An abnormal area scanning for scalable and energy-efficient and secure SensorNet management

Wireless Sensor Networks (WSNs) is a very attractive technique for a variety of applications due to many merits such as compact form, low-power and potential low cost. However, the more the number of sensor node is increased, the more difficult the manager monitors WSNs individually. And faults such as the malfunction of the sensor device itself are common due to the vulnerable security. Therefore, a new approach to manage secure sensorNet considering scalability, energy-efficiency and faulty tendency is needed. Therefore, we propose an abnormal area scanning algorithm using spatial, temporal correlation and in-network aggregation for scalable and energy-efficient secure sensorNet management. Simulations show that our scheme has good scalability and energy-efficiency characteristics, compared to the previous scheme and it can clearly identify the abnormal sensors with high accuracy even in the existence of normal sensors, abnormal sensor and event-detecting sensors.