Interconnected Graph Database for Resource Deployment Conflict Resolution
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Solution Overview
Problem
Traditional relational databases face challenges in managing complex data relationships and resource deployment conflicts across multiple systems, as they are limited to single-dimensional node definitions and lack interconnection capabilities between different systems.
Innovation Solution
An interconnected graph database system that identifies and remediates conflicts in resource deployment by analyzing relationships between nodes across multiple graph database systems, determining lateral relationships, and modifying nodes and relationships in real-time to prevent conflicts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional relational databases are used to manage complex data relationships, then data can be stored in tables with join algorithms, but the computational cost of querying relationships becomes highly burdensome as data and relationships become increasingly complex
Solution Approach 1:
The patent transitions from traditional two-dimensional relational table structures to a multi-dimensional graph database structure. Each node can have multiple property dimensions (e.g., program level, control level, focus area) and relationships can have multiple types (causal, influence, similar operation shift). This dimensional expansion allows complex relationships to be represented natively without requiring complex join algorithms, thereby reducing computational cost while improving adaptability to manage complex data relationships.
Solution Approach 2:
The patent segments the database into multiple independent graph database systems, each managing a specific dimension or aspect of the data (e.g., one graph for program-level relationships, another for control-level relationships). This segmentation allows each subsystem to handle specific relationship types efficiently without the computational burden of processing all complex relationships across the entire dataset, thus reducing overall query computational cost while maintaining the ability to manage complex relationships through the interconnected graph structures.
2Measurement precision
If traditional graph databases are used, then relationships or nodes can be defined, but they only allow relationships to be defined to a single dimension which limits the level of detail and granularity to which data can be precisely defined
Solution Approach 1:
The patent extends traditional single-dimensional graph relationships to multi-dimensional relationships by allowing nodes to have multiple property dimensions (program level, control level, focus area level) and relationships to have multiple relationship types (causal, influence, similar operation shift). This dimensional extension enables precise definition of data at multiple levels of granularity without requiring a completely new database architecture, thus improving measurement precision while managing complexity through structured dimensionality.
Solution Approach 2:
The patent implements a nested graph database structure where graph database systems are organized in hierarchical levels (program level graphs containing control level graphs containing focus area level graphs). Each nested graph contains nodes and relationships that are relevant to its specific level, allowing detailed granular data to be stored and queried within nested structures. This nesting approach enables high measurement precision at multiple granular levels while managing overall system complexity through the hierarchical organization.
3Adaptability or versatility
If traditional graph database systems are used, then nodes and relationships can be defined within a single system, but they are not configured for interconnection between nodes of different systems nor for identifying or mitigating deployment of conflicting resources
Solution Approach 1:
The patent creates a universal interconnected graph database system where multiple independent graph database systems can be linked through standardized relationship paths. The system can identify causal relationships, influence relationships, and similar operation shift relationships between nodes in different graph systems. This multi-functional capability allows the system to not only store data across multiple systems but also to automatically identify conflicts in resource deployment and mitigate them, thereby improving both adaptability and reliability simultaneously.
Solution Approach 2:
The patent implements a feedback mechanism that continuously monitors relationships between nodes across different graph database systems. When a resource deployment activity is detected in one system, the system queries related nodes in other systems through relationship paths to identify potential conflicts. This feedback loop enables real-time detection and mitigation of conflicting resource deployments across interconnected systems, improving reliability while maintaining the adaptability to handle diverse system interconnections.
Data Source
AI summary
The invention provides an interconnected graph database system, method and computer program product structured for identifying and remediating conflicts in resource deployment. In some embodiments, the present invention is configured to identify a source node of a plurality of first nodes of a first graph database system. The source node is typically associated with a first information technology operational activity. In addition, the present invention is configured for determining a lateral relationship between the source node of the first graph database system and a target node of a plurality of second nodes of a second graph database system. Moreover, the present invention is configured for determining that the lateral relationship between the source node and the target node comprises a conflict, and in response, blocking initiation of the first information technology operational activity.