Data Center Inventory Visualization via Hierarchical Tree Structures
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Solution Overview
Problem
Current systems fail to effectively visualize data center inventory and resource utilization hierarchies, leading to inefficiencies and increased costs due to complex relationships between data entities and the difficulty in pinpointing cost drivers within distributed computing systems.
Innovation Solution
A system and method that converts inventory data into a format file, creating a tree structure to model interconnections between data entities, allowing for a hierarchical view and node summaries that display cost and utilization data, enabling users to understand cost distribution and relationships through a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If enterprises use distributed computing systems with complex hierarchies to support enterprise-level management and data storage, then computing resources and functionality are improved, but understanding and tracking resource utilization and costs become significantly more difficult
Solution Approach 1:
The patent segments the complex distributed computing system into a hierarchical tree structure with data centers, servers, and virtual machines as distinct levels. Each node in the hierarchy can be individually analyzed, allowing enterprises to break down complex cost and utilization tracking into manageable segments at different hierarchical levels.
Solution Approach 2:
The patent adds a visual dimension to cost and utilization data by displaying hierarchical relationships and cost flows through graphical interfaces. This transforms abstract numerical data into visual representations showing how costs propagate through the hierarchy, making it easier to understand and track resource utilization across complex systems.
2Measurement precision
If enterprises implement detailed tracking of sub-costs for storage, memory, processing power, hardware, labor, and licensing across data entities, then cost accuracy is improved, but the time and resources required for calculation increase substantially
Solution Approach 1:
The patent performs preliminary calculations by automatically distributing top-down costs (such as data center labor and infrastructure) to servers and virtual machines before detailed analysis is needed. This pre-computation stores cost allocation data that can be quickly retrieved and displayed, eliminating the need for time-consuming recalculations when generating reports.
Solution Approach 2:
The patent creates simplified copies or representations of cost data at each hierarchical level, showing both bottom-up accrued costs and top-down distributed costs in parallel. This allows users to view multiple cost perspectives simultaneously without performing separate calculations, reducing the time required for comprehensive cost analysis.
3Ease of manufacture
If enterprises use separate reports with isolated utilization and cost parameters to analyze data center performance, then data organization is simplified, but the ability to form a complete picture of cost distribution and relationships is lost
Solution Approach 1:
The patent merges previously separate utilization and cost reports into a unified hierarchical view that displays both types of information together. The system combines bottom-up cost accrual data with top-down cost distribution data in single visualizations, allowing users to see the complete picture of cost distribution while maintaining organized data structures.
Solution Approach 2:
The patent creates a universal reporting framework that can display multiple types of information (utilization, costs, hierarchical relationships) through a single integrated interface. This multi-functional system replaces multiple separate reports while maintaining the organizational simplicity needed for easy data management.
Data Source
AI summary
A system can provide a visual representation of an inventory of data entities for a distributed computing system. Inventory data including cost and operational data for data entities such as data centers, servers, and virtual machines, can be converted into a format file. The format file can be used to create a tree of nodes and node summaries corresponding to the data entities. A user interface can display hierarchical and isolated views of the tree revealing parent child relationships between data entities within a computing system infrastructure. Node summaries including cost and utilization data can be displayed to reveal how specific sub-costs such as labor and licensing, are driven by data entities in one level of the infrastructure and pushed to respective parent or child data entities in other levels. Views of the tree can be used to determine areas of inefficiency or reduced value within the computing system.