Alarm Correlation Analysis via Multi-Engine Concurrency

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Solution Overview

Problem

Current alarm correlation analysis methods in communications networks face efficiency bottlenecks due to the limitations of single-engine analysis, which cannot fully utilize multi-core resources for parallel processing, leading to inadequate troubleshooting efficiency.

Innovation Solution

The proposed method involves grouping alarm analysis rules according to specific policies, with each group correlated to a dedicated analysis engine, allowing multiple engines to perform concurrent analysis on a large quantity of alarms, thereby fully utilizing multi-core resources and enhancing analysis efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If single-engine analysis is used for alarm correlation analysis, then the analysis process is simple, but the analysis efficiency is low and cannot meet increasing requirements

Engineering Contradiction:
Improvealarm correlation analysis efficiencyVSAvoidanalysis engine structure
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent divides the alarm correlation analysis function into multiple independent analysis engines, each responsible for specific alarm types or analysis tasks. This segmentation allows parallel processing of alarms across different engines, significantly improving analysis efficiency while maintaining manageable complexity through modular architecture

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent transitions from single-engine sequential analysis to multi-engine parallel analysis by adding a dimensional aspect of concurrency. Multiple analysis engines operate simultaneously on different alarm datasets, transforming the analysis process from one-dimensional sequential execution to multi-dimensional parallel execution, thereby resolving the efficiency bottleneck

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Productivity

If multi-core resources are not fully utilized, then the system structure remains simple, but parallel processing advantage cannot be exerted

Engineering Contradiction:
Improveparallel processing capabilityVSAvoidresource utilization mechanism
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent designs analysis engines that can be configured to handle different alarm types and analysis requirements, making them universally applicable. The same engine architecture can process various alarm correlations by loading different rule sets, maximizing the utilization of multi-core resources without requiring complex specialized hardware for each function

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

Solution Approach 2:

The patent implements dynamic task distribution where alarms are dynamically routed to appropriate analysis engines based on their characteristics. The system can adaptively assign alarm processing tasks to available cores, optimizing resource utilization in real-time without rigid fixed assignments, thus balancing complexity with enhanced parallel processing capability

Inventive Principle:
Principle #15Dynamics

Data Source

PatentEP2838228B1Alarm correlation analysis method, apparatus, and system
Publication Date: 2019.04.03 HUAWEI TECH CO LTD
  • EP2838228B1 patent drawingFigure 1A
  • EP2838228B1 patent drawingFigure 1B
  • EP2838228B1 patent drawingFigure 2A

AI summary

According to an alarm correlation analysis method, apparatus and system provided by embodiments of the present invention, alarm analysis rules are grouped according to a certain policy; each alarm analysis rule group is correlated with one analysis engine, and the analysis engine performs, according to an alarm analysis rule in the alarm analysis rule group corresponding to the analysis engine, correlation analysis for an alarm that has a correlation with the alarm analysis rule group, so that multiple analysis engines implement concurrent analysis on a large quantity of alarms, thereby fully utilizing a multi-core resource, and improving efficiency of alarm correlation analysis.