LÉvy Flights and Fractal Modeling of Internet Traffic

Terdik, György; Gyires, Tibor

doi:10.1109/tnet.2008.925630

Cited by 59 publications

(46 citation statements)

References 29 publications

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“…Moreover the rich class of tempered stable distributions was examined in [13,[20][21][22][23]. Some interesting applications of the class of tempered stable distributions one can find also in [24,25].…”

Section: Continuous Time Random Walkmentioning

confidence: 99%

Stochastic Modeling of Indoor Air Temperature

et al. 2013

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Temperature is one of the main parameters describing thermal comfort and indoor air quality. In this paper we propose an approach, based on a modification of the continuous time random walk, to model the indoor air temperature. We perform a statistical analysis of the recorded time series, that allows us to point out the main statistical properties of the recorded variable. The obtained conclusions about the nature of the process lead to a continuous time random walk, that in contrast to the classical approach, models time dependence of the jumps distribution. Moreover, we show that the waiting times can be modeled by a tempered stable distribution, which yields a subdiffusive behavior in short times and diffusive behavior in longer times. Finally, by conducting a simulation study we illustrate possible applications of the presented approach in the thermal comfort monitoring and forecasting.

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Section: Continuous Time Random Walkmentioning

confidence: 99%

Stochastic Modeling of Indoor Air Temperature

et al. 2013

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“…Terdik and Gyires [22] believe that it is time to reexamine the Poisson traffic assumption, because the amount of Internet traffic grows dramatically, and any irregularity of the network traffic, such as burstiness, might cancel out because of the huge number of different multiplexed flows.…”

Section: B Further Considerations On Modelingmentioning

confidence: 99%

LTE core network testing using generated traffic based on models from real-life data

Varga

Olaszi

2013

2013 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)

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The aim of this paper is to describe a general methodology for testing the mobile network core with traffic generated from a simulated access-segment. A main element of this methodology is to derive load models and mobility models from real-life traffic patterns, and use these -as well as prerecorded protocol messages -in the process. The Evolved Packet Core (EPC) of Long Term Evolution (LTE) provides a good base for presenting practical elements of this methodology. This paper demonstrates the workflow of this methodology through a practical example of EPC load testing. This demonstration covers issues related to nodes and interfaces covered during such tests; dialogs used for session and mobility control; and crosscorrelating message flows that effect various elements across the architecture.

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“…The truncated α-stable distribution introduces a cutoff in the power-law tail of the α-stable distribution [8]. Such a cutoff will ensure finite variance.…”

Section: B Truncated α-Stable Distributionmentioning

confidence: 99%

“…Considering that the network traffic is nonnegative, in this work we only consider truncated α-stable distribution which is totally positively skewed. It is defined by the characteristic function (CF) [8]:…”

Section: B Truncated α-Stable Distributionmentioning

confidence: 99%

“…Since the seminal work reported in [1], it has been widely accepted that aggregated network traffic in a variety of wireline and wireless networks exhibits burstiness and long-range dependence [2][3][4][5][6][7][8]. The burstiness is related to distributional property, and it implies huge fluctuations and non-Gaussian distributions [2], [3], [4].…”

Section: Introductionmentioning

confidence: 99%

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A Truncated alpha-Stable Long-Range Dependent Process Model for Modeling Network Traffic

Tang

Jiao

2010

2010 International Conference on Computational Intelligence and Software Engineering

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The burstiness and long-range dependence constitutes important characteristics of high-speed communication network traffic, which have been extensively studied in the past decade. Though several existing models can account for the long-range dependence, the burstiness has not been captured as well. In this paper, we propose a truncated α-stable longrange dependent process model (TSLRDP), which incorporates the long-range dependence and burstiness precisely into one model. Furthermore, it demonstrates considerable flexibility in adapting real traffic. A novel algorithmic procedure to estimate the model parameters from real traffic is presented. Simulation results show that the proposed TSLRDP model fits the real traffic accurately.

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LÉvy Flights and Fractal Modeling of Internet Traffic

Cited by 59 publications

References 29 publications

Stochastic Modeling of Indoor Air Temperature

Stochastic Modeling of Indoor Air Temperature

LTE core network testing using generated traffic based on models from real-life data

A Truncated alpha-Stable Long-Range Dependent Process Model for Modeling Network Traffic

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