Graph Database Simulation Model for Computing System Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern enterprise computing systems, often built from disparate components with incomplete knowledge of each other, face challenges in identifying redundancies or inefficiencies and predicting behavior under various scenarios, especially in cloud computing platforms where hardware resources require significant management to maintain availability and scalability.
Innovation Solution
A computing system simulation model is created using a graph database to simulate scenarios and determine necessary modifications, allowing for the testing of production systems to ensure accuracy and identify modifications such as component reconfiguration or inventory management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If disparate computing systems and data sources are integrated to form a complete system view, then system evaluation capability improves, but system complexity increases
Solution Approach 1:
The patent introduces a simulation environment as an intermediary layer between disparate computing systems and data sources. This simulation environment creates virtual models that represent the complex system relationships, allowing evaluation without directly integrating all underlying systems. The virtual components and their relationships in the simulation environment serve as a mediator that simplifies the evaluation process while maintaining system fidelity.
Solution Approach 2:
The patent creates virtual copies of computing system components within the simulation environment. These virtual components replicate the behavior and relationships of actual system components, enabling system evaluation through simulation rather than direct interaction with the complex underlying systems. This copying approach allows comprehensive system analysis without the complexity of integrating all actual systems.
2Measurement precision
If simulation models include comprehensive virtual components and relationships, then prediction accuracy improves, but model complexity increases
Solution Approach 1:
The patent segments the simulation model into distinct virtual components, each representing a specific computing system element. These segmented virtual components can be independently defined, managed, and updated, reducing the complexity of managing the overall model while maintaining comprehensive coverage. The graph database structure naturally supports this segmentation through nodes and edges representing discrete components and their relationships.
Solution Approach 2:
The simulation environment provides a universal platform that can model various computing system scenarios using the same virtual component framework. The graph database structure and simulation engine serve multiple functions including system modeling, scenario simulation, prediction, and analysis, reducing the need for separate complex models for different purposes.
3Loss of information
If virtual components are stored in a graph database with nodes and edges, then relationship tracking improves, but data structure complexity increases
Solution Approach 1:
The patent merges the representation of computing system components and their relationships into a unified graph database structure. Virtual components and their relationships are combined into nodes and edges within the same data structure, eliminating the need for separate storage mechanisms and simplifying relationship tracking while maintaining comprehensive information.
4Reliability
If simulation scenarios are executed against the simulation model, then system behavior prediction improves, but computational resources increase
Solution Approach 1:
The patent enables execution of simulation scenarios that can focus on specific aspects or portions of the system rather than requiring complete system simulation. This partial action approach allows prediction of system behavior for particular scenarios without the computational overhead of simulating every component and relationship in all possible detail, optimizing resource usage while maintaining prediction accuracy for the scenarios of interest.
Data Source
AI summary
Methods, systems and computer program products are described herein that enable executing simulation scenarios against a computing system simulation model to determine one or more appropriate modifications to a physical, operating computing system. The simulation model includes virtual components corresponding to a plurality of computing system components of the computing system. The virtual components of the simulation model are included in a graph database, and the virtual components correspond to one or more nodes and edges stored as a graph in the graph database. Execution of the simulation scenario produces a simulation result that is analyzed to determine at least one modification of the computing system, and where thereafter, the computing system is modified at least according to the determined modification. Embodiments also enable testing a physical computing system to determine whether the simulation model of the computing system is accurate, and/or to determine one or more computing system modifications.