Intelligent Network Analytics Architecture for Fault Detection

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Solution Overview

Problem

Operating large wireless telecommunication networks is labor-intensive and time-consuming, as operators must manually identify and solve network problems, which often only address issues at specific locations, leaving other areas vulnerable, and lack efficient feedback mechanisms for recurring issues.

Innovation Solution

Implementing an intelligent network analytics architecture (INAA) that monitors networks in real-time, automatically detects faults, develops and implements solutions, and predicts potential issues across the network, using a policy engine, learning/feedback system, and analytics library to analyze conditions and configure network settings.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual analysis by operators is used to identify and solve network problems, then labor intensity and time consumption increase, but the system can address specific location issues with human expertise

Engineering Contradiction:
Improvefault detection and correction speedVSAvoidsystem complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The network system performs self-diagnosis and self-correction through automated fault detection and resolution mechanisms. The system monitors its own operational status, identifies anomalies, and implements corrective actions without requiring continuous manual operator intervention, thereby increasing productivity while managing complexity through automation.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system incorporates feedback loops where operational data from network elements is continuously collected, analyzed, and used to adjust network configuration and detect faults. This closed-loop feedback mechanism enables automated decision-making and correction, improving response speed while systematically managing the complexity of network operations.

Inventive Principle:
Principle #23Feedback

2Reliability

If solutions are applied to only one location in the network, then the immediate problem is addressed, but other locations remain vulnerable to the same problem

Engineering Contradiction:
Improvenetwork-wide protectionVSAvoidsolution implementation complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The fault detection and correction system is designed to operate across multiple network locations simultaneously. Once a fault pattern is identified at one location, the system automatically applies the same corrective solution to other locations with similar configurations, providing network-wide protection while managing complexity through standardized remediation procedures.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system proactively identifies and applies corrections to potential fault locations before problems actually occur. By analyzing network configurations and operational patterns, the system preemptively implements protective measures across multiple locations, enhancing reliability while systematically managing the complexity of widespread deployment.

Inventive Principle:
Principle #10Preliminary action

3Adaptability or versatility

If manual problem-solving processes are used without feedback mechanisms, then individual problems are solved, but recurring issues lack efficient learning and prevention capabilities

Engineering Contradiction:
Improvelearning and prevention capabilityVSAvoidfeedback system complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements comprehensive feedback mechanisms that continuously collect data from fault detection, analysis, and correction processes. This feedback is used to update the system's knowledge base, improve future fault detection accuracy, and prevent recurring issues. The feedback loop systematically manages complexity by automating the learning process rather than requiring manual analysis of each new problem.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system replaces manual mechanical problem-solving processes with automated electronic analysis and decision-making systems. Machine learning algorithms and automated rule engines substitute for human operators in analyzing fault patterns and implementing corrections, thereby enhancing adaptability and learning capabilities while systematically managing the complexity of feedback processing.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS9888397B1Intelligent network analytics architecture
Publication Date: 2018.02.06 VERIZON PATENT & LICENSING INC
  • US9888397B1 patent drawing
  • US9888397B1 patent drawing
  • US9888397B1 patent drawing

AI summary

Techniques described herein may be used to implement an intelligent network analytics architecture (INAA) capable of monitoring a network in real-time and detecting faults occurring in the network. The INAA may develop and implement solutions to the problems, and subsequently verify that the solutions actually fixed the problems. The INAA may cause the solutions to be implemented throughout the network (and not just at the source of the initial problem). The INAA may identify other aspects of the network that are likely to experience similar (though not the same) problems in the future, develop solutions to those problems, and implement the solutions throughout the network. The INAA may enable an operator to participate in this process by providing a complete explanation of, and proposed solution to, a particular problem, and enabling the operator to approve, prevent, modify, postpone, etc., the implementation of the solution.