KPI Threshold Correlation Rule Engine for Dynamic Network Monitoring
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Solution Overview
Problem
Communication networks often rely on static systems that are difficult to configure, scale, and deploy, making it challenging to provide flexible, scalable, and diverse network services, especially with the dynamic addition or removal of network service providers and changes in network services, leading to complex monitoring of key performance indicators (KPIs).
Innovation Solution
A KPI monitoring and centralized data storage system that includes a network management platform, central data repository, and user equipment, enabling the generation and application of threshold correlation rules to simplify the monitoring of KPIs across multiple network services and devices, facilitating alert generation and action based on predefined thresholds and breach consistency conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If static systems are used for network monitoring, then system stability is maintained, but device complexity and difficulty of configuration increase
Solution Approach 1:
The patent implements dynamic threshold correlation rules that can be automatically adjusted based on network conditions. The system monitors KPIs and dynamically modifies alert thresholds and correlation criteria, transforming the static monitoring system into a dynamic one that adapts to changing network environments while maintaining stability through automated rule updates.
Solution Approach 2:
The system changes monitoring parameters by allowing operators to define custom thresholds, correlation criteria, and alert conditions. The platform enables parameter modification through automated rule generation and dynamic threshold adjustment, reducing the complexity of manual configuration while maintaining system stability.
2Adaptability or versatility
If multiple network service providers are added dynamically, then service versatility improves, but device complexity and monitoring difficulty increase
Solution Approach 1:
The patent creates a universal monitoring platform that handles multiple network service providers and diverse KPIs through a single integrated system. The threshold correlation rule engine universally applies to different network elements, enabling the system to monitor diverse services from multiple providers without increasing operational complexity.
Solution Approach 2:
The system segments monitoring functions into independent threshold correlation rules that can be individually configured and applied to different network elements. This segmentation allows the system to handle multiple service providers and diverse KPIs through modular rule sets, reducing overall monitoring complexity while maintaining service versatility.
3Measurement precision
If thousands of KPIs are monitored individually, then measurement precision improves, but device complexity and operation difficulty increase
Solution Approach 1:
The patent merges individual KPI monitoring into correlated threshold-based alert rules. Instead of managing thousands of separate KPIs, the system combines related metrics into unified correlation rules that trigger alerts based on predefined conditions, maintaining measurement precision while dramatically simplifying operation.
Solution Approach 2:
The system implements feedback mechanisms where monitored KPIs automatically update threshold correlations and alert conditions. This feedback loop allows the system to maintain precise monitoring of thousands of KPIs while reducing operational complexity through automated rule updates and dynamic threshold adjustment based on real-time performance data.
Data Source
AI summary
A method includes processing parameter selection inputs corresponding to a threshold correlation rule associated with monitoring a communication network. The method also includes processing node selection inputs. The method further includes causing a list of key performance indicators (KPIs) associated with monitoring the communication network to be populated based on the parameter selection inputs and the node selection inputs. The method also includes processing threshold comparison inputs and breach consistency condition inputs to generate the threshold correlation rule. The method further includes comparing KPI values to a threshold comparison target and causing an alert to be generated indicating that an operating state of the communication network is outside a preset performance level.