Long tail and small world characteristic of mobile internet traffic dynamics

With the wide spread of user-friendly mobile devices and applications, the broadband cellular network experiences a pronounced growth of traffic volume, and consumes a large amount of energy. To cope with these two challenges, it is important to understand the resource usage of base stations, which is the first step to manage the radio spectrum resources and network infrastructure efficiently. In this paper, we first use the Pearson's correlation to measure the dependency between base stations on the time variance of traffic load, which is the most direct pattern of resource usage in the cellular data network. By concentrating the analysis on relatively higher linear dependency between base stations, we construct a network in which the vertex and edge represents the base station and significant correlation of traffic dynamic between base stations, respectively. We characterize it in a way of weighted network, and considering the spatial deployment of base stations as well. Our findings are interesting and valuable. Specifically, such a network shows a “long tail” degree distribution, “small world” phenomenon and low modularity. And the spatial deployment of base stations has significant impact to the edge weight, rather than the topology.