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Published in:
Introduction to Fractals Read chapter Read first chapter

2014 | OriginalPaper | Chapter

Self-Similar Network Traffic Modeling Using Circulant Markov Modulated Poisson Process

Authors : Ranadheer Donthi, Ramesh Renikunta, Rajaiah Dasari, Malla Reddy Perati

Published in: Fractals, Wavelets, and their Applications

Publisher: Springer International Publishing

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Abstract

Most of the classical self-similar traffic models are asymptotic in nature. Hence, they are not suitable for queuing based performance evaluation. In this paper, we propose a model for self-similar traffic using Circulant Markov modulated Poisson process (CMMPP). This model is to match the variance of self-similar traffic and that of CMMPP over a time-scale. The resultant CMMPP consists of several two-state CMMPPs. We conclude from the numerical examples that self-similar traffic can be well represented by the proposed model.

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previous chapter Validation of Variance Based Fitting for Self-similar Network Traffic
next chapter Investigation of Priority Based Optical Packet Switch Under Self-Similar Variable Length Input Traffic Using Matrix Queueing Theory
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Metadata
Title
Self-Similar Network Traffic Modeling Using Circulant Markov Modulated Poisson Process
Authors
Ranadheer Donthi
Ramesh Renikunta
Rajaiah Dasari
Malla Reddy Perati
Copyright Year
2014
Book
Fractals, Wavelets, and their Applications

Print ISBN: 978-3-319-08104-5

Electronic ISBN: 978-3-319-08105-2

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-08105-2_29

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