International Journal on Smart Sensing and Intelligent Systems
Outlier detection plays a crucial role in secure monitoring in Wireless Sensor Networks (WSNs). Moreover, outlier detection techniques in WSN face the problem of limited resources of transmission bandwidth, energy consumption and storage capacity. In this paper, similar flocking model is proposed and a Cluster Algorithm based on Similar Flocking Model (CASFM) is put forward to detect outliers in real-time stream data collected by sensor nodes. The similar flocking model improves the Vicsek model by introducing the similarity between individuals and velocity updating rule, which causes similar objects to cluster quickly.