Communication Network Failsafe Control for Cascade Failure Reduction
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Solution Overview
Problem
Automated automation recommendations in communication networks can lead to cascade failures, necessitating human intervention to prevent network downtime and potential service disruptions.
Innovation Solution
A failsafe controller intercepts automation recommendations, implementing guard rails to allow safe operations and blocking potentially risky ones, using impact/risk parameters and failsafe behaviors to manage network changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated automation recommendations are implemented without human intervention, then productivity and response speed are improved, but reliability deteriorates due to cascade failures
Solution Approach 1:
The patent introduces an intermediary evaluation layer between automated recommendation generation and implementation. This intermediary assesses potential cascade failures by analyzing impact parameters before allowing automation to proceed, thus maintaining productivity while preventing reliability degradation through controlled automation.
Solution Approach 2:
The system performs preliminary evaluation of automation recommendations before execution by assessing impact parameters and potential cascade effects. This preliminary action identifies risky operations in advance, allowing safe automation to proceed while blocking potentially harmful actions, thereby resolving the contradiction between automation speed and network stability.
2Reliability
If continuous human intervention is required to prevent cascade failures, then reliability is improved, but device complexity and operational difficulty increase
Solution Approach 1:
The patent implements a self-service automation system that autonomously evaluates recommendations using predefined impact parameters and failsafe behaviors. The system serves itself by automatically identifying and blocking risky operations without requiring continuous human intervention, thus maintaining reliability while reducing operational complexity.
Solution Approach 2:
The system transforms the complex task of human oversight into automated parameter-based evaluation. By changing from human judgment to automated assessment of impact parameters (such as cascade failure risk, resource utilization thresholds), the system maintains reliability while significantly reducing device complexity and operational difficulty.
3Reliability
If comprehensive impact assessment is performed on all automation recommendations, then reliability is improved, but loss of time increases due to evaluation overhead
Solution Approach 1:
The patent applies partial assessment by focusing evaluation on critical impact parameters rather than comprehensive analysis of all possible effects. The system selectively assesses recommendations based on predefined failsafe behaviors and key risk indicators, achieving sufficient reliability for failure prevention while minimizing time loss through targeted rather than exhaustive evaluation.
Data Source
AI summary
In one embodiment, a method comprises determining whether an automation recommendation for a network is to be forwarded to a management system of the network, wherein the automation recommendation specifies an action to take with respect to a plurality of platforms of the network and is received from a recommendation system utilizing artificial intelligence to generate the automation recommendation; responsive to a determination to forward the automation recommendation, assessing an impact of the automation recommendation; and performing an action with respect to the automation recommendation based on the impact.