A server information monitoring method, device, electronic device and storage medium

Abstract

The present application provides a server information monitoring method, device, electronic device and storage medium, the method comprising: determining server basic data according to the influence relationship between various monitoring indicators of the server; monitoring server basic data; judging whether target data in the server affected by the server basic data has changed according to the change of the server basic data; when the target data in the server affected by the server basic data has changed, collecting the target data from the server. The method provided by the above scheme determines whether to collect the target data by detecting whether the target data in the server affected by the server basic data has changed, thereby reducing the number of times the target data is collected and reducing the data collection pressure of the server management software.

Description

Technical Field

[0001] The present application relates to the field of data management technology, and in particular to a server information monitoring method, device, electronic device and storage medium. Background Art

[0002] At present, the server information that server management software needs to monitor can be roughly divided into three parts: asset information, alarm information and performance information. Among them, the alarm information and performance information are collected more frequently, generally uninterruptedly or every minute, while the asset information is collected less frequently, generally once a day.

[0003] However, according to the actual situation, although server information is affected by many factors, the data change rate is small. If you choose to monitor all server information all the time in order to monitor the operating status of the server, it will increase the data collection pressure of the server management software. Summary of the invention

[0004] The present application provides a server information monitoring method, device, electronic device and storage medium to solve the defects of the prior art such as increasing the data collection pressure of server management software.

[0005] The first aspect of the present application provides a server information monitoring method, comprising:

[0006] Determine the basic data of the server based on the influence relationship between various monitoring indicators of the server;

[0007] Monitoring the basic data of the server;

[0008] According to the change of the basic data of the server, determining whether the target data in the server affected by the basic data of the server has changed;

[0009] When target data in the server affected by the server basic data changes, the target data is collected from the server.

[0010] Optionally, judging whether target data in the server affected by the server basic data has changed according to the change of the server basic data includes:

[0011] Input the basic data of the server within the preset monitoring period into the prediction model;

[0012] Based on the prediction model, according to the change of the server basic data within the preset monitoring period, it is determined whether the target data in the server affected by the server basic data has changed.

[0013] Optionally, judging whether target data in the server affected by the server basic data has changed based on the prediction model and according to changes of the server basic data within the preset monitoring period includes:

[0014] Based on the prediction model, determining the probability of change of the target data according to the change of the server basic data within the preset monitoring period;

[0015] Whether the target data has changed is determined according to the numerical value of the change probability of the target data.

[0016] Optionally, judging whether the target data has changed according to a numerical value of the probability of change of the target data includes:

[0017] Determine whether the change probability of the target data reaches a preset probability threshold;

[0018] When the change probability of the target data reaches a preset probability threshold, it is determined that the target data has changed.

[0019] Optionally, also include:

[0020] The accuracy of the prediction model is determined based on the comparison result between the collection result of the target data and the historical target data.

[0021] Optionally, before inputting the server basic data within the preset monitoring period into the prediction model, the method further includes:

[0022] According to the order of occurrence time of each of the server basic data, the server basic data are sorted accordingly to obtain a basic data set;

[0023] The basic data set is cleaned to remove abnormal data in the basic data set.

[0024] Optionally, the abnormal data includes invalid data and abnormal fluctuation data.

[0025] A second aspect of the present application provides a server information monitoring device, comprising:

[0026] A determination module is used to determine the basic data of the server according to the influence relationship between various monitoring indicators of the server;

[0027] A monitoring module, used for monitoring the basic data of the server;

[0028] A judgment module, used for judging whether the target data in the server affected by the server basic data has changed according to the change of the server basic data;

[0029] The data collection module is used to collect the target data from the server when the target data in the server affected by the server basic data changes.

[0030] Optionally, the judgment module is specifically used to:

[0031] Input the basic data of the server within the preset monitoring period into the prediction model;

[0032] Based on the prediction model, according to the change of the server basic data within the preset monitoring period, it is determined whether the target data in the server affected by the server basic data has changed.

[0033] Optionally, the judgment module is specifically used to:

[0034] Based on the prediction model, determining the probability of change of the target data according to the change of the server basic data within the preset monitoring period;

[0035] Whether the target data has changed is determined according to the numerical value of the change probability of the target data.

[0036] Optionally, the judgment module is specifically used to:

[0037] Determine whether the change probability of the target data reaches a preset probability threshold;

[0038] When the change probability of the target data reaches a preset probability threshold, it is determined that the target data has changed.

[0039] Optionally, the device further comprises:

[0040] The detection module is used to determine the accuracy of the prediction model based on the comparison result between the collection result of the target data and the historical target data.

[0041] Optionally, the device further comprises:

[0042] The data cleaning module is used to sort the server basic data according to the chronological order of occurrence of each server basic data to obtain a basic data set; and to clean the basic data set to eliminate abnormal data in the basic data set.

[0043] Optionally, the abnormal data includes invalid data and abnormal fluctuation data.

[0044] A third aspect of the present application provides an electronic device, comprising: at least one processor and a memory;

[0045] The memory stores computer-executable instructions;

[0046] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the method described in the first aspect and various possible designs of the first aspect.

[0047] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When a processor executes the computer-executable instructions, the method described in the first aspect and various possible designs of the first aspect are implemented.

[0048] The technical solution of this application has the following advantages:

[0049] The present application provides a server information monitoring method, device, electronic device and storage medium, the method comprising: determining server basic data according to the influence relationship between various monitoring indicators of the server; monitoring server basic data; judging whether target data in the server affected by the server basic data has changed according to the change of the server basic data; when the target data in the server affected by the server basic data has changed, collecting the target data from the server. The method provided by the above scheme determines whether to collect the target data by detecting whether the target data in the server affected by the server basic data has changed, thereby reducing the number of times the target data is collected and reducing the data collection pressure of the server management software. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application, and a person skilled in the art can also obtain other drawings based on these drawings.

[0051] Figure 1 This is a schematic diagram of the structure of the server information monitoring system based on the embodiment of the present application;

[0052] Figure 2 A flow chart of a server information monitoring method provided in an embodiment of the present application;

[0053] Figure 3 The prediction model calculation function image provided by the embodiment of the present application;

[0054] Figure 4 The server basic data image provided by the embodiment of the present application;

[0055] Figure 5 A schematic diagram of the structure of a server information monitoring device provided in an embodiment of the present application;

[0056] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0057] The above drawings have shown clear embodiments of the present application, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0059] In addition, the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. In the description of the following embodiments, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0060] At present, although server information is affected by many factors, the data change rate is relatively small. If you choose to monitor all server information all the time in order to monitor the operating status of the server, that is, collecting asset information when the service has not changed is equivalent to doing useless work, which increases the pressure on the server, increases the pressure on the management software, and also increases the data storage pressure on the database.

[0061] In response to the above problems, the server information monitoring method, device, electronic device and storage medium provided in the embodiments of the present application include: determining the server basic data according to the influence relationship between various monitoring indicators of the server; monitoring the server basic data; judging whether the target data in the server affected by the server basic data has changed according to the change of the server basic data; when the target data in the server affected by the server basic data has changed, collecting the target data from the server. The method provided by the above scheme determines whether to collect the target data by detecting whether the target data in the server affected by the server basic data has changed, thereby reducing the number of times the target data is collected and reducing the data collection pressure of the server management software.

[0062] The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0063] First, the structure of the server information monitoring system on which this application is based is described:

[0064] The server information monitoring method, device, electronic device and storage medium provided in the embodiments of the present application are suitable for monitoring and managing various status information and performance indicators of the server, such as Figure 1 , which is a schematic diagram of the structure of the server information monitoring system based on the embodiment of the present application, mainly includes a server and a server information monitoring device. Specifically, the server information monitoring device analyzes multiple monitoring indicators of the server, determines the influence relationship between the monitoring indicators, and monitors and manages multiple information of the server based on the influence relationship.

[0065] The embodiment of the present application provides a server information monitoring method for monitoring and managing various status information and performance indicators of a server. The execution subject of the embodiment of the present application is an electronic device, such as a server, a desktop computer, a laptop computer, a tablet computer, and other electronic devices that can be used to monitor information on the server.

[0066] like Figure 2 FIG. 1 is a flow chart of a server information monitoring method provided in an embodiment of the present application, the method comprising:

[0067] Step 201, determining server basic data according to the influence relationship between various monitoring indicators of the server.

[0068] It should be noted that the monitoring indicators include server temperature, fan speed, server humidity, battery information, memory growth rate and remaining memory, etc. Server basic data refers to the data among these monitoring indicators that are not affected by other monitoring indicators, such as server temperature and server humidity.

[0069] Specifically, based on the current server information monitoring needs, you can determine which monitoring indicators need to be monitored, then analyze the impact relationship between the various monitoring indicators based on the server's own properties, and then filter out server basic data that is not affected by other monitoring indicators from these monitoring indicators.

[0070] Step 202: monitor server basic data.

[0071] Specifically, the server basic data may be collected according to a preset data collection step to monitor the server basic data.

[0072] Step 203: According to the change of the basic data of the server, it is determined whether the target data in the server affected by the basic data of the server has changed.

[0073] Specifically, for each server basic data, when collecting the server basic data, the timestamp of data collection is recorded, and the changes of the server basic data are analyzed by combining the data collection results and the timestamp of each server basic data. Finally, according to the changes of the currently obtained server basic data, it is determined whether the target data affected by these server basic data has changed.

[0074] For example, when the server basic data is server temperature, since the fan speed in the server will increase as the server temperature increases, the corresponding target data may be fan information such as fan speed. Similarly, when the server basic data is server humidity, the target data affected by it may be battery information, etc.; when the server basic data is memory growth rate, the target data affected by it may be memory remaining, etc.

[0075] Step 204: when target data in the server affected by the server basic data changes, the target data is collected from the server.

[0076] Specifically, when it is determined that target data in the server affected by the server basic data has changed according to the change of the server basic data, the data collection process of the server management software is called to perform corresponding data collection on the changed target data.

[0077] Based on the above embodiment, as an implementable manner, in one embodiment, judging whether target data in the server affected by the server basic data has changed according to the change of the server basic data includes:

[0078] Step 2031, inputting the basic data of the server within the preset monitoring period into the prediction model;

[0079] Step 2032: Based on the prediction model, according to the change of the server basic data within the preset monitoring period, it is determined whether the target data in the server affected by the server basic data has changed.

[0080] The prediction model may be specifically constructed based on a classifier. When the prediction model determines that target data in the server affected by basic data of the server has changed, the output judgment result is 1. Otherwise, the output judgment result is 0.

[0081] Specifically, in one embodiment, based on the prediction model, the probability of target data change can be determined according to the change of server basic data within a preset monitoring period; and based on the numerical value of the target data change probability, it is determined whether the target data has changed.

[0082] The preset monitoring period may be 5 minutes or 1 hour, etc. The preset monitoring period may be designed according to the actual situation, and the present application embodiment does not limit it.

[0083] Specifically, the change probability calculation function of the target data can be determined according to the influence relationship and corresponding influence degree between various monitoring indicators of the server, and then a prediction model can be constructed based on the calculation function so that the prediction model can calculate the change probability of the target data according to the changes of the basic data of the server within a preset monitoring period.

[0084] For example, Figure 3 As shown, it is a prediction model calculation function image provided by an embodiment of the present application, wherein, Figure 3 The change probability calculation function (prediction model calculation function) of the target data shown is as follows:

[0085]

[0086] Among them, g(x) represents the probability of change of the current target data, x represents the change rate of the basic data of the server that can affect the target data within the preset monitoring period, and when x = 0, g(x) = 50%. As x gradually decreases, the function value g(x) tends to 0, and as x gradually increases, the function value g(x) gradually tends to 1.

[0087] Furthermore, in one embodiment, it can be determined whether the change probability of the target data reaches a preset probability threshold; when the change probability of the target data reaches the preset probability threshold, it is determined that the target data has changed.

[0088] The preset probability threshold may be 50% or 60%, etc., which may be set according to actual needs and is not limited in the application embodiment.

[0089] Based on the above embodiments, as an implementable method, in one embodiment, after the target data collection work is completed based on the judgment result of the prediction model, the accuracy of the prediction model can also be determined based on the comparison result between the target data collection result and the historical target data.

[0090] Specifically, it can start with deploying the prediction model. Each time after completing the target data collection work according to the judgment result of the prediction model, the current target data collection result is compared with the last collection result of the target data (historical target data) to obtain the corresponding comparison result. Then, based on the obtained comparison result, it is determined whether the target data has really changed. If the target data has indeed changed, it is determined that the judgment result of the prediction model is correct.

[0091] Exemplarily, the accuracy of the prediction model can be calculated according to the following formula:

[0092]

[0093] The correct number specifically refers to the correct judgment results output, and the total number specifically refers to the total number of judgment results output during the operation. Specifically, after each judgment is completed, the total number of data can be accumulated to record whether the judgment result is accurate. If it is accurate, the correct number is accumulated. As time goes by, the more predictions and judgments are made, the more accurate the accuracy judgment will be.

[0094] On the basis of the above embodiment, since the directly collected server basic data may contain certain noise data, which is not conducive to ensuring the accuracy of the subsequent judgment results, as an implementable manner, in one embodiment, before inputting the server basic data within the preset monitoring period into the prediction model, the method further includes:

[0095] Step 301, sorting the server basic data accordingly according to the order of occurrence time of each server basic data to obtain a basic data set;

[0096] Step 302: clean the basic data set to remove abnormal data in the basic data set.

[0097] Among them, the abnormal data includes invalid data and abnormal fluctuation data. Similarly, the abnormal data may also include missing values ​​and other data that are not conducive to ensuring the accuracy of subsequent judgment results.

[0098] Specifically, corresponding data analysis may be performed on the server basic data in the basic data set, and based on the data analysis result, it may be determined which data are abnormal data, and then the abnormal data may be removed from the basic data set.

[0099] For example, Figure 4 As shown, it is a server basic data image provided by an embodiment of the present application, wherein: Figure 4 The basic server data shown is the server temperature. Figure 4 The server basic data corresponding to 200 degrees and 0 degrees are obviously abnormal data, so these two abnormal data can be eliminated to avoid the abnormal data affecting subsequent judgment results.

[0100] The server information monitoring method provided in the embodiment of the present application determines the server basic data according to the influence relationship between various monitoring indicators of the server; monitors the server basic data; determines whether the target data in the server affected by the server basic data has changed according to the change of the server basic data; when the target data in the server affected by the server basic data has changed, collects the target data from the server. The method provided by the above scheme determines whether to collect the target data by detecting whether the target data in the server affected by the server basic data has changed, thereby reducing the number of times the target data is collected, reducing the data collection pressure of the server management software, and reducing the total amount of server information collected, and also reducing the data management pressure of the database.

[0101] An embodiment of the present application provides a server information monitoring device, which is used to execute the server information monitoring method provided in the above embodiment.

[0102] like Figure 5 , which is a schematic diagram of the structure of a server information monitoring device provided in an embodiment of the present application. The server information monitoring device 50 comprises: a determination module 501 , a monitoring module 502 , a judgment module 503 and a data acquisition module 504 .

[0103] Among them, the determination module is used to determine the server basic data according to the influence relationship between various monitoring indicators of the server; the monitoring module is used to monitor the server basic data; the judgment module is used to judge whether the target data in the server affected by the server basic data has changed according to the change of the server basic data; the data collection module is used to collect the target data from the server when the target data in the server affected by the server basic data has changed.

[0104] Specifically, in one embodiment, the judgment module is specifically used to:

[0105] Input the basic data of the server within the preset monitoring period into the prediction model;

[0106] Based on the prediction model, according to the changes of the server basic data within the preset monitoring period, it is judged whether the target data in the server affected by the server basic data has changed.

[0107] Specifically, in one embodiment, the judgment module is specifically used to:

[0108] Based on the prediction model, the probability of target data change is determined according to the changes in the basic server data within the preset monitoring period;

[0109] According to the numerical value of the target data's change probability, it is determined whether the target data has changed.

[0110] Specifically, in one embodiment, the judgment module is specifically used to:

[0111] Determine whether the change probability of the target data reaches a preset probability threshold;

[0112] When the change probability of the target data reaches a preset probability threshold, it is determined that the target data has changed.

[0113] Specifically, in one embodiment, the device further includes:

[0114] The detection module is used to determine the accuracy of the prediction model based on the comparison results between the target data collection results and the historical target data.

[0115] Specifically, in one embodiment, the device further includes:

[0116] The data cleaning module is used to sort the server basic data according to the chronological order of occurrence of the basic data of each server to obtain a basic data set; and to clean the basic data set to eliminate abnormal data in the basic data set.

[0117] Specifically, in one embodiment, the abnormal data includes invalid data and abnormal fluctuation data.

[0118] Regarding the server information monitoring device in this embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0119] The server information monitoring device provided in the embodiment of the present application includes a determination module for determining the server basic data according to the influence relationship between various monitoring indicators of the server; a monitoring module for monitoring the server basic data; a judgment module for judging whether the target data in the server affected by the server basic data has changed according to the change of the server basic data; and a data collection module for collecting the target data from the server when the target data in the server affected by the server basic data has changed. The device provided by the above scheme determines whether to collect the target data by detecting whether the target data in the server affected by the server basic data has changed, thereby reducing the number of target data collection times, reducing the data collection pressure of the server management software, and reducing the total amount of server information collection, and also reducing the data management pressure of the database.

[0120] An embodiment of the present application provides an electronic device for executing the server information monitoring method provided in the above embodiment.

[0121] like Figure 6FIG. 6 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 60 includes: at least one processor 61 and a memory 62 .

[0122] The memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the server information monitoring method provided in the above embodiment.

[0123] An electronic device provided in an embodiment of the present application is used to execute the server information monitoring method provided in the above embodiment. Its implementation method and principle are the same and will not be repeated here.

[0124] An embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the server information monitoring method provided in any of the above embodiments is implemented.

[0125] The storage medium containing computer executable instructions in the embodiment of the present application can be used to store computer executable instructions of the server information monitoring method provided in the aforementioned embodiment. Its implementation method and principle are the same and will not be repeated here.

[0126] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0127] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0128] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0129] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0130] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A server information monitoring method, characterized in that: include: Determine the basic data of the server based on the influence relationship between various monitoring indicators of the server; Monitoring the basic data of the server; According to the change of the basic data of the server, determining whether the target data in the server affected by the basic data of the server has changed; When target data in the server affected by the server basic data changes, collecting the target data from the server; The determining, according to the change of the server basic data, whether the target data in the server affected by the server basic data has changed includes: Input the basic data of the server within the preset monitoring period into the prediction model; Based on the prediction model, judging whether target data in the server affected by the server basic data has changed according to changes in the server basic data within the preset monitoring period; The determining, based on the prediction model and according to the change of the server basic data within the preset monitoring period, whether the target data in the server affected by the server basic data has changed includes: Based on the prediction model, determining the probability of change of the target data according to the change of the server basic data within the preset monitoring period; Determining whether the target data has changed according to the numerical value of the change probability of the target data; The change probability of the target data is determined based on the following formula: in, Indicates the probability of change of the current target data, Indicates the change rate of the server basic data within the preset monitoring period.

2. The method according to claim 1, characterized in that The determining, based on the numerical value of the probability of change of the target data, whether the target data has changed includes: Determine whether the change probability of the target data reaches a preset probability threshold; When the change probability of the target data reaches a preset probability threshold, it is determined that the target data has changed.

3. The method according to claim 1, characterized in that Also includes: The accuracy of the prediction model is determined based on the comparison result between the collection result of the target data and the historical target data.

4. The method according to claim 1, characterized in that: Before inputting the server basic data within the preset monitoring period into the prediction model, the method further includes: According to the order of occurrence time of each of the server basic data, the server basic data are sorted accordingly to obtain a basic data set; The basic data set is cleaned to remove abnormal data in the basic data set.

5. The method according to claim 4, characterized in that The abnormal data includes invalid data and abnormal fluctuation data.

6. A server information monitoring device, characterized in that: include: A determination module is used to determine the basic data of the server according to the influence relationship between various monitoring indicators of the server; A monitoring module, used to monitor the basic data of the server; A judgment module, used for judging whether the target data in the server affected by the server basic data has changed according to the change of the server basic data; A data collection module, used for collecting the target data from the server when the target data in the server affected by the basic data of the server changes; The judgment module is specifically used for: Input the basic data of the server within the preset monitoring period into the prediction model; Based on the prediction model, judging whether target data in the server affected by the server basic data has changed according to changes in the server basic data within the preset monitoring period; The judgment module is specifically used for: Based on the prediction model, determining the probability of change of the target data according to the change of the server basic data within the preset monitoring period; Determining whether the target data has changed according to the numerical value of the change probability of the target data; The change probability of the target data is determined based on the following formula: in, Indicates the probability of change of the current target data, Indicates the change rate of the server basic data within the preset monitoring period.

7. An electronic device, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the processor executes the computer-executable instructions, the method according to any one of claims 1 to 5 is implemented.

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