Outer Loop Health Checks for Faster Communication Network Validation
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Solution Overview
Problem
Self-organizing networks (SONs) in communication networks face challenges with serial/sequential modification and validation procedures that are too slow for modern networks with numerous nodes, leading to potential network inoperability due to time constraints and errors.
Innovation Solution
Implementing an outer loop health check (OLHC) system that allows parallel validation of network modifications, using machine learning and artificial intelligence to analyze logs of actions against historical data and thresholds, enabling rapid identification and remediation of errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If serial/sequential modification and validation procedures are used in SONs, then validation thoroughness is improved, but network productivity and speed of modifications deteriorate
Solution Approach 1:
The patent implements preliminary validation checks before modifications are fully enacted. The system performs pre-validation of modification parameters and predicts potential issues before they impact the network, allowing rapid modifications while maintaining reliability through advance verification.
Solution Approach 2:
The system enables continuous network operation during modification validation through parallel processing. Multiple validation checks occur simultaneously in the background while the network remains operational, eliminating the need for sequential stop-and-test procedures that halt productivity.
2Measurement precision
If serial/sequential modification and validation procedures are used in SONs, then error detection capability is improved, but time consumption and duration of modifications worsen
Solution Approach 1:
The system performs preliminary error detection through pre-validation of modification parameters against predefined rules and historical data before modifications are applied. This preliminary check catches potential errors early, preventing time-consuming rollback procedures and ensuring rapid, error-free modifications.
Solution Approach 2:
The patent replaces traditional sequential mechanical validation procedures with AI/ML-based predictive analytics. Machine learning models analyze modification patterns and predict potential errors in real-time, substituting slow sequential validation with fast parallel predictive analysis that maintains high error detection capability.
3Stability of the object's composition
If extensive validation and testing are performed on network modifications, then network stability is improved, but modification speed and responsiveness worsen
Solution Approach 1:
The system performs preliminary stability assessment through pre-validation checks that verify modification parameters against network stability criteria before enactment. This advance verification ensures network stability is maintained while enabling rapid modifications without extensive post-deployment testing.
Solution Approach 2:
The patent implements continuous feedback loops where AI/ML models learn from historical modification outcomes and network performance data. This feedback mechanism refines validation rules over time, improving network stability through accumulated knowledge while reducing the need for extensive validation on each new modification, thereby increasing modification speed.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, examining first actions imposed as part of a maintenance activity in respect of a communication network while the communication network is subjected to second actions as part of the maintenance activity, determining, based on the examining, that the first actions, in whole or in part, fail to adhere to a threshold, a requirement, or a specification, and based on the determining, reversing at least one action of the first actions. Other embodiments are disclosed.