Cross-Layer AI Fault Tracking for Application Anomaly Detection

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Solution Overview

Problem

Conventional network systems struggle with complex fault tracking and anomaly detection across multiple layers, particularly in 5G networks, as they are unable to correlate network problems with application issues, leading to inefficient performance improvement and scalability challenges.

Innovation Solution

A cross-layer automated fault tracking and anomaly detection system using artificial intelligence engines to correlate errors across various networking stack layers, including the transport, network, and media access control layers, to identify and address the root cause of application failures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional network monitoring is used, then network operations can be maintained, but fault tracking and anomaly detection across multiple layers become complex and ineffective

Engineering Contradiction:

Improvefault tracking accuracyVSAvoiderror tracking complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent combines error tracking across multiple network layers (application layer, transport layer, network layer, data link layer, physical layer) into a unified error database. This merging allows correlated analysis of errors from different layers to identify root causes, transforming the complex multi-layer tracking problem into a single integrated system that improves reliability without proportionally increasing complexity.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces an intermediary error database and analysis system that sits between the various network layers and the monitoring function. This intermediary collects, stores, and correlates errors from all layers, acting as a mediator that simplifies the tracking process by providing a centralized view rather than requiring direct monitoring of each layer separately.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If data sharing from application layer is restricted, then application security is maintained, but network cannot improve performance when problems occur

Engineering Contradiction:

Improveperformance improvement capabilityVSAvoidapplication error information availability

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The error database acts as an intermediary that receives error information from the application layer without requiring direct data sharing or integration into the application code. This intermediary approach allows the network to access application error data for performance improvement while maintaining application security and encapsulation boundaries.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments error information collection from error handling and recovery functions. Error data is collected and stored in the database separately, while application security and error response remain independent. This segmentation allows performance improvement through error analysis without compromising application layer security or requiring tight integration.

Inventive Principle:

Principle #1Segmentation

3Adaptability or versatility

If 5G networks add additional services, then network functionality is enhanced, but error tracking becomes more complicated

Engineering Contradiction:

Improveservice capabilityVSAvoiderror tracking complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The error database and tracking system is designed with universality to handle multiple 5G services and error types from different network layers. Rather than creating separate tracking mechanisms for each service, a single multi-functional error database collects and correlates errors from all services, reducing complexity while supporting enhanced network functionality.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Reliability

If restrictive SLA requirements are imposed, then service quality is improved, but control and recovery mechanisms become more difficult to implement

Engineering Contradiction:

Improveservice level agreement complianceVSAvoidcontrol and recovery mechanism implementation

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system implements feedback mechanisms where errors are continuously monitored, stored in the database, and analyzed to identify patterns and root causes. This feedback loop enables automated recovery actions and control adjustments to meet restrictive SLA requirements without manual intervention, simplifying the implementation of control and recovery mechanisms.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12375365B2Cross-layer automated fault tracking and anomaly detection

Publication Date: 2025.07.29 INTEL CORP

AI summary

Systems and techniques for cross-layer automated fault tracking and anomaly detection are described herein. Anomaly data may be obtained from a plurality of layers of a network. Elements of the anomaly data may be identified that correspond to a data flow of an application executing on the network. An artificial intelligence model may be trained using the elements of the anomaly data to generate an impact score for the application. The impact score may be generated for the application by evaluating current network metrics using the artificial intelligence model. An operational component of the network may be modified based on the impact score.