HAF uses an LLM agent and deadline-aware convex allocation to reach 90% SLO fulfillment in AI-RAN, improving AI request fulfillment from 51% to 85.3%.
Toward practical operation of deep rein forcement learning agents in real-world network management at open ra n edges
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Deadline-Driven Hierarchical Agentic Resource Sharing for AI Services and RAN Functions in AI-RAN
HAF uses an LLM agent and deadline-aware convex allocation to reach 90% SLO fulfillment in AI-RAN, improving AI request fulfillment from 51% to 85.3%.