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Towards Cognitive Autonomous Networks

Release Date: 2020/10/01
ISBN: 9781119586388
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Learn about the latest in cognitive and autonomous network management Towards Cognitive Autonomous Networks: Network Management Automation for 5G and Beyond delivers a comprehensive understanding of the current state-of-the-art in cognitive and autonomous network operation. Authors Mwanje and Bell fully describe today's capabilities while explaining the future potential of these powerful technologies. This book advocates for autonomy in new 5G networks, arguing that the virtualization of network functions render autonomy an absolute necessity. Following that, the authors move on to comprehensively explain the background and history of large networks, and how we come to find ourselves in the place we're in now. Towards Cognitive Autonomous Networks describes several novel techniques and applications of cognition and autonomy required for end-to-end cognition including: • Configuration of autonomous networks • Operation of autonomous networks • Optimization of autonomous networks • Self-healing autonomous networks The book concludes with an examination of the extensive challenges facing completely autonomous networks now and in the future.

Table of Contents

  1. Cover
  2. List of Contributors
  3. Foreword I
  4. Foreword II
  5. Preface
  6. 1 The Need for Cognitive Autonomy in Communication Networks
    1. 1.1 Complexity in Communication Networks
    2. 1.2 Cognition in Network Management Automation
    3. 1.3 Taxonomy for Cognitive Autonomous Networks
    4. References
  7. 2 Evolution of Mobile Communication Networks
    1. 2.1 Voice and Low‐Volume Data Communications
    2. 2.2 Mobile Broadband Communications
    3. 2.3 Network Evolution – Towards Cloud‐Native Networks
    4. 2.4 Multi‐Service Mobile Communications
    5. 2.5 Evolution of Transport Networks
    6. 2.6 Management of Communication Networks
    7. 2.7 Conclusion – Cognitive Autonomy in 5G and Beyond
    8. References
  8. 3 Self‐Organization in Pre‐5G Communication Networks
    1. 3.1 Automating Network Operations
    2. 3.2 Network Deployment and Self‐Configuration
    3. 3.3 Self‐Optimization
    4. 3.4 Self‐Healing
    5. 3.5 Support Function for SON Operation
    6. 3.6 5G SON Support and Trends in 3GPP
    7. 3.7 Concluding Remarks
    8. References
  9. 4 Modelling Cognitive Decision Making
    1. 4.1 Inspirations from Bio‐Inspired Autonomy
    2. 4.2 Self‐Organization as Visible Cognitive Automation
    3. 4.3 Human Cognition
    4. 4.4 Modelling Cognition: A Perception‐Reasoning Pipeline
    5. 4.5 Implications for Network Management Automation
    6. 4.6 Conclusions
    7. References
  10. 5 Classic Artificial Intelligence: Tools for Autonomous Reasoning
    1. 5.1 Classical AI: Expectations and Limitations
    2. 5.2 Expert Systems
    3. 5.3 Closed‐Loop Control Systems
    4. 5.4 Case‐Based Reasoning
    5. 5.5 Fuzzy Inference Systems
    6. 5.6 Bayesian Networks
    7. 5.7 Time Series Forecasting
    8. 5.8 Conclusion
    9. References
  11. 6 Machine Learning: Tools for End‐to‐End Cognition
    1. 6.1 Learning from Data
    2. 6.2 Neural Networks
    3. 6.3 A Dip into Deep Neural Networks
    4. 6.4 Reinforcement Learning
    5. 6.5 Conclusions
    6. References
  12. 7 Cognitive Autonomy for Network Configuration
    1. 7.1 Context Awareness for Auto‐Configuration
    2. 7.2 Multi‐Layer Co‐Channel PCI Auto‐Configuration
    3. 7.3 Energy Saving Management in Multi‐Layer RANs
    4. 7.4 Dynamic Baselines for Real‐Time Network Control
    5. 7.5 Conclusions
    6. References
  13. 8 Cognitive Autonomy for Network‐Optimization
    1. 8.1 Self‐Optimization in Communication Networks
    2. 8.2 Q‐Learning Framework for Self‐Optimization
    3. 8.3 QL for Mobility Robustness Optimization
    4. 8.4 Fuzzy Q‐Learning for Tilt Optimization
    5. 8.5 Interference‐Aware Flexible Resource Assignment in 5G
    6. 8.6 Summary and Open Challenges
    7. References
  14. 9 Cognitive Autonomy for Network Self‐Healing
    1. 9.1 Resilience and Self‐Healing
    2. 9.2 Overview on Cognitive Self‐Healing
    3. 9.3 Anomaly Detection in Radio Access Networks
    4. 9.4 Diagnosis and Remediation in Radio Access Networks
    5. 9.5 Knowledge Sharing in Cognitive Self‐Healing
    6. 9.6 The Future of Self‐Healing in Cognitive Mobile Networks
    7. References
  15. 10 Cognitive Autonomy in Cross‐Domain Network Analytics
    1. 10.1 System State Modelling for Cognitive Automation
    2. 10.2 Real‐Time User‐Plane Analytics
    3. 10.3 Real‐Time Customer Experience Management
    4. 10.4 Mobile Backhaul Automation
    5. 10.5 Summary
    6. References
  16. 11 System Aspects for Cognitive Autonomous Networks
    1. 11.1 The SON Network Management Automation System
    2. 11.2 NMA Systems as Multi‐Agent Systems
    3. 11.3 Post‐Action Verification of Automation Functions Effects
    4. 11.4 Optimistic Concurrency Control Using Verification
    5. 11.5 A Framework for Cognitive Automation in Networks
    6. 11.6 Synchronized Cooperative Learning in CANs
    7. 11.7 Inter‐Function Coopetition – A Game Theoretic Opportunity
    8. 11.8 Summary and Open Challenges
    9. References
  17. 12 Towards Actualizing Network Autonomy
    1. 12.1 Cognitive Autonomous Networks – The Vision
    2. 12.2 Modelling Networks: The System View
    3. 12.3 The Development – Operations Interface in CANs
    4. 12.4 CAN as Data Intensive Network Operations
    5. References
  18. Index
  19. End User License Agreement
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