Accurate identification technique of access path information for hierarchical geographic traffic network under big data construction

摘要

The traditional identification method of access path information requires a lot of data packets and uses a fixed probability, and the identification accuracy is low. To this end, a new method for accurate identification of access path information of hierarchical geographic traffic network is proposed. The access path information is marked with a certain probability, and part of the access path information of the corresponding router is recorded. According to the collected data packet, the accessed node reconstructs the path by using the access path information identified in the packet, to determine the identity range selection and identification format. According to the big data, the hierarchical geographic traffic network router is constructed. According to P_2, it is judged whether the current data packet is identified, and the identification result is judged by P_1. The particle cluster algorithm is used to optimize the identification result of the parameter and the penalty factor to complete the accurate identification of access path information of hierarchical geographic traffic network. The experimental results show that compared with the traditional method, the proposed technique has high accuracy and strong convergence, short time-consuming, the accuracy of the proposed method is about 92%, which has obvious advantages.