AI-NATIVE NETWORK FABRICS: THE SELF OPTIMIZING FRAMEWORK FOR INTENT BASED ROUTING, EDGE AWARE ADAPTATION, AND TRUSTLESS PACKET ORCHESTRATION DEVELOPING AUTONOMOUS NETWORKING SYSTEMS

The evolution of post-5G infrastructures demands a paradigm shift from static network architectures toward intelligent, adaptive, and secure systems. This paper introduces a self-optimizing framework for AI-native network fabrics, integrating intent-based routing, edge-aware adaptation, and trustless packet orchestration. These elements collectively form the foundation of autonomous networking systems capable of predictive control, zero-trust enforcement, and multi-domain coordination. By leveraging predictive analytics and distributed intelligence, this framework improves service continuity, enhances security assurance, and optimizes data flow across heterogeneous network environments.