RAN rApp Output Validation for Data Type and Value Consistency
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Solution Overview
Problem
Existing communication systems face challenges in managing inconsistent or invalid data types and values produced by Radio Access Network Intelligent Controller applications (rApps), which can lead to inefficiencies and resource mismanagement in wireless networks.
Innovation Solution
A method and apparatus for a first network apparatus to receive information about the registered data type and data output from rApps, performing determinations on data type inconsistencies and invalid values, and signaling indications to a second network apparatus for optimization, including blacklisting rApps with invalid outputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If rApps are deployed without data validation, then system complexity is reduced, but data reliability deteriorates due to inconsistent or invalid data types
Solution Approach 1:
The patent implements preliminary validation of data types and values before they are processed by the network. The validation mechanism checks data consistency and validity in advance, preventing invalid data from propagating through the system. This resolves the contradiction by maintaining data reliability through pre-validation while keeping the overall system architecture relatively simple.
Solution Approach 2:
The patent introduces an intermediary validation layer between data producers (rApps) and data consumers (network functions). This intermediary component validates data types and values without requiring complex changes to the existing rApp architecture, thus maintaining system simplicity while ensuring data reliability through the mediating validation process.
2Reliability
If data validation is performed on all rApp outputs, then data reliability is improved, but processing time increases
Solution Approach 1:
The patent implements selective validation that focuses on critical data types and values rather than validating every single data element. By validating only the most important aspects of rApp outputs, the system maintains high data reliability for critical parameters while minimizing the time overhead associated with comprehensive validation of all data.
3Adaptability or versatility
If inconsistent data types are allowed, then system adaptability is improved, but resource optimization deteriorates
Solution Approach 1:
The patent implements data validation with specific schemas and value constraints tailored to each data type and context. Rather than imposing a uniform validation approach, the system applies localized validation rules that ensure data consistency for each specific data category while allowing flexibility in how different types of data are structured and interpreted, thus maintaining both adaptability and resource optimization.
Data Source
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AI summary
There is provided an apparatus, computer program, and method for causing a first network apparatus, to perform: receiving, from a data registry, information about a form of a data type registered as being output by a non-real time Radio Access Network Intelligent Controller application, rApp; receiving, from the rApp, a data output; and using said information and the data output to perform at least one of: a first determination that determines that the registered data type is inconsistent in form with the data output; and a second determination that determines that the data output comprises invalid values; and signalling an indication of the result of said first and/or second determination to a second network apparatus.