Network Capability Exposure Using Active Inventory Validation
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Solution Overview
Problem
Existing network exposure functions do not consider network state or resource availability, leading to sub-optimal service experiences and potential failure to meet service level agreements.
Innovation Solution
A system and method that leverages network state information through an active inventory to validate and reserve resources for network capability requests, using an End-to-End Service Orchestrator and Network Exposure Function to ensure intelligent and efficient resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If network capabilities are exposed through standard APIs without considering network state, then API accessibility and ease of operation are improved, but service reliability and resource availability cannot be guaranteed
Solution Approach 1:
The system implements feedback mechanisms where the NEF queries network state information from the Network Subsystem and returns availability status to external entities. This feedback loop enables external entities to make informed decisions about resource allocation while maintaining API accessibility and improving service reliability.
Solution Approach 2:
The system performs preliminary validation of network resource availability before processing API requests. The NEF checks network state information in advance to determine whether requested capabilities can be fulfilled, preventing failed requests and ensuring SLA compliance while maintaining ease of operation.
2Measurement precision
If network state information is integrated with NEF, then resource validation accuracy is improved, but system complexity increases
Solution Approach 1:
The NEF serves as an intermediary between external entities and the Network Subsystem. It maintains a simplified interface for external entities while internally managing complex interactions with the network state. This mediator approach enables precise resource validation without exposing the complexity of network state management to external entities.
Solution Approach 2:
The NEF performs multiple functions including receiving API requests, querying network state information, validating resource availability, and returning appropriate responses. This multi-functionality consolidates complexity into a single component, improving measurement precision while managing system architecture complexity.
3Productivity
If real-time network state queries are implemented, then service quality optimization is improved, but processing time and system response delay increase
Solution Approach 1:
The system performs network state queries and availability validation in advance before processing API requests. By preparing network state information beforehand, the system can quickly respond to incoming requests without real-time queries, improving service quality while minimizing processing time.
Solution Approach 2:
The NEF autonomously queries and processes network state information without requiring external intervention or complex coordination. This self-service capability enables efficient resource validation and quick response to API requests, optimizing service quality while reducing processing time.
Data Source
AI summary
As described herein, a system, method, and computer program are provided for leveraging network state information when exposing network capabilities. A request for one or more capabilities of a network is received from an application by a platform that interfaces the network. The platform communicates with an active inventory of the network for handling the request.