企业AI智能体基础设施的层次化架构研究——基于云计算实践经验的分析框架

田一晴; 沈洋

doi:10.11959/j.issn.1000-0801.DXKX260135

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企业AI智能体基础设施的层次化架构研究——基于云计算实践经验的分析框架

更新时间：2026-05-07

- 企业AI智能体基础设施的层次化架构研究——基于云计算实践经验的分析框架
- Layered Architecture of Enterprise AI Agent Infrastructure: An Analytical Framework——Based on Cloud Computing Practice
- 电信科学 2026年
- 作者机构：
  
  北京邮电大学¹，北京市 100876
  北京欧珀通信有限公司¹，北京市 100026
- 作者简介：
  
  田一晴（2005-），女，本科在读，北京邮电大学，主要研究方向：电子科学与技术、人工智能网络应用、智能体工程化部署。
  沈洋（1974-），女，硕士，北京欧珀通信有限公司，中级工程师，蜂窝技术专家，主要研究方向：3GPP 5GA/6G 核心网演进，重点关注人工智能、通信感知、通用数据框架等技术。
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.DXKX260135
  中图分类号：
- 收稿：2026-02-28，
  
  修回：2026-04-10，
  
  录用：2026-04-16，
- 稿件说明：
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田一晴, 沈洋. 企业AI智能体基础设施的层次化架构研究——基于云计算实践经验的分析框架[J/OL]. 电信科学, 2026.

田一晴, 沈洋. Layered Architecture of Enterprise AI Agent Infrastructure: An Analytical Framework——Based on Cloud Computing Practice[J/OL]. Telecommunications Science, 2026.
田一晴, 沈洋. 企业AI智能体基础设施的层次化架构研究——基于云计算实践经验的分析框架[J/OL]. 电信科学, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260135.

田一晴, 沈洋. Layered Architecture of Enterprise AI Agent Infrastructure: An Analytical Framework——Based on Cloud Computing Practice[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260135.

摘要

大语言模型（large language model，LLM）的工程化落地催生了以自主决策与工具调用为核心的智能体（agent）系统。然而，将智能体从受控原型推向企业生产环境仍面临执行隔离、身份治理、工具生态治理、多体协同、可观测性和生态分发六类结构性挑战。已有研究多聚焦于智能体的推理架构或单一平台能力，缺乏面向企业全生命周期部署需求的系统性基础设施分析框架。本文从上述六类工程挑战出发，提出覆盖执行运行时、身份与安全、工具生态集成、多智能体编排、可观测性与评估、市场与生态分发的六层参考框架，并以主流云计算平台和开源社区项目的工程实践为参照进行双路径验证。在此基础上，将本框架与3GPP SA2#173会议关于6G核心网AI架构演进的研究进展进行对比，发现两者在智能体身份治理、工具调用机制、多智能体协作、安全管控等维度上呈现演进性趋同倾向（evolutionary convergence tendency）。需要指出的是，上述3GPP文稿均为标准化讨论阶段的技术提案，其最终走向仍有待后续标准化进程确认。本框架为理解面向6G的智能体原生网络架构演进提供了来自云计算实践的分析视角。

Abstract

The engineering deployment of large language models (LLMs) has given rise to agent systems with autonomous decision-making and tool-calling capabilities. However

transitioning from controlled prototypes to enterprise production still faces six structural challenges: execution isolation

identity governance

tool ecosystem governance

multi-agent coordination

observability

and ecosystem distribution. Existing research primarily focuses on agent reasoning architectures or individual platform capabilities

lacking a systematic infrastructure framework for full-lifecycle enterprise deployment. This paper proposes a six-layer reference framework covering agent runtime

identity and security

tool integration

multi-agent orchestration

observability and evaluation

and marketplace distribution. The design logic of each layer is validated through dual-path verification against both enterprise cloud platforms and open-source community projects. A systematic comparison with 3GPP SA2#173 research on KI#18 and KI#19 reveals an evolutionary convergence tendency across agent identity

tool invocation

multi-agent coordination

and governance security — subject to the caveat that all cited 3GPP contributions are discussion-stage proposals whose outcomes remain to be confirmed in subsequent standardization. The framework provides an analytical lens from cloud computing practice for understanding agent-native 6G network architecture evolution.

关键词

Keywords

references

GARTNER . Gartner predicts 40% of enterprise apps will feature task-specific AI agents by 2026 [R/OL ] . ( 2025-08-26 )[ 2026-03-01 ] . https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026 https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026 .

CLEANLAB . AI agents in production 2025: enterprise trends and best practices [R/OL ] . ( 2025 )[ 2026-03-01 ] . https://cleanlab.ai/ai-agents-in-production-2025/ https://cleanlab.ai/ai-agents-in-production-2025/ .

WANG L , MA C , FENG X , et al . A survey on large language model based autonomous agents [J ] . Frontiers of Computer Science , 2024 , 18 ( 186345 ): 1 - 26 .

WENG L . LLM-powered autonomous agents [EB/OL ] . ( 2023-06-23 )[ 2026-02-15 ] . https://lilianweng.github.io/posts/2023-06-23-agent/ https://lilianweng.github.io/posts/2023-06-23-agent/ .

GUO T , CHEN X , WANG Y , et al . Large language model based multi-agents: a survey of progress and challenges [C ] // Proceedings of the 33rd IJCAI , 2024 : 8048 - 8057 .

XI Z , CHEN W , GUO X , et al . The rise and potential of large language model based agents: a survey [J ] . Science China Information Sciences , 2023 , 66 ( 21301 ): 1 - 26 .

ZHENG L , CHIANG W L , SHENG Y , et al . Judging LLM-as-a-judge with MT-bench and chatbot arena [C ] // NeurIPS 36 . Red Hook : Curran Associates , 2023 : 46595 - 46623 .

ITU-R . Framework and overall objectives of the future development of IMT for 2030 and beyond [S ] . Recommendation ITU-R M.2160. Geneva : ITU-R , 2023 .

EHTESHAM A , SINGH A , GUPTA G K , et al . A survey of agent interoperability protocols: MCP, ACP, A2A, and ANP [J ] . arXiv preprint arXiv: 2505.02279 , 2025 .

Anthropic . Model context protocol specification [EB/OL ] . ( 2024-11-25 )[ 2026-02-15 ] . https://modelcontextprotocol.io https://modelcontextprotocol.io .

Google . Agent-to-agent (A2A) protocol specification [EB/OL ] . ( 2025-04-09 )[ 2026-02-15 ] . https://github.com/a2aproject/A2A https://github.com/a2aproject/A2A .

OpenID Foundation . Identity management for agentic AI [R ] . 2025 -10[2026-02-15 ] . https://openid.net/wp-content/uploads/2025/10/Identity-Management-for-Agentic-AI.pdf.

Amazon Web Services . Amazon Bedrock AgentCore documentation [EB/OL ] . ( 2025-06-01 )[ 2026-02-15 ] . https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/ https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/ .

OpenClaw . OpenClaw: self-hosted gateway for AI agents [EB/OL ] . [ 2026-03-01 ] . https://docs.openclaw.ai https://docs.openclaw.ai .

ClawHub . Public skill registry for OpenClaw [EB/OL ] . [ 2026-03-01 ] . https://clawhub.ai https://clawhub.ai .

AGACHE A , BROOKER M , IORDACHE A , et al . Firecracker: lightweight virtualization for serverless applications [C ] // 17th USENIX NSDI . Berkeley : USENIX Association , 2020 : 419 - 434 .

ETSI . Zero-touch network and service management (ZSM) reference architecture [S ] . ETSI GS ZSM 002 V1.1.1. Sophia Antipolis : ETSI , 2019 .

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