Communication method and apparatus for improving accuracy of adjusting an application layer parameter by a service provider
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Solution Overview
Problem
Current technologies fail to accurately adjust application layer parameters due to data privacy and security constraints, preventing network devices from sharing comprehensive data with service providers, which hinders optimal service experience.
Innovation Solution
A communication method involving multiple network devices exchanging and analyzing data to determine service experience information, using federated learning to create virtual models that protect privacy and enhance parameter adjustment accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network devices share comprehensive data with service providers to improve parameter adjustment accuracy, then service experience is improved, but data privacy and security are compromised
Solution Approach 1:
The patent divides data processing into segments: network devices perform local data analysis to extract features and generate analysis results, while raw data remains segmented at each device. Only processed analysis results are shared across the network, not the original comprehensive data, thus improving parameter adjustment accuracy without compromising data privacy and security.
Solution Approach 2:
The patent introduces an intermediary processing layer where network devices act as intermediaries between data generation and service provider parameter adjustment. These devices perform local analysis and feature extraction, serving as mediators that enable information sharing while protecting raw data privacy and security through centralized processing.
2Manufacturing precision
If network devices provide detailed private data to service providers, then application layer parameter adjustment is improved, but network security is compromised
Solution Approach 1:
The patent extracts only the necessary analysis results and features from comprehensive private data at each network device. By taking out and sharing only the processed analysis results rather than the original private data, the system achieves precise application layer parameter adjustment while minimizing network security risks associated with transmitting sensitive information.
Solution Approach 2:
The patent creates copies of processed analysis results at each network device, allowing these copies to be shared and used for parameter adjustment without exposing the original private data. This copying approach enables parameter adjustment precision while maintaining network security by working with derived information rather than source data.
3Reliability
If comprehensive data analysis is performed at each network device, then service experience is improved, but device complexity increases
Solution Approach 1:
The patent applies local quality by having each network device perform data analysis and feature extraction locally according to its specific characteristics and capabilities. Each device processes data with appropriate quality and depth for its role in the network, improving service experience while avoiding unnecessary complexity from uniform comprehensive processing across all devices.
Data Source
AI summary
A communication method and apparatus. A first network device obtains first information from a second network device. The first network device obtains second information from a third network device. The first network device determines first experience information of a service of the terminal based on the first information and the second information. The first network device sends the first experience information to a fourth network device, where the first experience information is for determining a parameter that is of the service of the terminal and that is on the fourth network device.