Network Science Theory and Applications

The first comprehensive book on the emerging field of network science, Network Science: Theory and Applications is an exhaustive review of terms, ideas, and practices in the various areas of network science. In addition to introducing theory and application in easy-to-understand, topical chapters, this book describes the historical evolution of network science through the use of illustrations, tables, practice problems with solutions, case studies, and applications to related Java software. Researchers, professionals, and technicians in engineering, computing, and biology will benefit from this overview of new concepts in network science.

Ted G. Lewis, PhD, is Professor of Computer Science at the Naval Postgraduate School, Monterey, California. He has written over thirty books during the course of his extensive career. Dr. Lewis is the former vice president of digital strategy for Eastman Kodak.

Preface/Foreword	p. ix
Origins	p. 1
What Is Network Science?	p. 5
A Brief History of Network Science	p. 8
General Principles	p. 19
Graphs	p. 23
Set-Theoretic Definition of a Graph	p. 25
Matrix Algebra Definition of a Graph	p. 33
The Bridges of Köet;nigsberg Graph	p. 38
Spectral Properties of Graphs	p. 42
Types of Graphs	p. 46
Topological Structure	p. 54
Graphs in Software	p. 63
Exercises	p. 68
Regular Networks	p. 71
Diameter, Centrality, and Average Path Length	p. 74
Binary Tree Network	p. 79
Toroidal Network	p. 85
Hypercube Networks	p. 89
Exercises	p. 95
Random Networks	p. 97
Generation of Random Networks	p. 100
Degree Distribution of Random Networks	p. 106
Entropy of Random Networks	p. 110
Properties of Random Networks	p. 118
Weak Ties in Random Networks	p. 125
Randomization of Regular Networks	p. 127
Analysis	p. 128
Exercises	p. 129
Small-World Networks	p. 131
Generating a Small-World Network	p. 135
Properties of Small-World Networks	p. 142
Phase Transition	p. 156
Navigating Small Worlds	p. 160
Weak Ties in Small-World Networks	p. 169
Analysis	p. 171
Exercises	p. 173
Scale-Free Networks	p. 177
Generating a Scale-Free Network	p. 180
Properties of Scale-Free Networks	p. 190
Navigation in Scale-Free Networks	p. 203
Analysis	p. 207
Exercises	p. 214
Emergence	p. 217
What is Network Emergence?	p. 219
Emergence in the Sciences	p. 223
Genetic Evolution	p. 225
Designer Networks	p. 233
Permutation Network Emergence	p. 243
An Application of Emergence	p. 252
Exercises	p. 258
Epidemics	p. 261
Epidemic Models	p. 264
Persistent Epidemics in Networks	p. 275
Network Epidemic Simulation Software	p. 287
Countermeasures	p. 289
Exercises	p. 297
Synchrony	p. 299
To Sync or Not to Sync	p. 300
A Cricket Social Network	p. 307
Kirchhoff Networks	p. 324
Pointville Electric Power Grid	p. 331
Exercises	p. 335
Influence Networks	p. 337
Anatomy of Buzz	p. 340
Power in Social Networks	p. 347
Conflict in I-Nets	p. 357
Command Hierarchies	p. 360
Emergent Power in I-Nets	p. 362
Exercises	p. 371
Vulnerability	p. 375
Network Risk	p. 378
Critical Node Analysis	p. 382
Game Theory Considerations	p. 407
The General Attacker-Defender Network Risk Problem	p. 408
Critical Link Analysis	p. 410
Stability Resilience in Kirchhoff Networks	p. 428
Exercises	p. 430
NetGain	p. 433
Classical Diffusion Equations	p. 436
Multiproduct Networks	p. 443
Java Method for Netgain Emergence	p. 447
Nascent Market Networks	p. 448
Creative Destruction Networks	p. 453
Merger and Acquisition Networks	p. 463
Exercises	p. 466
Biology	p. 469
Static Models	p. 471
Dynamic Analysis	p. 475
Protein Expression Networks	p. 481
Mass Kinetics Modeling	p. 484
Exercises	p. 490
Bibliography	p. 493
About the Author	p. 503
Index	p. 505
Table of Contents provided by Ingram. All Rights Reserved.

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Network Science Theory and Applications

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