5G Policy Control Network Element Dynamic Service Execution
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Solution Overview
Problem
In 5G communications networks, there is a lack of methods for policy determination using network data analytics functions (NWDAF) to dynamically adjust and refine service execution policies based on real-time network and terminal device parameters.
Innovation Solution
A policy determining method and apparatus that involves obtaining policy information from a data analytics network element, determining an execution policy based on this information, and dynamically adjusting it using a policy control network element, which includes sending service types and network parameters to determine and update policies for optimal service delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a data analytics network element is introduced to determine policies dynamically, then service quality and adaptability are improved, but device complexity and system architecture complexity increase
Solution Approach 1:
A data analytics network element is introduced as an intermediary component between the service management system and the network infrastructure. This intermediary collects network data, performs analytics processing, and generates policy recommendations, thereby enabling dynamic policy adjustment without requiring complex modifications to existing network elements. The intermediary nature isolates complexity to a dedicated analytics component while maintaining simplicity in other parts of the system.
Solution Approach 2:
The policy determination function is segmented into a separate data analytics network element, distinct from traditional network control elements. This segmentation allows the analytics function to be independently developed, deployed, and optimized. The policy determination process is divided into data collection, analytics processing, and policy generation stages, each handled by appropriate network elements, reducing overall system complexity while improving adaptability.
2Speed
If real-time data analytics are performed to adjust policies dynamically, then service quality and responsiveness are improved, but processing time and computational resources increase
Solution Approach 1:
The data analytics network element performs preliminary analytics processing on collected network data to pre-generate policy recommendations before actual policy adjustments are needed. By preparing policy options in advance based on trending data and predictive analytics, the system can rapidly implement policy changes when conditions warrant, reducing the real-time processing burden and accelerating policy adjustment speed.
Solution Approach 2:
A feedback mechanism is established where the data analytics network element continuously monitors policy effectiveness and network performance. The analytics results feed back into the policy determination process, enabling iterative optimization. This feedback loop allows the system to learn from past decisions and improve future policy adjustments, enhancing responsiveness while optimizing resource utilization through experience-based refinement.
Data Source
AI summary
Embodiments of this application relate to a policy determining method and a communications apparatus. The method includes: obtaining, by a policy control network element, policy information from a data analytics network element; and determining, by the policy control network element, an execution policy of a service based on the policy information. In the policy determining method in the embodiments of this application, dynamic adjustment and refined management on the execution policy can be implemented.