Network Rollback System for SON Configuration Errors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Self-Organizing Network (SON) processes in wireless communication networks can inadvertently cause unintended or unwanted configurations, leading to performance issues, and existing solutions lack effective mechanisms to revert changes made during optimization without affecting beneficial modifications.
Innovation Solution
A rollback system that includes modules to request, retrieve, determine, and apply cumulative change types to managed objects in a communication network, allowing for the reversal of changes made within a specified time period, thereby enabling network administrators to undo undesired changes while preserving beneficial configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SON processes continuously optimize network parameters, then network performance is improved, but unintended or unwanted configurations may occur
Solution Approach 1:
The system performs preliminary actions by maintaining a historical record of all parameter changes before optimization occurs. This allows the system to have a ready-to-apply backup state, enabling quick rollback if unintended configurations arise from SON optimization processes.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring network performance after SON-induced changes. When performance degradation or unintended configurations are detected, the system triggers a rollback to the previously recorded state, creating a closed-loop control system that self-corrects optimization errors.
2Object-affected harmful factors
If all changes are rolled back to maintain network stability, then harmful configurations are prevented, but beneficial modifications are also lost
Solution Approach 1:
The system applies local quality by enabling selective rollback of specific parameter changes rather than rolling back all changes uniformly. Network administrators can choose to revert only the harmful configurations while preserving beneficial modifications, allowing localized correction without global reversal.
Solution Approach 2:
The system utilizes parameter changes by tracking the state of individual network parameters before and after SON optimization. This granular tracking enables the rollback mechanism to selectively restore only those parameters that have deteriorated, while maintaining improved parameters at their optimized values.
3Ease of operation
If manual review of each change is performed before rollback, then precise control is achieved, but time consumption increases
Solution Approach 1:
The system implements self-service by automatically monitoring network performance metrics and identifying deteriorated parameters without requiring manual intervention. The rollback mechanism autonomously determines which changes to revert based on performance thresholds, eliminating the need for time-consuming manual review while maintaining precise control.
Solution Approach 2:
The system uses feedback loops to automatically detect performance degradation and trigger rollback actions. By continuously monitoring network parameters and comparing them against performance criteria, the system can automatically initiate rollbacks for deteriorated parameters without manual review, significantly reducing the time required while maintaining operational precision.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Systems and methods for undoing changes or modifications made to a communication network are described. In some embodiments, the systems and methods access a request to rollback one or more changes made to parameters of managed objects associated with a communication network within a given time period, retrieve information identifying the one or more changes made to the parameters of the managed objects within the given time period, and, for each managed object, determine a cumulative changetype (e.g., add, deleted, or update) associated with the one or more changes made to the parameters of the managed object and perform an action to apply the determined cumulative changetype to the managed object.