Research on Self-Similarity Network Traffic Modeling

Yu Zhang; Teng Fei Yin

doi:10.4028/www.scientific.net/AMM.110-116.2859

Paper Titles

Analytical Solution for Centrifugal Force Effect in Functionally Graded Hollow Sphere
p.2829

FEM Modeling of Beams Cyclic Loading Based on Ziegler-Prager and Armstrong-Frederick Kinematic Hardening Models
p.2838

Effects of Cut-Off Ratio on Performance of an Endoreversible Dual Cycle
p.2847

Modeling and Calculation of the Algorithm Structure of Compound Semiconductor-Type A³B⁵
p.2854

Research on Self-Similarity Network Traffic Modeling
p.2859

Study on a Robust Optimization Model for Project Scheduling Policies
p.2866

More Reliable Lifetime Distribution of System: A New Statistical Heuristic Model with Numeric Case Study
p.2872

The Effects of Fuel Injection Angle and Injection Velocity on Propulsive Droplets Sizing in a Duct
p.2879

Modeling Abrasion Resistant Materials by Modeling Large Sliding Frictional Contact
p.2888

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 110-116Research on Self-Similarity Network Traffic...

Research on Self-Similarity Network Traffic Modeling

Abstract:

This paper introduces the phenomenon of self-similar network, and then it gives the mathematical definition of self-similar and analysis for the network performance. Based on this, this paper puts forward a new mapping model of ON / OFF and the chaotic mapping model based on the ideas. The model simplifies the chaotic mapping function mapping model by choosing a random variable with a linear piecewise function. The model length is subject to the state heavy-tailed. This model can capture network traffic self-similarity.

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Periodical:

Applied Mechanics and Materials (Volumes 110-116)

Pages:

2859-2865

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.110-116.2859

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Online since:

October 2011

Authors:

Yu Zhang, Teng Fei Yin

Keywords:

Model, Network Volume, Self-Similar

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