Anomalous Traffic Filtering Algorithm for Power Wireless Sensor Networks Based on Feature Clustering
Qidi Jiao, Dingding Li, Shuai Cheng Li, Han Liu, Yifan Song · Journal of Physics Conference Series · 2025
Abstract Conventional power wireless sensor network anomalous traffic filtering algorithm measurement structure is generally set as a unidirectional structure, the filtering efficiency is low, resulting in an increase in the absolute error of the filtering measurement, which puts forward the design and analysis of the feature clustering-based power wireless sensor network anomalous traffic filtering algorithm. According to the current measurement requirements, first extract the abnormal traffic features, adopt the multi-order approach to improve the filtering efficiency, design the multi-order power wireless sensing network abnormal traffic filtering measurement structure, based on this, construct the feature clustering network abnormal traffic filtering algorithm model, and use the adaptive checking processing to realize the filtering measurement. The test results show that the absolute error of the final filtering algorithm is well controlled below 0.7, which indicates that the designed abnormal traffic filtering algorithm of electric power wireless sensor network combined with feature clustering is more flexible, versatile, and more targeted, and has practical application value.