中国联合网络通信有限公司研究院,北京 100048
[ "韩政鑫(1994-),女,硕士,中国联合网络通信有限公司研究院工程师,主要研究方向为下一代互联网、确定性网络、工业互联网等新技术和应用。" ]
何涛(1982-),男,硕士,中国联合网络通信有限公司研究院高级工程师,主要研究方向为数据通信、算网融合、智能体互联网等。
[ "韩梦瑶(1995- ),男,博士,中国联合网络通信有限公司研究院工程师,主要研究方向为下一代互联网架构演进与关键技术。" ]
[ "庞冉(1989- ),男,硕士,中国联合网络通信有限公司研究院正高级工程师,主要研究方向为数据通信、算网一体、下一代互联网等前沿技术。" ]
曹畅(1984 -),男,博士,中国联合网络通信有限公司研究院正高级工程师,主要研究方向为数据通信、算力网络、下一代互联网架构与核心技术。
唐雄燕(1967-),男,博士,中国联合网络通信有限公司研究院副院长、正高级工程师,主要研究方向为光纤传输、宽带通信、算力网络、下一代互联网前沿技术。
收稿:2026-02-13,
修回:2026-05-07,
录用:2026-05-07,
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韩政鑫, 何涛, 韩梦瑶, 等. 面向企业多智能体协同的专网架构及关键技术研究[J/OL]. 电信科学, 2026.
HAN Zhengxin, HE Tao, HAN Mengyao, et al. Research on Private Network Architecture and Key Technologies for Enterprise Multi-Agents Collaboration[J/OL]. Telecommunications Science, 2026.
韩政鑫, 何涛, 韩梦瑶, 等. 面向企业多智能体协同的专网架构及关键技术研究[J/OL]. 电信科学, 2026. DOI: 10.11959/j.issn.1000-0801.DXKX260108.
HAN Zhengxin, HE Tao, HAN Mengyao, et al. Research on Private Network Architecture and Key Technologies for Enterprise Multi-Agents Collaboration[J/OL]. Telecommunications Science, 2026. DOI: 10.11959/j.issn.1000-0801.DXKX260108.
人工智能正从以大模型为主导的阶段向自主协同的智能体方向演进。针对企业数字化转型中多智能体规模化协同面临的核心挑战,聚焦企业及园区应用场景,探索性地提出以“智能体网关”为核心枢纽的专网架构,研究涵盖智能体标识与注册、能力发现、高效通信以及安全协同的关键技术体系,并创新性地提出基于IPv6地址的智能体标识与语义路由机制。该架构依托智能体网关,通过网络层与应用层能力协同,实现异构智能体的可信接入、能力发现与高效协作,为企业及园区级智能体协同提供技术参考与实践路径。
Artificial intelligence (AI) is evolving from a stage dominated by large language models (LLMs) towards autonomously collaborative AI agents. To address the core challenges of large-scale multi-agent collaboration in enterprise digital transformation
focusing on enterprise and park application scenarios
an AI agent private network architecture with "AI agent gateway" as the core hub was exploratorily proposed. The key technology system covering AI agent identification and registration
capability discovery
efficient communication
and secure collaboration was studied
and an AI agent identification and semantic routing mechanism based on IPv6 addresses was innovatively proposed. Relying on the AI agent gateway
the architecture realizes trusted access
capability discovery
and efficient collaboration of heterogeneous AI agents through the collaboration between network layer and application layer capabilities
providing technical reference and practical paths for enterprise-level multi-agent collaboration.
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