Compound Call Detail Record Correlation for Arbitrage Detection
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Solution Overview
Problem
Current methods for detecting arbitrage in telephone traffic routing are unreliable and labor-intensive, as they rely on incomplete or missing call routing information, and are ineffective in analyzing call routing when records are created for individual call segments only.
Innovation Solution
A method that correlates originating and terminating Call Detail Records (CDRs) to create compound call records, maintaining key parameters from each segment and enriching them with analysis flags to identify arbitrage and routing anomalies, thereby providing a more accurate representation of call routing information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If call records are created for individual call segments only, then record creation is simple and fast, but call routing information is incomplete and unreliable for arbitrage detection
Solution Approach 1:
The patent merges multiple individual call segment records into a single compound call record that contains complete call routing information. This is achieved by correlating CDRs from different network elements and combining them to form a comprehensive view of the entire call path, thereby resolving the contradiction between simple record creation and information completeness.
Solution Approach 2:
The system performs preliminary correlation and aggregation of call segment records before analysis. By pre-processing and combining individual CDRs into compound records in advance, the system ensures that complete routing information is available when needed for arbitrage detection, without sacrificing the efficiency of individual record creation.
2Measurement precision
If multiple CDRs are aggregated into compound records to improve routing information, then billing accuracy and arbitrage detection improve, but system complexity increases
Solution Approach 1:
The patent segments the complex task of call record processing into distinct phases: individual CDR creation, correlation of CDRs, aggregation into compound records, and analysis. This segmentation allows each component to be handled independently with appropriate complexity, improving billing accuracy while managing overall system complexity through modular processing.
Solution Approach 2:
The system introduces an intermediary correlation and aggregation layer between individual CDR collection and final analysis. This intermediary component manages the complexity of combining multiple records by providing standardized interfaces and processing logic, thereby enabling improved billing accuracy without proportionally increasing overall system complexity.
3Reliability
If current methods are used for detecting arbitrage, then labor requirements are high and processes are manual, but implementation is straightforward with existing tools
Solution Approach 1:
The patent implements automated correlation and aggregation processes that self-service the complex task of arbitrage detection. The system automatically correlates CDRs, aggregates them into compound records, and identifies potential arbitrage cases without requiring manual intervention, thereby improving detection reliability while maintaining operational simplicity through automation.
Solution Approach 2:
The system incorporates feedback mechanisms where the results of compound record analysis feed back into the correlation and aggregation processes. This allows the system to continuously improve its arbitrage detection capabilities by learning from past cases, enhancing reliability while the automated feedback loops maintain operational simplicity by reducing manual analysis requirements.
Data Source
AI summary
A system and method for processing gathered call data from a network monitoring system to prepare the call data for analyzing call routing across a network, not limited to call data associated with the transit portion of a call path. The system and method include correlating call data to form a correlated set, ordering the call data in the correlated set to form a compound CDR, and enriching the compound CDR by comparing CDRs within the compound CDR to each other.