Network Fault Prioritization via User Impact Analysis
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Solution Overview
Problem
Current network monitoring systems face challenges in efficiently identifying and prioritizing faults in utility supply networks, as they generate overwhelming alarms, often prioritizing issues based on crude metrics that may not accurately reflect user impact, and struggle to distinguish between significant and minor faults, leading to delayed repairs and poor customer experience.
Innovation Solution
A method that combines objective network performance data with subjective user queries to identify faults, prioritizing issues that significantly impact user experience by comparing query thresholds and performance degradation against historical data, and verifying repairs through user behavior post-fix.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional alarm-based monitoring systems are used to track network faults, then comprehensive fault detection coverage is achieved, but the volume of alarms becomes overwhelming and difficult to prioritize
Solution Approach 1:
The patent segments the network into multiple geographic regions and divides alarms into hierarchical categories (critical, major, minor). This segmentation allows the system to manage overwhelming alarm volumes by organizing them into manageable groups that can be prioritized and routed to appropriate response teams based on severity and location.
Solution Approach 2:
The system changes the parameters used for alarm evaluation by introducing user impact metrics and geographic concentration factors. Instead of treating all alarms equally, the system dynamically adjusts alarm priority based on changing parameters such as number of affected users, location sensitivity, and time of day, enabling effective prioritization despite high alarm volumes.
2Productivity
If alarms are prioritized based on crude metrics such as number of users served or revenue generated, then prioritization automation is achieved, but accuracy in identifying user-impactful faults deteriorates
Solution Approach 1:
The system implements feedback loops where alarm prioritization is continuously refined based on actual user impact data and repair outcomes. User complaints, service quality metrics, and repair effectiveness feed back into the prioritization algorithm, allowing the system to learn and improve its accuracy over time while maintaining automated high-speed prioritization.
Solution Approach 2:
The patent creates a composite prioritization metric that combines multiple factors including user impact, geographic concentration, service level agreements, and historical data. This composite approach integrates diverse data sources into a unified prioritization score, achieving both automation speed and improved accuracy in identifying truly critical faults.
3Reliability
If network services are suspended for planned maintenance or upgrades, then network improvements are achieved, but service outages occur affecting user experience
Solution Approach 1:
The system performs preliminary actions by proactively scheduling maintenance during periods of low user impact and pre-coordinating with affected users. The prioritization system identifies optimal maintenance windows before outages occur, allowing the network to be upgraded with minimal disruption to user experience while still achieving necessary improvements.
4Productivity
If network congestion occurs due to high user demand, then network utilization is maximized, but service quality deteriorates
Solution Approach 1:
The system dynamically adjusts service prioritization and resource allocation based on real-time congestion levels and user impact metrics. During high-demand periods, the system automatically reprioritizes alarms and dispatches based on current network conditions, allowing critical services to receive preferential treatment while maintaining high overall network utilization without permanent quality deterioration.
Data Source
AI summary
A method of identifying faults in a utility supply network is disclosed. The method comprises identifying a first indication of a fault in the communications network based on a number of network performance queries received from users of user equipments (UEs) connected to the communications network within a first region of the communications network. The method further comprises identifying a second indication of a fault in the communications network based on network performance data associated with the first region. It is determined that a fault exists in the communications network based on identification of the first indication and the second indication.