A Human-in-the-Loop Architecture for Mobile Network: From the View of Large Scale Mobile Data Traffic

Unlike other radio signal services, 5G is anticipated to play a huge role in offering services to heterogeneous networks, technologies, and devices operating in different geographic regions to fulfill the high expectation of users with relatively low energy consumption, which implies the necessity for moving from a system-centric design to a more user- or even human- and data- centric design paradigm “to keep the human in the loop” in future network. It drives us to design a system with capacity to allocate network resource dynamically according to feedback from users. This paper presents a Human-In-The-Loop architecture for mobile network that discovers users’ needs on network resource by understanding data traffic usage behavior of users. Based on real data traffic of mobile network, we analyze data traffic patterns of heavy and normal users from the view of online browsing behavior and urban functional area to explain how and why the data traffic is consumed. Then we propose a Latent Dirichlet Allocation model based solution to correlate data traffic, user behavior, and urban ecology to gain deep insights into spatio-temporal dynamic of data traffic usage behavior for different groups of users. Drawing upon results from a comprehensive study of users in a metropolitan city in China, we achieve a broad understanding about the difference of data traffic usage patterns of heavy and normal user: (1) besides the amount of generated data traffic, two groups of users can be easily distinguished by usage behavior of limited number of applications at midnight, (2) the functions of locations have huge impact on data usage patterns of users, which implies that urban ecology will shape users’ online behavior. The results of this work can potentially be exploited to help to allocate network resource, improve Quality of Experience according to users’ needs, and even design the future network.