1st Edition
Evolutionary Dynamics of Complex Communications Networks
Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks.
Addressing the emerging aspects of modern network analysis and design, Evolutionary Dynamics of Complex Communications Networks introduces and develops a top-bottom approach where elements of the higher layer can be exploited in modifying the lowest physical topology—closing the network design loop in an evolutionary fashion similar to that observed in natural processes.
This book provides a complete overview of contemporary design approaches from the viewpoint of network science and complex/social network analysis. A significant part of the text focuses on the classification and analysis of various network modification mechanisms for wireless decentralized networks that exploit social features from relevant online social networks.
Each chapter begins with learning objectives and introductory material and slowly builds to more detailed analysis and advanced concepts. Each chapter also identifies open issues, while by the end of the book, potential research directions are summarized for the more interested researcher or graduate student.
The approach outlined in the book will help network designers and administrators increase the value of their infrastructure without requiring any significant additional investment. Topics covered include: basic network graph models and properties, cognitive methods and evolutionary computing, complex and social network analysis metrics and features, and analysis and development of the distinctive structure and features of complex networks.
Considering all aspects of modern network analysis and design, the text covers the necessary material and background to make it a suitable source of reference for graduate students, postdoctoral researchers, and scientists
Introduction
Fundamentals of Complex Networks
Complex Networks Fundamentals
Complex Network Taxonomy and Examples
Network Science
Content and Promise of Network Science
Networks and Network Research in the 21st Century
Status and Challenges of Network Science
Basic Network Graph Models and Properties
Graph Theory Fundamentals
Basic Definitions and Notation
Additional Definitions
Connectivity
Paths and Cycles
Flow
Planarity
Coloring (Covering)
Algebraic Graph Theory
Random Graphs
Basic Random Graph Models
Notation
Cognitive Methods and Evolutionary Computing
Brief History of Evolutionary Computing
Elements from Evolution Theory
Evolutionary Computing
Components of Evolutionary Algorithms
Representation
Fitness function
Population
Parent Selection
Variation Operators: Recombination and Mutation
Survivor selection
Initialization - Termination Conditions
Operation of Evolutionary Algorithm
Evolutionary Computing Approaches
Genetic Algorithms
Evolutionary Strategy
Genetic Programming
Evolutionary Programming
Evolutionary Computing at a Glance
Parameter Control in Evolutionary Algorithms
Special Forms of Evolution
Complex and Social Network Analysis Metrics and Features
Degree Distribution
Strength
Average Path Length
Clustering Coefficient
Definition
Extension to Weighted Graphs
Extension to Directed Graphs
Centrality
Degree Centrality
Closeness (Path) Centrality
Betweenness Centrality
Betweenness Centrality Approximation Methods
Eigenvector Centrality
Example of Centralities' Computation
Prestige
Degree Prestige
Inuence Domain
Proximity Prestige
Curvature
Metrics at a Glance
Distinctive Structure and Features of Complex Networks
Network Structure and Evolution
Small-world Paradigm
Prolegomena - Description of a Small-world network
Large-scale Experiments - \Six Degrees of Separation"
Watts and Strogatz Model (WS model)
Kleinberg's Mode
Examples and Applications
Scale-free Networks
Definition and Properties
Examples and Applications
Barabási-Albert Model
Extensions of the Barabási -Albert Model
Hyperbolic Structure of Complex Networks
Background on Hyperbolic Geometry
Evolutionary Models developed on the Hyperbolic Geometry
Expansion Properties
Definition and Analytical Properties
Applications of Expander Graphs
Conclusions
Evolutionary Approaches
A Brief Description of Wireless Multi-hop Communications
Topology Control (TC) and Inverse Topology Control (iTC)
Spatial graphs and small-world phenomenon
Inverse Topology Control based Approaches
Early approaches using wired shortcuts
Approaches using wireless shortcuts
Holistic Topology Modification Framework
Weighted Edge Churn Framework
Weighted Node Churn Framework
Combined Mechanism (WEC and WNC)
Optimization Methodology
Special Cases
Example 1: Elimination to Binary Graphs (SETM)
Example 2: Trust Management in Wireless Multi-hop
Networks
Conclusions
Commencement
Lessons Learned
Emerging Trends and their Benefits
Discussion on Evolutionary Topology Modification Mechanisms
The Road Ahead
Route Covered Already
Open Problems
Epilogue
Appendices
Geometric Probability
Probability Theory Elements
Probabilistic Modeling of the Deployment of a Wireless Multihop Network
Semirings and Path Problems
Monoids
Semirings
Examples
References
Author Index
Index
Biography
Vasileios Karyotis was born in Athens, Greece, in November 1980. He receivedhis Diploma in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), Greece, in 2004, his M.Sc. degree in Electrical Engineering from the University of Pennsylvania, U.S.A., in 2005 andhis Ph.D. degree in Electrical and Computer Engineering from NTUA, Greece, in 2009. Since 2009 he has been with the Network Management and Optimal Design (NETMODE) Lab of NTUA, Greece, where he is currently a senior researcher. His research interests span the areas of stochastic modeling and performance evaluation of communications networks, resource allocations, malware propagation and complex networks. Dr. Karyotis was awarded a fellowship from the Department of Electrical and Systems Engineering of the University of Pennsylvania (2004-2005) and one of two departmental fellowships for exceptional graduate students from the School of Electrical and Computer Engineering of NTUA (2007-2009). He has participated in the technical program committee of ICC and Globecom conferences since 2008 and 2008 respectively, and other conferences as well. He has acted as a reviewer for numerous journals and conferences IEEE, ACM, ICST, etc., such as the IEEE Trans. on Parallel and Distributed Systems, IEEE Trans. on Vehicular Technology, IEEE Trans. on Wireless Communications and IEEE Journal on Selected Areas in Communications. He is a member of the Technical Chamber of Greece since 2004, and a Member of the IEEE since 2003.
Eleni Stai was born in Athens, Greece, in July 1986. She received her Diploma in Electrical and Computer Engineering from the National Technical University of Athens, Greece, in 2009. She receivedher Bachelor's degree in Mathematics from the University of Athens in 2013. Currently, she is a Ph.D. student in the School of Electrical and Computer Engineering and a research assistant in the Network Managemen