Evaluation and Prediction of Network QoS Based on Multidimensional Data

Abstract

With the rapid development of modern society and economy, Internet has been widely used in all walks of life, and plays an irreplaceable important role. At the same time, the quality of computer network service has been put forward more specific requirements. How to realize network QoS assurance is always a hot research topic in the Internet field. This paper analyzes the defects of the current comprehensive evaluation of network QoS. Considering the shortcomings of traditional data processing methods will be infinitely magnified in the face of a large amount of data and various types of data, the author uses SAE network model to reduce data dimension and extract features. Then the improved GRA-TOPSIS model is used to comprehensively evaluate the network QoS. Finally, the improved Gray GM(1,1) model is used to predict the network performance, which provides a new idea for multi-level and multi-criteria evaluation and prediction.