Characterizing high-frequency subscriber sessions in cellular data networks

Cellular systems operate under restrictive constraints of resources including radio channel capacity and network processing capability. The tremendous growth in the cellular data network usage brings operators with unprecedented signaling overloads and threatens the stability of the network. Understanding the characteristics of the subscribers who are resource inefficient has an important significance of capacity planning and optimal allocation of resources. In this paper, we perform the first large-scale investigation of session characteristics of a particular category of mobile subscribers, called high-frequency subscribers who access network frequently based on anonymized traces of an city-wide operational 3G network. We fund that high-frequency subscribers can be extremely signaling resource-inefficient. For subscribers who activate more than 10 sessions per hour, they only account for 0.5% of the total subscribers and generate about 1.73% data traffic but roughly 12.6% of the signaling resources consumption. We also propose a novel approach for discovering their session patterns and study the applications that generate such session patterns from semantic level. We observed that the frequency of subscribers' session activation shows positive correlation with the periodicity of session intervals. We also found periodic session activations have a certain correlation with abnormal behaviors, to our best knowledge, we first report that although TCP SYN flooding is detected and blocked by security measures, attackers may still send requests for context activation continuously, which adds unwanted signaling loads. We demonstrate that our findings have significant implications on network optimization.