Managed Unit Self-Optimization Trigger Rules
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Solution Overview
Problem
Conventional network optimization for LTE systems is complex and labor-intensive, requiring manual intervention and high skill levels due to the lack of control support for self-optimization functions through the northbound interface between Network Management Systems and Element Management Systems, increasing processing time and complexity.
Innovation Solution
A managed unit executes self-optimization according to a self-optimization trigger rule, eliminating the need for manual configuration modification commands, thereby simplifying the process and reducing manual processing time, using classes such as SOManagementCapablity, SOTriggerRule, and SOProcess to automate optimization processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual analysis and configuration modification commands are used for self-optimization, then optimization can be performed, but the process complexity and processing time increase significantly
Solution Approach 1:
The managed unit is enabled to automatically execute self-optimization by evaluating trigger rules and implementing optimization actions without requiring manual intervention. The system self-services by autonomously collecting data, analyzing conditions, and applying optimizations based on predefined rules, eliminating the need for manual analysis and command execution while reducing process complexity
Solution Approach 2:
Trigger rules are pre-configured in the managed unit before optimization execution. These rules contain predefined conditions, thresholds, and optimization actions that are prepared in advance. When monitoring data satisfies these pre-set rules, the system automatically executes the corresponding optimization without requiring real-time manual analysis, thus reducing both complexity and processing time
2Productivity
If manual analysis and configuration modification commands are used for self-optimization, then optimization can be performed, but manual processing time increases
Solution Approach 1:
The managed unit autonomously performs the complete self-optimization workflow including data collection, rule evaluation, and action execution without human intervention. This automation eliminates manual processing time while maintaining high execution speed through continuous automated monitoring and immediate response when trigger conditions are met
Solution Approach 2:
The system implements continuous automated monitoring of network parameters and persistent evaluation of trigger rules in real-time. This continuous automated operation eliminates interruptions caused by manual analysis, ensuring uninterrupted optimization execution and significantly reducing the time from condition detection to optimization implementation
Data Source
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AI summary
A managed unit device, a self-optimization method and system are provided. The method includes: executing, by a managed unit, a self-optimization according to a self-optimization trigger rule. The self-optimization trigger rule is created by a managing unit according to a self-optimization capability supported by the managed unit. The technical solution avoids completing the self-optimization in a mode in which a user sends a corresponding configuration modification command, thereby greatly reducing the complexity of a self-optimization process the manual processing time of the self-optimization.