From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)

TL;DR

This paper introduces a hierarchical multi-agent architecture for autonomous networks, integrating self-awareness and shared memory to enhance resilience and reduce repair times in 5G environments.

Contribution

It proposes a novel hierarchical agent-native network architecture with self-awareness and shared memory, validated through 5G case studies showing improved resilience and repair efficiency.

Findings

System sustains throughput under congestion

Reduces Mean Time to Repair (MTTR) by 86%

Validates architecture in 5G Core environment

Abstract

Realizing Level 4/5 Autonomous Networks (AN) demands a shift from static automation to agent-native intelligence. Current operations, reliant on rigid scripts, lack the cognitive agency to handle off-nominal conditions. To address this, this letter proposes a hierarchical multi-agent reference architecture enabling high-level autonomy. The framework features a Dual-Driven Orchestrator that coordinates specialized Executive Agents, supported by a shared Public Memory for unified domain knowledge. A key innovation is the integration of agent self-awareness, which empowers the system to harmonize deliberative strategic governance with reflexive fault recovery. We instantiate and validate this architecture within a 5G Core environment. Case studies demonstrate that the system sustains critical throughput under congestion and reduces Mean Time to Repair (MTTR) by 86%, confirming its efficacy in unifying strategic planning with operational resilience.