Prediction and research of data traffics of wireless sensor networks based on RBF neural networks

With the quick development of wireless sensor networks, the security issue of data traffics in wireless sensor network is becoming more and more important. In this paper, nonlinear chaos theory and RBF Neural Networks are applied in modeling and forecasting traffic of wireless sensor network (WSN). The researches demonstrate that the data traffics of WSN can be predicted in precision range under some conditions. This provides a powerful support to apply WSN. Finally, simulation results and analysis are presented.