An MAP-based Poisson cluster model for Web traffic

In our Web traffic model, http session requests occur according to a Poisson process and each request induces multiple transmissions of sub-documents, called objects. We use a transient MAP process to model the epochs at which the transmissions of objects associated to a given document are initiated. The lengths of transmission of the objects are modeled as i.i.d, random variables. We analyze the distribution of the total number of objects being in transmission at any given time and determine its auto-correlation function.