Communications Device Diagnostics via Remote Data Correlation
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Solution Overview
Problem
Current IP telephony troubleshooting methods, such as syslog and RTCP-XR call statistics, often fail to provide sufficient data for efficient fault diagnosis, leading to prolonged service interruptions and increased burden on end users due to the complexity of VOIP systems and limited logging options in live environments.
Innovation Solution
A method and system for providing diagnostics and troubleshooting tools that involve defining data elements associated with communications device operation, setting thresholds, capturing diagnostics and fault events, and transmitting this data to a remote computing device for analysis, enabling efficient fault diagnosis and timely resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional troubleshooting methods (syslog, RTCP-XR) are used, then the system maintains simplicity in implementation, but the diagnostic data sufficiency deteriorates leading to prolonged fault resolution times
Solution Approach 1:
The system performs preliminary data collection and analysis by continuously monitoring communications device operations, capturing call detail records, and pre-processing diagnostic information before faults occur. This allows the system to have diagnostic data ready when faults happen, eliminating the need for reactive data collection and reducing fault resolution time.
Solution Approach 2:
The invention introduces an intermediary diagnostic system that sits between the communications device and the troubleshooting process. This intermediary automatically collects, correlates, and analyzes data from multiple sources (call detail records, device operations, network conditions) and presents synthesized diagnostic information to technicians, improving measurement precision without requiring complex manual troubleshooting procedures.
2Loss of information
If comprehensive logging is enabled in live environments, then the diagnostic information completeness improves, but the system complexity and performance overhead increase
Solution Approach 1:
The system extracts only the most relevant diagnostic information from communications device operations by defining specific data elements of interest (call detail records, error conditions, performance metrics). Instead of logging all possible data, the system selectively captures and correlates only those elements that provide actionable diagnostic value, reducing information loss without adding unnecessary complexity.
Solution Approach 2:
The diagnostic system is designed to universally collect and correlate multiple types of data (call detail records, device operations, network conditions) through a single integrated platform. This multi-functional approach consolidates what would otherwise require multiple separate logging systems into one unified solution, improving information completeness while managing system complexity.
3Measurement precision
If detailed fault analysis data is collected and transmitted to remote devices, then the fault diagnosis accuracy improves, but the data transmission overhead and processing burden increase
Solution Approach 1:
The system performs preliminary data processing and correlation locally at the communications device before transmission. By pre-analyzing call detail records and device operation data, the system identifies and transmits only the most relevant fault indicators and correlated information, rather than transmitting all raw data. This reduces data transmission energy while maintaining high fault diagnosis accuracy.
Solution Approach 2:
The diagnostic system applies local quality processing by tailoring the level of data collection and transmission to the specific fault condition detected. Different fault types trigger different data collection strategies, transmitting only the relevant subset of information needed for that particular diagnosis. This optimized approach maintains diagnostic accuracy while minimizing unnecessary data transmission energy consumption.
Data Source
AI summary
A method facilitating the support of a communications device via diagnostic tools on the communications device and a remote computing device of monitoring predefined data elements associated with the operation of said communications device.