  In this paper it presents, develops and discusses the existence of a process
with long scope memory structure, representing of the independence between the
degree of randomness of the traffic generated by the sources and flow pattern
exhibited by the network. The process existence is presented in term of a new
algorithmic that is a variant of the maximum likelihood estimator (MLE) of
Whittle, for the calculation of the Hurst exponent (H) of self-similar
stationary second order time series of the flows of the individual sources and
their aggregation. Also, it is discussed the additional problems introduced by
the phenomenon of the locality of the Hurst exponent, that appears when the
traffic flows consist of diverse elements with different Hurst exponents. The
instance is exposed with the intention of being considered as a new and
alternative approach for modeling and simulating traffic in existing computer
networks.
