网络拓扑构建数据的生成方法、装置、设备和存储介质
By converting natural language into machine-understandable prompts and breaking down the topology building task, the problem of low efficiency in manually building network topologies is solved, achieving efficient and accurate network topology data generation, which is suitable for various complex cloud environments.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- PENG CHENG LAB
- Filing Date
- 2026-03-06
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, relying on professional engineers to manually build network topologies is difficult to keep up with the rapid pace of business iterations, resulting in low efficiency in generating network topology construction data. This is especially true when deployed on cloud platforms, where inconsistencies in configuration, resource conflicts, and logical deviations are likely to occur.
By acquiring the natural language description of the network topology to be constructed, a pre-trained network topology construction model is used to transform it into machine-understandable prompt text. This is then broken down into two stages: topology prediction and configuration supplementation, generating network topology data containing runtime configuration information.
It improves the efficiency of generating network topology construction data, ensures the accuracy of results, avoids repeated debugging, and is suitable for scenarios such as cloud-native applications, multi-tenant enterprise cloud environment management, and intelligent edge computing resource orchestration.
Smart Images
Figure CN122420126A_ABST