Unified Network Congestion Detection via Multi-Layer Data Correlation
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Solution Overview
Problem
Traditional performance monitoring tools in modern networks operate in silos, failing to provide a comprehensive view of network performance from an end-user perspective and do not analyze correlated information across multiple layers of the network stack, making it challenging to obtain business-level insights and control.
Innovation Solution
A method for automated detection of congestion incidents in enterprise networks, involving real-time data collection, performance metric computation, peak usage time detection, and identification of root causes, with capabilities for cross-company comparison and prediction of future congestion incidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional performance monitoring tools operate in silos on individual network layers, then each tool can monitor its specific layer, but they fail to provide a comprehensive view of network performance from end-user perspective
Solution Approach 1:
The patent combines multiple siloed monitoring tools into a unified system that collects and analyzes data across all network layers (application, transport, network, data link, and physical layers) simultaneously. This integration enables comprehensive end-user experience measurement while managing complexity through centralized architecture.
Solution Approach 2:
The monitoring system is designed to perform multiple functions across different network layers using a single unified platform. It can monitor application performance, network traffic, device status, and user experience simultaneously, making the system versatile and comprehensive rather than specialized for single-layer monitoring.
2Loss of information
If traditional tools do not analyze correlated information across multiple layers, then implementation is simpler, but business-level insights and control cannot be obtained
Solution Approach 1:
The patent introduces correlation analysis mechanisms that act as intermediaries between different network layer data. These mechanisms connect and correlate information from application layer, transport layer, network layer, data link layer, and physical layer, enabling comprehensive business-level insights by synthesizing multi-layer correlated information.
3Reliability
If real-time network data is collected and analyzed across multiple layers, then comprehensive congestion detection is achieved, but computational complexity and data processing requirements increase
Solution Approach 1:
The patent segments the network monitoring system into distinct functional modules corresponding to different network layers (application layer monitoring, transport layer monitoring, network layer monitoring, etc.). Each module processes data for its specific layer, reducing overall computational complexity while maintaining comprehensive multi-layer analysis capability for accurate congestion detection.
Data Source
AI summary
A system and method for client network congestion analysis and management is disclosed. According to one embodiment, the method includes: collecting real-time network data; executing calculations on the real-time network data to compute performance metrics; detecting peak usage time; and detecting one or more congestion incidents, wherein a congestion incident comprises a persistence of one or more metrics over a time window that comprises detecting a proportion of metric values crossing a threshold that exceeds a defined percentage amount, detecting a time-ordered stretch of metric values that exceeds a defined threshold, or combinations thereof.