A distributed fault-tolerant algorithm for event detection using heterogeneous wireless sensor networks

Distributed event detection using wireless sensor networks has received growing interest in recent years. In such applications, a large number of inexpensive and unreliable sensor nodes are distributed in a geographical region to make firm and accurate local decisions about the presence or absence of specific events based on their sensor readings. However, sensor readings can be unreliable, due to either noise in the sensor readings or hardware failures in the devices, and may cause nodes to make erroneous local decisions. We present a general fault-tolerant event detection scheme that allows nodes to detect erroneous local decisions based on the local decisions reported by their neighbors. This detection scheme does not assume homogeneity of sensor nodes and can handle cases where nodes have different accuracy levels. We prove analytically that the derived fault-tolerant estimator is optimal under the maximum a posteriori (MAP) criterion. An equivalent weighted voting scheme is also derived. Further, we describe two new error models that take into account the neighbor distance and the geographical distributions of the two decision quorums. These models are particularly suitable for detection applications where the event under consideration is highly localized. Our fault-tolerant estimator is simulated using a network of 1024 nodes deployed randomly in a square region and assigned random probability of failures.