A large model-based deterministic network traffic quality of service identification method
By adopting a network traffic service quality identification method based on a large model, the problem of automated identification and dynamic optimization of traffic service quality requirements in existing technologies is solved. It realizes automated, automated, and semantic identification of traffic characteristics and business semantics, thereby improving the configuration accuracy of network traffic service quality and the system operating efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2026-06-16
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient in terms of automated identification of network traffic quality of service requirements, mapping relationship between traffic semantics and QoS requirements, combination of network context information and dynamic optimization capabilities. They are difficult to adapt to large-scale, dynamically changing network environments, resulting in unreasonable quality of service configuration and low resource utilization.
A deterministic network traffic quality of service identification method based on a large model is adopted. By collecting and preprocessing network data, a unified structured traffic representation is constructed, semantic attributes are extracted, a mapping relationship between traffic features and business semantics is established, and QoS inference is performed using a large model in combination with network context information, supporting incremental updates.
It enables automated identification of traffic QoS requirements, improves the accuracy of QoS configuration and system operating efficiency, can dynamically adapt to changes in the network environment, reduce computational overhead, and enhance the effectiveness of scheduling decisions.
Smart Images
Figure CN122420139A_ABST