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Behavior predictability and consistency of mobile users' traffic usage between different years based on entropy theory

Predicting mobile users' future traffic usage plays an important role for mobile operators to optimize their services. Although a variety of prediction methods have been proposed and applied to this issue, none of them could answer whether the users' traffic behaviors can be predicted. By employing the entropy theory, this paper analyzes the predictability of users' behaviors on traffic types and accounts. Moreover, the mobile network traffic data collected from a major city in China is utilized to test the entropy theory and reveal the accuracy levels. Furthermore, by comparing the prediction results between the years 2012 and 2014, a conclusion is drawn that a large portion of users' behaviors can be predicted, but their traffic usage habits become more difficult to predict in 2014 than in 2012. The results also imply that different entropies achieve more similar predictability in 2014 than in 2012, which indicates the consistency of users' behaviors. Overall, this study reveals the predictability and consistency of users' behavior, which is of great significance for mobile operators.