Traffic modeling for communications networks: A multifractal approach based on few parameters |
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| Authors: | Maykon Renan P. da Silva Flávio Geraldo C. Rocha |
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| Affiliation: | 1. Systems Engineering Department, KFUPM, Dhahran 31261, Saudi Arabia;2. School of Automation, Beijing Institute of Technology, Beijing, China;1. Departamento de Control Automatico, CINVESTAV-IPN (National Polytechnic Institute), Mexico City, Mexico;2. Departamento de Computacion, CINVESTAV-IPN (National Polytechnic Institute), Mexico City, Mexico;1. Department of Mathematics, Harbin Institute of Technology, Weihai 264209, PR China;2. The Guangdong Key Laboratory of Intelligent Information Processing, College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, PR China;1. School of Mathematics and Statistics, Xuzhou University of Technology, Xuzhou 221000, Jiangsu, China;2. MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha 410081, Hunan, China;3. School of Information Sciences and Engineering, Chengdu University, Chengdu 610106, Sichuan, China;4. School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, Jiangsu, China |
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| Abstract: | In this work, in order to model network traffic processes, an efficient multifractal model is proposed based on fewer parameters than other models present in the literature, called 2PEMV. The 2PEMV model (2-Parameter Exponential Modeling for Multipliers’ Variance) is based on a multiplicative cascade in the wavelet domain capable of synthesizing communication network traffic traces which present characteristics such as self-similarity and wide Multifractal Spectrum Width (MSW). For such a purpose, in the 2PEMV model, the energy decay of the wavelet coefficients is captured by means of an exponential modeling for the multipliers’ variance along the cascade scales. The performance of the 2PEMV model to represent the network traffic characteristics is evaluated in comparison to other models present in the literature through simulations that are carried out using real communication network traffic traces. |
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