KP-A: A Unified Network Knowledge Plane for Catalyzing Agentic Network Intelligence
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911050326081536 |
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| author | Tang, Yun Zou, Mengbang Nezami, Zeinab Zaidi, Syed Ali Raza Guo, Weisi |
| author_facet | Tang, Yun Zou, Mengbang Nezami, Zeinab Zaidi, Syed Ali Raza Guo, Weisi |
| contents | The emergence of large language models (LLMs) and agentic systems is enabling autonomous 6G networks with advanced intelligence, including self-configuration, self-optimization, and self-healing. However, the current implementation of individual intelligence tasks necessitates isolated knowledge retrieval pipelines, resulting in redundant data flows and inconsistent interpretations. Inspired by the service model unification effort in Open-RAN (to support interoperability and vendor diversity), we propose KP-A: a unified Network Knowledge Plane specifically designed for Agentic network intelligence. By decoupling network knowledge acquisition and management from intelligence logic, KP-A streamlines development and reduces maintenance complexity for intelligence engineers. By offering an intuitive and consistent knowledge interface, KP-A also enhances interoperability for the network intelligence agents. We demonstrate KP-A in two representative intelligence tasks: live network knowledge Q&A and edge AI service orchestration. All implementation artifacts have been open-sourced to support reproducibility and future standardization efforts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_08164 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | KP-A: A Unified Network Knowledge Plane for Catalyzing Agentic Network Intelligence Tang, Yun Zou, Mengbang Nezami, Zeinab Zaidi, Syed Ali Raza Guo, Weisi Networking and Internet Architecture Artificial Intelligence Software Engineering The emergence of large language models (LLMs) and agentic systems is enabling autonomous 6G networks with advanced intelligence, including self-configuration, self-optimization, and self-healing. However, the current implementation of individual intelligence tasks necessitates isolated knowledge retrieval pipelines, resulting in redundant data flows and inconsistent interpretations. Inspired by the service model unification effort in Open-RAN (to support interoperability and vendor diversity), we propose KP-A: a unified Network Knowledge Plane specifically designed for Agentic network intelligence. By decoupling network knowledge acquisition and management from intelligence logic, KP-A streamlines development and reduces maintenance complexity for intelligence engineers. By offering an intuitive and consistent knowledge interface, KP-A also enhances interoperability for the network intelligence agents. We demonstrate KP-A in two representative intelligence tasks: live network knowledge Q&A and edge AI service orchestration. All implementation artifacts have been open-sourced to support reproducibility and future standardization efforts. |
| title | KP-A: A Unified Network Knowledge Plane for Catalyzing Agentic Network Intelligence |
| topic | Networking and Internet Architecture Artificial Intelligence Software Engineering |
| url | https://arxiv.org/abs/2507.08164 |