Temperature detection method and device of hyper-fusion all-in-one machine, electronic equipment and storage medium

Abstract

The invention discloses a temperature detection method and device of a hyper-fusion all-in-one machine, electronic equipment and a storage medium, and relates to the technical field of hyper-fusion all-in-one machines, and the method comprises the steps: obtaining at least one piece of first temperature data through at least one first temperature sensor configured in the hyper-fusion all-in-one machine; at least one second temperature sensor in the hyper-fusion all-in-one machine obtains at least one piece of second temperature data; determining a three-dimensional thermodynamic diagram matched with the hyper-fusion all-in-one machine according to the at least one first temperature data and the at least one second temperature data; according to the three-dimensional thermodynamic diagram, the working state description information matched with the hyper-fusion all-in-one machine is determined, so that more comprehensive temperature data in the hyper-fusion all-in-one machine can be provided for a user, the temperature in the hyper-fusion all-in-one machine does not need to be checked point by point, the technical problem that the efficiency of obtaining the overall temperature in the hyper-fusion all-in-one machine is low is solved, and the user experience is improved. The technical effect of improving the efficiency of obtaining the overall temperature in the hyper-fusion all-in-one machine is achieved.

Description

Technical Field

[0001] This application relates to the field of hyperconverged infrastructure, specifically to a temperature detection method, apparatus, electronic device, and storage medium for a hyperconverged infrastructure. Background Technology

[0002] Hyperconverged appliances are products that integrate computing, storage, networking, and related management software into a single device based on a hyperconverged architecture. Delivered as an all-in-one appliance, they enable dynamic resource scheduling through software-defined technology. This helps enterprises quickly build cloud data centers and simplifies the management of IT equipment, improves operational efficiency, and allows for flexible resource expansion.

[0003] Currently, temperature monitoring methods for hyperconverged infrastructure rely solely on point-type temperature sensors, which can only monitor the operating temperature of the hyperconverged infrastructure point by point, resulting in low efficiency in obtaining the overall internal temperature of the hyperconverged infrastructure. Summary of the Invention

[0004] This application provides a temperature detection method, apparatus, electronic device, and storage medium for hyperconverged infrastructure, in order to at least solve the problem of low efficiency in obtaining the overall internal temperature of hyperconverged infrastructure in related technologies.

[0005] This application provides a temperature detection method for a hyperconverged infrastructure, comprising: acquiring at least one first temperature data using at least one first temperature sensor configured in the hyperconverged infrastructure, wherein the first temperature data acquired by the first temperature sensor is used to indicate temperature information of the configuration area where the first temperature sensor is located; acquiring at least one second temperature data using at least one second temperature sensor in the hyperconverged infrastructure, wherein the second temperature sensor is configured in a functional component of the hyperconverged infrastructure, and the second temperature data is used to indicate temperature information inside the functional component; determining a three-dimensional thermal map matching the hyperconverged infrastructure based on at least one first temperature data and at least one second temperature data, wherein the three-dimensional thermal map is used to indicate temperature information at multiple locations in the internal space of the hyperconverged infrastructure; and determining operating status description information matching the hyperconverged infrastructure based on the three-dimensional thermal map.

[0006] This application also provides a temperature detection device for a hyperconverged infrastructure, comprising: a first acquisition unit, configured to acquire at least one first temperature data through at least one first temperature sensor configured in the hyperconverged infrastructure, wherein the first temperature data acquired by the first temperature sensor is used to indicate temperature information of the configuration area where the first temperature sensor is located; a second acquisition unit, configured to acquire at least one second temperature data through at least one second temperature sensor in the hyperconverged infrastructure, wherein the second temperature sensor is configured in a functional component in the hyperconverged infrastructure, and the second temperature data is used to indicate temperature information inside the functional component that is matched therewith; a first determination unit, configured to determine a three-dimensional heat map matching the hyperconverged infrastructure based on at least one first temperature data and at least one second temperature data, wherein the three-dimensional heat map is used to indicate temperature information at multiple locations in the internal space of the hyperconverged infrastructure; and a second determination unit 508, configured to determine working status description information matching the hyperconverged infrastructure based on the three-dimensional heat map.

[0007] This application also provides an electronic device, including: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of the temperature detection method of any of the above-described hyperconverged integrated machines.

[0008] This application also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the steps of the temperature detection method of any of the above-described hyperconverged integrated machines.

[0009] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the above-described hyperconverged integrated machine temperature detection methods.

[0010] This application utilizes a temperature sensor located in the northern part of the hyperconverged appliance and a second temperature sensor embedded in the functional components to construct a three-dimensional thermal map reflecting the internal temperature distribution of the hyperconverged appliance. The three-dimensional thermal map is then used to determine the operating status description information matching the hyperconverged appliance, enabling the provision of more comprehensive temperature data to users. This eliminates the need to check the internal temperature of the hyperconverged appliance point by point, thereby improving the efficiency of obtaining the overall internal temperature of the hyperconverged appliance and solving the technical problem of low efficiency in obtaining the overall internal temperature of the hyperconverged appliance. Attached Figure Description

[0011] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A hardware structure block diagram of a server device for a temperature detection method of a hyperconverged integrated machine provided in this application embodiment;

[0013] Figure 2 This is a schematic diagram of one of the optional temperature detection methods for a hyperconverged infrastructure according to an embodiment of this application;

[0014] Figure 3 This is a second schematic diagram of an optional temperature detection method for a hyperconverged infrastructure according to an embodiment of this application;

[0015] Figure 4 This is a third schematic diagram of an optional temperature detection method for a hyperconverged infrastructure according to an embodiment of this application;

[0016] Figure 5 This is a fourth schematic diagram of an optional temperature detection method for a hyperconverged infrastructure according to an embodiment of this application;

[0017] Figure 6 This is a fifth schematic diagram of an optional temperature detection method for a hyperconverged infrastructure according to an embodiment of this application;

[0018] Figure 7 This is a schematic diagram (six) of an optional temperature detection method for a hyperconverged infrastructure according to an embodiment of this application;

[0019] Figure 8 This is a schematic diagram (seventh) of an optional temperature detection method for a hyperconverged infrastructure according to an embodiment of this application;

[0020] Figure 9 This is a schematic diagram (eighth) of an optional temperature detection method for a hyperconverged infrastructure according to an embodiment of this application.

[0021] Figure 10 This is a structural block diagram of a temperature detection device for a hyperconverged integrated machine according to an embodiment of this application;

[0022] Figure 11 This is a schematic diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0024] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0025] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] The methods and embodiments provided in this application can be executed on a server device or a similar computing device. Taking running on a server device as an example, Figure 1 This is a hardware structure block diagram of a computer device for a temperature detection method in a hyperconverged infrastructure according to an embodiment of this application. Figure 1 As shown, the server device may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The server device may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the server equipment described above. For example, the server equipment may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0027] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the temperature detection method of the hyperconverged integrated machine in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to server devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0028] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the server device. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0029] This embodiment provides a temperature detection method for a hyperconverged infrastructure. Figure 2 This is a flowchart of a temperature detection method for a hyperconverged infrastructure according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps:

[0030] S202, at least one first temperature data is acquired by at least one first temperature sensor configured in the hyper-converged appliance, wherein the first temperature data acquired by the first temperature sensor is used to indicate the temperature information of the configuration area where the first temperature sensor is located;

[0031] Optionally, in this embodiment, the hyperconverged appliance is an integrated information technology device based on a hyperconverged architecture. It can integrate computing, storage, networking, and server virtualization resources into a single unit device. It may also include elements such as backup software and snapshot technology, and achieve resource pooling and management through software-defined technology. Multiple devices in the hyperconverged appliance can be aggregated through a network to achieve modular horizontal scaling and form a unified resource pool.

[0032] Optionally, in this embodiment, the first temperature data is used to indicate the temperature information within the configuration area where the first temperature sensor is located. When the target point is located in the area configured by the first temperature sensor, the temperature information corresponding to the target point can be obtained through the first temperature sensor.

[0033] Optionally, in this embodiment, the configuration area of ​​the first temperature sensor can be adjusted according to the specific hyperconverged appliance. For example, for a hyperconverged appliance with a compact chassis design, in order to accurately monitor the heat dissipation of core components, the first temperature sensor can be configured near the heat sink of the central processing unit or the exhaust vent of the power module; while for a model with a modular architecture containing multiple node units, in order to comprehensively capture the temperature distribution during the operation of the entire machine and ensure that the cooling system starts or stops according to the actual heat load, the first temperature sensor can be configured at the intersection of the air ducts between the nodes; or the first temperature sensor can be evenly configured in a grid pattern in the hyperconverged appliance.

[0034] Optionally, in this embodiment, when performing temperature detection of the hyperconverged appliance, the temperature information of multiple target points within the configuration area where the first temperature sensor is located is obtained through at least one first temperature sensor configured in the hyperconverged appliance, thereby obtaining the first temperature data.

[0035] S204, at least one second temperature sensor in the hyperconverged appliance acquires at least one second temperature data, wherein the second temperature sensor is configured in a functional component in the hyperconverged appliance, and the second temperature data is used to indicate the temperature information inside the matched functional component.

[0036] Optionally, in this embodiment, the second temperature sensor is a temperature sensor of a functional component configured in the hyperconverged infrastructure, used to acquire temperature information of the functional component when it is idle or working, and to feed back the acquired temperature information.

[0037] Optionally, in this embodiment, the second temperature data can be temperature information used to indicate the temperature inside a functional component that matches it. For example, when the target point is inside a functional component, the temperature information of the target point can be obtained by comparing it with the second temperature data inside the functional component.

[0038] Optionally, in this embodiment, the second temperature sensor is integrated into the functional components of the hyper-converged infrastructure, such as the central processing unit, memory disk, hard disk, etc., and the temperature information inside the functional components is obtained through the second temperature sensor when the functional components are working or idle.

[0039] S206, determine a three-dimensional thermal map matching the hyperconverged appliance based on at least one first temperature data and at least one second temperature data, wherein the three-dimensional thermal map is used to indicate temperature information at multiple locations within the internal space of the hyperconverged appliance;

[0040] Optionally, in this embodiment, the three-dimensional heat map can be a temperature information visualization chart based on three-dimensional spatial coordinates. The temperature information of multiple spatial coordinates or target points in the hyper-converged integrated machine can be intuitively reflected by displaying different colors corresponding to the temperature values ​​of the three-dimensional heat map.

[0041] Optionally, in this embodiment, after obtaining at least one first temperature data and at least one second temperature data, a three-dimensional thermal map matching the hyperconverged appliance is determined by the at least one first temperature data and at least one second temperature data, so that the temperature information inside the hyperconverged appliance can be obtained through the three-dimensional thermal map.

[0042] S208, based on the three-dimensional heat map, determines the working status description information that matches the hyper-converged integrated machine.

[0043] Optionally, in this embodiment, the working status description information can be the overall operating status of the hyperconverged appliance at a certain point in time or within a certain time range, which is based on the analysis of a three-dimensional heat map. This includes, but is not limited to, the heat distribution within the hyperconverged appliance, temperature alarm information, temperature control strategy, fan speed, etc.

[0044] Further examples, such as Figure 3 As shown, this is a three-dimensional heat map in a three-dimensional coordinate system. Through this three-dimensional heat map, the temperature information of positions 302 and 304 can be intuitively obtained as part of the working status description information of the hyper-converged integrated machine.

[0045] It should be noted that the heat source distribution in a hyperconverged appliance is complex, and a single temperature sensor cannot capture the details of temperature changes throughout the entire chassis. By adding a first temperature sensor to the hyperconverged appliance and using it to obtain temperature information within its configured area to directly monitor the temperature of key components, and then combining this with temperature data from a second temperature sensor of the functional components, a three-dimensional heat map can be constructed, thereby providing a clear view of the temperature distribution within the hyperconverged appliance.

[0046] Specifically, the first and second temperature sensors together form a multi-dimensional temperature monitoring network. The former focuses on the environment within the hyperconverged appliance, while the latter focuses on the functional components of the hyperconverged appliance. The combination of their data makes the temperature distribution information more comprehensive and accurate. The 3D thermal map can transform this series of temperature data into intuitive visual information, facilitating the rapid identification of abnormal temperature areas and trends. The operating status description information provides a comprehensive assessment of the current temperature state and the planning of subsequent control strategies, enabling the hyperconverged appliance to maintain a good operating condition in most situations.

[0047] Through the embodiments of this application, by simultaneously utilizing a temperature sensor configured in the north of the hyperconverged appliance and a second temperature sensor embedded in the functional components, a three-dimensional thermal map reflecting the internal temperature distribution of the hyperconverged appliance is constructed. The three-dimensional thermal map is then used to determine the working status description information matching the hyperconverged appliance, enabling the provision of more comprehensive temperature data to users. This eliminates the need to check the internal temperature of the hyperconverged appliance point by point, thereby improving the efficiency of obtaining the overall internal temperature of the hyperconverged appliance and solving the technical problem of low efficiency in obtaining the overall internal temperature of the hyperconverged appliance.

[0048] As an optional approach, a three-dimensional thermal map matching the hyperconverged infrastructure is determined based on at least one first temperature data and at least one second temperature data, including:

[0049] S1, determine a first temperature information set based on at least one first temperature data, wherein the first temperature information set includes first temperature information of at least one first target point, and the first target point is located in a configuration area that matches it;

[0050] S2, determine a second temperature information set based on at least one second temperature data, wherein the second temperature information set includes second temperature information for at least one second target point, and the second target point is located inside a matching functional component;

[0051] S3, determine the union between the first temperature information set and the second temperature information set as the reference temperature information set;

[0052] S4 determines a three-dimensional thermal map that matches the hyperconverged integrated machine based on a set of reference temperature information.

[0053] Optionally, the first temperature set may be determined by at least one first temperature data, including temperature information of at least one first target point, and the first target point is located in a configuration area that matches it, which can be understood as the first target point being located in a configuration area with a certain first temperature sensor.

[0054] Optionally, the second temperature set may be determined by at least one second temperature data, containing second temperature information for each of at least one second target point, and the second target point is located inside a functional component that matches it. This can be understood as the second target point being located in a functional component carrying a second temperature sensor.

[0055] To further illustrate, optionally, such as Figure 4 As shown, the hyperconverged appliance 402 includes functional components 404, 406, and 408. Functional component 404 is equipped with a temperature sensor 410, functional component 406 with a temperature sensor 412, and functional component 408 with a temperature sensor 414, for monitoring its own temperature. In addition, the hyperconverged appliance 402 also has temperature sensors 416, 418, 420, and 422 distributed on it, allowing for the detection of the temperature of the entire hyperconverged appliance or other areas.

[0056] Optionally, in this embodiment, the reference temperature information set can be obtained by the union of the first temperature information set and the second temperature information set, and can be used to construct a three-dimensional heat map of temperature and location information, and may include the location and temperature information of multiple reference information points.

[0057] Optionally, in this embodiment, determining the first temperature information set based on at least one first temperature data means collecting temperature data from the configuration area of ​​the hyperconverged appliance and forming an information set containing specific temperature details of at least one first target point within that area.

[0058] To illustrate further, optionally, for the rack configuration area of ​​a certain hyperconverged appliance, if the first temperature sensor detects the temperature from the top ventilation opening of the rack, this location can be the first target point. The corresponding first temperature information can include the temperature value at that point, as well as information such as the time and trend of the temperature change.

[0059] Optionally, in this embodiment, determining the second temperature information set based on at least one second temperature data means that after collecting at least one set of temperature data related to a specific functional component from a device such as a hyperconverged appliance, the information set containing specific temperature details of at least one second target point inside these components is generated through analysis and processing.

[0060] To further illustrate, optionally, if the temperature information of multiple second target points in the core area of ​​the central processing unit is obtained through the second temperature sensor configured in the central processing unit, the information of each second target point may include the specific temperature value of the second target point, and may also include information such as the time and trend of change corresponding to that temperature.

[0061] Optionally, in this embodiment, the union of the first temperature information set and the second temperature information set is determined as the reference temperature information set. This means merging the collected first temperature information set and the second temperature information set to form a reference temperature information set that includes the ambient temperature and internal temperature information of the functional components within the hyperconverged appliance. This covers the comprehensiveness of the internal temperature monitoring of the hyperconverged appliance and provides a data foundation for the subsequent construction of a three-dimensional heat map.

[0062] Optionally, in this embodiment, determining the three-dimensional heat map matching the hyperconverged appliance based on the reference temperature information set means generating a three-dimensional heat map inside the hyperconverged appliance by using data from the reference temperature information set, combined with a three-dimensional spatial model, and through interpolation and color mapping techniques.

[0063] It should be noted that the internal environment of a hyperconverged infrastructure is complex, and data from a single type of sensor is insufficient to fully understand the temperature conditions. By acquiring a first set of temperature information and a second set of temperature information, which cover a wide range of factors from the ambient temperature inside the hyperconverged infrastructure to the internal temperature of functional components, and merging the two sets to form a reference temperature information set, the comprehensiveness of the data for constructing a 3D heat map can be improved, thereby enhancing the accuracy of the 3D heat map.

[0064] In this embodiment, a first temperature information set is determined based on at least one first temperature data point, wherein the first temperature information set includes first temperature information for at least one first target point located in a matching configuration area; a second temperature information set is determined based on at least one second temperature data point, wherein the second temperature information set includes second temperature information for at least one second target point located inside a matching functional component; the union of the first and second temperature information sets is determined as a reference temperature information set; and a three-dimensional heat map matching the hyperconverged appliance is determined based on the reference temperature information set. By acquiring the first and second temperature information sets, a multi-dimensional acquisition is achieved, encompassing the ambient temperature inside the hyperconverged appliance to the internal temperature of the functional components. Merging the two sets to form the reference temperature information set achieves the technical objective of improving the comprehensiveness of the data used to construct the three-dimensional heat map, thereby improving the accuracy of the three-dimensional heat map.

[0065] As an optional approach, a 3D thermal map matching the hyperconverged infrastructure is determined based on a set of reference temperature information, including:

[0066] S1, Based on the reference temperature information set, determine at least one discrete feature point in the three-dimensional coordinate system, wherein the coordinate information of the discrete feature point is determined according to the position information of the target point in the target temperature information set, and the value of the discrete feature point is determined according to the temperature information corresponding to the target point.

[0067] S2, use at least one discrete feature point to substitute into the model to construct a formula, and determine the target mapping relationship based on the solution results, wherein the target mapping relationship is used to indicate the mapping relationship between position information and temperature information;

[0068] S3, obtain the target temperature information set according to the target mapping relationship, wherein the target temperature information set includes multiple locations in the internal space of the hyper-converged integrated machine and their corresponding temperature information;

[0069] S4. Based on the color representation model and the target temperature information set, color rendering is performed in the three-dimensional coordinate system to obtain a three-dimensional heat map.

[0070] Optionally, in this embodiment, discrete feature points refer to points that represent temperature values ​​at specific locations in a three-dimensional coordinate system. These points are determined based on the location information and temperature values ​​in the target temperature information set and are the basic elements used to construct a three-dimensional heat map.

[0071] Optionally, in this embodiment, the model construction formula is used to determine the specific construction formula of the three-dimensional heat map through at least one discrete feature point, and can be a multiple linear regression model or a Gaussian process regression model.

[0072] To further illustrate, in an optional embodiment, when there are three discrete feature points, if a three-dimensional heatmap is constructed using a multiple linear regression model, the target mapping relationship can be determined using formula (1) and based on the solution results:

[0073] t=w1x+w2y+w3z+b (1);

[0074] Where t represents the first temperature information, x, y, and z are the coordinates of three discrete feature points in the three-dimensional coordinate system, w1, w2, and w3 are the weight coefficients to be solved, and b is the bias term. Then, the system of equations is solved using the least squares method to obtain the specific values ​​of w1, w2, w3, and b, thus determining the target mapping relationship, which can be used to calculate the temperature at any location within the configuration area.

[0075] In another alternative embodiment, when there are two discrete feature points, if a Gaussian process regression model is used to construct a three-dimensional heat map, the target mapping relationship can be determined using formula (2) and based on the solution results:

[0076] t(x,y,z)~GP(m(x,y,z),k((x,y,z),(x′,y′,z′))) (2);

[0077] Where t(x,y,z) represents the temperature information corresponding to the target point (x,y,z); GP represents a Gaussian process; m(x,y,z) is the mean function, which can be simplified to 0, meaning that the temperature data is assumed to fluctuate around the mean of 0; k((x,y,z), (x′,y′,z′)) is the covariance function, used to describe the temperature correlation between the target points (x,y,z) and (x′,y′,z′).

[0078] Optionally, in this embodiment, the color representation model is used to map points in the three-dimensional coordinate system to different colors according to temperature information, thereby realizing color rendering of the three-dimensional heat map.

[0079] Optionally, in this embodiment, based on the target temperature information set, multiple points inside the hyperconverged integrated machine are selected as discrete feature value points. The coordinate positions of these points can be determined by the actual location information of the target points, such as the sensor installation location or the center point of the component, while the values ​​are determined by the real-time temperature information of the corresponding points. This process transforms the temperature data into points in a three-dimensional coordinate system, which is the preliminary preparation for constructing a three-dimensional heat map.

[0080] Next, by inputting the data of discrete feature points into the model construction formula, the distribution pattern of temperature values ​​in three-dimensional space is calculated, thereby fitting the actual temperature data and establishing a target mapping relationship between location information and temperature information. That is, given any point inside the hyperconverged integrated machine, the temperature value at that point can be predicted.

[0081] Then, using the previously established target mapping relationship, the temperature value of each grid point inside the hyperconverged appliance can be calculated, thus forming a target temperature information set containing temperature information for the entire chassis. Each data point in this set corresponds one-to-one with a three-dimensional coordinate, providing a comprehensive view of the temperature distribution inside the hyperconverged appliance.

[0082] Finally, using the data from the target temperature information set, color rendering is performed in a three-dimensional coordinate system to convert the temperature values ​​into a visual color representation.

[0083] It should be noted that by constructing the model and calculating the target mapping relationship, the temperature status of locations that are not directly measured can be predicted; the generation of the target temperature information set further expands the coverage of temperature data and enables a global grasp of temperature information; finally, the application of the color representation model makes the temperature distribution visible, which facilitates the rapid identification and processing of abnormal temperature areas, enabling the hyperconverged appliance to maintain stable and efficient operation.

[0084] According to the embodiments of this application, at least one discrete feature point is determined in a three-dimensional coordinate system based on a reference temperature information set. The coordinates of the discrete feature point are determined based on the position information of the target point in the target temperature information set, and the numerical value of the discrete feature point is determined based on the temperature information corresponding to the target point. The at least one discrete feature point is substituted into the model construction formula, and a target mapping relationship is determined based on the solution results. This target mapping relationship indicates the mapping relationship between position information and temperature information. A target temperature information set is obtained based on the target mapping relationship. This target temperature information set includes multiple locations within the internal space of the hyperconverged infrastructure and their corresponding temperature information. Color rendering is performed in a three-dimensional coordinate system based on the color representation model and the target temperature information set to obtain a three-dimensional heat map. By calculating the target mapping relationship and generating the target temperature information set through the model construction formula, abnormal temperature areas can be quickly identified, improving the efficiency of managing the hyperconverged infrastructure.

[0085] As an optional approach, before determining the union of the first temperature information set and the second temperature information set as the reference temperature information set, the following steps are also included:

[0086] S1, determine a first weight set based on the location of at least one first temperature sensor, wherein the first weight set includes at least one weight that matches the configuration location of the first temperature sensor;

[0087] S2, determine a second weight set based on the location of the functional component corresponding to at least one second temperature sensor, wherein the second weight set includes at least one weight that matches the location of the functional component;

[0088] S3. In the case where there are multiple temperature information points corresponding to the same third target point in the union of the first temperature information set and the second temperature information set, the multiple temperature information points are weighted and summed based on the first weight set and the second weight set to obtain the third temperature information corresponding to the third target point.

[0089] Optionally, in this embodiment, the first position weight set is a weight set determined by the configuration position of at least one first temperature sensor. In the first position weight set, each weight corresponds to a position. When the first temperature sensor is located at a certain position, the first temperature sensor is assigned a weight that matches that position.

[0090] Optionally, in this embodiment, the first position weight set is a weight set determined by the position of the functional component corresponding to at least one second temperature sensor. In the second position weight set, each weight corresponds to a position. When the functional component is located at a certain position, the second temperature sensor in the functional component is assigned a weight that matches the position.

[0091] Optionally, in this embodiment, the first temperature sensor is distributed in various locations inside the hyperconverged infrastructure, such as around the chassis or near internal heat sources. The weight of each sensor is determined based on its contribution to overall temperature monitoring. The weight is related to factors such as the heat source density and importance of the area monitored by the first temperature sensor; a higher weight is assigned to a sensor located in a location with high heat source density or high importance.

[0092] Optionally, in this embodiment, the second temperature sensor is directly disposed inside the functional component. Since the heat generated by these components has a significant impact on the overall temperature distribution, the data of the second temperature sensor is assigned a weight based on the location of the corresponding functional component. The weight value reflects the degree of influence of the functional component on the overall thermal environment.

[0093] Optionally, in this embodiment, during the construction of the three-dimensional heat map, it may be encountered that data monitored by multiple sensors correspond to the same third target point. In this case, the data are weighted and summed using a first weight set and a second weight set to obtain the comprehensive temperature value of the point, thereby obtaining more accurate temperature information and improving the accuracy of the obtained reference temperature information.

[0094] It should be noted that, to ensure the accuracy of temperature data, weight values ​​need to be assigned to each sensor based on the importance of its location, forming a first weight set and a second weight set. When data from multiple sensors correspond to the same spatial coordinate point, a weighted summation method is used to fuse these data according to their respective weight values. This reduces the impact of data fluctuations on the accuracy of the heatmap and improves the accuracy of the obtained reference temperature information.

[0095] In this embodiment, a first weight set is determined based on the location of at least one first temperature sensor, wherein the first weight set includes at least one weight matching the configuration location of the first temperature sensor; a second weight set is determined based on the location of the functional component corresponding to at least one second temperature sensor, wherein the second weight set includes at least one weight matching the location of the functional component; when multiple temperature information points correspond to the same third target point in the union of the first and second temperature information sets, the multiple temperature information points are weighted and summed based on the first and second weight sets to obtain the third temperature information corresponding to the third target point. When data from multiple sensors correspond to the same spatial coordinate point, the weighted summation method is used to weight and sum these data according to their respective weight values, thereby reducing the impact of data fluctuations on the accuracy of the heat map and improving the accuracy of the obtained reference temperature information.

[0096] As an optional approach, a 3D thermal map matching the hyperconverged infrastructure is determined based on a set of reference temperature information, including:

[0097] S1, Obtain the configuration distribution characteristics of at least one first temperature sensor;

[0098] S2, under the condition that the first temperature sensor is uniformly configured inside the hyper-converged integrated machine with configuration distribution characteristics, the three-dimensional thermal map is determined by the interpolation result of the reference temperature information set;

[0099] S3, when the configuration distribution characteristics indicate the configuration location of the first temperature sensor inside the hyperconverged appliance, and are related to the temperature distribution characteristics inside the hyperconverged appliance, a three-dimensional thermal map is determined based on the heat conduction model and the reference temperature information set;

[0100] S4, when the configuration distribution characteristics indicate the configuration position of the first temperature sensor inside the hyperconverged appliance, and are related to the airflow distribution characteristics inside the hyperconverged appliance, a three-dimensional thermal map is determined by combining airflow data and a set of reference temperature information, wherein the airflow data is used to represent the airflow direction and airflow speed inside the hyperconverged appliance.

[0101] Optionally, in this embodiment, the configuration distribution feature refers to the configuration status of the first temperature sensor in the hyper-converged integrated machine, so that different three-dimensional heat map determination methods can be selected according to different configuration statuses.

[0102] Optionally, in this embodiment, different methods for determining the three-dimensional thermal map can be selected based on the configuration distribution characteristics of at least one first temperature sensor. When the configuration distribution characteristics indicate that the first temperature sensors are uniformly configured within the hyperconverged infrastructure, the three-dimensional thermal map is determined using the interpolation results of a reference temperature information set. When the configuration distribution characteristics indicate that the configuration position of the first temperature sensors within the hyperconverged infrastructure is related to the temperature distribution characteristics within the hyperconverged infrastructure, the three-dimensional thermal map is determined based on a heat conduction model and a reference temperature information set. When the configuration distribution characteristics indicate that the configuration position of the first temperature sensors within the hyperconverged infrastructure is related to the airflow distribution characteristics within the hyperconverged infrastructure, the three-dimensional thermal map is determined by combining airflow data and a reference temperature information set.

[0103] To further illustrate, optionally, in one embodiment, if the acquired configuration distribution characteristics show that the first temperature sensor is uniformly configured inside the hyperconverged appliance, such as arranged in a 5cm×5cm grid spacing within the chassis, then after acquiring the reference temperature information set, temperature estimation can be performed on areas where no sensors are deployed using Kriging interpolation. For example, when sensors are uniformly distributed in areas such as compute nodes, storage modules, and power supply areas, the interpolation results can smoothly fill the temperature transitions between each area, ultimately generating a three-dimensional thermal map covering the entire interior of the appliance, thus clearly presenting the global temperature gradient within the hyperconverged appliance.

[0104] like Figure 5 As shown, the hyperconverged appliance 502 contains functional components 504 and 506, as well as temperature sensors 508, 510, 512, and 514. These temperature sensors are evenly distributed within the hyperconverged appliance. Therefore, when determining the three-dimensional thermal map inside the hyperconverged appliance 502, the three-dimensional thermal map is determined by interpolation results from a reference temperature information set.

[0105] In another embodiment, if the configuration distribution characteristics indicate that the location of the first temperature sensor is related to the temperature distribution characteristics inside the hyperconverged infrastructure, such as the sensors being concentrated around high-heat-generating components like the central processing unit (CPU) and hard drives, then a heat conduction model, such as the Fourier heat conduction equation, needs to be used to process the set of reference temperature information. For example, if the temperature displayed by the sensor near the CPU is 65°C and that of the hard drive area is 42°C, the heat conduction rate and attenuation law in the metal chassis and air medium can be calculated through the model. This can accurately reconstruct the temperature field diffusion process of heat dissipation from high-heat-generating components to the surrounding area, thereby generating a three-dimensional thermal map reflecting the heat conduction path.

[0106] Further examples, such as Figure 6As shown, the hyperconverged appliance 602 contains functional components 604 and 606, both located in the lower half of the appliance. Therefore, temperature sensors 608 and 610 are arranged around functional component 604, and temperature sensors 612 and 614 are arranged around functional component 606. Since there are no functional components in the upper half of the hyperconverged appliance 602, a temperature sensor 616 is arranged there. Because the placement of the temperature sensors within the hyperconverged appliance is related to the internal temperature distribution characteristics, a three-dimensional thermal map is determined based on the heat conduction model and a set of reference temperature information.

[0107] In another embodiment, if the configuration distribution characteristics show that the configuration position of the first temperature sensor is related to the airflow distribution characteristics, such as the sensor being arranged along the air outlet of the cooling fan and the turning point of the air duct, then it is necessary to combine the airflow data, such as when the fan speed is 1500 r / min, the airflow direction in the air duct is from back to front, the flow velocity is 2 m / s and the reference temperature information is combined. If the temperature measured by the air outlet sensor is 38°C and the temperature in the middle section of the air duct is 45°C, it can be known from the airflow direction that the heat gradually decreases as it is transferred forward with the airflow. Combined with the flow velocity, the heat diffusion rate can be calculated. The final generated three-dimensional thermal map can simultaneously reflect the temperature distribution and the heat migration trend driven by the airflow.

[0108] Further examples, such as Figure 7 As shown, the hyperconverged appliance 702 contains functional components 704 and 706, as well as air outlets 708 and 710. Temperature sensors 712 and 714 are arranged around air outlet 708, and temperature sensors 716 and 718 are arranged around air outlet 710. Since the arrangement of the temperature sensors inside the hyperconverged appliance is related to the airflow distribution characteristics inside the hyperconverged appliance, a three-dimensional thermal map is determined by combining airflow data and a set of reference temperature information.

[0109] It should be noted that the temperature distribution inside the hyperconverged infrastructure is determined by a variety of factors, including heat source distribution, airflow organization, and material thermal conductivity. The configuration and distribution characteristics of the first temperature sensor directly affect the coverage and accuracy of the temperature data. When the sensors are uniformly configured, interpolation methods can fill in the gaps between data points, generating a smooth temperature distribution map. When the sensor configuration is related to the heat source distribution, using a heat conduction model can more accurately predict the heat transfer path, generating a three-dimensional thermal map reflecting the influence of the heat source. When the sensor configuration is related to the airflow distribution, combining airflow data for analysis can take into account the influence of airflow on the temperature distribution, generating a more accurate temperature distribution map.

[0110] This application embodiment obtains the configuration distribution characteristics of at least one first temperature sensor; when the configuration distribution characteristics indicate that the first temperature sensor is uniformly configured inside the hyperconverged infrastructure, a three-dimensional thermal map is determined by interpolation results from a reference temperature information set; when the configuration distribution characteristics indicate that the configuration position of the first temperature sensor inside the hyperconverged infrastructure is related to the temperature distribution characteristics inside the hyperconverged infrastructure, a three-dimensional thermal map is determined based on a heat conduction model and a reference temperature information set; when the configuration distribution characteristics indicate that the configuration position of the first temperature sensor inside the hyperconverged infrastructure is related to the airflow distribution characteristics inside the hyperconverged infrastructure, a three-dimensional thermal map is determined by combining airflow data and a reference temperature information set, wherein the airflow data is used to represent the airflow direction and airflow velocity inside the hyperconverged infrastructure. By selecting different thermal map determination methods based on different configuration distribution characteristics, the most suitable method for determining the three-dimensional thermal map can be flexibly selected according to the configuration characteristics of the first temperature sensor, thereby improving the accuracy of the obtained three-dimensional thermal map.

[0111] As an optional approach, after determining a three-dimensional thermal map matching the hyperconverged appliance based on at least one first temperature data and at least one second temperature data, the method further includes:

[0112] S1, obtain the first temperature corresponding to the target area through a three-dimensional thermal map;

[0113] S2, when the first temperature meets the first temperature condition, a first adjustment signal is sent to the hyper-converged appliance, wherein the first adjustment signal is used to adjust the heat dissipation strategy of the hyper-converged appliance;

[0114] Alternatively, S3, the second adjustment signal is sent to the hyperconverged appliance, wherein the second adjustment signal is used to adjust the operating voltage or frequency of the functional components corresponding to the target area;

[0115] Alternatively, S4, a third adjustment signal is sent to the hyperconverged appliance, wherein the third adjustment signal is used to adjust the flow rate and pressure of the liquid cooling system in the hyperconverged appliance;

[0116] S5, obtain the second temperature corresponding to the target area.

[0117] Optionally, in this embodiment, the first adjustment signal is used to adjust the heat dissipation strategy within the hyperconverged appliance. The heat dissipation strategy is used to adjust the speed or setting of the fan used for cooling within the hyperconverged appliance. When the first temperature is within a first threshold range, the heat dissipation strategy may be to set the fan speed to the first setting or the first speed. When the first temperature is within a second threshold range, the heat dissipation strategy may be to set the fan speed to the second setting or the second speed.

[0118] Optionally, in this embodiment, the second adjustment signal is a signal used to adjust the operating voltage or frequency of the functional components corresponding to the target area. When the three-dimensional heat map shows that the temperature of the target area continues to rise to a threshold due to the high-frequency operation of the central processing unit, the second adjustment signal can reduce the operating frequency or voltage of the central processing unit, reduce its power consumption and heat generation, and avoid problems such as device frequency reduction and shutdown caused by local overheating; while when the temperature is within a safe range and the load is high, the signal can also appropriately increase the voltage or frequency to release performance, thereby achieving a dynamic balance between device stability and operating efficiency, ensuring that the hyper-converged integrated machine is always in a highly efficient and reliable operating state.

[0119] Optionally, in this embodiment, the third adjustment signal is used to adjust the flow rate and pressure of the liquid cooling system within the hyperconverged infrastructure. When the 3D thermal map shows an abnormally high temperature in the target area within the hyperconverged infrastructure, the third adjustment signal can increase the flow rate of the liquid cooling pipeline in that area and increase the system pressure, accelerating the circulation speed of the coolant, enhancing the heat absorption efficiency of high-heat-generating components, and rapidly reducing the local temperature. Conversely, when the overall operating load is low and the temperature is within a safe range, the signal can reduce the flow rate and pressure, reducing the energy consumption of the liquid cooling pump while ensuring heat dissipation, achieving a dynamic balance between heat dissipation performance and energy consumption, and ensuring stable operation of the hyperconverged infrastructure under the premise of efficient heat dissipation.

[0120] Optionally, in this embodiment, a three-dimensional thermal map can accurately identify temperature anomalies in the target area, and different heat dissipation methods can be selected based on the temperature level and the evaluation results of heat dissipation efficiency. When the temperature is slightly higher than the first threshold, and the heat dissipation efficiency evaluation shows that the current heat dissipation system still has significant redundancy, the heat dissipation strategy is adjusted first. If the temperature continues to rise to the second threshold, and the heat dissipation efficiency evaluation shows that simply adjusting the heat dissipation strategy has limited effect (e.g., the fan is running at full speed but the temperature is still rising), the operating frequency of high-function components is reduced through a second adjustment signal. When the temperature is higher than the third threshold, and the heat dissipation efficiency evaluation shows that the liquid cooling system still has adjustment space (e.g., the current flow rate and pressure have not reached the maximum threshold), the parameters of the liquid cooling system are adjusted. Specifically, by selecting different heat dissipation strategies for different temperature conditions, not only is the real-time temperature status considered, but also the efficiency and cost of different cooling methods are combined, achieving flexible adjustment and optimization of the temperature control strategy.

[0121] In this embodiment, a first temperature corresponding to a target area is obtained through a three-dimensional thermal map. If the first temperature meets the first temperature condition, a first adjustment signal is sent to the hyper-converged appliance, whereby the first adjustment signal is used to adjust the heat dissipation strategy of the hyper-converged appliance; or, a second adjustment signal is sent to the hyper-converged appliance, whereby the second adjustment signal is used to adjust the operating voltage or frequency of the functional components corresponding to the target area; or, a third adjustment signal is sent to the hyper-converged appliance, whereby the third adjustment signal is used to adjust the flow rate and pressure of the liquid cooling system in the hyper-converged appliance; and a second temperature corresponding to the target area is obtained. By selecting different heat dissipation strategies for adjustment under different temperature conditions, not only is the real-time temperature status considered, but also the efficiency and cost of different cooling methods are combined, achieving flexible adjustment and optimization of the temperature control strategy.

[0122] As an optional approach, if the second temperature satisfies the second temperature condition, the method further includes at least one of the following:

[0123] S1, send the fourth adjustment signal to the hyper-converged all-in-one machine and display the first prompt information, wherein the fourth adjustment signal is used to shut down the functional components corresponding to the target area, and the first prompt information is used to indicate that the temperature of the target area exceeds the preset temperature threshold.

[0124] S2, send the fifth adjustment signal to the hyperconverged appliance and display the second prompt message, wherein the fifth adjustment signal is used to shut down the hyperconverged appliance and the second prompt message is used to indicate that the hyperconverged appliance is in a dormant state;

[0125] S3, send the sixth adjustment signal to the hyper-converged appliance and display the third prompt message. The sixth adjustment signal is used to migrate the target task being performed by the functional component corresponding to the target area to other functional components. The third prompt message is used to indicate that the target task has been migrated to the target functional component.

[0126] Optionally, in this embodiment, after receiving the first adjustment signal, the second adjustment signal, or the third adjustment signal, if the second temperature corresponding to the target area is obtained after temperature adjustment and the second temperature condition is met, it means that the effect of the temperature adjustment strategy is not ideal and additional adjustment instructions need to be executed.

[0127] Optionally, in this embodiment, if the second temperature meets the second temperature condition, the fourth adjustment signal can be used to adjust the functional components corresponding to the target area, and the first prompt information can be used to indicate that the temperature of the target area exceeds the preset temperature threshold.

[0128] Optionally, in this embodiment, if the second temperature meets the second temperature condition, the entire hyperconverged appliance can be shut down via the fifth adjustment signal, and the hyperconverged appliance can be prompted to be in a dormant state via the second prompt message.

[0129] Optionally, in this embodiment, if the second temperature meets the second temperature condition, the target task being performed by the functional component corresponding to the target area can be transferred to another functional component via the sixth adjustment signal, and the target task can be prompted to move to the target functional component via the third prompt message. Furthermore, since the target task has been transferred to another functional component, the operating voltage or frequency of the functional component corresponding to the target area can be further reduced by sending the second adjustment signal back to the hyperconverged infrastructure.

[0130] It should be noted that when a single functional component overheats, a fourth adjustment signal can be sent to shut it down, preventing localized failure; a fifth adjustment signal can shut down the entire appliance, preventing more serious hardware damage; and a sixth adjustment signal can enable rapid task migration, maintaining business continuity and reducing the workload of functional components, thereby lowering their corresponding temperatures. By using multiple temperature adjustment signals, the hyperconverged appliance's further cooling strategies can be flexibly determined, minimizing interruptions to normal services and improving the appliance's operational stability.

[0131] In this embodiment, a fourth adjustment signal is sent to the hyperconverged appliance, and a first prompt message is displayed. The fourth adjustment signal is used to shut down the functional components corresponding to the target area, and the first prompt message indicates that the temperature of the target area exceeds a preset temperature threshold. A fifth adjustment signal is sent to the hyperconverged appliance, and a second prompt message is displayed. The fifth adjustment signal is used to shut down the hyperconverged appliance, and the second prompt message indicates that the hyperconverged appliance is in a sleep state. A sixth adjustment signal is sent to the hyperconverged appliance, and a third prompt message is displayed. The sixth adjustment signal is used to migrate the target task being performed by the functional components corresponding to the target area to other functional components, and the third prompt message indicates that the target task has been migrated to a target functional component. By using multiple different temperature adjustment signals, further heat dissipation strategies for the hyperconverged appliance can be flexibly determined, minimizing interruptions to normal services and improving the operational stability of the hyperconverged appliance.

[0132] As an optional solution, in order to better understand the process of the temperature detection method of the hyperconverged integrated machine described above, the following describes the execution flow of the temperature detection method of the hyperconverged integrated machine in conjunction with optional embodiments, but it is not intended to limit the technical solution of the embodiments of this application.

[0133] It's important to note that with the rapid development of information technology and cloud computing, the performance and reliability of hyperconverged infrastructure (HCI) appliances, as core equipment in data centers, are becoming increasingly crucial. However, the operating temperature of HCI appliances directly impacts their stability and lifespan; excessively high temperatures can lead to server malfunctions, component failures, or even damage. Currently, temperature monitoring of HCI appliances primarily relies on traditional temperature sensors and simple temperature display interfaces, showing localized temperatures as points. This method cannot provide detailed information about the server's internal temperature or display it in a planar manner, meaning it cannot determine the temperature value based on arbitrary spatial coordinates within the appliance. Therefore, a solution is needed that can construct a real-time 3D heat map of the server and perform corresponding temperature control based on the heat map data, replacing points with planar data to ensure the stable operation of the appliance and its components and improve its reliability. Furthermore, as a new type of server architecture, HCI appliances integrate computing, storage, and networking functions, resulting in abundant component resources and a more complex internal temperature distribution. Components such as the CPU, memory, and hard drive generate significant heat. Failure to effectively manage and control this heat can lead to equipment malfunctions, performance degradation, or even damage. Therefore, a more advanced temperature monitoring and control system is required.

[0134] Based on the above problems, this embodiment proposes a 3D thermal map design and temperature control processing scheme for hyperconverged integrated machines, which enriches the temperature acquisition methods of hyperconverged integrated machines, infers the temperature distribution of the entire three-dimensional space based on the temperature of key monitoring points, and draws 3D graphics to display comprehensive temperature data. Furthermore, it formulates alarm and processing strategies for the temperature monitoring situation inside the integrated machine, thereby improving the lifespan and stability of the hyperconverged integrated machine.

[0135] Optionally, the temperature acquisition scheme for the hyperconverged appliance provided in this embodiment involves installing multiple temperature sensors inside the hyperconverged appliance to collect internal temperature data. The installation and arrangement of the temperature sensors need to consider the heat distribution and airflow characteristics inside the hyperconverged appliance to ensure the accuracy and representativeness of the collected temperature data. During normal operation of the components inside the hyperconverged appliance, the operating temperature of some components with temperature feedback functions can be collected in real time. The sensor location information and the location information of the component center point are both system-recorded values. These values ​​are combined with the temperatures collected by the temperature sensors and the temperatures collected by various components of the appliance to form comprehensive data. Each data point in the comprehensive data includes spatial location information and a temperature value. The integrated comprehensive data undergoes data processing, and obviously non-smooth and invalid data is removed according to the temperature time series.

[0136] Hyperconverged infrastructure spatial positioning, such as Figure 8As shown in (a) above, this is a hyperconverged appliance, where F represents the front of the hyperconverged appliance, B represents the rear of the hyperconverged appliance, L represents the left side of the hyperconverged appliance, and R represents the right side of the hyperconverged appliance. For example... Figure 8 As shown in (b), the hyperconverged appliance is placed within a three-dimensional coordinate system, where X represents the left-right space, Y represents the front-back space, and Z represents the top-bottom space. The front of the appliance is parallel to the X-axis, the right side is parallel to the Y-axis, and the height of the appliance is used as the Z-axis. T(x, y, z) represents the temperature of the hyperconverged appliance at the three-dimensional coordinate system (x, y, z).

[0137] Based on the temperature data collected by the hyperconverged system platform, combined with the real-time operating temperatures of temperature sensors (with spatial locations determined) and various components (with spatial locations based on the center point of the component), numerous three-dimensional discrete temperature points Tn(xn,yn,zn) are formed within the chassis of the hyperconverged appliance. Through all the three-dimensional discrete temperature points, combined with a specific 3D rendering model, a 3D thermal distribution map of the hyperconverged appliance is constructed, and red, green, blue, and alpha (RGBA) transparency values ​​are calculated based on the temperature values, such as red representing high temperature and blue representing low temperature.

[0138] Once the 3D thermal map of the hyperconverged appliance is completed, the temperature value at any location within the appliance's internal space can be queried using the 3D thermal map. For example, temperature data around peak points can be retrieved through the thermal map. If the temperature value is about to reach the maximum withstand temperature of the component corresponding to this location, a temperature alarm is generated on the hyperconverged platform, and the fan speed of the appliance is adjusted through the Baseboard Manager Controller (BMC) protocol to adjust the cooling strategy. If the temperature continues to rise and exceeds the maximum withstand temperature of the component, a protection strategy is activated. The hyperconverged platform generates a critical alarm and puts the appliance into maintenance mode, while simultaneously calling the BMC remote command to shut down the appliance for cooling.

[0139] As further illustrated, the optional example shown in the figure is a flowchart of a 3D thermal map design and temperature control processing scheme for a hyperconverged integrated machine provided in this embodiment. Its specific implementation method is as follows: Figure 9 As shown:

[0140] S902, for collecting temperature data from the hyperconverged infrastructure;

[0141] S904 is used for processing spatial and temperature data.

[0142] S906, construct a three-dimensional heat map model;

[0143] S908 executes the intelligent temperature control processing module to control the operating temperature of the hyperconverged all-in-one machine;

[0144] When the operating temperature inside the hyperconverged infrastructure exceeds the preset upper limit, the S910 will adjust its cooling strategy or shut down.

[0145] Optionally, in this embodiment, the temperature sensor and its spatial location information for the hyperconverged infrastructure are determined, and the location information of the components whose temperature needs to be acquired is determined. Then, a data acquisition module is configured to collect temperature data: collecting the temperature values ​​of the temperature sensors and the corresponding collection time, obtaining the normal operating temperature value of the components, and integrating the location information of each point to form time-based temperature key values ​​and location key values ​​data pairs. A 3D heat map is constructed: based on the time-based temperature key values ​​and location key values ​​data pairs, numerous discrete feature points are formed in a three-dimensional coordinate system, and combined with a specific formula, a 3D heat map is constructed and displayed as a wave graph, with relevant RGBA configured according to the temperature value. The internal temperature of the hyperconverged infrastructure is controlled through an intelligent temperature control processing module: an alarm function is configured to generate alarms of corresponding levels based on the heat map; a BMC calling module is configured to call BMC commands for heat dissipation regulation and the operation of turning the hyperconverged infrastructure on and off, etc.; the operating status of the hyperconverged infrastructure is tested through a testing system: the hyperconverged infrastructure operates normally, and the degree of construction of the temperature control system and the 3D heat map is tested to ensure that it can be displayed and that each component is monitored normally.

[0146] It should be noted that the installation location and number of temperature sensors need to be determined based on the specific situation of the hyperconverged appliance; the configuration of the data acquisition module needs to be determined based on the type and number of temperature sensors; and the configuration of the BMC calling module needs to be determined based on the type and version of the BMC. Traditional temperature control methods for hyperconverged appliances that only use sensors monitor the temperature values ​​at various locations within the appliance, which is a point-based approach and cannot generate continuous temperature prediction curves. This embodiment, through the 3D construction of the hyperconverged appliance's thermal map, forms a thermal wave diagram, providing a clearer and more intuitive understanding of the real-time temperature status inside the appliance. Temperature control measures are then implemented for temperature-sensitive components, improving component lifespan and enhancing the stability of the hyperconverged system by using a surface-based approach instead of point-based methods. Furthermore, unlike the traditional method of simply collecting temperature data using temperature sensors, this embodiment also collects the real-time operating temperature of each component through the appliance's BMC when collecting spatial temperature values, enriching the spatial distribution of temperature values ​​and improving the accuracy of the 3D thermal map construction.

[0147] Optionally, in this embodiment, a reasonable temperature collection module, a 3D model construction module, and a system intelligent processing module are designed. The temperature collection module collects temperature values ​​in real time through temperature sensors distributed throughout the hyperconverged appliance. Simultaneously, the hyperconverged system calls the appliance's BMC management system to collect the real-time operating temperatures of various components (network cards, disks, RAID cards, etc.), combining them to form a data pair based on time-series spatial location and corresponding temperature values. The 3D model building module, based on the collected temperature data and time reference, forms numerous key discrete feature points of a 3D heatmap and uses calculation formulas to draw the wave surface of the heatmap. It also dynamically calculates RGBA values ​​(red represents high temperature, blue represents low temperature) based on the temperature values, forming a 3D heatmap of the hyperconverged appliance's interior. The system's intelligent processing module intelligently monitors the temperature values ​​of each component under the current heatmap based on the maximum operating temperature that each component can withstand. After comparison, it activates corresponding protection strategies. If the temperature is too high but has not reached the critical value, it adjusts the cooling system (fan speed) to improve heat dissipation efficiency. If the overall temperature of the appliance or a key component exceeds the maximum temperature threshold, it automatically remotely calls BMC commands to shut down the appliance. Throughout the entire protection process, the hyperconverged platform generates alarm information of corresponding levels.

[0148] Through the embodiments of this application, a thermal wave map is formed by constructing a 3D thermal map of the hyperconverged all-in-one machine. The real-time temperature status inside the all-in-one machine can be understood more clearly and intuitively in a surface manner. Temperature control measures can be taken for temperature-sensitive components. The lifespan of components can be improved by replacing points with surfaces, and the stability of the hyperconverged system can be enhanced. Furthermore, the real-time operating temperature of each component is collected through the BMC of the all-in-one machine, which enriches the spatial distribution of its temperature values ​​and improves the accuracy of the 3D thermal map construction.

[0149] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0150] Based on this understanding, the technical solution of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0151] This embodiment also provides a temperature detection device for a hyperconverged infrastructure, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0152] Figure 10 This is a structural block diagram of a temperature detection device for a hyperconverged integrated machine according to an embodiment of this application, as shown below. Figure 10 As shown, it includes:

[0153] The first acquisition unit 1002 is used to acquire at least one first temperature data through at least one first temperature sensor configured in the hyper-converged all-in-one machine, wherein the first temperature data acquired by the first temperature sensor is used to indicate the temperature information of the configuration area where the first temperature sensor is located.

[0154] The second acquisition unit 1004 is used to acquire at least one second temperature data from at least one second temperature sensor in the hyperconverged appliance, wherein the second temperature sensor is configured in a functional component in the hyperconverged appliance, and the second temperature data is used to indicate the temperature information inside the matched functional component.

[0155] The first determining unit 1006 is used to determine a three-dimensional thermal map matching the hyperconverged appliance based on at least one first temperature data and at least one second temperature data. The three-dimensional thermal map is used to indicate temperature information at multiple locations in the internal space of the hyperconverged appliance.

[0156] The second determining unit 1008 is used to determine the working status description information that matches the hyper-converged integrated machine based on the three-dimensional heat map.

[0157] As an optional solution, the first determining unit 506 includes: a first determining module, configured to determine a first temperature information set based on at least one first temperature data, wherein the first temperature information set includes first temperature information of at least one first target point, and the first target point is located in a matching deployment area; a second determining module, configured to determine a second temperature information set based on at least one second temperature data, wherein the second temperature information set includes second temperature information of at least one second target point, and the second target point is located inside a matching functional component; a third determining module, configured to determine the union between the first temperature information set and the second temperature information set as a reference temperature information set; and a fourth determining module, configured to determine a three-dimensional thermal map matching the hyper-converged integrated machine based on the reference temperature information set.

[0158] As an optional solution, the fourth determining module includes: a first determining submodule, used to determine at least one discrete feature point in a three-dimensional coordinate system based on a set of reference temperature information, wherein the coordinate information of the discrete feature point is determined based on the position information of the target point in the set of target temperature information, and the value of the discrete feature point is determined based on the temperature information corresponding to the target point; a substitution submodule, used to substitute at least one discrete feature point into the model construction formula and determine the target mapping relationship based on the solution result, wherein the target mapping relationship is used to indicate the mapping relationship between position information and temperature information; a first obtaining submodule, used to obtain a set of target temperature information based on the target mapping relationship, wherein the set of target temperature information includes multiple positions in the internal space of the hyper-converged integrated machine and their corresponding temperature information; and a rendering submodule, used to perform color rendering in a three-dimensional coordinate system based on the color representation model and the set of target temperature information to obtain a three-dimensional heat map.

[0159] As an optional solution, the third determining module includes: a second determining submodule, used to determine a first weight set based on the location of at least one first temperature sensor before determining the union between the first temperature information set and the second temperature information set as the reference temperature information set, wherein the first weight set includes at least one weight matching the configuration location of the first temperature sensor; a third determining submodule, used to determine a second weight set based on the location of the functional component corresponding to at least one second temperature sensor, wherein the second weight set includes at least one weight matching the location of the functional component; and a summing submodule, used to perform a weighted summation of the multiple temperature information corresponding to the same third target point based on the first weight set and the second weight set when multiple temperature information corresponds to the same third target point in the union between the first temperature information set and the second temperature information set, to obtain the third temperature information corresponding to the third target point.

[0160] As an optional solution, the fourth determining module includes: a second acquisition submodule, used to acquire the configuration distribution characteristics of at least one first temperature sensor; a fourth determining submodule, used to determine a three-dimensional thermal map by interpolation results of a reference temperature information set when the configuration distribution characteristics indicate that the first temperature sensors are uniformly configured inside the hyperconverged appliance; a fifth determining submodule, used to determine a three-dimensional thermal map based on a heat conduction model and a reference temperature information set when the configuration distribution characteristics indicate that the configuration position of the first temperature sensor inside the hyperconverged appliance is related to the temperature distribution characteristics inside the hyperconverged appliance; and a sixth determining submodule, used to determine a three-dimensional thermal map by combining airflow data and a reference temperature information set when the configuration distribution characteristics indicate that the configuration position of the first temperature sensor inside the hyperconverged appliance is related to the airflow distribution characteristics inside the hyperconverged appliance, wherein the airflow data is used to represent the airflow direction and airflow velocity inside the hyperconverged appliance.

[0161] As an optional solution, the first determining unit 1006 includes: a first acquisition module, used to acquire a first temperature corresponding to the target area through a three-dimensional thermal map; a first sending module, used to send a first adjustment signal to the hyper-converged appliance when the first temperature meets the first temperature condition, wherein the first adjustment signal is used to adjust the heat dissipation strategy of the hyper-converged appliance; or, a second sending module, used to send a second adjustment signal to the hyper-converged appliance, wherein the second adjustment signal is used to adjust the operating voltage or frequency of the functional components corresponding to the target area; or, a third sending module, used to send a third adjustment signal to the hyper-converged appliance, wherein the third adjustment signal is used to adjust the flow rate and pressure of the liquid cooling system in the hyper-converged appliance; and a second acquisition module, used to acquire a second temperature corresponding to the target area.

[0162] As an optional solution, the second acquisition module includes: a first sending submodule, used to send a fourth adjustment signal to the hyperconverged appliance and display a first prompt message, wherein the fourth adjustment signal is used to shut down the functional component corresponding to the target area, and the first prompt message is used to indicate that the temperature of the target area exceeds a preset temperature threshold; a second sending submodule, used to send a fifth adjustment signal to the hyperconverged appliance and display a second prompt message, wherein the fifth adjustment signal is used to shut down the hyperconverged appliance, and the second prompt message is used to indicate that the hyperconverged appliance is in a sleep state; a third sending submodule, used to send a sixth adjustment signal to the hyperconverged appliance and display a third prompt message, wherein the sixth adjustment signal is used to migrate the target task being performed by the functional component corresponding to the target area to another functional component, and the third prompt message is used to indicate that the target task has been migrated to the target functional component.

[0163] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0164] For a description of the features of the temperature detection device in the embodiment of the hyperconverged infrastructure, please refer to the relevant description of the temperature detection method in the embodiment of the hyperconverged infrastructure, which will not be repeated here.

[0165] Embodiments of this application also provide an electronic device. Figure 11 This is a schematic diagram of an electronic device according to an embodiment of this application, such as... Figure 11 As shown, the electronic device includes a memory and a processor, the memory storing a computer program, and the processor being configured to run the computer program to perform the steps in any of the above embodiments of the temperature detection method for the hyperconverged integrated machine.

[0166] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0167] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0168] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above embodiments of the temperature detection method for hyperconverged integrated machines when running.

[0169] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0170] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0171] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the methods in various embodiments of this application; the computer program product further includes a non-volatile computer-readable storage medium storing the computer program, which, when executed by a processor, implements the steps of the temperature detection method for the hyperconverged integrated machine in various embodiments of this application.

[0172] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0173] The temperature detection method for a hyperconverged integrated machine provided in this application has been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A temperature detection method for a hyperconverged integrated machine, characterized in that, include: At least one first temperature data is acquired by at least one first temperature sensor configured in the hyperconverged appliance, wherein the first temperature data acquired by the first temperature sensor is used to indicate the temperature information of the configuration area where the first temperature sensor is located. At least one second temperature sensor in the hyperconverged appliance acquires at least one second temperature data, wherein the second temperature sensor is configured in a functional component of the hyperconverged appliance, and the second temperature data is used to indicate the temperature information inside the matched functional component; A three-dimensional thermal map matching the hyperconverged appliance is determined based on at least one first temperature data and at least one second temperature data, wherein the three-dimensional thermal map is used to indicate temperature information at multiple locations within the internal space of the hyperconverged appliance; Based on the three-dimensional heat map, determine the working status description information that matches the hyper-converged integrated machine.

2. The method according to claim 1, characterized in that, The step of determining a three-dimensional thermal map matching the hyperconverged integrated machine based on at least one first temperature data and at least one second temperature data includes: A first temperature information set is determined based on at least one of the first temperature data, wherein the first temperature information set includes first temperature information for at least one first target point, and the first target point is located in the configuration area that matches it; A second temperature information set is determined based on at least one of the second temperature data, wherein the second temperature information set includes second temperature information for at least one second target point, the second target point being located inside the functional component to which it is matched; The union of the first temperature information set and the second temperature information set is determined as the reference temperature information set; Based on the reference temperature information set, a three-dimensional thermal map matching the hyperconverged integrated machine is determined.

3. The method according to claim 2, characterized in that, The step of determining a three-dimensional thermal map matching the hyperconverged integrated machine based on the reference temperature information set includes: Based on a set of reference temperature information, at least one discrete feature point is determined in a three-dimensional coordinate system. The coordinate information of the discrete feature point is determined based on the position information of the target point in the set of target temperature information, and the value of the discrete feature point is determined based on the temperature information corresponding to the target point. The model is constructed by substituting at least one of the discrete feature points into the model, and the target mapping relationship is determined based on the solution results, wherein the target mapping relationship is used to indicate the mapping relationship between the location information and the temperature information; A target temperature information set is obtained based on the target mapping relationship, wherein the target temperature information set includes multiple locations in the internal space of the hyper-converged integrated machine and their corresponding temperature information; The color representation model and the target temperature information set are used to perform color rendering in the three-dimensional coordinate system to obtain the three-dimensional heat map.

4. The method according to claim 2, characterized in that, Before determining the union of the first temperature information set and the second temperature information set as the reference temperature information set, the method further includes: A first weight set is determined based on the location of at least one of the first temperature sensors, wherein the first weight set includes at least one weight that matches the configuration location of the first temperature sensor; A second weight set is determined based on the location of the functional component corresponding to at least one of the second temperature sensors, wherein the second weight set includes at least one weight that matches the location of the functional component; If, in the union of the first temperature information set and the second temperature information set, there are multiple temperature information sets corresponding to the same third target point, the multiple temperature information sets are weighted and summed based on the first weight set and the second weight set to obtain the third temperature information corresponding to the third target point.

5. The method according to claim 3, characterized in that, Based on the reference temperature information set, a three-dimensional thermal map matching the hyperconverged integrated machine is determined, including: Obtain the configuration distribution characteristics of at least one of the first temperature sensors; When the configuration distribution characteristics indicate that the first temperature sensor is uniformly configured inside the hyperconverged integrated machine, the three-dimensional thermal map is determined by the interpolation result of the reference temperature information set; When the configuration distribution characteristics indicate the configuration location of the first temperature sensor inside the hyperconverged appliance, and are related to the temperature distribution characteristics inside the hyperconverged appliance, the three-dimensional thermal map is determined based on the heat conduction model and the reference temperature information set. When the configuration distribution characteristics indicate the configuration location of the first temperature sensor inside the hyperconverged appliance, and are related to the airflow distribution characteristics inside the hyperconverged appliance, the three-dimensional thermal map is determined by combining the airflow data and the reference temperature information set, wherein the airflow data is used to represent the airflow direction and airflow velocity inside the hyperconverged appliance.

6. The method according to any one of claims 1 to 5, characterized in that, After determining a three-dimensional thermal map matching the hyperconverged infrastructure based on at least one first temperature data and at least one second temperature data, the method further includes: The first temperature corresponding to the target area is obtained through the three-dimensional thermal map; If the first temperature meets the first temperature condition, a first adjustment signal is sent to the hyperconverged appliance, wherein the first adjustment signal is used to adjust the heat dissipation strategy of the hyperconverged appliance; or, A second adjustment signal is sent to the hyper-converged infrastructure, wherein the second adjustment signal is used to adjust the operating voltage or frequency of the functional component corresponding to the target area; or, A third adjustment signal is sent to the hyperconverged appliance, wherein the third adjustment signal is used to adjust the flow rate and pressure of the liquid cooling system in the hyperconverged appliance; Obtain the second temperature corresponding to the target area.

7. The method according to claim 6, characterized in that, If the second temperature satisfies the second temperature condition, the method further includes at least one of the following: The fourth adjustment signal is sent to the hyper-converged all-in-one machine, and the first prompt message is displayed. The fourth adjustment signal is used to turn off the functional components corresponding to the target area, and the first prompt message is used to indicate that the temperature of the target area exceeds a preset temperature threshold. The fifth adjustment signal is sent to the hyperconverged appliance, and the second prompt message is displayed. The fifth adjustment signal is used to shut down the hyperconverged appliance, and the second prompt message is used to indicate that the hyperconverged appliance is in a dormant state. The sixth adjustment signal is sent to the hyper-converged appliance, and a third prompt message is displayed. The sixth adjustment signal is used to migrate the target task being performed by the functional component corresponding to the target area to other functional components, and the third prompt message is used to indicate that the target task has been migrated to the target functional component.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the temperature detection method for the hyperconverged integrated machine as described in any one of claims 1 to 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, it implements the steps of the temperature detection method for the hyperconverged integrated machine as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the temperature detection method for the hyperconverged integrated machine as described in any one of claims 1 to 7.

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