SANNet: A Semantic-Aware Agentic AI Networking Framework for Multi-Agent Cross-Layer Coordination Article Swipe
Yong Xiao
,
Haibo Zhou
,
LI Xu-bo
,
Ying Gao
,
Guangming Shi
,
Ping Zhang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2505.18946
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2505.18946
Agentic AI networking (AgentNet) is a novel AI-native networking paradigm that relies on a large number of specialized AI agents to collaborate and coordinate for autonomous decision-making, dynamic environmental adaptation, and complex goal achievement. It has the potential to facilitate real-time network management alongside capabilities for self-configuration, self-optimization, and self-adaptation across diverse and complex networking environments, laying the foundation for fully autonomous networking systems in the future. Despite its promise, AgentNet is still in the early stage of development, and there still lacks an effective networking framework to support automatic goal discovery and multi-agent self-orchestration and task assignment. This paper proposes SANNet, a novel semantic-aware agentic AI networking architecture that can infer the semantic goal of the user and automatically assign agents associated with different layers of a mobile system to fulfill the inferred goal. Motivated by the fact that one of the major challenges in AgentNet is that different agents may have different and even conflicting objectives when collaborating for certain goals, we introduce a dynamic weighting-based conflict-resolving mechanism to address this issue. We prove that SANNet can provide theoretical guarantee in both conflict-resolving and model generalization performance for multi-agent collaboration in dynamic environment. We develop a hardware prototype of SANNet based on the open RAN and 5GS core platform. Our experimental results show that SANNet can significantly improve the performance of multi-agent networking systems, even when agents with conflicting objectives are selected to collaborate for the same goal.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2505.18946
- https://arxiv.org/pdf/2505.18946
- OA Status
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- https://openalex.org/W4414581916
All OpenAlex metadata
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- DOI
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https://doi.org/10.48550/arxiv.2505.18946Digital Object Identifier
- Title
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SANNet: A Semantic-Aware Agentic AI Networking Framework for Multi-Agent Cross-Layer CoordinationWork title
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preprintOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-05-25Full publication date if available
- Authors
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Yong Xiao, Haibo Zhou, LI Xu-bo, Ying Gao, Guangming Shi, Ping ZhangList of authors in order
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https://arxiv.org/abs/2505.18946Publisher landing page
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https://arxiv.org/pdf/2505.18946Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2505.18946Direct OA link when available
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0Total citation count in OpenAlex
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