scholarly journals Self-similar Traffic Analysis at Network Layer Level. Part II: Application

2021 ◽  
Author(s):  
Ginno Millán
Keyword(s):  
High Speed ◽  
Computer Network ◽  
The Self ◽  
Long Range Dependence ◽  
Traffic Flows ◽  
Efficient Tool ◽  
Network Layer ◽  
Self Similar ◽  
Novel Concept ◽  
Speed Computer

In previous work has been proposed, and theoretically confirmed, that the self-similar whit long-range dependence traffic flows may be limited to the network layer. In this paper applies this novel concept to the study of traffic recorded in an IEEE 802.3u network environment whit the aim to prove their validity as a simply and efficient tool for high speed computer network traffic flows analysis.

scholarly journals Discussion of the Analysis of Self-similar Teletraffic with Long-range Dependence (LRD) at the Network Layer Level

2010 ◽  
Vol 5 (5) ◽  
pp. 799
Author(s):  
Ginno Millán ◽  
Héctor Kaschel ◽  
Gastón Lefranc
Keyword(s):  
Long Range ◽  
High Speed ◽  
Computer Network ◽  
Specific Task ◽  
Traffic Flows ◽  
Network Layer ◽  
Traffic Models ◽  
Self Similar ◽  
Speed Computer ◽  
Theoretical Foundations

Traffic streams, sources as well as aggregated traffic flows, often exhibit long-range-dependent (LRD) properties. This paper presents the theoretical foundations to justify that the behavior of traffic in a high-speed computer network can be modeled from a self-similar perspective by limiting its scope of analysis to the network layer, since the most relevant properties of self-similar processes are consistent for use in the formulation of traffic models when performing this specific task.

scholarly journals Self-similar Traffic Analysis at Network Layer Level. Part I: Fundamentals

2021 ◽  
Author(s):  
Ginno Millán
Keyword(s):  
Long Range ◽  
High Speed ◽  
Computer Network ◽  
Specific Task ◽  
Traffic Flows ◽  
Network Layer ◽  
Traffic Models ◽  
Self Similar ◽  
Speed Computer ◽  
Theoretical Foundations

Traffic streams, sources as well as aggregated traffic flows, often exhibit long-range-dependent (LRD) properties. This paper presents the theoretical foundations to justify that the behavior of traffic in a high-speed computer network can be modeled from a self-similar perspective by limiting its scope of analysis at the network layer, given that the most relevant properties of self-similar processes are consistent for use in the formulation of traffic models when performing this specific task.

scholarly journals The Associative Multifractal Process: A Novel Model for Computer Network Traffic Flows

2021 ◽  
Author(s):  
Ginno Millán ◽  
Gastón Lefranc ◽  
Román Osorio-Comparán
Keyword(s):  
Mathematical Model ◽  
Time Series ◽  
High Speed ◽  
Computer Network ◽  
Traffic Flows ◽  
Multifractal Formalism ◽  
Proposed Model ◽  
Self Similar ◽  
Speed Computer ◽  
Novel Model

A novel constructive mathematical model based on the multifractal formalism in order to accurately characterizing the localized fluctuations present in the course of traffic flows today high-speed computer networks is presented. The proposed model has the target to analyze self-similar second-order time series representative of traffic flows in terms of their roughness and impulsivity.

scholarly journals The Associative Multifractal Process: A Novel Model for Computer Network Traffic Flows

2021 ◽  
Author(s):  
Ginno Millán ◽  
Gastón Lefranc ◽  
Román Osorio-Comparán
Keyword(s):  
Mathematical Model ◽  
Time Series ◽  
High Speed ◽  
Computer Network ◽  
Traffic Flows ◽  
Multifractal Formalism ◽  
Proposed Model ◽  
Self Similar ◽  
Speed Computer ◽  
Novel Model

A novel constructive mathematical model based on the multifractal formalism in order to accurately characterizing the localized fluctuations present in the course of traffic flows today high-speed computer networks is presented. The proposed model has the target to analyze self-similar second-order time series representative of traffic flows in terms of their roughness and impulsivity.

scholarly journals A simplified multifractal model for self-similar traffic flows in high-speed computer networks revisited

2021 ◽  
Author(s):  
Ginno Millán ◽  
G. Lefranc
Keyword(s):  
Computer Networks ◽  
Hurst Exponent ◽  
High Speed ◽  
Second Order ◽  
The Self ◽  
Traffic Flows ◽  
Self Similar ◽  
Speed Computer

In the context of the simulations carried out using a simplified multifractal model that is proposed to give an explanation to the locality phenomenon that appears in the estimation of the Hurst exponent in the second-order stationary series that represent the self-similar traffic flows in high-speed computer networks, its formulation is perfected to reduce the variability in the singularity limits and it is demonstrated through by its wavelet variant that this modification leads to a higher resolution in the interval of interest under study.

scholarly journals Un modelo multifractal simplificado para flujos de tráfico autosimilares

2018 ◽  
pp. 20-25
Keyword(s):  
Computer Networks ◽  
Network Flow ◽  
Hurst Exponent ◽  
High Speed ◽  
The Self ◽  
Traffic Flows ◽  
Self Similarity ◽  
Temporal Series ◽  
Self Similar ◽  
Speed Computer

Un modelo multifractal simplificado para flujos de tráfico autosimilares A simplified multifractal model for self-similar traffic flows Ginno Millán Universidad Católica del Norte, Larrondo 1281, Coquimbo, Chile DOI: https://doi.org/10.33017/RevECIPeru2014.0003/ Resumen Este artículo propone un nuevo modelo multifractal, con el ánimo de proveer una posible explicación al fenómeno de localidad que aparece en la estimación del exponente de Hurst en series temporales estacionarias de segundo orden, representativas de los flujos de tráfico autosimilares en las actuales redes de computadoras de alta velocidad. Analíticamente se demuestra que este fenómeno se presenta cuando los flujos se componen de diversos tipos de tráficos con diferentes exponentes de Hurst. Descriptores: Autosimilitud, exponente de Hurst (H), fenómeno de localidad, multifractales. Abstract This paper proposes a new multifractal model, with the aim to provide a possible explanation to the locality phenomena to appear in the estimation of Hurst exponent in stationary second order temporal series, representing the self-similar traffic flows in high-speed computer networks. Analytically it is shown that this phenomenon occurs if the network flow consists of several components whit different Hurst exponents. Keywords: Self-similarity, Hurst exponent (H), locality phenomena, multifractals.

scholarly journals A generalized multifractal model for self-similar traffic flows in high-speed computer networks

2021 ◽  
Author(s):  
Ginno Millán
Keyword(s):  
Computer Networks ◽  
Network Traffic ◽  
Hurst Exponent ◽  
High Speed ◽  
Second Order ◽  
The Self ◽  
Traffic Flows ◽  
Temporal Series ◽  
Self Similar ◽  
Speed Computer

This paper proposes a new multifractal model with the aim to provide a possible explanation for the locality phenomena to appear in the estimation of the Hurst exponent in stationary second order temporal series, representing the self-similar traffic flows in high-speed computer networks. Analytically it is shown that this phenomenon occurs if the network traffic flows consists of several components whit different Hurst exponents.

Representative Time Series Fractal Analysis of the Traffic Flows of a Dedicated High-Speed Link

2021 ◽  
Author(s):  
Ginno Millan ◽  
manuel vargas ◽  
Guillermo Fuertes
Keyword(s):  
Time Series ◽  
Traffic Flow ◽  
Long Range ◽  
Computer Networks ◽  
Fractal Analysis ◽  
High Speed ◽  
Long Range Dependence ◽  
Traffic Flows ◽  
Speed Computer

Fractal behavior and long-range dependence are widely observed in measurements and characterization of traffic flow in high-speed computer networks of different technologies and coverage levels. This paper presents the results obtained when applying fractal analysis techniques on a time series obtained from traffic captures coming from an application server connected to the internet through a high-speed link. The results obtained show that traffic flow in the dedicated high-speed network link exhibited fractal behavior since the Hurst exponent was in the range of 0.5, 1, the fractal dimension between 1, 1.5, and the correlation coefficient between -0.5, 0. Based on these results, it is ideal to characterize both the singularities of the fractal traffic and its impulsiveness during a fractal analysis of temporal scales. Finally, based on the results of the time series analyzes, the fact that the traffic flows of current computer networks exhibited fractal behavior with a long-range dependence was reaffirmed.

scholarly journals A simple multifractal model for self-similar traffic flows in high-speed computer networks

2021 ◽  
Author(s):  
Ginno Millán
Keyword(s):  
High Speed ◽  
Process Models ◽  
Traffic Modeling ◽  
Traffic Flows ◽  
Markov Modulated Poisson Process ◽  
Traffic Trace ◽  
Self Similar ◽  
Markov Modulated ◽  
Speed Computer ◽  
Fitting Model

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.

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