Statistical Methods in Network Traffic

The analysis of network traffic data is of considerable interest for those working with computer networks and road transport systems. This article provides a brief overview of the modeling frameworks commonly used for describing network traffic. It covers stochastic models to describe variation in patterns of traffic flow in time, including a comparison of methods commonly used for electronic and road networks. Statistical inference for traffic models can be challenging, because the most readily available data are traffic counts observed at various network locations, but these typically provide only indirect information about the quantities of interest (e.g., traffic rates on routes through the network). We discuss methods of network tomography that address this kind of problem. Finally, we look at stochastic traffic assignment models (primarily for road traffic systems), which seek to describe the route flow dynamics of systems in which travelers attempt to minimize their own travel time.