Machine room resource planning method and device, electronic equipment and storage medium

Abstract

The application provides a machine room resource planning method and device, electronic equipment and a storage medium. The average machine room wireless user number and user flow usage data of a to-be-planned integrated area are acquired. The flow prediction result of the to-be-planned integrated area is generated according to the average wireless user number and the user flow usage data. The machine room resource planning scheme of the to-be-planned integrated area is generated according to the flow prediction result. The to-be-planned integrated area is planned according to the machine room resource planning scheme. The application predicts the flow usage of the to-be-planned integrated area according to the average machine room wireless user number and the user flow usage data of the to-be-planned integrated area, and then plans the machine room resource of the to-be-planned integrated area according to the prediction result, thereby effectively planning and constructing the machine room.

Description

Technical Field

[0001] This invention relates to the field of resource scheduling technology, and in particular to a method, apparatus, electronic device and storage medium for planning data center resources. Background Technology

[0002] Data centers generally refer to places where telecommunications companies, China Netcom, China Mobile, dual-line providers, power companies, and government or enterprise entities provide IT services to users and employees. The servers in data centers run many services, such as mobile MMS, SMS, and voice services. Data centers are very important; without them, work and life would be greatly affected.

[0003] The challenge facing operators is how to transform the existing communication equipment rooms and equipment in order to make full use of existing resources while gradually transforming traditional networks into new SDN / NFV networks.

[0004] In conclusion, the problems existing in the data center reconstruction urgently need to be solved. Summary of the Invention

[0005] This invention provides a method, apparatus, electronic device, and storage medium for planning data center resources, so as to effectively plan and construct data centers.

[0006] This invention provides a method for planning data center resources, comprising:

[0007] Obtain the average number of wireless users in the data center and user traffic usage data of the integrated area to be planned;

[0008] Based on the average number of wireless users and the user traffic usage data, generate the traffic prediction results for the comprehensive area to be planned;

[0009] Based on the traffic prediction results, a data center resource planning scheme for the comprehensive area to be planned is generated;

[0010] Resource planning is carried out on the comprehensive area to be planned according to the data center resource planning scheme.

[0011] According to a method for planning data center resources provided by the present invention, the average number of wireless users in the data center of the comprehensive area to be planned is obtained through the following steps:

[0012] Obtain the number of resident wireless users and the number of aggregation equipment rooms in the planned integrated area;

[0013] The average number of wireless users per computer room in the planned integrated area is calculated based on the number of permanent wireless users in the integrated area and the number of data centers in the integrated area.

[0014] According to a data center resource planning method provided by the present invention, the user traffic usage data includes user activity, bandwidth consumption, and the amount of data generated by users.

[0015] According to a method for planning data center resources provided by the present invention, based on the average number of wireless users and the user traffic usage data, a traffic prediction result for the comprehensive area to be planned is generated, specifically including:

[0016] The user activity level, bandwidth consumption, and user-generated data volume are input into a pre-built user traffic prediction model to obtain user traffic prediction data.

[0017] Based on the average number of wireless users and the user traffic prediction data, the traffic prediction result for the planned integrated area is obtained.

[0018] According to a data center resource planning method provided by the present invention, a data center resource planning scheme for the area to be planned is generated based on the traffic prediction results, specifically including:

[0019] If the traffic prediction result is higher than the first prediction threshold, a planning scheme to increase data center resources is generated.

[0020] If the traffic prediction result is lower than the second prediction threshold, a planning scheme for merging data center resources is generated.

[0021] Wherein, the first prediction threshold is greater than the second prediction threshold.

[0022] According to a data center resource planning method provided by the present invention, after generating a data center resource planning scheme for the area to be planned based on the traffic prediction results, the method further includes:

[0023] Obtain the computer room operation data of the comprehensive area to be planned;

[0024] Based on the data center operation data, abnormal operation data was filtered out;

[0025] Based on the abnormal operation data, the target faulty computer room was identified;

[0026] Generate maintenance notification information corresponding to the target faulty computer room.

[0027] The present invention also provides a planning device for data center resources, comprising:

[0028] The data acquisition unit is used to acquire the average number of wireless users in the computer room and user traffic usage data of the integrated area to be planned;

[0029] A traffic prediction unit is used to generate a traffic prediction result for the comprehensive area to be planned based on the average number of wireless users and the user traffic usage data.

[0030] The scheme generation unit is used to generate a data center resource planning scheme for the comprehensive area to be planned based on the traffic prediction results.

[0031] The resource planning unit is used to perform resource planning for the comprehensive area to be planned according to the data center resource planning scheme.

[0032] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the data center resource planning method described above.

[0033] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the data center resource planning method as described above.

[0034] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the data center resource planning method as described above.

[0035] This invention provides a method, apparatus, electronic device, and storage medium for planning data center resources. The method involves acquiring the average number of wireless users and user traffic usage data for a planned integrated area; generating a traffic prediction result for the planned integrated area based on the average number of wireless users and the user traffic usage data; generating a data center resource planning scheme for the planned integrated area based on the traffic prediction result; and performing resource planning for the planned integrated area based on the data center resource planning scheme. This invention effectively plans and constructs data centers by predicting traffic usage in the planned integrated area based on the average number of wireless users and user traffic usage data, and then performing data center resource planning based on the prediction results. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0037] Figure 1 This is a flowchart illustrating the data center resource planning method provided by the present invention;

[0038] Figure 2 This is a schematic diagram of the structure of the data center resource planning device provided by the present invention;

[0039] Figure 3This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0041] To address the problems existing in the prior art, this invention proposes a method for planning data center resources to effectively plan data center resources. The method includes:

[0042] Step 110: Obtain the average number of wireless users in the data center and user traffic usage data of the comprehensive area to be planned.

[0043] In step 110, the comprehensive area, also known as the integrated zone, refers to the target comprehensive area that needs to be planned. The division of a comprehensive area is based on certain planning and considerations, dividing a region according to specific standards and objectives to achieve effective management and development. Specific methods for dividing comprehensive areas can vary depending on the specific circumstances and objectives. The following are common division steps:

[0044] Determine the purpose of the division: First, it is necessary to clarify the purpose and needs of dividing the comprehensive area, such as urban planning, economic development, environmental protection, and resource management. Clarifying the purpose will help determine the basis and standards for the division.

[0045] Collect basic data: Collect relevant basic data, including data on geography, economy, population, environment, resources, etc. This data will provide a basis and support for the division.

[0046] Determine the classification criteria: Based on the purpose of the classification and the basic data collected, determine the classification criteria and indicators. For example, factors such as population density, economic development level, land use type, and ecological environment status can be considered as the basis for classification.

[0047] Classification Methods: Based on the established standards and indicators, select a suitable classification method. Common methods include the analytic hierarchy process (AHP), cluster analysis, spatial interpolation, and expert evaluation. The specific method chosen should be weighed against the actual situation and objectives.

[0048] Boundary delineation: The boundary is determined based on the selected delineation method and standards. Boundary delineation can be based on spatial analysis, expert judgment, model calculation, etc.

[0049] Evaluation and Adjustment: After the division is completed, the results are evaluated, and adjustments and optimizations are made as needed. The evaluation can be based on the degree of achievement of the division objectives, feasibility, fairness, and other aspects.

[0050] It should be noted that delineating integrated zones is a complex task that requires comprehensive consideration of multiple factors and the needs of stakeholders.

[0051] The number of wireless users in a data center refers to the number of wireless users served by a single data center, while the average number of wireless users in a data center refers to the average number of wireless users served by each data center within a certain area. This average number is obtained by dividing the total number of wireless users within a certain area by the total number of data centers within that area.

[0052] User traffic usage data is used to characterize user data usage. By analyzing user traffic usage data, we can understand users' data usage habits and thus predict their future data usage. Generally, user traffic usage data includes data such as user activity, bandwidth consumption, data volume estimates, and seasonal and trend changes.

[0053] Step 120: Generate the traffic prediction result of the area to be planned based on the average number of wireless users and the user traffic usage data.

[0054] In step 120, a traffic prediction result for the planned integrated service area needs to be generated based on the average number of wireless users and the user traffic usage data. During the prediction process, a targeted machine learning model can be modeled and trained to predict traffic results, outputting the traffic usage of all wireless users within a certain area over a certain period, i.e., the traffic prediction result for the planned integrated service area. Specifically, data analysis tools and techniques, such as time series analysis, regression analysis, and machine learning, can be used to model and predict historical data. These tools can help discover hidden patterns and correlations and generate traffic prediction models.

[0055] Step 130: Based on the traffic prediction results, generate a data center resource planning scheme for the comprehensive area to be planned.

[0056] In step 130, generating a data center planning scheme based on the traffic forecast results ensures that the data center can meet future traffic demands. Since the data center planning scheme is generated based on the traffic forecast results, it's understood that the more aspects the traffic forecast results cover, the more effective the planning scheme will be. For example, when the traffic forecast results include data such as user activity, bandwidth consumption, and the amount of data generated by users, the planning scheme can include:

[0057] Bandwidth planning: Based on projected traffic demand, assess whether current bandwidth capacity is sufficient to support future traffic. If traffic projections exceed existing bandwidth limitations, consider increasing bandwidth capacity by working with network service providers to upgrade network connectivity.

[0058] Hardware planning: Based on the predicted traffic demand, assess whether the current server, storage, and network equipment is sufficient to handle future traffic loads. If the predicted traffic exceeds the capacity of the existing equipment, consider increasing the number of devices, upgrading equipment performance, or introducing more efficient equipment.

[0059] Network architecture planning: Based on traffic prediction results, reassess the data center's network architecture. Consider factors such as network topology, switch layout, and router configuration to optimize traffic transmission and management.

[0060] Power and Cooling Planning: Based on projected traffic demand, ensure the data center has sufficient power supply and cooling capacity. Assess whether the current power and cooling systems can meet future traffic loads, and upgrade and expand them if necessary.

[0061] Security Planning: Based on traffic forecasting results, reassess the data center's security measures. Ensure that physical and network security measures are adaptable to future traffic demands, and plan security strategies for traffic peaks and special events.

[0062] Disaster recovery and mitigation planning: Based on traffic forecasting results, consider the disaster recovery and mitigation capabilities of the data center. Ensure the data center has backup and redundancy mechanisms to cope with possible failures, power outages, or natural disasters.

[0063] Monitoring and Management Planning: Based on traffic forecasting results, assess whether the data center's monitoring and management system can support future traffic demands. Ensure the data center has real-time traffic monitoring, fault detection, and performance management capabilities.

[0064] Step 140: Perform resource planning for the planned integrated area according to the data center resource planning scheme.

[0065] This invention provides a method, apparatus, electronic device, and storage medium for planning data center resources. The method involves acquiring the average number of wireless users and user traffic usage data for a planned integrated area; generating a traffic prediction result for the planned integrated area based on the average number of wireless users and the user traffic usage data; generating a data center resource planning scheme for the planned integrated area based on the traffic prediction result; and performing resource planning for the planned integrated area based on the data center resource planning scheme. This invention effectively plans and constructs data centers by predicting traffic usage in the planned integrated area based on the average number of wireless users and user traffic usage data, and then performing data center resource planning based on the prediction results.

[0066] According to a method for planning data center resources provided by the present invention, the average number of wireless users in the data center of the comprehensive area to be planned is obtained through the following steps:

[0067] Obtain the number of resident wireless users and the number of aggregation equipment rooms in the planned integrated area;

[0068] The average number of wireless users per computer room in the planned integrated area is calculated based on the number of permanent wireless users in the integrated area and the number of data centers in the integrated area.

[0069] In this embodiment, the number of wireless users in a data center refers to the number of wireless users served by a single data center, while the average number of wireless users in a data center refers to the average number of wireless users served by each data center within a certain area. This average number is obtained by dividing the total number of wireless users within a certain area by the total number of data centers within that area. That is, the average number of wireless users in a data center to be planned can be obtained by dividing the number of permanent wireless users in the data center by the number of data centers that aggregate the data center.

[0070] According to a data center resource planning method provided by the present invention, the user traffic usage data includes user activity, bandwidth consumption, and the amount of data generated by users.

[0071] In this embodiment, traffic prediction is a complex process involving many factors and uncertainties. Therefore, it is best to combine multiple methods and data sources to simulate and test multiple scenarios to obtain more accurate prediction results. Specifically, traffic prediction can be based on user traffic usage data, including user activity, bandwidth consumption, and the amount of data generated by users.

[0072] User Activity: Understanding user activity is fundamental to traffic forecasting. The number of active users represents the number of users accessing the system simultaneously within a specific time period. Based on past data or market research, trends and changes in user activity can be identified. This helps in estimating the number of concurrent connections that need to be handled within a given timeframe.

[0073] Bandwidth consumption: Different types of applications and services have different bandwidth requirements. For example, video streaming and large file transfers may consume more bandwidth. The required bandwidth can be estimated based on the type of application and service, as well as how users use these services.

[0074] User-generated data volume: In addition to the number of users, the amount of data generated by users also needs to be considered. For example, the size of files uploaded and downloaded on the website, the number of emails sent and received, etc. Estimating these data volumes can help predict the total traffic volume.

[0075] In addition, user traffic usage data can also include seasonal and trend changes and user behavior patterns.

[0076] Seasonal and trend variations: Some apps and services may be affected by seasonal and trend factors, such as holiday shopping seasons, specific events, or new product launches. Considering these variations can help predict future traffic more accurately.

[0077] User behavior patterns: Analyzing user behavior patterns can provide useful insights into traffic patterns. For example, understanding the distribution of user access times, access frequency, and the pages and functions accessed can help predict traffic peaks and troughs.

[0078] According to a method for planning data center resources provided by the present invention, based on the average number of wireless users and the user traffic usage data, a traffic prediction result for the comprehensive area to be planned is generated, specifically including:

[0079] The user activity level, bandwidth consumption, and user-generated data volume are input into a pre-built user traffic prediction model to obtain user traffic prediction data.

[0080] Based on the average number of wireless users and the user traffic prediction data, the traffic prediction result for the planned integrated area is obtained.

[0081] In this embodiment, the user activity, bandwidth consumption, and user-generated data volume are input into a pre-built user traffic prediction model to obtain user traffic prediction data. Based on the average number of wireless users and the user traffic prediction data, the traffic prediction result for the planned integrated area is generated. Specifically, user traffic prediction can be performed by modeling and training a targeted machine learning model, and the user activity, bandwidth consumption, and user-generated data volume are input into the pre-built user traffic prediction model. Here, it can be trained using a labeled training dataset, which can be input into an initialized keyword recognition model for training. Specifically, after inputting the data from the training dataset into the initialized traffic prediction model, the model output prediction result, i.e., the traffic prediction result, can be obtained. The accuracy of the prediction model can be evaluated based on the traffic prediction result and the aforementioned labels, thereby updating the model parameters. For the traffic prediction model, the accuracy of the model prediction result can be measured by a loss function. The loss function is defined on a single training data point and is used to measure the prediction error of a training data point. Specifically, the loss value of the training data point is determined by the label of the single training data point and the model's prediction result for that training data point. In actual training, a training dataset contains a large number of training data points. Therefore, a cost function is generally used to measure the overall error of the training dataset. The cost function is defined on the entire training dataset and is used to calculate the average prediction error of all training data, which can better measure the model's prediction performance. For general machine learning models, the aforementioned cost function, plus a regularization term to measure model complexity, can serve as the training objective function. Based on this objective function, the loss value of the entire training dataset can be calculated. There are many commonly used loss functions, such as 0-1 loss function, squared loss function, absolute loss function, log loss function, cross-entropy loss function, etc., which can all be used as loss functions for machine learning models, and will not be elaborated on here. In the embodiments of this application, any one of these loss functions can be selected to determine the training loss value. Based on the training loss value, the backpropagation algorithm is used to update the model parameters. After several iterations, a trained traffic prediction model can be obtained. Specifically, the number of iterations can be preset, or training can be considered complete when the accuracy requirement on the test set is met.

[0082] According to a data center resource planning method provided by the present invention, a data center resource planning scheme for the area to be planned is generated based on the traffic prediction results, specifically including:

[0083] If the traffic prediction result is higher than the first prediction threshold, a planning scheme to increase data center resources is generated.

[0084] If the traffic prediction result is lower than the second prediction threshold, a planning scheme for merging data center resources is generated.

[0085] Wherein, the first prediction threshold is greater than the second prediction threshold.

[0086] In this embodiment, the traffic prediction result includes user traffic usage. When the traffic usage exceeds a first prediction threshold, it is determined that there are too few data centers in the integrated area to meet the user demand. Therefore, a plan to increase data center resources is generated, and the specific number of additional data center resources can be determined based on the portion of traffic usage exceeding the first prediction threshold. Similarly, when the traffic usage is below a second prediction threshold, it is determined that there are too many data centers in the integrated area, with supply exceeding user demand. Therefore, a plan to merge data center resources is generated, and the specific number of merged data center resources can be determined based on the portion of traffic usage exceeding the first prediction threshold.

[0087] According to a data center resource planning method provided by the present invention, after generating a data center resource planning scheme for the area to be planned based on the traffic prediction results, the method further includes:

[0088] Obtain the computer room operation data of the comprehensive area to be planned;

[0089] Based on the data center operation data, abnormal operation data was filtered out;

[0090] Based on the abnormal operation data, the target faulty computer room was identified;

[0091] Generate maintenance notification information corresponding to the target faulty computer room.

[0092] In this embodiment, to eliminate the impact of a faulty data center, operational data of the data centers in the planned integrated area can be obtained. This operational data includes the operational data of all data centers in the planned integrated area. The operational data of all data centers is traversed, and abnormal operational data is filtered out. Subsequently, based on the IP information of the abnormal operational data, the corresponding target faulty data center is located, and maintenance notification information corresponding to the target faulty data center is generated. The maintenance notification information includes the IP information of the target faulty data center, the fault type, and other information.

[0093] refer to Figure 2 The planning device for data center resources provided by the present invention will be described below. The planning device for data center resources described below and the planning method for data center resources described above can be referred to in correspondence.

[0094] The present invention also provides a planning device for data center resources, comprising:

[0095] Data acquisition unit 210 is used to acquire the average number of wireless users in the computer room and user traffic usage data of the integrated area to be planned;

[0096] Traffic prediction unit 220 is used to generate traffic prediction results for the comprehensive area to be planned based on the average number of wireless users and the user traffic usage data;

[0097] The scheme generation unit 230 is used to generate a data center resource planning scheme for the comprehensive area to be planned based on the traffic prediction results.

[0098] Resource planning unit 240 is used to perform resource planning for the comprehensive area to be planned according to the data center resource planning scheme.

[0099] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include a processor 310, a communications interface 320, a memory 330, and a communication bus 340. The processor 310, communications interface 320, and memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions from the memory 330 to execute a data center resource planning method. This method includes: acquiring the average number of wireless users and user traffic usage data for the data center area to be planned.

[0100] Based on the average number of wireless users and the user traffic usage data, generate the traffic prediction results for the comprehensive area to be planned;

[0101] Based on the traffic prediction results, a data center resource planning scheme for the comprehensive area to be planned is generated;

[0102] Resource planning is carried out on the comprehensive area to be planned according to the data center resource planning scheme.

[0103] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0104] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer is able to execute the data center resource planning method provided by the above methods, the method comprising:

[0105] Obtain the average number of wireless users in the data center and user traffic usage data of the integrated area to be planned;

[0106] Based on the average number of wireless users and the user traffic usage data, generate the traffic prediction results for the comprehensive area to be planned;

[0107] Based on the traffic prediction results, a data center resource planning scheme for the comprehensive area to be planned is generated;

[0108] Resource planning is carried out on the comprehensive area to be planned according to the data center resource planning scheme.

[0109] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for planning data center resources provided by the methods described above, the method comprising:

[0110] Obtain the average number of wireless users in the data center and user traffic usage data of the integrated area to be planned;

[0111] Based on the average number of wireless users and the user traffic usage data, generate the traffic prediction results for the comprehensive area to be planned;

[0112] Based on the traffic prediction results, a data center resource planning scheme for the comprehensive area to be planned is generated;

[0113] Resource planning is carried out on the comprehensive area to be planned according to the data center resource planning scheme.

[0114] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0115] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for planning data center resources, characterized in that, include: The average number of wireless users in the data center and user traffic usage data of the integrated development zone to be planned are obtained. The average number of wireless users in the data center of the integrated development zone to be planned is obtained through the following steps: the number of resident wireless users in the integrated development zone and the number of aggregation data centers in the integrated development zone are obtained; the number of resident wireless users in the integrated development zone is divided by the number of aggregation data centers in the integrated development zone to calculate the average number of wireless users in the data center of the integrated development zone to be planned. Based on the average number of wireless users in the data center and the user traffic usage data, a traffic prediction result for the comprehensive service area to be planned is generated; the user traffic usage data includes user activity, bandwidth consumption, and the amount of data generated by users; specifically, the traffic prediction result for the comprehensive service area to be planned is generated based on the average number of wireless users in the data center and the user traffic usage data, including: The user activity level, bandwidth consumption, and user-generated data volume are input into a pre-built user traffic prediction model to obtain user traffic prediction data. Based on the average number of wireless users in the data center and the user traffic prediction data, the traffic prediction result of the comprehensive area to be planned is generated; Based on the traffic prediction results, a data center resource planning scheme for the planned integrated area is generated; specifically, the data center resource planning scheme for the planned integrated area is generated based on the traffic prediction results, including: When the traffic prediction result is higher than the first prediction threshold, a planning scheme for increasing data center resources is generated, and the specific amount of data center resources to be increased is determined based on the portion of traffic usage that exceeds the first prediction threshold. When the traffic prediction result is lower than the second prediction threshold, a planning scheme for merging data center resources is generated, and the specific quantity of merged data center resources is determined based on the portion of traffic usage that is lower than the second prediction threshold. Wherein, the first prediction threshold is greater than the second prediction threshold; Resource planning is carried out on the comprehensive area to be planned according to the data center resource planning scheme.

2. The method for planning data center resources according to claim 1, characterized in that, After generating the data center resource planning scheme for the planned integrated area based on the traffic prediction results, the method further includes: Obtain the computer room operation data of the comprehensive area to be planned; Based on the data center operation data, abnormal operation data was filtered out; Based on the abnormal operation data, the target faulty computer room was identified; Generate maintenance notification information corresponding to the target faulty computer room.

3. A planning device for computer room resources, characterized in that, include: The data acquisition unit is used to acquire the average number of wireless users in the data center and user traffic usage data of the integrated area to be planned; wherein, the average number of wireless users in the data center of the integrated area to be planned is acquired through the following steps: acquiring the number of resident wireless users in the integrated area to be planned and the number of data centers in the integrated area; dividing the number of resident wireless users in the integrated area by the number of data centers in the integrated area to calculate the average number of wireless users in the data center of the integrated area to be planned. The traffic prediction unit is used to generate a traffic prediction result for the comprehensive service area to be planned based on the average number of wireless users in the data center and the user traffic usage data; the user traffic usage data includes user activity, bandwidth consumption, and the amount of data generated by users; generating the traffic prediction result for the comprehensive service area to be planned based on the average number of wireless users in the data center and the user traffic usage data specifically includes: The user activity level, bandwidth consumption, and user-generated data volume are input into a pre-built user traffic prediction model to obtain user traffic prediction data. Based on the average number of wireless users in the data center and the user traffic prediction data, a traffic prediction result for the comprehensive area to be planned is generated; a scheme generation unit is used to generate a data center resource planning scheme for the comprehensive area to be planned based on the traffic prediction result; generating the data center resource planning scheme for the comprehensive area to be planned based on the traffic prediction result specifically includes: when the traffic prediction result is higher than a first prediction threshold, generating a planning scheme to increase data center resources, and determining the specific number of additional data center resources based on the portion of traffic usage exceeding the first prediction threshold; when the traffic prediction result is lower than a second prediction threshold, generating a planning scheme to merge data center resources, and determining the specific number of merged data center resources based on the portion of traffic usage lower than the second prediction threshold; wherein, the first prediction threshold is greater than the second prediction threshold; The resource planning unit is used to perform resource planning for the comprehensive area to be planned according to the data center resource planning scheme.

4. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the data center resource planning method as described in any one of claims 1 to 2.

5. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the data center resource planning method as described in any one of claims 1 to 2.

6. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the data center resource planning method as described in any one of claims 1 to 2.

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