PIN Service Parameter Learning Through Network Function Mediation
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Solution Overview
Problem
Existing systems face challenges in dynamically configuring parameters for personal Internet of Things (IoT) services after user subscription, particularly in Personal IoT Networks (PINs), where devices like smart watches and mobile phones interact with wearable devices, requiring efficient management of subscription, application, network, session, and gateway information data.
Innovation Solution
A method and apparatus for a first and second network function to learn and send configuration parameters based on identifiers, including subscription, application, network, session, and gateway information data, ensuring accurate and dynamic service configuration for PIN elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If parameters are manually configured for each PIN service after user subscription, then service configuration accuracy is improved, but system complexity and configuration time increase significantly
Solution Approach 1:
The system enables automatic parameter configuration through the AF sending service parameters to the NEF, which then automatically obtains configuration parameters from the UDR using the GPSI identifier. This self-service mechanism eliminates manual configuration while maintaining accuracy, as the system automatically retrieves and applies the correct parameters for each PIN service.
Solution Approach 2:
The NEF acts as an intermediary between the AF and the UDR, facilitating automatic parameter configuration. The NEF receives service parameters from the AF, uses the GPSI to query the UDR for configuration parameters, and applies these parameters to the PIN service. This intermediary approach simplifies the overall system by centralizing the configuration process.
2Adaptability or versatility
If dynamic parameter configuration is implemented for subscribed PIN services, then service adaptability is improved, but information management complexity increases
Solution Approach 1:
The UDR serves as a universal repository storing configuration parameters for multiple PIN services under a single user profile. The system uses a unified approach where the AF sends service parameters, the NEF queries the UDR using the GPSI, and retrieves all necessary configuration parameters (subscription data, application data, network data, session data, service instance data, gateway information data) in one process, reducing information management overhead.
3Measurement precision
If multiple identifiers are used to associate communication devices with services, then service tracking accuracy is improved, but system operation complexity increases
Solution Approach 1:
The NEF acts as an intermediary that handles the complexity of identifier management. The system uses the GPSI (external identifier) as the primary key for querying the UDR, while internally maintaining associations with other identifiers (SUPI, PDU session information, network identifiers, etc.). The NEF automatically manages these associations, presenting a simplified interface to the AF while ensuring accurate device-service tracking.
Data Source
AI summary
A parameter obtaining method and apparatus, a first network function, and a second network function are provided. The parameter obtaining method includes: learning, by the first network function, a configuration parameter of a target service on the basis of a first identifier or a second identifier. The configuration parameter includes at least one of the following: subscription data of the target service; application data of the target service; network data, session data or service instance data of the target service; or gateway information data of the target service. The first identifier is associated with the second identifier, and the first identifier or the second identifier is associated with one or more first communication devices.