A new method for the probabilistic and statistical analysis of information flows in telecommunication networks

A new method is proposed for the analysis of the stochastic structure of chaotic information flows in convergent telecommunication networks. The proposed method is based on a stochastic model of a telecommunication network which has the form of a superposition of some simple sequential-parallel structures. This model quite naturally generates mixtures of gamma-distributions for the network operation execution time. The parameters of the mixture of gamma-distributions characterize the stochastic structure of chaotic information flows in the network. The problem of statistical estimation of the parameters of gamma-distributions is solved by the EM-algorithm. To trace the variation of the stochastic structure of information flows in time, the EM-algorithm is applied for the moving window. The software for the division of distribution mixtures is developed and documented. The real input data is used. The interpretation of results is given.