Network Resilience via Cascading Risk Simulation
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Solution Overview
Problem
Conventional methods for reducing network faults and improving resilience are reactive, ad-hoc, and manual, making them unsuitable for large, complex, and interdependent networks. These methods fail to anticipate unique 'Black Swan' failures and are ineffective in designing resilient networks after component failures.
Innovation Solution
A computer-implemented method that quantifies component-level risks, simulates cascades of these risks throughout the network, and determines the network-level risk as a risk status in a resilience spectrum. This method integrates measures of cascade resilience related to structure, flow, and recovery, and is applicable to various networked infrastructures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional reactive and manual methods are used to address network faults, then fault remediation can be performed, but the methods are not scalable to large networks and fail to anticipate future failures
Solution Approach 1:
The patent applies preliminary action by proactively identifying critical components and potential failure pathways before actual failures occur. The system uses risk assessment models to predict which components are most likely to fail and simulate cascading failure scenarios, enabling preventive measures to be taken in advance rather than reacting after failures manifest.
Solution Approach 2:
The patent creates a virtual copy or digital twin of the network to perform simulations and risk analyses. By modeling the network structure and running virtual failure scenarios on this copy, the system can assess resilience and identify vulnerabilities without disrupting the actual network operations, enabling scalable analysis of large complex networks.
2Ease of operation
If manual fault analysis and remediation are performed, then specific faults can be addressed, but the process is ad-hoc and lacks holistic network view
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor network state, component health, and failure risks. The system provides feedback about the current network condition, identified vulnerabilities, and recommended actions to operators, enabling informed decision-making that considers the holistic network context rather than isolated faults.
Solution Approach 2:
The patent merges multiple functions into an integrated risk management platform that combines network monitoring, risk assessment, failure simulation, and remediation guidance. This unified system provides operators with a comprehensive view of network health and resilience, eliminating the need to switch between separate tools for different network functions.
3Reliability
If conventional methods focus on preventing component failure, then component reliability can be improved, but network resilience after failure is not facilitated
Solution Approach 1:
The patent prepares for post-failure scenarios by pre-identifying critical components and simulating failure cascades before they occur. The system determines which components are most important to protect and what remediation actions should be taken in advance, enabling the network to respond effectively when failures do occur rather than being caught off guard.
Solution Approach 2:
The patent uses virtual network models to test and develop resilience strategies by simulating various failure scenarios. These simulations allow operators to practice response procedures and refine recovery plans in a risk-free environment, improving the network's adaptability and resilience when actual failures occur without compromising component prevention efforts.
Data Source
AI summary
In an embodiment, a computer implemented method is provided. The method may include quantifying a plurality of component level risks for at least a subset of components in the network. The method may further include simulating cascades of the component level risks, with each corresponding component designated as a risk seed of the subset of components, throughout the network. The method may additionally include quantifying the network level risk as a risk status in a resilience spectrum based on the simulated cascades.