Spatio-temporal modeling of traffic workload in a campus WLAN

Campus wireless LANs (WLANs) are complex systems with hundreds of access points (APs) and thousands of users. Their performance analysis calls for realistic models of their elements, which can be input to simulation and testbed experiments but also taken into account for theoretical work. However, only few modeling results in this area are derived from real measurement data, and rarely do they provide a complete and consistent view of entire WLANs. In this work, we address this gap relying on extensive traces collected from the large wireless infrastructure of the University of North Carolina. We present a first system-wide, multi-level modeling approach for characterizing the traffic demand in a campus WLAN. Our approach focuses on two structures of wireless user activity, namely the wireless session and the network flow. We propose statistical distributions for their attributes, aiming at a parsimonious characterization that can be the most flexible foundation for simulation studies. We simulate our models and show that the synthesized traffic is in good agreement with the original trace data. Finally, we investigate to what extent these models can be valid at finer spatial aggregation levels of traffic load, e.g., for modeling traffic demand in hotspot APs.