AI-Augmented Cross-Domain Resource Orchestration in Next-Generation Mobile Networks
DOI:
https://doi.org/10.66280/ijair.v1i2.110Keywords:
next-generation mobile networks; cross-domain orchestration; artificial intel- ligence; network slicing; edge computing; resource optimizationAbstract
Next-generation mobile networks are evolving from communication infrastructures into integrated service systems that jointly deliver connectivity, computation, storage, intelli- gence, and security. In this transition, resource management can no longer remain confined to isolated domains such as radio access, transport, core networks, or edge clouds. Future ser- vices, including immersive media, vehicle-to-everything coordination, industrial control, and distributed AI inference, demand end-to-end orchestration across heterogeneous resources with strict requirements on latency, reliability, energy efficiency, and adaptability. This pa- per examines AI-augmented cross-domain resource orchestration as a foundational capability for 5G-Advanced and beyond-5G networks. It defines the scope of cross-domain resources, analyzes the limitations of conventional domain-specific orchestration, and presents a lay- ered architecture in which artificial intelligence supports intent understanding, global state perception, demand prediction, policy generation, and closed-loop control. To concretize the discussion, the paper introduces mathematical formulations for utility-aware resource allocation and SLA-constrained optimization, and provides illustrative figures on orchestra- tion workflows and performance gains. It further discusses practical applications in network slicing, edge intelligence, vehicular networking, industrial systems, and green networking. Finally, it identifies key implementation challenges related to explainability, interoperabil- ity, data governance, and security. The study argues that AI-augmented orchestration is not simply an automation upgrade, but a structural shift toward intent-driven autonomous mobile networks.
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