Summary of Telops: Ai-driven Operations and Maintenance For Telecommunication Networks, by Yuqian Yang et al.
TelOps: AI-driven Operations and Maintenance for Telecommunication Networks
by Yuqian Yang, Shusen Yang, Cong Zhao, Zongben Xu
First submitted to arxiv on: 6 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents TelOps, an artificial intelligence-driven operations and maintenance (O&M) framework specifically designed for Telecommunication Networks (TNs). Unlike existing AIOps solutions for IT systems, which are topologically independent and have homogeneous software, O&M for TNs faces unique challenges due to its topological dependence on network components, heterogeneous software, and limited failure data. The authors provide a comprehensive comparison between TelOps and AIOps, and conduct a proof-of-concept case study on failure diagnosis for a real industrial TN. This work opens the door to applying AI techniques in TN automation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary TelOps is a new way to use artificial intelligence (AI) to help keep telecommunication networks running smoothly. Right now, it’s hard to use AI for this job because of the special challenges that come with working on these networks. The biggest challenge is that all the parts of the network are connected in complex ways, so you can’t just apply AI solutions designed for other types of systems. This paper introduces TelOps, a new way to use AI to help keep telecommunication networks running. It’s the first time someone has tried to use AI in this specific way. |
