Research on Network Traffic Monitoring Based on Time Series Prediction with Information Theoretic Entropy Value Judgment and Improved Moving Average Method

Abstract

Web traffic monitoring is of great importance in today's rapidly evolving Internet. Currently, existing web traffic monitoring models rely on huge data sets for analysis and prediction, and small and micro websites do not have huge data sets, which is not conducive to their development planning and commercialisation. This paper proposes a time series prediction method for web traffic monitoring based on information theoretic entropy evaluation and improved moving average method, which does not require a huge initial data set and ensures the accuracy of data prediction through entropy evaluation.