Network Trace Correlation for Root Cause Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern telecommunications networks face service degradation due to data traffic congestion, leading to packet loss, queuing delays, and connection issues, which degrade Quality of Service (QoS) and Quality of User Experience (QoE), as conventional approaches rely on manual analysis of data traffic at individual nodes, making it difficult to identify root causes and optimize services effectively.
Innovation Solution
The solution involves collecting and correlating trace files from multiple nodes across the network to automatically identify the root cause of service degradation, providing alert notifications and optimization recommendations to network administrators, enabling timely and efficient service optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual analysis of data traffic at individual nodes is used, then device complexity is reduced, but measurement precision and productivity deteriorate
Solution Approach 1:
The patent merges trace data from multiple network nodes into a unified trace file, combining information that would otherwise be分散 at individual nodes. This allows comprehensive network-wide analysis while maintaining manageable system complexity through automated processing of the consolidated data.
Solution Approach 2:
The patent introduces an intermediary system that collects, correlates, and analyzes trace files from multiple nodes. This intermediary automatically processes the data to identify root causes, eliminating the need for complex manual analysis while improving measurement precision through systematic data correlation.
2Device complexity
If manual analysis of data traffic is used, then device complexity is reduced, but productivity deteriorates
Solution Approach 1:
The system implements self-service through automated trace file collection, correlation, and analysis. The network management system automatically identifies service degradation issues and root causes without requiring manual intervention, significantly improving productivity while keeping the interface simple for operators.
Solution Approach 2:
The patent establishes a feedback loop where trace data is continuously collected, analyzed, and used to identify optimization opportunities. This automated feedback mechanism enables rapid detection and response to network issues, improving service optimization speed without increasing operational complexity.
3Measurement precision
If trace files from multiple nodes are collected and correlated, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent segments the trace correlation process into distinct functional modules: trace file collection from individual nodes, correlation processing to link related traces, and analysis to identify root causes. This segmentation improves measurement precision through comprehensive data linkage while managing complexity through modular architecture.
4Productivity
If automated trace file analysis is implemented, then productivity improves, but use of energy increases
Solution Approach 1:
The patent applies partial action by focusing computational resources on analyzing only the trace files and data packets relevant to identified service degradation issues. Rather than continuously processing all network traffic data, the system activates automated analysis only when performance thresholds are breached, improving productivity while controlling energy consumption.
Data Source
AI summary
The techniques described herein present opportunities for service providers and/or network providers to optimize the Quality of User Experience (QoE) for data services by determining, using a broader network-based approach, the root cause of problems causing a service degradation. To determine the root cause of the problems, the techniques may collect different trace files from multiple different nodes in the telecommunications network. Each trace file includes a log of trace identifiers for numerous different data packets that have been generated, received, transmitted, relayed, and/or routed via the node in the telecommunications network, and each trace file log entry may be associated with a timestamp. Once collected, the techniques may correlate the different trace files from the multiple different nodes to identify, using a broader network-based analysis, service optimization opportunities.