TIBFIT: trust index based fault tolerance for arbitrary data faults in sensor networks

Since sensor data gathering is the primary functionality of sensor networks, it is important to provide a fault tolerant method for reasoning about sensed events in the face of arbitrary failures of nodes sending in the event reports. In this paper, we propose a protocol called TIBFIT to diagnose and mask arbitrary node failures in an event-driven wireless sensor network. In our system model, sensor nodes are organized into clusters with rotating cluster heads. The nodes, including the cluster head, can fail in an arbitrary manner generating missed event reports, false reports, or wrong location reports. Correct nodes are also allowed to make occasional natural errors. Each node is assigned a trust index to indicate its track record in reporting past events correctly. The cluster head analyzes the event reports using the trust index and makes event decisions. TIBFIT is analyzed and simulated using the network simulator ns-2 and its coverage evaluated with a varying number and varying intelligence of the malicious nodes. We show that once TIBFIT gathers enough system state, accurate event detection is possible even if more than 50% of the network nodes are compromised.