Data-Driven Network Fault Isolation With Self-Service Automation

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Solution Overview

Problem

Current network maintenance for hybrid SD-WAN and VPN networks relies heavily on manual labor, which is time-consuming and labor-intensive, due to the complexity and instability of these technologies.

Innovation Solution

A data-driven automation platform with a data connector, policy designer, and self-service engine that integrates network data, develops policies, and utilizes microservices to automate network fault isolation with AI/ML capabilities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual work is used to troubleshoot SD-WAN problems, then network maintenance can be performed, but the process becomes time-consuming and labor intensive

Engineering Contradiction:

Improvenetwork maintenance capabilityVSAvoidtroubleshooting time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system enables automated self-service troubleshooting through AI/ML algorithms that automatically analyze network data, identify faults, and execute remediation actions without human intervention. The orchestration platform performs autonomous diagnostic workflows, eliminating the need for manual technician intervention while maintaining reliable network maintenance capabilities.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical troubleshooting processes are replaced with automated computational systems. The patent substitutes human technicians performing manual diagnostics with an automated orchestration platform that uses machine learning models, data analytics, and automated workflow execution to identify and resolve network issues, dramatically reducing troubleshooting time while maintaining reliability.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual work is used to troubleshoot SD-WAN problems, then network maintenance can be performed, but the process becomes labor intensive

Engineering Contradiction:

Improvenetwork maintenance capabilityVSAvoidmaintenance efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If hybrid network solution combining SD-WAN and VPN is implemented, then telecommunication needs are met, but network maintenance complexity increases

Engineering Contradiction:

Improvetelecommunication capabilityVSAvoidnetwork maintenance complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The orchestration platform provides universal troubleshooting capabilities that work across multiple network technologies including SD-WAN, VPN, IPSec, and various protocol layers. The system uses unified AI/ML models and standardized diagnostic workflows that can handle diverse network configurations and fault types, simplifying maintenance of complex hybrid networks by providing a single multi-functional management interface.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces an orchestration platform as an intermediary layer between network operators and the complex hybrid network infrastructure. This intermediary abstracts the complexity of SD-WAN, VPN, IPSec, and protocol-layer interactions, providing simplified automated troubleshooting that manages the underlying complexity while presenting a unified interface to operators.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Adaptability or versatility

If SD-WAN technology is deployed, then dynamic connection capabilities and cost-saving benefits are achieved, but stability and predictability decrease

Engineering Contradiction:

Improvedynamic connection capabilityVSAvoidnetwork stability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system implements continuous feedback loops where AI/ML models constantly monitor network performance, detect anomalies, and automatically adjust configurations to maintain stability. The orchestration platform uses real-time data collection, analysis, and automated remediation to counteract the inherent instability of dynamic SD-WAN environments, providing feedback-driven stabilization while preserving adaptive capabilities.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12375340B2Data driven systems and methods to isolate network faults

Publication Date: 2025.07.29 AT&T INTELLECTUAL PROPERTY I L P

AI summary

Methods, systems and computer readable media for isolating network faults are provided. A data driven automation services module is provided including a data connector, a data driven policy designer and a data driven self-service engine. The data connector collects data from the plurality of network data sources and integrates the data into shared communities for insight development. The data driven policy designer creates and stores templates and develops policies to implement service tasks to identify and isolate network problems. The data driven self-service engine integrates the network and its orchestration capabilities with big data technology to develop a plurality of microservices to perform service tasks.