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Multi-Fractal Traffic and Anomaly Detection in Computer Communications by Ming Li at Abbey's Bookshop,
Multi-Fractal Traffic and Anomaly Detection in Computer Communications
— —
Ming Li

Multi-Fractal Traffic and Anomaly Detection in Computer Communications

Ming Li

$147

Hardback

Not in-store but you can order this
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English
CRC Press
29 December 2022
Distributed systems; Computer architecture & logic design
This book provides a comprehensive theory of mono- and multi-fractal traffic, including the basics of long-range dependent time series and 1/f noise, ergodicity and predictability of traffic, traffic modeling and simulation, stationarity tests of traffic, traffic measurement and the anomaly detection of traffic in communications networks.

Proving that mono-fractal LRD time series is ergodic, the book exhibits that LRD traffic is stationary. The author shows that the stationarity of multi-fractal traffic relies on observation time scales, and proposes multi-fractional generalized Cauchy processes and modified multi-fractional Gaussian noise. The book also establishes a set of guidelines for determining the record length of traffic in measurement. Moreover, it presents an approach of traffic simulation, as well as the anomaly detection of traffic under distributed-denial-of service attacks.

Scholars and graduates studying network traffic in computer science will find the book beneficial.
By:  
Imprint:   CRC Press
Country of Publication:   United Kingdom
Dimensions:   Height: 254mm,  Width: 178mm, 
Weight:   707g
ISBN:   9781032408460
ISBN 10:   1032408464
Pages:   282
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active

Ming Li, PhD, is a professor at Ocean College, Zhejiang University and the East China Normal University. He has been a contributor for many years to the fields of computer science, mathematics, statistics, and mechanics. He has authored more than 200 articles and 5 monographs on the subjects.

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