesian and Neyman-Pearson approaches in simulated sensor networks demonstrate that the proposed algorithm is able to achieve better detection and better balance between detection accuracy and energy usage. Our work makes it possible to perform energy-efficient fault-tolerant detection in a wireless sensor network.