3D data center resource use monitoring visualization method

Abstract

The invention relates to the technical field of data management, and provides a 3D data center resource use monitoring visualization method, which comprises the following steps: constructing a three-dimensional digital twinborn scene of a data center physical environment, creating and maintaining an independent data unit for each physical equipment instance to be monitored, associating the collected multi-dimensional operation monitoring data to a corresponding data unit in real time; according to a monitoring dimension selected by a user, obtaining a corresponding monitoring index value from a data unit associated with a target physical equipment instance, and according to a predefined visual mapping rule, driving to generate a visual state body associated with the three-dimensional model of the physical equipment instance in space; and rendering the three-dimensional digital twinborn scene at the visual angle of the real model of the three-dimensional display interface, and superposing and rendering the corresponding visual state body at the corresponding position of the three-dimensional model of each physical equipment instance at the visual angle of the resource. According to the method, real-time dynamic linkage of data and visual performance can be realized, and the operation and maintenance response timeliness is enhanced.

Description

Technical Field

[0001] This invention relates to the field of data management technology, and in particular to a 3D data center resource usage monitoring and visualization method. Background Technology

[0002] With the rapid development of cloud computing, big data, and artificial intelligence technologies, data centers, as the core physical infrastructure supporting massive computing, storage, and network services, are becoming increasingly large in scale and complex in structure. Against this backdrop, data center operation and maintenance management faces unprecedented challenges. How to monitor the operating status, resource utilization efficiency, energy consumption distribution, and environmental conditions of each physical device within the data center in real time, intuitively, and with precision has become crucial to ensuring the stable, efficient, and green operation of the data center. Effective monitoring and visualization methods are the foundation for operation and maintenance personnel to conduct situational awareness, capacity planning, rapid fault location, and energy efficiency optimization.

[0003] Currently, industry monitoring of data center resources generally relies on data indicator dashboards or two-dimensional data charts (such as line charts, bar charts, and pie charts). While these traditional methods can provide basic numerical statistics and trend information, their inherent presentation formats have significant limitations and shortcomings, mainly in the following aspects: 1. Lack of Spatial and Physical Topology Relationships: Traditional two-dimensional UI interfaces are inherently abstract and symbolic, completely failing to reproduce the true physical layout and spatial topology relationships within a data center. Maintenance personnel cannot visually see the specific location of a server rack within the server room, or the specific unit (U) of a server within a rack, making it even more difficult to understand the physical connections between devices, such as cooling and power supply. This lack of spatial information leads to inefficient fault location and impact analysis, often requiring maintenance personnel to combine drawings and on-site inspections, resulting in slow response times.

[0004] 2. Coarse-grained monitoring with a lack of device-level visibility: Existing monitoring solutions often focus on aggregated data at the virtualization resource pool or overall data center level, such as displaying the average CPU utilization or total energy consumption of the entire cluster. However, "hot spots" or performance bottlenecks within a data center often originate from anomalies in individual physical devices. Due to the lack of ability to independently track and visualize data for each individual physical device (such as a single server, storage array, or network switch), operations and maintenance personnel find it difficult to quickly locate specific faulty or high-load devices from macroscopic aggregated data, resulting in insufficient granularity and accuracy of monitoring.

[0005] 3. Information presentation is not intuitive and has a high cognitive threshold: Resource utilization, energy consumption, temperature readings, etc., are all abstract numbers or percentages. Presenting this data through tables or two-dimensional charts requires maintenance personnel to have a high level of professional skills and data interpretation ability, making it impossible to achieve an intuitive understanding at a glance. In emergency alarm or rapid inspection scenarios, it is necessary to identify abnormal states from a large number of numbers and curves, which is time-consuming and labor-intensive, and prone to oversights due to visual fatigue.

[0006] 4. Fragmented Multi-Dimensional Data and Lack of Correlational Analysis Views: Resources, energy consumption, temperature, load capacity, and equipment status are several key dimensions for assessing data center health. Current technologies typically distribute this data across different monitoring subsystems or different chart tabs. This fragmented presentation makes it difficult for operations personnel to comprehensively analyze, within the same spatiotemporal context, whether "servers with high CPU usage are also high-energy-consuming and high-heat-generating devices," thus hindering rapid root cause analysis and optimization decisions.

[0007] The root cause of the aforementioned technical defects lies in the fact that the traditional two-dimensional plane-based monitoring interface has an irreconcilable contradiction with the inherent three-dimensional physical space attributes of the data center. It cannot transform the three-dimensional structure of the actual equipment and its spatial relationships into an effective visualization carrier, nor can it dynamically and uniformly encode and present abstract, multi-source heterogeneous operational data in a way that conforms to human spatial cognition habits.

[0008] Chinese patent CN110083119A discloses a digital twin-based visualized power system data center monitoring system and method. In practical applications, this solution is used for modeling and monitoring of the entire data center or specific equipment types. Its data acquisition and processing primarily serve "virtual-real mapping" and "remote control," without creating and maintaining an independent, fine-grained data unit for each individual physical device (such as a single server or storage device). Therefore, it cannot achieve independent, real-time, and accurate monitoring and historical tracing of multi-dimensional indicators such as single device resource utilization (such as CPU, memory), energy consumption, and temperature, making it difficult to accurately pinpoint the specific individual device causing performance bottlenecks or failures.

[0009] Therefore, how to provide an intuitive monitoring and visualization method that can deeply integrate data center physical space information and real-time operation data to achieve multi-dimensional correlation from macro to micro, from whole to individual, in order to solve the core problems of existing technologies such as unintuitive monitoring, inaccurate positioning, and low analysis efficiency has become an urgent technical problem to be solved. Summary of the Invention

[0010] In view of this, in order to overcome the shortcomings of the prior art, the present invention aims to provide a 3D data center resource usage monitoring and visualization method.

[0011] This invention provides a 3D data center resource usage monitoring and visualization method, which includes the following steps: S1: Construct a 3D digital twin scenario of the data center physical environment, create and maintain an independent data unit for each physical device instance to be monitored in the 3D digital twin scenario, and associate the collected multi-dimensional operation monitoring data of the physical device instance with the corresponding data unit in real time; S2: Based on the monitoring dimension selected by the user, obtain the corresponding monitoring index value from the data unit associated with the target physical device instance, and drive the generation of a visual state body that is spatially associated with the 3D model of the physical device instance and whose visual attributes change dynamically with the monitoring index value according to the predefined visual mapping rules. S3: Provides the ability to switch between a real model view and a resource visualization view in the 3D display interface. Renders the 3D digital twin scene in the real model view, and overlays and renders the corresponding visualization state body at the corresponding position of the 3D model of each physical device instance in the resource visualization view, based on the 3D digital twin scene.

[0012] Optionally, in the 3D data center resource usage monitoring and visualization method of the present invention, step S1 involves constructing a three-dimensional digital twin scene of the data center physical environment, including: Hierarchical 3D geometric modeling is performed on the entities within the data center to form a hierarchical set of 3D models. The entities include computer rooms and micro-modules that represent spatial range, racks for carrying IT equipment, and IT and infrastructure equipment entities, including servers, storage devices, network devices, power supply equipment, and cooling equipment. During modeling, the physical dimensions and installation location data of each entity are used for construction. Then, according to the actual spatial layout and topological relationships, the three-dimensional models at all levels are assembled and integrated to form a complete three-dimensional digital twin scene that reflects the physical structure of the data center.

[0013] Optionally, in the 3D data center resource usage monitoring and visualization method of the present invention, in step S1, multi-dimensional operation monitoring data is associated with the corresponding data unit in real time in the following manner: Assign a unique identifier to each physical device instance to be monitored within the data center, and instantiate an independent data structure bound to that identifier as its data unit. The data stream generated by the physical device instance is continuously collected through the monitoring agent or interface, and the collected data is classified by dimension and then updated to its data unit. Multidimensional operation monitoring data includes at least resource utilization data, energy consumption data, temperature data, load-bearing data, and equipment status alarm data. Resource utilization data includes one or more of the following: CPU utilization, memory utilization, storage utilization, and network bandwidth utilization.

[0014] Optionally, in the 3D data center resource monitoring visualization method of the present invention, in step S2, the visual mapping rule defines a method for converting monitoring index values ​​into core visual attributes of the visualization status body. The core visual attributes include at least the rendering height and display color of the visualization status body. When the monitoring index value is obtained, a percentage value representing the current load level is calculated based on the monitoring index value, and the height ratio to be rendered and the color to be displayed of the visualization status body are determined synchronously based on the percentage value.

[0015] Optionally, the 3D data center resource usage monitoring visualization method of the present invention synchronously determines the height ratio that the visualization state volume should be rendered based on the percentage value in the following manner: The calculated percentage value representing the current load level is used as the proportion of the height of the visualized state body in the vertical direction to the total height of the 3D model of its associated physical device instance. During rendering, the rendering height of the visual status volume is equal to the product of the total height of the 3D model of the physical device instance and the percentage value. The level of the monitoring indicator is intuitively reflected by the filling height of the visual status volume in the model space.

[0016] Optionally, the 3D data center resource usage monitoring visualization method of the present invention synchronously determines the color that the visualization status volume should display based on the percentage value in the following manner: Multiple consecutive percentage threshold intervals are predefined, and each percentage threshold interval is associated with a color that indicates a specific state. The calculated percentage value representing the load level is matched with the percentage threshold range to determine the percentage threshold range to which it belongs, and the color associated with the percentage threshold range is assigned as the display color of the visualization status volume.

[0017] Optionally, in the 3D data center resource usage monitoring visualization method of the present invention, in step S3, the real model perspective is used to display the physical layout and asset distribution of the data center. Under this perspective, the 3D display interface only renders the original 3D digital twin scene constructed in step S1 without the modification of the visualization state body; the resource visualization perspective is used to monitor the operating status. Under this perspective, based on the original 3D digital twin scene, the 3D display interface overlays and renders the dynamically changing visualization state body at the 3D model position of each physical device instance according to the result of step S2, transforming the abstract multi-dimensional monitoring data into a concrete visual form.

[0018] Optionally, in the 3D data center resource usage monitoring and visualization method of the present invention, step S3 provides a perspective switching function as follows: a set of mode switching controls is set on the three-dimensional display interface, the mode switching controls include status visualization, capacity visualization, energy consumption visualization and temperature visualization options corresponding to different monitoring dimensions; in response to the user's trigger operation on any option, the current display mode is switched to the resource visualization perspective; according to the monitoring dimension corresponding to the triggered option, the process of step S2 is called to update or generate the visualization status of all relevant physical device instances in the scene, refresh the three-dimensional display interface, and globally present the distribution of visualization status of all physical devices in that dimension.

[0019] Optionally, the 3D data center resource usage monitoring and visualization method of the present invention, after responding to the user's trigger operation for capacity visualization or energy consumption visualization options, provides a monitoring granularity selection function in the following manner: providing a secondary selection control, which provides two monitoring granularity options: device level and rack level; when the user selects the device level option, an independent visualization status body is generated for each independent physical device instance; when the user selects the rack level option, the monitoring data of all physical device instances in the same rack in the selected dimension are aggregated and calculated, and a unified visualization status body representing its overall load level is generated based on the three-dimensional model of the rack.

[0020] Optionally, in the 3D data center resource usage monitoring and visualization method of the present invention, step S3 further includes interaction and alarm location in the following manner: Users can interact with the 3D model of the physical device instance or its superimposed visual state volume by clicking or selecting in the 3D display interface. In response to a selection action, detailed multi-dimensional operational monitoring data stored in the data unit corresponding to the physical device instance is displayed on the side of the interface or in a separate panel. It supports global filtering based on the display color of the visual status entity. By locating and highlighting all visual status entities whose current display color is a warning or alarm color and their associated physical device instances with one click, it helps to identify devices with abnormal status.

[0021] The 3D data center resource usage monitoring visualization method of the present invention is as follows:

[0022] In practical applications, the 3D data center resource usage monitoring and visualization method of this invention has the following beneficial technical effects: 1. Achieve refined management and precise monitoring at the equipment level. By creating and maintaining an independent data unit for each monitorable physical device within the data center, monitoring data is collected, stored, and bound at the device level. This enables operations and maintenance personnel to grasp the specific values ​​and levels of core indicators such as CPU, memory, storage, energy consumption, and temperature of each device in real time and accurately, rather than relying on vague aggregated averages. This provides a data granularity and reliability foundation for precise capacity planning, energy efficiency auditing, and fault tracing.

[0023] 2. Enhance operational intuitiveness and situational awareness efficiency through 3D twin visualization. Abstract numerical monitoring data is transformed into "visualized status entities" with height and color attributes, overlaid on 3D device models, through visual mapping rules. Indicators such as resource utilization and energy consumption are intuitively mapped to the proportion of the status entity filling the device space, with colors dynamically changing according to preset thresholds. This presentation method transforms numbers and charts that previously required professional interpretation into a visual language that aligns with human spatial and color intuition. This allows operations and maintenance personnel to instantly grasp the overall health status, hotspot distribution, and anomaly locations of the entire data center or a specific area, reducing cognitive load and improving the efficiency of daily inspections and situation assessments.

[0024] 3. Construct a three-dimensional monitoring system that integrates spatial context and optimize the fault location and root cause analysis process. The established 3D digital twin scenario fully replicates the physical layout and spatial topology of the data center. When running under the "resource visualization perspective," the status of devices is no longer an isolated number, but a visualized entity placed in a real spatial location. Maintenance personnel can directly locate faulty devices in 3D space based on alarm colors and clearly see which server room, rack, and USB port it is in, shortening the mean time to locate faults. It supports overlaying different dimensions of visualized status entities in the same spatial view, making correlational issues such as "whether high-load devices are causing localized overheating" readily apparent, improving the efficiency and accuracy of root cause analysis for complex problems.

[0025] 4. Enable real-time dynamic linkage between data and visual presentation to enhance the timeliness of operation and maintenance response. The monitoring data stream, data processing engine, and 3D rendering engine are tightly integrated. Once the metrics data of any monitored device change, its corresponding data unit will be updated in real time, immediately triggering the recalculation and rendering of the visual attributes of the "visual state volume" bound to that device. The entire 3D monitoring view is a dynamic, real-time feedback "living system" of the physical world's state. Any abnormal state will receive significant visual feedback in the 3D interface within seconds, transforming the monitoring system from a "historical recorder" into a "real-time dashboard," significantly improving the operation and maintenance team's response speed and proactivity to emergencies.

[0026] 5. Possesses excellent architectural flexibility and scalability for large-scale deployment. The hierarchical model architecture and standardized data unit interface design give the system clear modularity, enabling it to flexibly adapt to data center environments of different sizes and from different vendors. Whether it's a single server room or a hyperscale data center spanning multiple regions, it can be expanded by adding models and connecting to data sources. Independent data units and visualization rules allow for the flexible addition of monitoring device types or monitoring metric dimensions without refactoring the entire system, thus ensuring the long-term evolution of the technical solution and its potential to adapt to future needs. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 A schematic diagram of a three-dimensional digital twin scene constructed according to the method of Exemplary Embodiment 2 of the present invention; Figure 2 This is a schematic diagram of a rack model reconstructed by 3D twinning according to Exemplary Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of a server model reconstructed by the method of Exemplary Embodiment 2 according to the present invention; Figure 4 This is a schematic diagram of a three-dimensional digital twin scene of a data center from the perspective of a real model of the method according to Exemplary Embodiment 2 of the present invention; Figure 5 This is a schematic diagram of a three-dimensional digital twin scene of a data center from the resource visualization perspective of the method of Exemplary Embodiment 2 of the present invention; Figure 6 This is a schematic diagram of a perspective switching method according to an exemplary embodiment 2 of the present invention; Figure 7 This is a schematic diagram of the overall resource usage from a rack perspective according to the method of Exemplary Embodiment 2 of the present invention; Figure 8 This is a schematic diagram of resource conditions from the device perspective of the method according to Exemplary Embodiment 2 of the present invention; Figure 9 This is a schematic diagram of resource conditions from another device perspective of the method according to Exemplary Embodiment 2 of the present invention. Detailed Implementation

[0029] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0030] It should be noted that, in the absence of conflict, the following embodiments and features can be combined with each other; and, based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0031] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this disclosure, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein. Example 1

[0032] Exemplary embodiment 1 of the present invention provides a 3D data center resource usage monitoring and visualization method, which is implemented according to the following steps: S1: Construct a 3D digital twin scenario of the data center physical environment, create and maintain an independent data unit for each physical device instance to be monitored in the 3D digital twin scenario, and associate the collected multi-dimensional operation monitoring data of the physical device instance with the corresponding data unit in real time.

[0033] Specifically, in this embodiment, hierarchical three-dimensional geometric modeling is performed on the entities within the data center to form a hierarchical set of three-dimensional models. The entities include server rooms and micro-modules representing spatial range, racks for carrying IT equipment, and IT and infrastructure equipment entities, including servers, storage devices, network devices, power supply equipment, and cooling equipment. During modeling, the models are constructed based on the physical dimensions and installation location data of each entity, and the three-dimensional models at each level are assembled and integrated according to the actual spatial layout and topological relationships to form a complete three-dimensional digital twin scene that reflects the physical structure of the data center.

[0034] In this embodiment, a unique identifier is assigned to each physical device instance to be monitored in the data center, and an independent data structure bound to the identifier is instantiated as its data unit. The data stream generated by the physical device instance is continuously collected through the monitoring agent or interface, and the collected data is updated to its data unit after being classified by dimension. The multi-dimensional operation monitoring data includes at least resource utilization data, energy consumption data, temperature data, load-bearing data, and equipment status alarm data. The resource utilization data includes one or more of CPU utilization, memory utilization, storage utilization, and network bandwidth utilization.

[0035] S2: Based on the monitoring dimension selected by the user, obtain the corresponding monitoring index value from the data unit associated with the target physical device instance, and drive the generation of a visual state body that is spatially associated with the 3D model of the physical device instance and whose visual attributes change dynamically with the monitoring index value according to the predefined visual mapping rules.

[0036] The visual mapping rule defines the conversion method from monitoring index values ​​to the core visual attributes of the visualized status body. These core visual attributes include at least the rendering height and display color of the visualized status body. When a monitoring index value is obtained, a percentage value representing the current load level is calculated based on the monitoring index value, and the height ratio to be rendered and the color to be displayed of the visualized status body are determined synchronously based on this percentage value.

[0037] As an optional example, this embodiment synchronously determines the height ratio that the visualization status body should be rendered based on the percentage value in the following manner: the calculated percentage value representing the current load level is used as the ratio of the height of the visualization status body in the vertical direction to the total height of the 3D model of its associated physical device instance; during rendering, the rendering height of the visualization status body is made equal to the product of the total height of the 3D model of the physical device instance and the percentage value, and the level of the monitoring indicator is intuitively reflected by the fill height of the visualization status body in the model space.

[0038] As an optional example, this embodiment determines the color to be displayed for the visualization status body synchronously based on the percentage value in the following manner: predefine multiple consecutive percentage threshold intervals, associate each percentage threshold interval with a color that indicates a specific status; match the calculated percentage value representing the load level with the percentage threshold intervals to determine the percentage threshold interval to which it belongs, and assign the color associated with the percentage threshold interval as the display color of the visualization status body.

[0039] S3: Provides the ability to switch between a real model view and a resource visualization view in the 3D display interface. Renders the 3D digital twin scene in the real model view, and overlays and renders the corresponding visualization state body at the corresponding position of the 3D model of each physical device instance in the resource visualization view, based on the 3D digital twin scene.

[0040] In this embodiment, the real model perspective is used to display the physical layout and asset distribution of the data center. From this perspective, the 3D display interface only renders the original 3D digital twin scene constructed in step S1 without the modification of the visualization state body. The resource visualization perspective is used to monitor the operating status. From this perspective, based on the original 3D digital twin scene, the 3D display interface overlays and renders the dynamically changing visualization state body at the 3D model position of each physical device instance according to the result of step S2, transforming the abstract multi-dimensional monitoring data into a concrete visual form.

[0041] In this embodiment, the perspective switching function is provided as follows: a set of mode switching controls is set on the 3D display interface. The mode switching controls include status visualization, capacity visualization, energy consumption visualization, and temperature visualization options corresponding to different monitoring dimensions. In response to the user's trigger operation on any option, the current display mode is switched to the resource visualization perspective. According to the monitoring dimension corresponding to the triggered option, the process of step S3 is called to update or generate the visualization status of all relevant physical device instances in the scene, refresh the 3D display interface, and globally present the distribution of visualization status of all physical devices in this dimension.

[0042] It should be noted that, in response to the user's trigger operation for the capacity visualization or energy consumption visualization options, this embodiment provides the monitoring granularity selection function in the following manner: a secondary selection control is provided, which offers two monitoring granularity options: device level and rack level; when the user selects the device level option, an independent visualization status body is generated for each independent physical device instance; when the user selects the rack level option, the monitoring data of all physical device instances in the same rack in the selected dimension are aggregated and calculated, and a unified visualization status body representing its overall load level is generated based on the rack's three-dimensional model.

[0043] In practical applications, step S3 also includes interaction and alarm location in the following manner: Users can interact with the 3D model of a physical device instance or its superimposed visual status entity by clicking or selecting in the 3D display interface; in response to the selection operation, detailed multi-dimensional operation monitoring data stored in the data unit corresponding to the physical device instance is displayed on the side of the interface or in a separate panel; global filtering is supported based on the display color of the visual status entity, and all visual status entities with the current display color of warning or alarm color and their associated physical device instances are located and highlighted with one click to help identify devices with abnormal status. Example 2

[0044] Exemplary Example 2 of the present invention provides a 3D data center resource usage monitoring and visualization method. This embodiment further illustrates the 3D data center resource usage monitoring and visualization method in a specific scenario.

[0045] Figure 1 This is a schematic diagram of a three-dimensional digital twin scene constructed according to the method of Exemplary Embodiment 2 of the present invention. Figure 2 This is a schematic diagram of a rack model reconstructed by 3D twinning according to the method of Exemplary Embodiment 2 of the present invention. Figure 3 This is a schematic diagram of a server model reconstructed using the method of Exemplary Embodiment 2 according to the present invention. Figures 1 to 3 As shown in this embodiment, the three-dimensional digital twin scene performs 3D twin reconstruction of all equipment in the data center, including micro-modules, racks, servers, storage devices, network devices, UPS, etc.

[0046] When device data is unitized, the data of all devices in the data center (resource usage data (rated, real-time), device parameters, model, status data, load capacity, energy consumption, temperature, etc.) are tracked through independent data indicators, rather than calculating the total data or virtualized resource data. Each device has an independent data value, and this independent data value is assigned to a specific 3D device in the 3D engine.

[0047] Figure 4 This is a schematic diagram of a three-dimensional digital twin scene of a data center from the perspective of a real model according to the method of Exemplary Embodiment 2 of the present invention. Figure 5 This is a schematic diagram of a three-dimensional digital twin scene of a data center from the perspective of resource visualization according to the method of Exemplary Embodiment 2 of the present invention. Figure 6 This is a schematic diagram of a perspective switching method according to an exemplary embodiment 2 of the present invention.

[0048] like Figures 4 to 6As shown in this embodiment, the default view of the entire data center 3D scene and UI is displayed. The upper right corner of the central 3D scene window has a show / hide button, and below it are four buttons: status visualization, capacity visualization, energy consumption visualization, and temperature visualization. The 3D scene defaults to displaying a 3D realistic model view; clicking on capacity visualization, energy consumption visualization, or temperature visualization switches to a resource visualization view.

[0049] Clicking the capacity visualization button brings up two sub-buttons. Clicking the first button, the rack U-position button, switches the 3D scene to a resource visualization view. This view presents a twin of the actual equipment at its proportional volume. The height of the entire rack represents the maximum value of resources, energy consumption, load-bearing capacity, and status level. The color is variable, driven by real-time data, using 0-59% green, 60-79% blue, 80-89% yellow, and above 90% red. For example, when the real-time resource usage is 50%, the height of the entire twin is 50% of the rack height, and the twin is green, allowing users to intuitively see the total resource usage from the current rack perspective. Figure 7 This is a schematic diagram of the overall resource usage from a rack perspective according to the method of Exemplary Embodiment 2 of the present invention.

[0050] When you click the energy consumption visualization button, two sub-buttons appear. Clicking the first button, "Device Dimension," will open the 3D scene and switch to the resource visualization view. Figure 8 This is a schematic diagram of resource status from a device perspective according to the method of Exemplary Embodiment 2 of the present invention. This perspective differs from the rack U-position perspective, presenting resource visualization from the perspective of a single device. Dimensionally, the height of the entire rack represents the maximum value of resources, energy consumption, load-bearing capacity, and status. The color is a variable color driven by real-time data, using 0-59% green, 60-79% blue, 80-89% yellow, and above 90% red. For example, when the real-time resource usage is 50%, the height of the entire twin is 50% of the rack height, and the twin color is green, allowing the user to intuitively see the current resource usage of the server. Figure 9 This is a schematic diagram of resource conditions from another device perspective of the method according to Exemplary Embodiment 2 of the present invention.

[0051] In practical applications, the 3D data center resource usage monitoring and visualization method of this invention has the following beneficial technical effects: 1. Achieve refined management and precise monitoring at the equipment level. By creating and maintaining an independent data unit for each monitorable physical device (such as servers, storage devices, and network devices) within the data center, monitoring data is collected, stored, and bound at the device level. This enables operations and maintenance personnel to grasp the specific values ​​and levels of core indicators such as CPU, memory, storage, energy consumption, and temperature of each device in real time and accurately, rather than relying on vague aggregated averages. This provides a data granularity and reliability foundation for precise capacity planning (such as precise allocation of rack space and power), energy efficiency auditing (locating high-energy-consuming devices), and fault tracing (quickly locating abnormal devices).

[0052] 2. Enhance operational intuitiveness and situational awareness efficiency through 3D twin visualization. Abstract numerical monitoring data is transformed into "visualized status entities" with height and color attributes, overlaid on 3D device models, through visual mapping rules. The levels of indicators such as resource utilization and energy consumption are intuitively mapped to the proportion (height) of the status entity filling the device space, while the color dynamically changes according to preset thresholds (e.g., green / normal, yellow / warning, red / alarm). This presentation method transforms numbers and charts that originally required professional interpretation into a visual language that aligns with human spatial and color intuition. This allows operations and maintenance personnel to instantly grasp the overall health status, hotspot distribution, and anomaly locations of the entire data center or a specific area, reducing cognitive load and improving the efficiency of daily inspections and situation assessments.

[0053] 3. Construct a three-dimensional monitoring system that integrates spatial context and optimize the fault location and root cause analysis process. The established 3D digital twin scenario fully replicates the physical layout and spatial topology of the data center. When running under the "resource visualization perspective," the status of devices is no longer an isolated number, but a visualized entity placed in a real spatial location. Maintenance personnel can directly locate faulty devices in 3D space based on alarm colors (such as red), clearly seeing which server room, rack, and USB port it is in, shortening the mean time to locate faults. It supports overlaying different dimensions (such as capacity and temperature) of visualized status entities in the same spatial view, making correlational issues such as "whether high-load devices are causing localized overheating" readily apparent, improving the efficiency and accuracy of root cause analysis for complex problems.

[0054] 4. Enable real-time dynamic linkage between data and visual presentation to enhance the timeliness of operation and maintenance response. The monitoring data stream, data processing engine, and 3D rendering engine are tightly integrated. Once the metrics of any monitored device change, its corresponding data unit will be updated in real time, immediately triggering the recalculation and rendering of the visual attributes (height and color) of the "visualized status volume" bound to that device. The entire 3D monitoring view is a dynamic, real-time feedback "living system" of the physical world's state. Any abnormal state (such as a sudden surge in CPU usage to the alarm threshold) will provide significant visual feedback in the 3D interface within seconds (such as the status volume turning red and its height increasing), transforming the monitoring system from a "historical recorder" into a "real-time dashboard," significantly improving the operation and maintenance team's response speed and initiative to emergencies.

[0055] 5. Possesses excellent architectural flexibility and scalability for large-scale deployment. The hierarchical model architecture (data center-region-rack-equipment) and standardized data unit interface design give the system clear modularity, enabling it to flexibly adapt to data center environments of different sizes and from different vendors. Whether it's a single server room or a hyperscale data center spanning multiple regions, it can be expanded by adding models and connecting to data sources. Independent data units and visualization rules allow for the flexible addition of monitoring device types or monitoring metric dimensions without refactoring the entire system, thus ensuring the long-term evolution of the technical solution and its potential to adapt to future needs.

[0056] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0057] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A 3D data center resource usage monitoring and visualization method, characterized in that, Includes the following steps: S1: Construct a 3D digital twin scenario of the data center physical environment, create and maintain an independent data unit for each physical device instance to be monitored in the 3D digital twin scenario, and associate the collected multi-dimensional operation monitoring data of the physical device instance with the corresponding data unit in real time; S2: Based on the monitoring dimension selected by the user, obtain the corresponding monitoring index value from the data unit associated with the target physical device instance, and drive the generation of a visual state body that is spatially associated with the 3D model of the physical device instance and whose visual attributes change dynamically with the monitoring index value according to the predefined visual mapping rules. S3: Provides the ability to switch between a real model view and a resource visualization view in the 3D display interface. Renders the 3D digital twin scene in the real model view, and overlays and renders the corresponding visualization state body at the corresponding position of the 3D model of each physical device instance in the resource visualization view, based on the 3D digital twin scene.

2. The 3D data center resource usage monitoring and visualization method according to claim 1, characterized in that, In step S1, a three-dimensional digital twin scene of the data center physical environment is constructed, including: Hierarchical 3D geometric modeling is performed on the entities within the data center to form a hierarchical set of 3D models. The entities include computer rooms and micro-modules that represent spatial range, racks for carrying IT equipment, and IT and infrastructure equipment entities, including servers, storage devices, network devices, power supply equipment, and cooling equipment. During modeling, the physical dimensions and installation location data of each entity are used for construction. Then, according to the actual spatial layout and topological relationships, the three-dimensional models at all levels are assembled and integrated to form a complete three-dimensional digital twin scene that reflects the physical structure of the data center.

3. The 3D data center resource usage monitoring and visualization method according to claim 1, characterized in that, In step S1, the multi-dimensional operation monitoring data is correlated to the corresponding data units in real time in the following manner: Assign a unique identifier to each physical device instance to be monitored within the data center, and instantiate an independent data structure bound to that identifier as its data unit. The data stream generated by the physical device instance is continuously collected through the monitoring agent or interface, and the collected data is classified by dimension and then updated to its data unit. Multidimensional operation monitoring data includes at least resource utilization data, energy consumption data, temperature data, load-bearing data, and equipment status alarm data. Resource utilization data includes one or more of the following: CPU utilization, memory utilization, storage utilization, and network bandwidth utilization.

4. The 3D data center resource usage monitoring and visualization method according to claim 1, characterized in that, In step S2, the visual mapping rule defines the conversion method from monitoring index values ​​to the core visual attributes of the visual status body. The core visual attributes include at least the rendering height and display color of the visual status body. When the monitoring index value is obtained, a percentage value representing the current load level is calculated based on the monitoring index value, and the height ratio to be rendered and the color to be displayed of the visual status body are determined synchronously based on the percentage value.

5. The 3D data center resource usage monitoring and visualization method according to claim 4, characterized in that, The height proportion that the visual state volume should be rendered should be determined synchronously based on this percentage value in the following manner: The calculated percentage value representing the current load level is used as the proportion of the height of the visualized state body in the vertical direction to the total height of the 3D model of its associated physical device instance. During rendering, the rendering height of the visual status volume is equal to the product of the total height of the 3D model of the physical device instance and the percentage value. The level of the monitoring indicator is intuitively reflected by the filling height of the visual status volume in the model space.

6. The 3D data center resource usage monitoring and visualization method according to claim 4, characterized in that, The colors that the visual status unit should display should be determined synchronously based on this percentage value as follows: Multiple consecutive percentage threshold intervals are predefined, and each percentage threshold interval is associated with a color that indicates a specific state. The calculated percentage value representing the load level is matched with the percentage threshold range to determine the percentage threshold range to which it belongs, and the color associated with the percentage threshold range is assigned as the display color of the visualization status volume.

7. The 3D data center resource usage monitoring and visualization method according to claim 1, characterized in that, In step S3, the real model perspective is used to display the physical layout and asset distribution of the data center. From this perspective, the 3D display interface only renders the original 3D digital twin scene constructed in step S1 without any visualization state volume modification. The resource visualization perspective is used to monitor the operating status. From this perspective, based on the original 3D digital twin scene, the 3D display interface overlays and renders the dynamically changing visualization state volume at the 3D model position of each physical device instance according to the result of step S2, transforming the abstract multi-dimensional monitoring data into a concrete visual form.

8. The 3D data center resource usage monitoring and visualization method according to claim 1, characterized in that, In step S3, the perspective switching function is provided as follows: a set of mode switching controls is set on the three-dimensional display interface. The mode switching controls include status visualization, capacity visualization, energy consumption visualization and temperature visualization options corresponding to different monitoring dimensions. In response to the user's trigger operation for any option, the current display mode is switched to the resource visualization perspective. Based on the monitoring dimension corresponding to the triggered option, the process of step S2 is invoked to update or generate the visualization status of all relevant physical device instances in the scene, refresh the 3D display interface, and globally present the distribution of the visualization status of all physical devices under this dimension.

9. The 3D data center resource usage monitoring and visualization method according to claim 8, characterized in that, After responding to user triggers for capacity visualization or energy consumption visualization options, the monitoring granularity selection function is provided as follows: a secondary selection control is provided, offering two monitoring granularity options: device level and rack level. When the user selects the device level option, an independent visualization status body is generated for each individual physical device instance. When the user selects the rack level option, the monitoring data of all physical device instances within the same rack in the selected dimension are aggregated and calculated, and a unified visualization status body representing its overall load level is generated based on the rack's 3D model.

10. The 3D data center resource usage monitoring and visualization method according to claim 1, characterized in that, Step S3 also includes interaction and alarm location in the following manner: Users can interact with the 3D model of the physical device instance or its superimposed visual state volume by clicking or selecting in the 3D display interface. In response to a selection action, detailed multi-dimensional operational monitoring data stored in the data unit corresponding to the physical device instance is displayed on the side of the interface or in a separate panel. It supports global filtering based on the display color of the visual status entity. By locating and highlighting all visual status entities whose current display color is a warning or alarm color and their associated physical device instances with one click, it helps to identify devices with abnormal status.

Images