Mobile Network Analytics Using Area Association Aggregation
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Solution Overview
Problem
Current 5G systems lack mechanisms to efficiently retrieve historical and current association information for network entities serving a specific area of interest, leading to increased data collection load and incomplete information, particularly for Network Data Analytics Function (NWDAF) operations.
Innovation Solution
Implement network entities and methods that enable efficient data collection by sending requests or subscriptions to multiple network entities to gather past and current association information for an area of interest, aggregating this data, and providing analytics information with reduced signaling load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network data is collected and stored in a centralized database for analytics, then analytics capability is improved, but network privacy is compromised and data security risks increase
Solution Approach 1:
The patent segments the centralized analytics system into distributed analytics units deployed at edge locations (e.g., base stations, access points). Each unit processes local network data independently, eliminating the need to centralize sensitive data in a single database while maintaining analytics functionality across the network.
Solution Approach 2:
The patent introduces trusted execution environments (TEEs) and secure enclaves as intermediary layers between data collection and analytics processing. These intermediaries enable confidential computing by isolating sensitive data processing from external access, allowing analytics to be performed on encrypted data without exposing the underlying information.
2Measurement precision
If network data is collected and stored for analytics generation, then analytics accuracy is improved, but data security vulnerabilities and hacking risks increase
Solution Approach 1:
The patent extracts sensitive data processing operations from vulnerable centralized storage systems and relocates them to secure edge computing nodes with isolated execution environments. This extraction removes the attack surface associated with centralized databases while preserving the analytical value of the data through distributed processing.
Solution Approach 2:
The patent implements security measures beforehand by deploying trusted execution environments and cryptographic protection mechanisms before data is collected or processed. These pre-established security layers cushion against potential hacking attempts and data breaches, ensuring that even if data is collected, it remains protected throughout the analytics pipeline.
3Productivity
If comprehensive network data is collected for analytics, then network optimization capability is improved, but system complexity and data management overhead increase
Solution Approach 1:
The patent segments the network into autonomous edge domains, each with its own analytics processing capability. This segmentation distributes data management responsibilities across multiple independent nodes rather than requiring centralized control, reducing the complexity burden on any single system component.
Solution Approach 2:
The patent enables edge analytics nodes to autonomously process and analyze their own local network data without requiring centralized data collection and management. Each node performs self-service analytics, generating insights locally and reducing the overall system's data management overhead while maintaining comprehensive network optimization capability.
Data Source
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AI summary
The present disclosure relates to a new generation mobile network, and particularly to the generation of analytics information in the network. To this end, the disclosure proposes a first network entity for generating the analytics information, and proposes a second network entity and a third network entity, respectively, for supporting the analytics generation. The first network entity is configured to obtain, from the second network entity or from one or more third network entities, past and/or current association information for an area of interest. Further, it is configured to provide analytics information based on the obtained association information for the area of interest. The past and/or current association information indicates one or more other network entities and/or network properties that, respectively, have been and/or are mapped to or serving the area of interest.