DEPENDENCE APPROXIMATION OF THE HURST COEFFICIENT ON THE TRAFFIC DISTRIBUTION PARAMETER
Keywords:quality of service, Hurst coefficient, self-similar traffic.
Background. Despite the popularity of the model of self-similar traffic, until now a number of tasks of assessing the quality of service in the packet communication network remains unresolved. Because of the lack of a rigorous theoretical base that can complement the classical queuing theory when designing a packet-based communication network with self-similar traffic, there is no reliable and recognized methodology for calculating parameters and quality indicators for information distribution systems under conditions of the self-similarity effect.
Objective. The aim of the paper is the improvement of the accuracy of calculating the quality of service characteristics by obtaining a new formula for calculating the traffic self-similarity coefficient, depending on the parameter of the form of the Weibull or Pareto distributions. Self-similar traffic or the time interval between stream packets is described by these distributions.
Methods. To calculate the QoS characteristics, you only need to know the parameter a of the Weibull or Pareto distribution form and there is no need to calculate in a rather complicated way, for example, the R/S-method, the self-similarity coefficient of Hurst for traffic.
Results. A significant difference between the real and the linear dependence of the self-similarity coefficient H on the parameter a of the Weibull distribution form or on the parameter a of the Pareto distribution form is detected.
Conclusions. The use of real functional dependences of H on a allows enhancing the accuracy of calculating the quality of service characteristics.
Keywords: quality of service: Hurst coefficient: self-similar traffic.
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