面向智能体人工智能时代的语义万物互联网
Towards Semantic Internet of Everything in the Age of Agentic AI
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- Beijing University of Posts and Telecommunications（北京邮电大学）
- ZGC Institute of Ubiquitous-X Innovation and Applications（ZGC泛在X创新与应用研究院）
- Xiong’an Aerospace Information Research Institute（雄安航天信息研究院）
- China Mobile Research Institute（中国移动研究院）
机构由 AI 辅助整理，请以论文原文为准。
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中文总结 AI 辅助
针对现有语义通信方案难复用的问题，提出可组合服务架构SIoE，含三个平面，通过智能体规划器实现服务组合，以车联网案例验证其可行性并指出关键挑战。
中文摘要 AI 辅助
语义通信通过传输任务相关信息提升任务效能，但现有多数方案仍为任务特定的端到端流水线，难以跨模型、应用及部署环境复用。在此背景下，本文提出语义万物互联网（SIoE），这是一种可组合服务架构，将异构通信与人工智能（AI）功能表示为具备能力配置的服务，并依据应用目标协调这些服务。SIoE包含三个平面：任务与服务平面、智能体编排平面、语义能力平面。在该框架中，任务需求通过语义服务水平协议（SLA）捕获，而智能体规划器在确定性兼容性、资源、隐私及策略验证下发现并组合候选能力。来自通信、语义及任务层面的反馈支持持续适配与重新规划。一项轻型车联网（V2X）案例研究展示了在明确服务约束下基于配置的能力规划。结果证明了将服务目标与固定通信实现解耦的可行性，同时也突出了关键开放挑战，包括语义SLA设计、能力互操作性、可扩展规划及可信执行。
英文摘要
Semantic communication improves task effectiveness by transmitting task-relevant information. However, most existing schemes remain organized as task-specific, end-to-end pipelines, which are difficult to reuse across models, applications, and deployment environments. Against this background, we propose the Semantic Internet of Everything (SIoE), a composable service architecture that represents heterogeneous communication and artificial intelligence (AI) functions as capability-profiled services and coordinates them according to application objectives. SIoE comprises three planes: a task and service plane, an agentic orchestration plane, and a semantic capability plane. In this framework, task requirements are captured via a semantic service-level agreement (SLA), while an agentic planner discovers and composes candidate capabilities under deterministic compatibility, resource, privacy, and policy validation. Feedback from the communication, semantic, and task levels enables continuous adaptation and replanning. A lightweight vehicle-to-everything case study illustrates profile-grounded capability planning under explicit service constraints. The results demonstrate the feasibility of decoupling service objectives from fixed communication implementations and also highlight key open challenges, including semantic SLA design, capability interoperability, scalable planning, and trustworthy execution.
