From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866911700274380800 |
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| author | Wu, Binghan Wang, Shoufeng Liu, Yunxin Zhang, Ya-Qin Sifakis, Joseph Ouyang, Ye |
| author_facet | Wu, Binghan Wang, Shoufeng Liu, Yunxin Zhang, Ya-Qin Sifakis, Joseph Ouyang, Ye |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_20608 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA) Wu, Binghan Wang, Shoufeng Liu, Yunxin Zhang, Ya-Qin Sifakis, Joseph Ouyang, Ye Artificial Intelligence Networking and Internet Architecture 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. |
| title | From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA) |
| topic | Artificial Intelligence Networking and Internet Architecture |
| url | https://arxiv.org/abs/2605.20608 |