Large Scale Networks : Modeling and Simulation book cover
1st Edition

Large Scale Networks
Modeling and Simulation

ISBN 9781498750172
Published October 10, 2016 by CRC Press
286 Pages - 35 Color & 79 B/W Illustrations

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Book Description

This book offers a rigorous analysis of the achievements in the field of traffic control in large networks, oriented on two main aspects: the self-similarity in traffic behaviour and the scale-free characteristic of a complex network. Additionally, the authors propose a new insight in understanding the inner nature of things, and the cause-and-effect based on the identification of relationships and behaviours within a model, which is based on the study of the influence of the topological characteristics of a network upon the traffic behaviour. The effects of this influence are then discussed in order to find new solutions for traffic monitoring and diagnosis and also for traffic anomalies prediction.

Although these concepts are illustrated using highly accurate, highly aggregated packet traces collected on backbone Internet links, the results of the analysis can be applied for any complex network whose traffic processes exhibit asymptotic self-similarity, perceived as an adaptability of traffic in networks. However, the problem with self-similar models is that they are computationally complex. Their fitting procedure is very time-consuming, while their parameters cannot be estimated based on the on-line measurements. In this aim, the main objective of this book is to discuss the problem of traffic prediction in the presence of self-similarity and particularly to offer a possibility to forecast future traffic variations and to predict network performance as precisely as possible, based on the measured traffic history.

Table of Contents


Preface ………………………………………………………………………………………………………………… 4

1. State of the art and trends in informatic network modelling *

1.1 Self-similarity and fractals in traffic modelling *

1.1.1 The building of a framework *

1.1.2 Mathematical background of self-similar processes *

1.2 Models of complex networks *

1.3 Scale free networks *

1.3.1 Basic properties of SFNs *

1.3.2 Distances and bounds in SFN *

1.4 Current trends in traffic flow and complex networks modelling *

2. Flow traffic models *

2.1 Background in traffic modelling *

2.1.1 The definition of the informational traffic *

2.1.2 Internet teletraffic modelling *

2.1.3 Internet teletraffic engineering *

2.1.4 Internet traffic times series modelling *

2.2 Renewal traffic models *

2.2.1 Poisson processes *

2.2.2 Bernoulli processes *

2.2.3 Phase-type Renewal processes *

2.3 Markov traffic models *

2.3.1 Markov-Modulated Traffic Models *

2.2.2 Markov-Modulated Poisson process *

2.3.3 Transition-Modulated Processes *

2.4 Fluid traffic models *

2.5 Autoregressive traffic models *

2.5.1 Linear Autoregressive Models (AR) *

2.5.2 Moving Average Series (MA) models *

2.5.3 Autoregressive Moving Average Series (ARMA) models *

2.5.4 Integrated Autoregressive Moving-Average (ARIMA) models *

2.5.5 Fractional Integrated Autoregressive Moving-Average (FARIMA) models *

2.6 TES traffic models *

2.6.1 TES processes *

2.6.2 The empirical TES methodology *

2.7 Self-similar traffic models *

3. Self similarity in traffic *

3.1 Self-Similar Traffic and Network Performance *

3.1.1 Quality of service and resource allocation *

3.1.2 The concept of self-similarity *

3.1.3 The effects of self-similarity on network performance *

3.2 The mathematics of self-similar processes *

3.2.1. Stationary random processes *

3.2.2. Continuous time self-similar processes *

3.2.3. Discrete time self-similar processes *

3.2.4. Properties of the fractal processes *

3.3 Self similar traffic modelling *

3.3.1 Single source traffic models *

3.3.2 Aggregate traffic models *

3.3.3 Procedures for synthetic self-similar traffic generation *

3.3.4 The Fast Fourier Transform method (FFT) *

3.4 Evidence of self-similarity in real traffic *

3.4.1 Rescaled range method *

3.4.2 Dispersion-time analysis *

3.4.3 Periodogram method *

3.4.4 Whittle estimator *

3.4.5 Wavelet based method *

3.5 Application specific models *

3.5.1 Internet application specific traffic models *

3.5.2 Models for TCP flows *

4. Topological models for complex networks *

4.1 Topology of real networked: empirical results *

4.1.1 World-Wide Web *

4.1.2 The Internet *

4.2 Random graph theory *

4.2.1 Erdös-Rényi model *

4.2.2 Subgraphs *

4.2.3 The evolution of the graph *

4.2.4 Degree distribution *

4.2.5 The connection degree (connectivity) and diameter *

4.2.6 Clustering coefficient *

4.2.7 Graph spectrum *

4.3 Small-world networks *

4.3.1 The Watts-Strogats (WS) model *

4.3.2 Properties of small-world networks *

4.4 The scale-free model *

4.4.1 Definition of the scale-free model (SF) *

4.4.2 Theoretical aspects *

4.4.3 Limit cases of the SF model *

4.4.4 Properties of the scale-free model *

5. Topology and traffic simulations in complex networks *

5.1 Example of building and simulating a network *

5.1.1 Simple simulation example *

5.2 The construction of complex network topologies *

5.2.1 The construction of a random network *

5.2.2 The construction of a small world network *

5.2.3 The construction of a scale-free network *

5.3 Analyses and topological comparisons of complex networks *

5.4 Self-similar traffic simulation *

5.5 Traffic simulation on combined topologies of networks and traffic sources *

5.5.1 Details on the used topologies and traffic sources *

5.5.2 Hurst parameter estimation results *

5.5.3 The influence of topology upon the traffic *

6. Case studies *

6.1 Hurst exponent analysis on real traffic *

6.1.1 Traffic capture *

6.1.2 Graphical estimator graphics *

6.2 Inferring statistical characteristics as an indirect measure of the quality of service *

6.2.1 Defining an inference model *

6.2.2 Highlighting network similarity *

6.2.3 Case study – inter-domain characteristic interference *

6.3 Modelling nonlinear phenomena in complex networks and detecting traffic anomalies *

6.3.1 Introduction *

6.3.2 Self-similarity characteristic of the informational traffic in networks *

6.3.3 Using similarity in network management 150

6.3.4 Test platform and processing procedure for traffic analysis *

6.3.5 Discussion on experimental results of case studies *

6.3.6 Recent trends in traffic self-similarity assessment for cloud data modelling……………………………… 158

6.4 Optimization of Quality of Services by monitoring cloud traffic……………..………………………………….. *

6.4.1 Monitoring the dynamics of network traffic in cloud ……………………………. 164

6.4.2 Coping with traffic uncertainty for load balancing in cloud 169

6.4.3 Wide-area data analysis for detection changes in traffic patterns 172

6.4.4 Monitoring cloud services using NetFlow standard 175

6.4.5 Implementing cloud services in the automation domain 180

6.5 Developing and validating strategies for traffic monitoring on RLS models 182

6.5.1 Simulation framework 182

6.5.2 Algorithms ran in simulation 186

6.5.3 Performance analysis 201

References……………………………………………………………………………………………………………... 197




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Radu Dobrescu was born in 1946. He received his Dipl.Eng. degree in Automatic Control from the Faculty of Control and Computers of the Polytechnical Institute of Bucharest in 1968. In 1976, he received his Ph.D. degree in Automatic Control of Electrical Processes from the Polytechnical Institute of Bucharest, Romania. Currently, Dr. Dobrescu is a Professor in the Department of Automation and Industrial Informatics of the Faculty of Automatic Control and Computers, POLITEHNICA University of Bucharest. Since 1992, he has been a Ph.D. adviser in the field of Systems Engineering for more than 50 Ph.D. students.

His scientific work falls under three main domains: Data acquisition, processing, and transmission; Networked control systems; Modeling of complex systems. Prof. Dobrescu has published more than 30 books and university courses, approximately 80 scientific papers in journals, and over 120 papers in volumes of international conferences. He has been the project manager for around 30 research projects. Additionally, he was the Organizer as General Chairman of seven biennial International Symposiums on Interdisciplinary Approaches in Fractal Analysis (IAFA 2003-2015). Prof. Dobrescu has been an IEEE Member since 1991 and an IEEE Senior Member since 2005, and he served as the chair of the IEEE Romania Section from 2010-2014. His monograph, "Complexity and Information," was published by the Romanian Academy Publishing House in 2010 and has since obtained the "Grigore Moisil" Academy Prize.

Florin Ionescu was born in 1945. He received his Dipl.-Eng. Degree in 1968, and his Dr. Eng in the field of Machine Tools, inclusively Cutting and Cutting Tools, Hydraulic Drives and Automation at "Politehnica" University Bucharest, Romania (RO) in 1981. He subsequently worked at "Politehnica" University Bucharest, Romania (RO) first as an Assistant then as a Professor (1969–1987). From 1987-1989, he was a Research Fellow (RF) of Alexander von Humboldt Foundation (AvH) at RWTH-Aachen, D. Later, he was a RF and guest Professor at Technical University Darmstadt, D (1989-1991) and was habilitated in 1991. During the years of 1991-2010, he taught as a Professor at University of Applied Sciences, Konstanz (UAS-KN), D. Simultaneously, he was the Director of Mechatronics Department at UAS-KN (1994-2011). Prof. Ionescu has been the Director of Steinbeis Transfer Centre Maschinendynamik, Hydraulic and Pneumatik, KN, Steinbeis-Foundation (STW) since 1992. Currently, Prof. Ionescu is a Professor for Interface Simulations and Director of Steinbeis Transfer Institute Dynamic Systems, KN, Steinbeis University Berlin (SHB).

His research topics include: Modeling and Simulation, Object Oriented Modeling, and Simulation. He is also interested in the Modeling of Small Models towards Large Scale Models; Models of any Machine; Robot; Sensor; Driving and Control System; Human Operator; Logistic Device/Installations of large/extra-large systems. Prof. Ionescu was awarded several Doctor Honoris Causa and Honorary Professorship Titles by several European Universities. He is the (co)editor and (co)author of approximately 40 (multi-chapter) books, lecture scripts; over 500 papers, research reports, and/or articles issued in Journals. Prof. Ionescu presented at International Conferences: IFAC, WCNA, IEEE, IMEKO, IASTED, ISMA, KES, ASME, SICPF, ICIAM, ICMAs, 5th ICMEN, etc., where he was active as IPC–Member, President of Sections, Speaker. From 2001-2005, he was Vice-President and Editor-in-Chief of ARA Journal. of American-Romanian Academy of Arts and Sciences (USA/CND). Prof. Ionescu is Member of some International Professional Associations, Technical Committees, Editorial Boards and Reviewer for International Conferences, Journals and Edition Houses, Auditor and Evaluator for RDI Projects.