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Fractal Teletraffic Modeling and Delay Bounds in Computer Communications
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Fractal Teletraffic Modeling and Delay Bounds in Computer Communications

Book Details

Format Paperback / Softback
ISBN-10 1032215267
ISBN-13 9781032215266
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date May 27th, 2024
Print length 220 Pages
Weight 440 grams
Ksh 8,650.00
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By deploying time series analysis, Fourier transform, functional analysis, min-plus convolution, and fractional order systems and noise, this book proposes fractal traffic modeling and computations of delay bounds, aiming to improve the quality of service in computer communication networks.

By deploying time series analysis, Fourier transform, functional analysis, min-plus convolution, and fractional order systems and noise, this book proposes fractal traffic modeling and computations of delay bounds, aiming to improve the quality of service in computer communication networks.

As opposed to traditional studies of teletraffic delay bounds, the author proposes a novel fractional noise, the generalized fractional Gaussian noise (gfGn) approach, and introduces a new fractional noise, generalized Cauchy (GC) process for traffic modeling.

Researchers and graduates in computer science, applied statistics, and applied mathematics will find this book beneficial.

Ming Li, PhD

, is a professor at Ocean College, Zhejiang University, and the East China Normal University. He has been an active contributor for many years to the fields of computer communications, applied mathematics and statistics, particularly network traffic modeling, fractal time series, and fractional oscillations. He has authored more than 200 articles and 5 monographs on the subjects. He was identified as the Most Cited Chinese Researcher by Elsevier in 2014–2020. Professor Li was recognized as a top 100,000 scholar in all fields in 2019–2020 and a top 2% scholar in the field of Numerical and Computational Mathematics in 2021 by Prof. John P. A. Ioannidis, Stanford University.


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