VoIP Fault Location Detection via Call Detail Record Analysis
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Solution Overview
Problem
VoIP service providers face challenges in detecting faults and maintaining network quality, as existing systems lack proactive measures to address potential issues before they become catastrophic failures, and there is a need to enhance predictive maintenance using quality of service metrics from call detail records.
Innovation Solution
A monitoring system that collects and analyzes multiple call detail records across a VoIP network to detect faults, identify fault locations, and generate maintenance alerts, including call loop events, fault location detection, and trunk failure predictions, using a rules-based engine and processing modules to correlate and process the data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fault detection methods are used in VoIP networks, then fault detection capability is limited, but system complexity remains low
Solution Approach 1:
The system performs preliminary actions by continuously collecting and analyzing call detail records to establish baseline quality metrics and detect trends before failures occur. This proactive approach enables predictive maintenance by identifying potential issues in advance, improving fault detection capability without requiring complex real-time intervention systems
Solution Approach 2:
The patent introduces an intermediary analysis layer that processes call detail records and quality metrics between the network elements and maintenance operations. This intermediary system correlates data from multiple sources to identify faults and trends, enhancing detection capability while maintaining manageable system complexity through modular architecture
2Reliability
If reactive maintenance is performed after failures occur, then maintenance cost is reduced, but network reliability deteriorates
Solution Approach 1:
The system performs preliminary analysis of call detail records to detect trends and anomalies before they result in network failures. By identifying potential issues in advance through continuous monitoring and correlation of quality metrics, the system enables proactive maintenance actions that prevent failures, thereby improving network reliability without significant time loss
Solution Approach 2:
The patent implements feedback mechanisms where analyzed call detail records and detected trends trigger alerts and maintenance workflows. This feedback loop enables the system to respond to potential failures before they occur, improving both network reliability and response time by providing early warning signals that initiate preventive maintenance actions
3Measurement precision
If comprehensive monitoring of all call detail records is implemented, then fault detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system extracts and focuses on specific relevant fields from call detail records that are most indicative of faults and quality issues. By selecting and analyzing only the critical data elements rather than processing all raw data comprehensively, the system maintains high fault detection accuracy while reducing processing complexity through targeted data extraction
Solution Approach 2:
The patent segments the data processing task by dividing call detail record analysis into distinct analytical components and processing stages. This segmentation allows the system to handle different types of data and analysis separately, improving fault detection accuracy through specialized processing while managing complexity through modular, organized data handling approaches
Data Source
AI summary
An arrangement analyzes a plurality of call detail records from multiple sources and find those records related to multiple attempts to set up a particular user's call(s). The call detail records are filtered to establish an understanding of fault location likely to be responsible for what is deemed to be a defective call.