5G Network Alarm Prioritization Engine
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Solution Overview
Problem
In 5G Telco networks, network administrators face challenges in prioritizing problems due to complexity and shared infrastructure, making it difficult to discern which issues are most urgent from a business cost standpoint, leading to potential downtime and financial losses.
Innovation Solution
A prioritization engine that receives problem notifications from various network components, constructs a mapping matrix to assign weights based on resource types and service classes, and creates a problem-impact matrix to prioritize issues, allowing administrators to address the most critical problems first.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If network administrators monitor all network components in a shared Telco network, then network health visibility is improved, but the complexity of prioritizing problems increases
Solution Approach 1:
The patent segments the network monitoring system into multiple specialized components: an analytics engine that performs root cause analysis, a prioritization engine that ranks problems, and a mapping matrix that correlates network resources. This segmentation allows each component to handle specific tasks, reducing the overall complexity faced by administrators while maintaining comprehensive visibility.
Solution Approach 2:
The patent introduces an intermediary prioritization engine that acts as a mediator between the raw network monitoring data and the administrators. This intermediary automatically analyzes, correlates, and prioritizes problems using the mapping matrix, eliminating the need for administrators to manually assess hundreds or thousands of network issues.
2Productivity
If multiple tenants share the same network infrastructure, then data availability and resource utilization are improved, but the ability to discern which tenants are impacted by which problems deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the prioritization engine continuously receives problem notifications from the analytics engine and updates the mapping matrix accordingly. This feedback loop ensures that as new problems arise or existing problems evolve, the system automatically re-evaluates and re-prioritizes issues based on current tenant impacts, maintaining accurate visibility despite dynamic resource sharing.
Solution Approach 2:
The patent adds a new dimension of analysis by creating a multi-layer mapping matrix that correlates problems across physical, virtual, and service layers with specific tenants. This dimensional expansion allows the system to track and attribute problems to affected tenants even in a highly virtualized environment, providing the necessary visibility without reducing resource utilization.
3Reliability
If network administrators address all problems simultaneously, then comprehensive remediation is achieved, but downtime and financial losses increase
Solution Approach 1:
The patent applies preliminary action by having the prioritization engine pre-rank all detected problems before administrators begin remediation. The system automatically scores and orders problems based on their impact on tenants and services, allowing administrators to immediately begin addressing the most critical issues first without needing to assess priorities during the remediation process, thereby reducing overall downtime.
Solution Approach 2:
The patent introduces dynamics by making the problem prioritization adaptive and changeable in real-time. As new problems are detected or existing problems are resolved, the prioritization engine dynamically re-evaluates and re-orders the problem list. This dynamic approach ensures that administrators always work on the currently most critical issues, optimizing remediation efficiency while maintaining comprehensive coverage of all problems.
Data Source
AI summary
Examples herein describe systems and methods for alarm prioritization in a Telco network. A prioritization engine can receive root cause problems and impacted network components from a network analysis module. The prioritization engine can define a mapping matrix that weights the problems according to network component type and service level. Using the problem weights, the prioritization engine can construct a problem-impact matrix that includes impact weights. The impact weights can be summed for each problem, as can the problem weights. The problems with the highest summed weights can then be prioritized first. The summed weights can also be based on predicted failure costs, such that the most expensive problems are prioritized first. The prioritization engine can send prioritized alerts for the problems for display on a graphical user interface (“GUI”).