Cognitive networks can dynamically adapt their operational parameters in response to user needs or changing environmental conditions. They can learn from these adaptations and exploit knowledge to make future decisions. Cognitive networks are the future, and they are needed simply because they enable users to focus on things other than configuring and managing networks. Without cognitive networks, the pervasive computing vision calls for every consumer to be a network technician. The applications of cognitive networks enable the vision of pervasive computing, seamless mobility, ad-hoc networks, and dynamic spectrum allocation, among others. In detail, the authors describe the main features of cognitive networks clearly indicating that cognitive network design can be applied to any type of network, being fixed or wireless. They explain why cognitive networks promise better protection against security attacks and network intruders and how such networks will benefit the service operator as well as the consumer. Cognitive Networks Explores the state-of-the-art in cognitive networks, compiling a roadmap to future research.  Covers the topic of cognitive radio including semantic aspects. Presents hot topics such as biologically-inspired networking, autonomic networking, and adaptive networking. Introduces the applications of machine learning and distributed reasoning to cognitive networks.   Addresses cross-layer design and optimization. Discusses security and intrusion detection in cognitive networks. Cognitive Networks is essential reading for advanced students, researchers, as well as practitioners interested in cognitive & wireless networks, pervasive computing, distributed learning, seamless mobility, and self-governed networks. With forewords by Joseph Mitola III as well as Sudhir Dixit.

Table of Contents:
Contributors xi Foreword 1 xv Foreword 2 xix Preface xxi Acknowledgements xxiii Introduction xxv 1 Biologically Inspired Networking 1 Kenji Leibnitz, Naoki Wakamiya and Masayuki Murata 1.1 Introduction 1 1.2 Principles of Biologically Inspired Networking 2 1.3 Swarm Intelligence 9 1.4 Evolutionary and Adaptive Systems 14 1.5 Conclusion 19 References 19 2 The Role of Autonomic Networking in Cognitive Networks 23 John Strassner 2.1 Introduction and Background 23 2.2 Foundations of Autonomic Computing 24 2.3 Advances in Autonomic Computing – Autonomic Networking 26 2.4 The FOCALE Architecture 34 2.5 Application to Wired and Wireless Cognitive Networks 44 2.6 Challenges and Future Developments 48 2.7 Conclusions 50 Glossary 50 References 51 3 Adaptive Networks 53 Jun Lu, Yi Pan, Ryota Egashira, Keita Fujii, Ariffin Yahaya and Tatsuya Suda 3.1 Introduction 53 3.2 Dynamic Factors 54 3.3 Network Functions 55 3.4 Representative Adaptation Techniques 59 3.5 Discussion 73 3.6 Conclusion 74 References 74 4 Self-Managing Networks 77 Raouf Boutaba and Jin Xiao 4.1 Introduction: Concepts and Challenges 77 4.2 The Vision and Challenges of Self-Management 78 4.3 Theories for Designing Self-Managing Networks 81 4.4 Self-Management Intelligence: To Know and to Act 83 4.5 Self-Management Advances in Specific Problem Domains 86 4.6 Benchmarking and Validation 90 4.7 Self-Stabilization 91 4.8 Conclusion 92 References 93 5 Machine Learning for Cognitive Networks: Technology Assessment and Research Challenges 97 Thomas G. Dietterich and Pat Langley 5.1 Introduction 97 5.2 Problem Formulations in Machine Learning 99 5.3 Tasks in Cognitive Networking 105 5.4 Open Issues and Research Challenges 113 5.5 Challenges in Methodology and Evaluation 116 5.6 Summary 117 Acknowledgements 118 References 118 6 Cross-Layer Design and Optimization in Wireless Networks 121 Vineet Srivastava and Mehul Motani 6.1 Introduction 121 6.2 Understanding Cross-Layer Design 123 6.3 General Motivations for Cross-Layer Design 124 6.4 A Taxonomy of Cross-Layer Design Proposals 129 6.5 Proposals for Implementing Cross-Layer Interactions 134 6.6 Cross-Layer Design Activity in the Industry and Standards 136 6.7 The Open Challenges 138 6.8 Discussion 141 6.9 Conclusions 143 References 143 7 Cognitive Radio Architecture 147 Joseph Mitola III 7.1 Introduction 147 7.2 CRA I: Functions, Components and Design Rules 158 7.3 CRA II: The Cognition Cycle 174 7.4 CRA III: The Inference Hierarchy 179 7.5 CRA V: Building the CRA on SDR Architectures 187 7.6 Summary and Future Directions 199 References 201 8 The Wisdom of Crowds: Cognitive Ad Hoc Networks 203 Linda Doyle and Tim Forde 8.1 Introduction 203 8.2 Towards Ad Hoc Networks 204 8.3 A Cognitive Ad Hoc Network 206 8.4 The Wisdom of Crowds 211 8.5 Dynamic Spectrum: Scenarios for Cognitive Ad Hoc Networks 214 8.6 Summary and Conclusions 219 References 220 9 Distributed Learning and Reasoning in Cognitive Networks: Methods and Design Decisions 223 Daniel H. Friend, Ryan W. Thomas, Allen B. MacKenzie and Luiz A. DaSilva 9.1 Introduction 223 9.2 Frameworks for Learning and Reasoning 224 9.3 Distributed Learning and Reasoning within an MAS Framework 227 9.4 Sensory and Actuator Functions 236 9.5 Design Decisions Impacting Learning and Reasoning 237 9.6 Conclusion 243 References 244 10 The Semantic Side of Cognitive Radio 247 Allen Ginsberg, William D. Horne and Jeffrey D. Poston 10.1 Introduction 247 10.2 Semantics, Formal Semantics and Semantic Web Technologies 248 10.3 Community Architecture for Cognitive Radio 251 10.4 Device Architecture for Cognitive Radio and Imperative Semantics 261 10.5 An Architecture for Cognitive Radio Applications 265 10.6 Future of Semantics in Cognitive Radio 268 10.7 Conclusion 268 References 268 11 Security Issues in Cognitive Radio Networks 271 Chetan N. Mathur and K. P. Subbalakshmi 11.1 Introduction 271 11.2 Cognitive Radio Networks 272 11.3 Building Blocks of Communication Security 275 11.4 Inherent Reliability Issues 278 11.5 Attacks on Cognitive Networks 279 11.6 Cognitive Network Architectures 285 11.7 Future Directions 286 11.8 Conclusions 289 Acknowledgements 289 References 289 12 Intrusion Detection in Cognitive Networks 293 Hervé Debar 12.1 Introduction 293 12.2 Intrusion Detection 293 12.3 Threat Model 301 12.4 Integrated Dynamic Security Approach 305 12.5 Discussion 310 12.6 Conclusion 311 References 312 13 Erasure Tolerant Coding for Cognitive Radios 315 Harikeshwar Kushwaha, Yiping Xing, R. Chandramouli and K.P. Subbalakshmi 13.1 Introduction 315 13.2 Spectrum Pooling Concept 318 13.3 Overview of Erasure Channels 319 13.4 Traditional Erasure Codes 321 13.5 Digital Fountain Codes 322 13.6 Multiple Description Codes 328 13.7 Applications 329 13.8 Conclusion 330 References 330 Index 333