1st Edition

Evolutionary Dynamics of Complex Communications Networks

    316 Pages 56 B/W Illustrations
    by CRC Press

    316 Pages 56 B/W Illustrations
    by CRC Press

    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

    Approach and Objectives
    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 
         Paths and Cycles 
         Coloring (Covering) 
         Algebraic Graph Theory
    Random Graphs
         Basic Random Graph Models

    Cognitive Methods and Evolutionary Computing
    Brief History of Evolutionary Computing
    Elements from Evolution Theory
    Evolutionary Computing 
         Components of Evolutionary Algorithms
         Fitness function
         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
    Average Path Length
    Clustering Coefficient 
         Extension to Weighted Graphs 
         Extension to Directed Graphs
         Degree Centrality
         Closeness (Path) Centrality
         Betweenness Centrality 
         Betweenness Centrality Approximation Methods 
         Eigenvector Centrality
         Example of Centralities' Computation
         Degree Prestige 
         Inuence Domain 
         Proximity Prestige
    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

    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

    Lessons Learned 
         Emerging Trends and their Benefits 
         Discussion on Evolutionary Topology Modification Mechanisms
    The Road Ahead 
         Route Covered Already
         Open Problems


    Geometric Probability
    Probability Theory Elements
    Probabilistic Modeling of the Deployment of a Wireless Multihop Network

    Semirings and Path Problems

    Author Index


    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