Network Analysis for Grouping Connected Nodes and Mitigating Risks
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Solution Overview
Problem
Existing network analysis techniques fail to accurately identify and mitigate risks in interconnected systems by grouping connected objects, leading to cascading failures and suboptimal performance due to the complexity of interdependencies among nodes in large networks.
Innovation Solution
A detection system that identifies rooted and nonrooted groups of connected nodes in a directed network using a two-part process, determining risk values, and initiating remedial measures to reconfigure the network, thereby mitigating risks by identifying root nodes, child nodes, and nodes with the highest outdegrees to form groups and assess their risk levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network analysis techniques are used to identify and group connected objects, then risk mitigation capability is improved, but the complexity of analyzing interdependencies among nodes in large networks increases
Solution Approach 1:
The patent segments the network into distinct groups based on connectivity patterns. It identifies rooted groups (containing nodes with no incoming links) and non-rooted groups (containing only nodes with incoming links), thereby dividing the complex network analysis into manageable segments that can be processed independently.
Solution Approach 2:
The patent performs preliminary classification of nodes into rooted and non-rooted groups before conducting detailed risk analysis. This preliminary action simplifies subsequent analysis by pre-organizing nodes based on their connectivity characteristics, reducing the complexity of interdependency analysis.
2Measurement precision
If traditional grouping methods are used, then implementation is simpler, but accuracy in identifying risk groups deteriorates
Solution Approach 1:
The patent divides the network into rooted and non-rooted groups based on the presence or absence of incoming links. This segmentation provides a precise and systematic method for identifying risk groups, improving accuracy by considering the directional nature of network connections rather than using undifferentiated grouping methods.
Solution Approach 2:
The patent applies different analysis criteria to different types of groups. Rooted groups are identified by the presence of root nodes (nodes with no incoming links), while non-rooted groups are identified by containing only nodes with incoming links. This local differentiation improves grouping accuracy by tailoring the identification method to the specific structural characteristics of each group type.
3Measurement precision
If all nodes are analyzed individually, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent merges nodes into groups based on their connectivity patterns. By analyzing groups rather than individual nodes, it maintains measurement precision through systematic group identification while significantly reducing processing time. The parallel processing of multiple groups further accelerates analysis without sacrificing accuracy.
Solution Approach 2:
The patent performs partial analysis by focusing on group-level characteristics rather than exhaustive individual node analysis. This approach achieves sufficient precision for risk identification while reducing processing time, as the group structure captures essential interdependency patterns without requiring detailed examination of every individual node connection.
Data Source
AI summary
Groups of connected nodes in a network of nodes can be detected for evaluating and mitigating risks of the network of nodes. For example, a system can process one or more subnetworks of the network of nodes in parallel. For each subnetwork, the system can identify root nodes and their reachable nodes to create rooted groups of connected nodes. The system then can determine outdegrees of the remaining nodes in the network. The system can identify reachable nodes from a remaining node of the highest outdegree to create a nonrooted group of connected nodes. The system can estimate a risk value based on the number of rooted groups and nonrooted groups, the number of nodes in each rooted group and nonrooted group, and the attributes of the nodes in each group. The system can mitigate potential risks by reconfiguring the network of nodes.