Digital media flow forecasting system based on scene digitization technology

Abstract

In order to improve the traffic prediction capability of digital media network video communication, we propose a traffic prediction system based on traffic features. The distributed sensing information collection and multi-dimensional spatial storage structure model is built, and the time series reconstruction is realized by using multi-source information fusion and feature reorganization method. The embedded program is developed and designed for predicting video communication traffic in digital media networks by using wireless ZigBee networking control protocol, and the transmission prediction of communication traffic is realized by traffic feature fusion analysis. The simulation results show that this method can predict the video traffic of digital media network with high accuracy and good transmission reliability.