Data Mining Based Modeling and Application of Mobile Video Service Awareness

With the popularity of 4G mobile networks, mobile video service becomes the key service in the 4G era. In order to improve users’ awareness and increase the network optimization efficiency, it is important to establish a scientific and accurate model to evaluate the video service from the user’s perception. In this paper, we focus on the video streaming traffic and propose a modelling approach to evaluate the video service performance. The essential characteristics of video traffic are taken into account. Based on the hierarchical clustering and the Pearson correlation coefficient method, key factors of video service perception are determined. Furthermore, the threshold values of key factors are obtained through extensive user surveys and simulation tests. The results of the application in the realistic network demonstrate the effectiveness of the proposed model. In addition, results show the proposed model enables the telecom operator to evaluate the video service quality of each user or user group, which helps improve the network optimization efficiency.