Characterizing spatial and temporal dynamics of mobile internet services in cellular data network

Understanding spatial and temporal dynamics of mobile internet services in cellular data network can be of great help to network management and service provisioning. To this end, we conduct the detailed measurement analysis of spatial and temporal dynamics from point of view of traffic generated by subscribers. The analyzation is based on a large-scale data set collected from a commercial ISP covering an entire city in Southern China. We analyze individual subscriber behaviors and observe a significant variation in network usage among subscribers. We characterize mobile internet services spatial and temporal dynamics and identity their relation to traffic volume. The data set tracks more than 3 million mobile subscribers. To handle the problem of big data processing, the data are parallel processed using MapReduce programming model, a novel framework for distributed computing with proved high efficiency and low cost features. Generally, our observations deliver important insights into mobile internet service and mobile subscriber behavior.