@Article{JICS-9-210,
author = {Rajaiah Dasari and Malla Reddy Perati},
title = {Internet Traffic Modelling -Variance Based Markovian Fitting of Fractal Point Process from Self-Similarity Perspective},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {9},
number = {3},
pages = {210--223},
abstract = { Most  of  the  proposed  self-similar  traffic  models  could  not  address  fractal  onset  time  at  which 
self-similar  behavior  actually  begins.  This  parameter  has  considerable  impact  on  network  performance. 
Fractal point process (FPP) emulates self-similar traffic and involves fractal onset time (FOT). However, this 
process  is  asymptotic  in  nature  and  has  less  effective  in  queueing  based  performance.  In  this  paper,  we 
propose a model of variance based Markovian fitting. The proposed method is to match the variance of FPP 
and  superposed  Markov  modulated  Poisson  Process  (MMPP)  while  taking  FOT  into  consideration. 
Superposition consists of several interrupted Poisson processes (IPPs) and Poisson process. We present how 
well  resultant  MMPP  could  approximate  FPP  which  emulates  self-similar  traffic.  We  investigate  queueing 
behavior of resultant queueing system in terms of a packet loss probability. We demonstrate how FOT affects 
the fitting model and queueing behavior. We conclude from the numerical example that network nodes with a 
self-similar input traffic can be well represented by a queueing system with MMPP input 
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22581.html}
}