This book explores how Artificial Intelligence (AI) and Software-Defined Networking (SDN) can transform the way modern networks are designed, secured, and operated. In an era shaped by cloud computing, IoT, 5G, and edge computing, traditional network management is no longer enoughthis book reveals how AI agents bring autonomy, intelligence, and adaptability to meet these challenges.

The book starts with the foundational concepts in AI and SDN, guiding readers toward advanced architectures and real-world applications. It examines urgent needs such as scalable, self-healing networks and proactive cybersecurity, showing how AI techniquesincluding reinforcement learning, graph neural networks, and explainable AIcan achieve intent-based networking, cognitive healing, federated learning, and intelligent automation. Each chapter combines conceptual overviews with detailed discussions, case studies, and actionable insights, making it accessible to students, researchers, engineers, and decision-makers alike. It bridges technical depth with broader considerations such as ethics, governance, energy efficiency, and disaster recovery. It unifies AI and networking into a single, practical framework rather than treating them as separate fields. The inclusion of curated resources, from books and blogs to courses and glossaries, supports ongoing learning beyond the text itself.

This book serves as a roadmap, guiding readers in designing intelligent, secure, and adaptive network ecosystemsessential for those aiming to lead the next generation of decentralized, resilient, and AI-driven digital infrastructure.

What you will learn:

• Understand core AI-agent architectures and their integration with Software-Defined Networking for scalable, adaptive environments.
• How to use ML, deep learning, reinforcement learning, and graph neural networks to optimize, automate, and secure networks.
• How to develop AI-enabled networks with real-world case studies from telecom, smart cities, and enterprise IT.

• Explore trends like federated learning, edge AI, programmable optical networks, and AI-driven disaster recovery
  Who this book is for:

  This book serves network architects and engineers using AI-driven automation to solve scalability and complexity challenges. It guides AI researchers and data scientists applying advanced methods for smarter, more efficient networks. Security professionals will also find value in AI-driven threat detection, incident response, and collaborative defense.

  Bridges AI and networking into one cohesive, practical framework for modern, intelligent network design Balances deep technical insight with ethics, governance, energy efficiency, and disaster recovery Serves as a strategic roadmap to build adaptive, decentralized, and AI-driven digital infrastructure

  Autorentext

  Het Mehta is a Software Developer at Cisco, where he is at the forefront of revolutionizing network infrastructure through the strategic convergence of Software-Defined Networking (SDN), security automation, and Artificial Intelligence (AI). His work is dedicated to developing intelligent, software-defined systems that possess the autonomy and adaptability required to meet the demands of modern cloud, 5G, and edge computing environments.

  Het’s expertise spans high-performance SD-WAN solutions, cloud integration, and kernel-level development. His unique background in embedded systems provides a critical perspective on the hardware-software synergy necessary for building resilient, high-performance network fabrics. He has contributed his research on intelligent networking to prestigious forums, including IEEE publications, and serves the academic community as a technical judge for major IEEE-affiliated international conferences in the domains of information networking and computer automation.

  Pioneering the next generation of AI-driven networking, Het focuses on developing intelligent systems that enable proactive threat detection, autonomous configuration, and dynamic resource management. His professional vision is to create network ecosystems that not only respond to change but proactively anticipate it.

  In this book, Het shares his deep expertise and actionable frameworks, guiding readers—from network engineers and security professionals to researchers and technology leaders—through the essential blueprint for designing, securing, and operating the intelligent, autonomous networks of tomorrow.

  Inhalt

  Chapter 1: AI-Agent Architectures for Decentralized Network Management.- Chapter 2: Adaptive AI Agents for Intent-Based Networking (IBN).- Chapter 3: Federated Learning for Collaborative Network Optimization.- Chapter 4: AI Agents for Cross-Layer Network Orchestration.- Chapter 5: Digital Twins for AI-Driven Network Simulations.- Chapter 6: Cognitive AI Agents for Proactive Network Healing.- Chapter 7: AI-Powered Dynamic Policy Management in SDN.- C hapter 8: Reinforcement Learning for Autonomous Traffic Engineering.- Chapter 9: Ethical AI Agents for Responsible Network Management.- Chapter 10: AI Agents for Network Threat Intelligence and Response.- Chapter 11: AI-Driven Resource Allocation in Multi-Tenant SDN Environments.- Chapter 12: AI Agents for Edge-Centric SDN Management.- Chapter 13: AI-Augmented Network Function Chaining in SDN.- Chapter 14: AI Agents for Zero-Touch Provisioning in SDN.- Chapter 15: Leveraging Graph Neural Networks for SDN Management.- Chapter 16: AI-Enhanced Security for Programmable Data Planes.- Chapter 17: Personalized Network Management with AI Agents.- Chapter 18: AI-Driven Energy Efficiency in SDN.- Chapter 19: AI-Powered Collaborative Security for Multi-Domain SDN.- Chapter 20: AI in Programmable Optical Networks with SDN.- Chapter 21: AI-Driven Predictive Analytics for SDN Scalability.- Chapter 22: Democratizing AI-Driven SDN Management with Open Source.- Chapter 23: AI Agents for SD-WAN Optimization.- Chapter 24: AI-Driven Security for SD-WAN.- Chapter 25: Ensuring Business Continuity with AI-Driven Disaster Recovery. Chapter 26: Additional Resources and Glossary.