A temperature rise early warning monitoring method and system suitable for a data center room and a medium

Abstract

This invention discloses a method, system, and medium for temperature rise early warning monitoring in data center computer rooms. The method includes: setting the server or rack to be monitored; acquiring the indicator data of the server or rack at time t; predicting the temperature rise ΔT of the server or rack using a temperature rise early warning model; comparing T+ΔT with a temperature threshold T′ and adjusting the terminal cooling capacity; where T is the temperature of the server at time t; and acquiring the indicator data of the server or rack at time t+1 and performing prediction and adjustment. This invention quickly locates servers that may generate hotspots based on early warning monitoring parameters, enabling precise early cooling supply and improving cooling capacity utilization efficiency. It can accurately, quickly, and effectively prevent local hotspots in the computer room, maximizing the utilization of the air conditioning system's cooling capacity. Compared with existing air conditioning systems, it can further improve the energy efficiency of the air conditioning terminal system. Furthermore, it provides a theoretical basis for the cooling capacity allocation of the air conditioning terminal system.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of temperature rise prediction, and particularly relates to a temperature rise early warning monitoring method and system suitable for a data center room and a medium. BACKGROUND

[0002] The rapid development of the information technology industry leads to exponential explosive growth of data, and servers for processing data are gradually upgraded to high-performance computers. However, high-performance computers are prone to local temperature hotspots, which reduces the reliability, durability and cooling efficiency of the server, consumes a large amount of energy, and increases the energy cost of users and enterprises.

[0003] At present, the industry often uses temperature sensors to monitor whether the server produces a local hotspot. If the temperature point is higher than the temperature monitoring threshold, the frequency of the end air cabinet is increased to increase the cooling capacity. However, this general method has a lag in eliminating hot spots after the hot spot appears, which not only has a large safety hazard, but also easily leads to repeated frequency increase and decrease of the end air cabinet, resulting in a large waste of energy, which is a pain point and problem in the data center industry. SUMMARY

[0004] The main purpose of the present application is to overcome the shortcomings and deficiencies of the prior art, and to provide a temperature rise early warning monitoring method and system suitable for a data center room and a medium, which can accurately and quickly predict the temperature rise of the server, provide a theoretical basis for the advance control of the cooling capacity of the air conditioning system, and reduce the time lag of the control system. On the premise of ensuring the safety of the room, energy saving is maximized.

[0005] In order to achieve the above purpose, the following technical solutions are adopted in the present application:

[0006] In one aspect of the present application, a temperature rise early warning monitoring method suitable for a data center room is provided, which comprises the following steps:

[0007] Setting a monitored server or cabinet;

[0008] Obtaining the temperature rise early warning model of the monitored server or cabinet; t time index data;

[0009] Predicting the temperature rise of the monitored server or cabinet using the temperature rise early warning model T ;

[0010] Comparing T+ Δ T with the temperature threshold T’ , and controlling the end cooling capacity; wherein T is the outlet temperature of the server or cabinet t at the moment;

[0011] Obtaining the temperature rise early warning model of the monitored server or cabinet;t+ The steps of using time-indicator data for prediction and regulation.

[0012] As a preferred technical solution, the setting of the monitored server or cabinet specifically includes:

[0013] Pressure and speed sensors are installed on both the air intake and exhaust sides of the servers or racks in the data center, and a temperature sensor is installed on the air exhaust side of the servers or racks.

[0014] As a preferred technical solution, the acquisition of the monitored server or cabinet... t The specific time-based indicator data is as follows:

[0015] Obtain the geometric feature parameters of the monitored server a , b , l , A Server operating power consumption Q a Total pressure of internal fans in the server P fan Server inlet airflow velocity V in Outlet airflow velocity V out Server entry pressure P in Server outbound pressure P out and servers or racks t Exit temperature at time T .

[0016] As a preferred technical solution, the temperature rise early warning model includes a laminar flow temperature rise early warning model and a turbulent flow temperature rise early warning model. The temperature rise early warning model is used to predict the temperature rise Δ of the monitored server or cabinet. T Specifically:

[0017] Calculate ∆ P j = P in - P out and ,in, This refers to the pressure at the rack entrance. The pressure at the rack exit; V in The airflow velocity of the cold air at the rack entrance. V out The hot airflow velocity at the rack exit; p air density;

[0018] Assuming laminar airflow, calculate the average airflow velocity through the server based on the airflow equation for the rack server. V ;

[0019] According to the formula calculate Re ,in p is the dynamic viscosity coefficient of the fluid. D h The hydraulic diameter; determining the laminar flow state. Re Is 1 greater than 2000? Re If 1 < 2000, then ∆ is calculated according to the laminar flow temperature rise early warning model. T And output the results;

[0020] like Re If 1 > 2000, then assume the airflow is turbulent; calculate the average airflow velocity through the server based on the airflow equation for the rack server. V ;

[0021] According to the formula Recalculate under turbulent conditions Re 2. Judgment Re Is 2 greater than 4000? Re If 2 > 4000, then ∆ is calculated according to the turbulent temperature rise early warning model. T And output the result; such as 2000< Re If 2 < 4000, then estimate ∆ using interpolation. T And output the results.

[0022] As a preferred technical solution, the airflow equation for the rack server is:

[0023] ;

[0024] The temperature rise early warning model is specifically as follows:

[0025] ;

[0026] ;

[0027] in, n and m For model parameters, n =1 m =1 indicates a laminar flow temperature rise early warning model. n =2 m =1.75 indicates a turbulent temperature rise early warning model; a , b , l , A For the geometric feature parameters of the server; ∆ Pj = P in - P out , This refers to the pressure at the rack entrance. The pressure at the rack exit; V in The airflow velocity of the cold air at the rack entrance. V out The hot airflow velocity at the rack exit; p air density; ; , k in , k out These are the resistance loss coefficients at the server's entrance and exit points, respectively. , This represents the average power consumption of the rack-mounted servers. c p For the heat capacity of air, V The average airflow velocity through the server; A For the server opening flow area; ; P fan Provides the server's cooling fans with total pressure to overcome the internal resistance of the server.

[0028] As a preferred technical solution, the above-mentioned... T+ ∆ T With temperature threshold T’ The comparison is performed, and the terminal cooling capacity is adjusted accordingly, specifically as follows:

[0029] like T+ ∆ T > T' , T For servers or racks t The outlet temperature at any given time is used to determine whether the frequency of the terminal air handling unit has reached the upper limit of the air handling unit frequency. If not, the frequency of the terminal air handling unit is increased; otherwise, the opening of the proportional integral valve is increased to increase the cooling capacity.

[0030] like T+ ∆ T < T'- 1. Determine if the opening of the proportional-integral valve is equal to the lower limit opening. If not, reduce the opening of the proportional-integral valve of the terminal air handling unit; otherwise, reduce the frequency of the terminal air handling unit to reduce the cooling capacity.

[0031] like T’ - 1 <T+ ∆ T < T' Then the cooling capacity at the terminal remains unchanged.

[0032] Another aspect of the present invention provides a temperature rise early warning and monitoring system suitable for data center computer rooms, applied to the above-mentioned temperature rise early warning and monitoring method suitable for data center computer rooms, including a preprocessing module, a data acquisition module, a temperature rise prediction module, and a cooling capacity control module.

[0033] The preprocessing module is used to configure the server or cabinet being monitored.

[0034] The data acquisition module is used to acquire data from the monitored server or rack. t Time-based indicator data;

[0035] The temperature rise prediction module is used to predict the temperature rise ∆ of the monitored server or cabinet based on the temperature rise early warning model. T ;

[0036] The cooling capacity control module is used to... T+ ∆ T With temperature threshold T’ Compare and adjust the terminal cooling capacity; among which T For servers or racks t The exit temperature at that moment;

[0037] After the cooling capacity control module adjusts the cooling capacity at the terminal, the data acquisition module re-acquires the data of the monitored server or cabinet. t+ The system uses real-time indicator data and iteratively predicts and regulates the data.

[0038] In another aspect, the present invention provides a storage medium storing a program that, when executed by a processor, implements the above-described temperature rise early warning and monitoring method applicable to data center computer rooms.

[0039] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0040] (1) In order to accurately, quickly and effectively avoid the generation of local hot spots in the computer room and maximize the use of the cooling capacity of the air conditioning system, this invention proposes a temperature rise early warning and monitoring method suitable for the computer room environment of the data center. It can quickly locate the hot spot location based on the early warning monitoring parameters, realize accurate cooling supply in advance, and improve the cooling capacity utilization efficiency.

[0041] (2) A temperature rise prediction algorithm for data center computer room environment is proposed, which can provide a theoretical basis for the cooling capacity allocation of air conditioning terminal system. Compared with the operation of existing air conditioning system, hot spots can be eliminated in advance, further improving the operating energy efficiency of air conditioning terminal system. Attached Figure Description

[0042] Figure 1 This is a flowchart of a temperature rise early warning and monitoring method applicable to data center computer rooms according to an embodiment of the present invention;

[0043] Figure 2 This is a floor plan of the air supply system of the machine room according to an embodiment of the present invention;

[0044] Figure 3 This is a floor plan of the air supply system of the machine room according to an embodiment of the present invention.

[0045] Figure 4 This is a sensor layout plan of a data center server according to an embodiment of the present invention;

[0046] Figure 5 This is a flowchart of the data center temperature rise early warning algorithm according to an embodiment of the present invention;

[0047] Figure 6 This is a schematic diagram of the structure of a temperature rise early warning and monitoring system suitable for data center computer rooms according to an embodiment of the present invention;

[0048] Figure 7 This is a schematic diagram of the structure of the storage medium according to an embodiment of the present invention. Detailed Implementation

[0049] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort are within the scope of protection of the present application.

[0050] Example 1:

[0051] like Figure 1 As shown, this embodiment provides a temperature rise early warning monitoring method suitable for data center computer rooms. Its automatic temperature rise early warning control logic includes the following steps:

[0052] S1. Set up monitoring targets near the server rack. This invention is applicable not only to air supply room but also to air supply room. The monitoring location diagram is as follows. Figure 2 , Figure 3 As shown; Figure 4 As shown, pressure sensors and speed sensors are installed at both ends of the server in the data center rack, and a temperature sensor is installed at the end of the server's cold airflow.

[0053] Obtain the geometric feature parameters of the monitored server a , b , l , A Server operating power consumption Q a Total pressure of internal fans in the server P fan Server inlet airflow velocityV in Outlet airflow velocity V out Server entry pressure P in Server outbound pressure P out and servers or racks t Exit temperature at time T ;

[0054] S2. Use a server temperature rise early warning algorithm to predict the temperature rise ∆ of the monitored server or cabinet. T ;

[0055] Furthermore, in step S2, such as Figure 5 As shown, the server temperature rise early warning algorithm is used to predict the temperature rise ∆ of the monitored server or cabinet. T Specifically:

[0056] Calculate ∆ P j = P in - P out and ,in, This refers to the pressure at the rack entrance. The pressure at the rack exit; V in The airflow velocity of the cold air at the rack entrance. V out The hot airflow velocity at the rack exit; p air density;

[0057] Assuming laminar airflow, calculate the average airflow velocity through the server based on the airflow equation for the rack server. V ;

[0058] According to the formula calculate Re ,in p is the dynamic viscosity coefficient of the fluid. D h The hydraulic diameter; determining the laminar flow state. Re Is 1 greater than 2000? Re If 1 < 2000, then ∆ is calculated according to the laminar flow temperature rise early warning model. T And output the results;

[0059] like Re If 1 > 2000, then assume the airflow is turbulent; calculate the average airflow velocity through the server based on the airflow equation for the rack server. V ;

[0060] According to the formula Recalculate under turbulent conditions Re 2. Judgment Re Is 2 greater than 4000? Re If 2 > 4000, then ∆ is calculated according to the turbulent temperature rise early warning model. T And output the result; such as 2000< Re If 2 < 4000, then estimate ∆ using interpolation. T And output the results.

[0061] Furthermore, the derivation process of the airflow equation and temperature rise early warning model for the rack server is as follows:

[0062] According to the airflow mechanism, we know that:

[0063] ;

[0064] in, , indicates the pressure at the rack entrance, in Pa;

[0065] p The air density in this embodiment is 1.1685. ;

[0066] V in The airflow velocity of the cold air at the rack entrance, m / s;

[0067] , indicates the pressure at the cabinet outlet, in Pa;

[0068] V out The hot air velocity at the rack outlet, m / s;

[0069] This represents the sum of resistance encountered by the cold airflow as it passes through the server;

[0070] This indicates the local resistance loss at the inlet. k in It is the resistance loss coefficient at the server entry point, in this embodiment k in =0.5, V It is based on the average airflow speed of the server;

[0071] This indicates localized resistance loss at the export point. k out It is the resistance loss coefficient at the server entry point, in this embodiment k out =1, VThis represents the average airflow velocity through the server;

[0072] This represents the friction loss along the server's internal layered structure.

[0073] l It is the server length;

[0074] l This is the friction factor; if the fluid is in a laminar flow state, then... If the fluid is in a turbulent state, then , , p It is the dynamic viscosity coefficient of the fluid, in this invention ;

[0075] , indicating the hydraulic diameter;

[0076] P fan The server's cooling fan provides total pressure to overcome the server's internal resistance, Pa;

[0077] The airflow equation under laminar flow conditions is derived as follows:

[0078] ;

[0079] The airflow flow rate equation under turbulent conditions is derived as follows:

[0080] ;

[0081] Assumption:

[0082] ;

[0083] ;

[0084] ;

[0085] ;

[0086] ;

[0087] Therefore, the airflow equation for a rack server is:

[0088] ;

[0089] in n and m For model parameters, n =1 m =1 indicates a laminar flow temperature rise early warning model. n =2m =1.75 indicates a turbulence model;

[0090] According to the principle of energy conservation in server rack airflow, we know that:

[0091] ;

[0092] in, Q a This represents the average power consumption of the rack-mounted servers, expressed in kW. c p This represents the heat capacity of air, which is taken as 1.00065 kJ / kg / K in this invention; A The flow area of ​​the server opening is represented in meters. 2 ;

[0093] Assumption:

[0094] ;

[0095] ;

[0096] The mathematical representation of the temperature rise warning model for rack servers is derived as follows:

[0097] ;

[0098] S3, Prediction T+ ∆ T With temperature threshold T’ Compare and adjust the terminal cooling capacity; among which T For servers or racks t The exit temperature at that moment;

[0099] (1) If T+ ∆ T > T' If the frequency of the terminal air handling unit reaches the upper limit of the air handling unit frequency, then the frequency of the terminal air handling unit is increased; otherwise, the opening of the proportional integral valve is increased to increase the cooling capacity.

[0100] (2) If T+ ∆ T < T'- 1. Determine if the opening of the proportional-integral valve is equal to the lower limit opening. If not, reduce the opening of the proportional-integral valve of the terminal air handling unit; otherwise, reduce the frequency of the terminal air handling unit to reduce the cooling capacity.

[0101] (3) If T’ - 1 <T+ ∆ T < T' Then the cooling capacity at the terminal remains unchanged.

[0102] S4. Return to step S2 and reacquire the monitored server's data. t+ The indicator data at time 1 is used for cyclical prediction and control in step S3.

[0103] Example 2:

[0104] In this embodiment, a specific implementation of the present invention is illustrated using a server as an example, and the technical solution in Embodiment 1 is clearly and completely described:

[0105] (1) Obtaining parameters of the monitored objects and installing monitoring facilities:

[0106] Build an automated control system;

[0107] Temperature sensors, pressure sensors, and speed sensors are installed at the server entrance, and pressure sensors and speed sensors are installed at the server exit.

[0108] Install frequency converters on terminal air handling units;

[0109] Obtain characteristic parameters of the server such as length, width, height, and internal fan pressure;

[0110] (2) Predict server temperature points:

[0111] Obtain the monitoring parameters at time t;

[0112] Incorporate monitoring information into the mathematical model of server temperature rise in the rack. ;

[0113] The system according to Figure 5 The calculation process predicts ∆ T ;

[0114] like T+ ∆ T > T' If the frequency of the terminal air handling unit reaches the upper limit of the air handling unit frequency, then the frequency of the terminal air handling unit is increased; otherwise, the opening of the proportional integral valve is increased to increase the cooling capacity.

[0115] like T+ ∆ T < T'- 1. Determine if the opening of the proportional-integral valve is equal to the lower limit opening. If not, reduce the opening of the proportional-integral valve of the terminal air handling unit; otherwise, reduce the frequency of the terminal air handling unit to reduce the cooling capacity.

[0116] like T’ - 1 <T+ ∆ T < T' Then the cooling capacity at the terminal remains unchanged.

[0117] Example 3:

[0118] like Figure 6 As shown in this embodiment, a temperature rise early warning and monitoring system suitable for data center computer rooms is provided. The system includes a preprocessing module, a data acquisition module, a temperature rise prediction module, and a cooling capacity control module.

[0119] The preprocessing module is used to configure the server or cabinet being monitored.

[0120] The data acquisition module is used to acquire data from the monitored server or rack. t Time-based indicator data;

[0121] The temperature rise prediction module is used to predict the temperature rise ∆ of the monitored server or cabinet based on the temperature rise early warning model. T ;

[0122] The cooling capacity control module is used to... T+ ∆ T With temperature threshold T’ Compare and adjust the terminal cooling capacity; among which T For servers or racks t The exit temperature at that moment;

[0123] After the cooling capacity control module adjusts the cooling capacity at the terminal, the data acquisition module re-acquires the data of the monitored server or cabinet. t+ The system uses real-time indicator data and iteratively predicts and regulates the data.

[0124] It should be noted that the system provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure can be divided into different functional modules to complete all or part of the functions described above. This system is a temperature rise early warning and monitoring method for data center computer rooms applied to Embodiments 1 and 2.

[0125] Example 4:

[0126] like Figure 7 As shown, in this embodiment, a storage medium is also provided, storing a program. When the program is executed by a processor, it implements a temperature rise early warning and monitoring method suitable for data center computer rooms, as described in Embodiments 1 and 2. Specifically:

[0127] Configure the server or rack to be monitored;

[0128] Obtain the monitored server or rack t Time-based indicator data;

[0129] A temperature rise early warning model is used to predict the temperature rise ∆ of the monitored server or cabinet. T ;

[0130] Will T+ ∆ T With temperature threshold T’ Compare and adjust the terminal cooling capacity; among which T For servers or racks tThe exit temperature at that moment;

[0131] Obtain the monitored server or rack t+ The steps of using time-indicator data for prediction and regulation.

[0132] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0133] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for temperature rise early warning and monitoring applicable to data center computer rooms, characterized in that, Includes the following steps: Configure the server or rack to be monitored; Obtain the monitored server or rack t Time-based indicator data; A temperature rise early warning model is used to predict the temperature rise ∆ of the monitored server or cabinet. T The temperature rise early warning model includes a laminar flow temperature rise early warning model and a turbulent flow temperature rise early warning model. The temperature rise early warning model is used to predict the temperature rise ∆ of the monitored server or cabinet. T Specifically: Calculate ∆ P j = P in - P out and ,in, This refers to the pressure at the rack entrance. The pressure at the rack exit; V in The airflow velocity of the cold air at the rack entrance. V out The hot airflow velocity at the rack exit; ρ air density; Assuming laminar airflow, calculate the average airflow velocity through the server based on the airflow equation for the rack server. V ; According to the formula calculate Re ,in μ is the dynamic viscosity coefficient of the fluid. D h The hydraulic diameter; determining the laminar flow state. Re Is 1 greater than 2000? Re If 1 < 2000, then ∆ is calculated according to the laminar flow temperature rise early warning model. T And output the results; like Re If 1 > 2000, then assume the airflow is turbulent; calculate the average airflow velocity through the server based on the airflow equation for the rack server. V ; According to the formula Recalculate under turbulent conditions Re 2. Judgment Re Is 2 greater than 4000? Re If 2 > 4000, then ∆ is calculated according to the turbulent temperature rise early warning model. T And output the result; such as 2000< Re If 2 < 4000, then estimate ∆ using interpolation. T And output the results; The airflow equation for the rack server is: ； The temperature rise early warning model is specifically as follows: ； ； in, n and m For model parameters, n =1 m =1 indicates a laminar flow temperature rise early warning model. n =2 m =1.75 indicates a turbulent temperature rise early warning model; a , b , l , A For the geometric feature parameters of the server; ∆ P j = P in - P out , This refers to the pressure at the rack entrance. The pressure at the rack exit; V in The airflow velocity of the cold air at the rack entrance. V out The hot airflow velocity at the rack exit; ρ air density; ; , k in , k out These are the resistance loss coefficients at the server's entrance and exit points, respectively. , This represents the average power consumption of the rack-mounted servers. c p For the heat capacity of air, V The average airflow velocity through the server; A For the server opening flow area; ; P fan Provides the server's cooling fans with the total pressure needed to overcome the internal resistance of the server; Will T+ ∆ T With temperature threshold T’ Compare and adjust the terminal cooling capacity; among which T For servers or racks t The exit temperature at that moment; The steps to obtain the t+1 time-time indicator data of the monitored server or cabinet and perform prediction and control.

2. The temperature rise early warning and monitoring method for data center computer rooms according to claim 1, characterized in that, The specific settings for the monitored server or rack are as follows: Pressure and speed sensors are installed on both the air intake and exhaust sides of the servers or racks in the data center, and a temperature sensor is installed on the air exhaust side of the servers or racks.

3. The temperature rise early warning and monitoring method for data center computer rooms according to claim 1, characterized in that, The acquisition of the time-t indicator data of the monitored server or cabinet specifically involves: Obtain the geometric feature parameters of the monitored server a , b , l , A , A This represents the flow area of ​​the server opening. l This refers to the server length; the server's operating power consumption. Q a Total pressure of internal fans in the server P fan Server inlet airflow velocity V in Outlet airflow velocity V out Server entry pressure P in Server outbound pressure P out and servers or racks t Exit temperature at time T .

4. The temperature rise early warning and monitoring method for data center computer rooms according to claim 1, characterized in that, The T+ ∆ T With temperature threshold T’ The comparison is performed, and the terminal cooling capacity is adjusted accordingly, specifically as follows: like T+ ∆ T>T' , T For servers or racks t The outlet temperature at any given time is used to determine whether the frequency of the terminal air handling unit has reached the upper limit of the air handling unit frequency. If not, the frequency of the terminal air handling unit is increased; otherwise, the opening of the proportional integral valve is increased to increase the cooling capacity. like T+ ∆ T <T’- 1. Determine if the opening of the proportional-integral valve is equal to the lower limit opening. If not, reduce the opening of the proportional-integral valve of the terminal air handling unit; otherwise, reduce the frequency of the terminal air handling unit to reduce the cooling capacity. like T’ - 1 <T+ ∆ T <T’ Then the cooling capacity at the terminal remains unchanged.

5. A temperature rise early warning and monitoring system suitable for data center computer rooms, characterized in that, The temperature rise early warning and monitoring method for data center computer rooms, applicable to any one of claims 1-4, includes a preprocessing module, a data acquisition module, a temperature rise prediction module, and a cooling capacity control module; The preprocessing module is used to configure the server or cabinet being monitored. The data acquisition module is used to acquire data from the monitored server or rack. t Time-based indicator data; The temperature rise prediction module is used to predict the temperature rise ∆ of the monitored server or cabinet based on the temperature rise early warning model. T ; The cooling capacity control module is used to... T+ ∆ T With temperature threshold T’ Compare and adjust the terminal cooling capacity; among which T For servers or racks t The exit temperature at that moment; After the cooling capacity control module adjusts the cooling capacity at the terminal, the data acquisition module re-acquires the data of the monitored server or cabinet. t+ The system uses real-time indicator data and iteratively predicts and regulates the data.

6. A storage medium storing a program, characterized in that: When the program is executed by the processor, it implements the temperature rise early warning and monitoring method for data center computer rooms as described in any one of claims 1-4.

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