Modeling web search query traffic with batch arrival processes

This thesis aims to study the Batch Markovian Arrival Process as a possible candidate to model the input stream of a queueing system. The characterization of the process is based on the estimation of the corresponding probability density function exploiting a non- parametric density estimation technique: the Generalized Cross Entropy method. The estimation provided by the proposed method is compared with an alternative one already studied in literature exploiting a Markov Modulated Poisson Process to model the arrival process.