Internet router modeling using Circulant Markov modulated Poisson process- impact of fractal onset time (FOT)

Ramesh Renikunta (), Rajaiah Dasari () and Malla Reddy Perati ()
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Ramesh Renikunta: Kakatiya Institute of Technology & Science
Rajaiah Dasari: Kakatiya University
Malla Reddy Perati: Kakatiya University

OPSEARCH, 2016, vol. 53, issue 2, No 6, 317-328

Abstract: Abstract Fractal point process (FPP) emulates self-similar traffic and its important characteristic is fractal onset time (FOT). However, this process being asymptotic in nature has less effective in queueing based performance analysis. In this paper, we propose a model of variance based Markovian fitting. The proposed method is to match the variance of FPP and that of superposed Circulant Markov modulated Poisson Process (CMMPP). Superposition consists of several 2-state CMMPPs and Poisson process. We present how well resultant CMMPP could approximate FPP which emulates self-similar traffic. We investigate queueing behavior of resultant queueing system in terms of packet loss probability. We demonstrate how FOT affects the fitting model and queueing behavior. Analytical results are compared with the simulation results without FOT for the validation. We conclude from the numerical example that network nodes with a self-similar input traffic can be well represented by a queueing system with CMMPP input.

Keywords: Self-similarity; Fractal point process; Fractal onset time; Circulant Markov modulated Poisson process; Variance; Packet loss probability (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s12597-015-0239-0

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