Abstract:
The paper considers the main ways of describing the process that characterizes the arrival
of packets to a multiservice node of a telecommunications network. The features of the process
under consideration are best represented by the cumulative distribution function A(t). It determines
the distribution of the interval size between the moments of arrival of neighboring packets to the
multiservice node. These intervals are random values. If it is not possible to perform measurements
that allow the choosing of the A(t) function, then the distribution law of random variables is selected
based on reasonable assumptions. For telephone switching nodes, the Poisson flow hypothesis was
used, which is often similar to the symmetric distribution of the number of calls at time interval t. The
results of traffic measurements for multiservice switching nodes showed that the studied distribution
is inherently asymmetric. This paper mainly considers the possibility of choosing the A(t) function
based on the measurement results presented in a form of the histogram a(t), which contains a series
of values. This histogram allows us to obtain the desired distribution as a stepwise function by
integration of the a(t). Practical interest is associated with the possibility of reducing the number
of readings used to assess the A(t) function. The methods used by some authors are based on the
application of arbitrarily chosen functions A(t) with so-called heavy tails. The proposed approach is
based on real distributions defined at a finite time interval. As a result of this research, a methodology
has been developed to accurately describe the process of packet arrival at the input of the multiservice
node. The proposed methodology is based on analytical methods. It guarantees error minimization
when investigating the probabilistic characteristics of a switching node in a multiservice network.
