Graph Time Layer Model for Network Object Relationship Analysis

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Solution Overview

Problem

Existing systems fail to effectively display across-time relationship patterns and status effects between parent and child computer network objects, particularly in complex environments with virtual and cloud computing, where snapshot views do not adequately identify causal patterns due to dynamic changes in resource allocation and object status.

Innovation Solution

A method and system that create a graph time layer model showing relationships between parent and child virtual machines or computer network objects over time, allowing users to visualize the status of these relationships at intervals, with options for searching and filtering to identify problematic child objects across a specified time frame.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a snapshot view of the graph is used to show current relationships and status, then the current state of objects and relationships is clearly displayed, but the ability to identify causal patterns over time is lost due to dynamic changes in resource allocation and object status

Engineering Contradiction:

Improveaccuracy of identifying causal patternsVSAvoidloss of historical relationship data

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The system performs preliminary actions by capturing and storing relationship snapshots at multiple time points before analysis is needed. This allows historical relationship data to be preserved and made available for later causal pattern analysis, resolving the contradiction between showing current state clearly and preserving historical information.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates copies of the graph data at different time points (time-layered copies) rather than modifying the original graph structure. Each copy represents the state at a specific time, allowing users to compare historical states with current state without losing any information, thereby enabling causal pattern identification while preserving complete historical data.

Inventive Principle:

Principle #26Copying

2Loss of information

If multiple snapshot views are used to track object status changes over time, then historical data is preserved, but the complexity of analyzing causal patterns increases due to the need to manually correlate multiple views

Engineering Contradiction:

Improvepreservation of historical relationship dataVSAvoidcomplexity of analyzing causal patterns

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system merges multiple snapshot views into a single integrated time-layered graph display. This combines historical data preservation with simplified analysis by presenting all time points in one unified view, allowing users to see causal patterns across time without manually correlating separate views, thus reducing analytical complexity while maintaining data integrity.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system adds a time dimension to the traditional graph view, transforming a static 2D graph into a time-layered visualization that incorporates temporal information. This dimensional enhancement allows historical data to be preserved and analyzed simultaneously in a single view, reducing the complexity of causal pattern analysis by making temporal relationships visually apparent rather than requiring manual correlation of multiple separate views.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Loss of information

If detailed time-layered information is displayed for all objects, then comprehensive causal pattern analysis is enabled, but the clarity of individual object status becomes reduced due to information overload

Engineering Contradiction:

Improvecompleteness of causal pattern dataVSAvoidease of identifying individual object status

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The system applies local quality by allowing users to focus on specific objects or regions of interest within the time-layered graph. When examining a particular object, the system can emphasize its time-layered status changes while de-emphasizing or hiding less relevant information about other objects. This maintains complete causal pattern data in the background while improving the ease of identifying individual object status through selective visualization enhancement.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11227079B2Automatic creation of graph time layer of model of computer network objects and relationships

Publication Date: 2022.01.18 BMC HELIX INC

AI summary

A method and system create a model of a set of relationships between a set of parent computer network objects and a set of corresponding child computer network objects, over a period of time, and output a user interface graphing the model in a single view to illustrate the set of relationships over the period of time. The parent computer network objects include virtual machines and the child computer network objects include hosts. The user interface includes a search option to provide for a search of problems with the child computer network objects over the period of time.