Tag-Based Network Troubleshooting for Root Cause Detection
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Solution Overview
Problem
Existing communication systems struggle to pinpoint the root cause of network performance degradation, leading to inefficiencies and disruptions.
Innovation Solution
A troubleshooting system that utilizes tagging modules and a tag analyzer to associate tags with network entities based on telemetry data, enabling identification of network issues and providing recommendations for resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional network monitoring methods are used, then network traffic can be observed, but root cause identification is inefficient and time-consuming
Solution Approach 1:
The patent segments network issues into distinct tagged categories (performance tags, connectivity tags, security tags, etc.) that can be independently identified and analyzed. This segmentation allows the system to break down complex network problems into manageable, taggable units that can be quickly correlated to identify root causes, thereby reducing troubleshooting time and improving efficiency.
Solution Approach 2:
The patent introduces tags as an intermediary layer between raw network telemetry data and root cause analysis. These tags serve as mediators that categorize and structure network issues, enabling efficient correlation and analysis. The tag-based intermediary system transforms unstructured network data into organized, searchable information that accelerates root cause identification.
2Measurement precision
If comprehensive network monitoring is implemented, then network performance can be tracked, but pinpointing the specific root cause becomes difficult
Solution Approach 1:
The patent applies local quality by assigning specific tags to different aspects of network entities based on their local characteristics and issues. Each network entity (device, link, service) receives customized tags that reflect its specific performance metrics, connectivity status, security posture, and other localized attributes. This localized tagging approach enables precise root cause identification by highlighting specific quality issues at each network point.
Solution Approach 2:
The patent uses visual tagging analogous to color changes, where different tag types and priorities visually distinguish various network issues. The system categorizes tags by type (performance, connectivity, security) and priority levels, creating a visual language that quickly communicates the nature and severity of root causes. This tagging visualization transforms complex network data into easily interpretable information.
3Ease of operation
If manual troubleshooting processes are used, then detailed analysis is possible, but the process is complex and time-consuming
Solution Approach 1:
The patent implements self-service troubleshooting through automated tag generation, correlation, and analysis. The system automatically collects network telemetry data, generates appropriate tags, correlates tags across network entities, and identifies root causes without requiring manual intervention. This automation simplifies the troubleshooting process while maintaining comprehensive analysis, thereby reducing both complexity and time requirements.
Solution Approach 2:
The patent transforms troubleshooting from a manual process to an automated one by changing the operational parameters of the system. The introduction of structured tags with defined types, priorities, and correlations fundamentally alters how troubleshooting is performed, enabling automated analysis that is both simpler and faster than manual methods while preserving diagnostic depth.
Data Source
AI summary
A network troubleshooting system may include one or more tagging modules configured to associate tags with various network entities. The tags may identify issues experienced or exhibited by the tagged network entity and/or may provide contextual information for the tagged network entity. The network troubleshooting system may include a tag analyzer that correlates the various tags and the associated network entities to identify causes or generally facilitate the mitigation of the issues.