Cluster adaptation method to enhance performance of filtering scheme in sensor networks

Sensor networks are the next generation of technology for use in various applications, including tracking, monitoring and control. However, sensor networks still have some inherent security and hardware problems. The cluster routing scheme has been proposed in attempt to reduce duplication reports. Moreover, statistical en-route filtering (SEF) has been proposed to detect and drop the injected fabricated report found in the sensor network. When SEF method is applied in cluster-based sensor networks, their detection capabilities may be quite poor because the proposed schemes do not consider each possible feature that may be present. To solve this problem, we propose a cluster adaptation method to enhance the performance of SEF. The proposed method uses a fuzzy logic approach to form an efficient cluster for SEF. The sufficient performance of the proposed method is shown by the simulation results.