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

Author(s):  
Ranadheer Donthi ◽  
Ramesh Renikunta ◽  
Rajaiah Dasari ◽  
Malla Reddy Perati
2021 ◽  
Author(s):  
Ginno Millán

This paper presents a simple and fast technique of multifractal traffic modeling. It proposes a method of fitting model to a given traffic trace. A comparison of simulation results obtained for an exemplary trace, multifractal model and Markov Modulated Poisson Process models has been performed.


Author(s):  
Ginno Millán

This paper presents a simple and fast technique of multifractal traffic modeling. It proposes a method of fitting model to a given traffic trace. A comparison of simulation results obtained for an exemplary trace, multifractal model and Markov Modulated Poisson Process models has been performed.


2001 ◽  
Author(s):  
Raghuveer M. Rao ◽  
Seungsin Lee ◽  
Rajesh Narasimha ◽  
Soheil A. Dianat

2021 ◽  
Author(s):  
Ginno Millán

This paper presents a simple technique of multifractal traffic modeling. It proposes a method of fitting model to a given traffic trace. A comparison of simulation results obtained for an exemplary trace, multifractal model and Markov Modulated Poisson Process models has been performed.


2021 ◽  
Vol 208 ◽  
pp. 107318
Author(s):  
Yoel G. Yera ◽  
Rosa E. Lillo ◽  
Bo F. Nielsen ◽  
Pepa Ramírez-Cobo ◽  
Fabrizio Ruggeri

2015 ◽  
Vol 26 ◽  
pp. 103-123 ◽  
Author(s):  
Armelle Guillou ◽  
Stéphane Loisel ◽  
Gilles Stupfler

Author(s):  
Dimitar Radev ◽  
Izabella Lokshina ◽  
Svetla Radeva

The paper examines self-similar properties of real telecommunications network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Simulation with stochastic and long range dependent traffic source models is performed, and the algorithms for buffer overflow simulation for finite buffer single server model under self-similar traffic load SSM/M/1/B are explained. The algorithms for modeling fixed-length sequence generators that are used to simulate self-similar behavior of wireless IP network traffic are developed and applied. Numerical examples are provided, and simulation results are analyzed.


Author(s):  
Naji Najari ◽  
Samuel Berlemont ◽  
Gregoire Lefebvre ◽  
Stefan Duffner ◽  
Christophe Garcia

Sign in / Sign up

Export Citation Format

Share Document