Data Center Visualization Scatter Plot for Resource Allocation
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Solution Overview
Problem
Current data center management software lacks a comprehensive visual representation that provides an overview of health and available capacity, making it difficult for administrators to manage and allocate resources effectively.
Innovation Solution
A visual representation system using a scatter plot to display cloud groups, where each group is represented by a circle indicating available capacity and health status, with interactive features for resource allocation and management, such as drag-and-drop functionality for placing virtual machines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If management software provides status information in a hierarchical structure, then detailed information about individual resources is available, but an overall overview of health and capacity is not provided
Solution Approach 1:
The patent segments the data center into visual groups (cloud groups, clusters, nodes) represented as distinct visual elements in the scatter plot. Each group can be independently analyzed and interacted with, allowing administrators to see both individual details and overall patterns simultaneously. The hierarchical data is segmented into visual categories that can be filtered and sorted.
Solution Approach 2:
The patent transforms the traditional hierarchical one-dimensional navigation into a two-dimensional scatter plot visualization. The X-axis represents health status while the Y-axis represents capacity, creating a new dimensional space where data points can be visually analyzed for patterns, trends, and outliers that are not visible in traditional hierarchical views.
2Ease of operation
If traditional management software is used, then resource monitoring is possible, but allocation and reclamation actions are not integrated into the visual representation
Solution Approach 1:
The patent merges the visualization function with the allocation and reclamation functions into a single integrated interface. Administrators can perform allocation actions directly on the scatter plot by selecting cloud groups and initiating allocation workflows from the visual representation itself, combining what were previously separate functions into one unified system.
Solution Approach 2:
The system provides automated allocation and reclamation actions that can be initiated through the visual interface. The scatter plot enables administrators to self-service resource allocation by visually identifying suitable cloud groups and triggering automated workflows, reducing the need for complex manual configuration and integration.
3Quantity of substance
If the amount of data and number of virtual machines increases, then data center capacity grows, but managing the data center becomes more challenging
Solution Approach 1:
The patent uses color coding in the scatter plot to represent different health statuses and capacity levels. Cloud groups are colored based on their health state (e.g., green for healthy, yellow for at-risk, red for faulty), allowing administrators to quickly identify problematic areas without examining individual data points. This visual encoding reduces the cognitive load when managing large quantities of resources.
Solution Approach 2:
The patent transforms complex resource parameters (CPU utilization, memory usage, disk I/O, network I/O) into simplified visual representations on the scatter plot. The X and Y axes represent aggregated parameters (health status and capacity), converting detailed numerical data into intuitive visual patterns that are easy to interpret even as data center capacity grows.
Data Source
AI summary
A system, method, and medium for generating a visual representation of a data center. The data center includes multiple cloud groups, and each cloud group is represented with a circle in the visual representation. The size of the circle represents the aggregate capacity of the cloud group. The visual representation is a scatter plot with a horizontal axis measuring health and a vertical axis measuring available capacity. Circles are placed within the scatter plot based on the health and available capacity of their corresponding cloud groups. The color of the circle is based on the health of the corresponding cloud group, and the density of the color is based on the available capacity of the corresponding cloud group.