Characterizing User Behavior in Mobile Internet

TLDR

Smart devices have enabled ubiquitous mobile Internet access, driving rapid growth. This study analyzes mobile user behavior in China using one week of core 2G/3G traffic data, focusing on data usage, mobility patterns, and application usage. The authors classify users into groups based on traffic data to examine resource consumption patterns. The analysis shows that heavy‑traffic and high‑mobility users consume large amounts of data and radio resources, that data usage and mobility are linked to application access, that users can be clustered by application behavior, and that these insights can guide operators in resource provisioning and mobility management.

Abstract

Smart devices bring us the ubiquitous mobile accessing to Internet, making mobile Internet grow rapidly. Using the mobile traffic data collected at core metropolitan 2G and 3G networks of China over a week, this paper studies the mobile user behavior from three aspects: 1) data usage; 2) mobility pattern; and 3) application usage. We classify mobile users into different groups to study the resource consumption in mobile Internet. We observe that traffic heavy users and high mobility users tend to consume massive data and radio resources simultaneously. Both the data usage and the mobility pattern are closely related to the application access behavior of the users. Users can be clustered through their application usage behavior, and application categories can be identified by the ways to attract the users. Our analysis provides an comprehensive understanding of user behavior in mobile Internet, which may be used by network operators to design appropriate mechanisms in resource provision and mobility management for resource consumers based on different categories of applications.