A Cellular Automata Based Scheme for Energy Efficient Fault Diagnosis in WSN

The faulty nodes in WSN (Wireless Sensor Network) may badly affect the network performance while trying to reach an agreement on an event. This effectively leads to deviation from the desired outcome and unproductive computational overhead. Identification of network region with faulty nodes is, therefore, a necessity to ensure agreement on an issue/event simultaneously limiting the computational overhead. This work proposes a CA (Cellular Automata) based scheme that can efficiently diagnose the region of faulty nodes in a WSN. The scheme is developed around the special class of CA called SACA. This enables fast identification of faulty region with marginal additional computation and the network bandwidth.