CN116016601A - Situation awareness equipment-based operation data acquisition method, equipment and medium - Google Patents

Abstract

The present application relates to a method, device, and medium for collecting operation data of equipment based on situational awareness, including the following steps: S101, based on the operation data collection requirements of the plant side equipment, preset operation data collection parameters, wherein the operation data collection parameters Including but not limited to: region, group, IP list, device type, collection frequency, time interval, and type of operation data; S102, based on the preset operation data collection parameters, generate a startup command for the operation data collection script; S103, Upload the operation data collection script to the plant side equipment; S104, remotely start the operation data collection script according to the startup command, and the operation data collection script performs the processing of the plant side equipment according to the received command Run data collection. By decoupling the operation data collection and reporting service from the application software, the range of target equipment for operation data collection is expanded.

Description

Method, device and medium for collecting operation data of equipment based on situational awareness

technical field

The present application relates to the technical field of industrial control security, in particular to a method, device and medium for collecting operation data of equipment based on situational awareness.

Background technique

Security Situation Awareness of the Energy Industry Internet Platform (hereinafter referred to as "Situation Awareness") is an important part of the Energy Industry Internet Platform. Situational awareness and traceability forensics. The security situation awareness plant-side platform (hereinafter referred to as the "plant-side platform") refers to the network security comprehensive detection system deployed in the plants of various energy groups. It consists of special equipment such as data acquisition devices, plant-level analysis platforms, firewalls, switches, Common devices such as encryption machines are jointly composed.

The station-side platform plays an important role in collecting station network data and analyzing the network security situation. The operation of the station-side platform equipment directly affects the effectiveness of situational awareness decision-making. Therefore, it is necessary to collect and analyze the operating status data of the platform equipment on the plant side, to be able to analyze the operating conditions of the platform equipment on the plant side, so that the software and hardware of the equipment can be kept in the optimal working state at all times, and analyzed and reported stably and accurately data. At present, the equipment on the factory station side collects some operating data through active collection and regular reporting. For general equipment such as switches, firewalls, and encryption machines, it usually supports reporting specified performance data through syslog. For data collection devices and factory-level analysis platforms For special equipment such as special equipment, data collection services and regular reporting services are usually installed. Through the regular reporting service, the operating data is synchronized to the center-side platform, and then the application of the situational awareness center-side platform analyzes and displays various operating data.

In the existing technology, the operating status data is actively reported by the situation awareness plant side platform equipment through the data interface or syslog, and the reported data is processed and displayed by the situation awareness center side platform, but the operation status data collection and reporting function is integrated In the application software of the plant side equipment of the situation awareness system, the coupling with the application software is too high, which is not conducive to the modification and expansion of the operation status data collection capability.

Contents of the invention

The present application provides a method, device, and medium for collecting operation data of equipment based on situational awareness. By decoupling the operation data collection and reporting service from the application software, the range of target equipment for operation data collection is expanded.

In the first aspect, the present application provides a method for collecting operation data of equipment based on situational awareness, including the following steps: S101. Based on the operation data collection requirements of the plant side equipment, preset operation data collection parameters, wherein the operation data collection The parameters include but are not limited to: region, group, IP list, device type, collection frequency, time interval, and type of operation data; S102, based on the preset operation data collection parameters, generate a startup command for the operation data collection script; S103 . Upload the operation data collection script to the plant side equipment; S104. Remotely start the operation data collection script according to the startup command, and the operation data collection script performs the operation on the plant side equipment according to the received command The operating data is collected.

Preferably, the following steps are also included: S105, the operation data collection script uploads the collection results to the data processing module of the center side platform according to the collection frequency in the operation data collection parameters; S106, the data processing module according to the collection frequency As a result, alarm information is generated according to the operation data alarm rules; wherein the operation data alarm rules include operation data alarm threshold rules and operation data alarm trend rules, and the operation data alarm threshold rules include but are not limited to: the operation value of the operation data is higher than The preset value is n times or lower than the preset value for n times; the operation data alarm trend rule includes but is not limited to: the operation value of the operation data increases for n consecutive times or decreases for n consecutive times or the growth rate is higher than the preset value or The reduction rate is lower than the preset value.

Preferably, the following step is further included: S107, the data processing module generates an operation trend graph according to the collection result.

Preferably, the following steps are also included: S108, the data processing module pushes the generated alarm information to the alarm sending module of the central platform and pushes the generated operation trend graph to the report display module of the central platform , the alarm sending module sends alarm information, and the report display module displays the operation trend graph of the plant side equipment through a web page.

Preferably, if the collection result satisfies the operation data alarm threshold rule or the operation data alarm trend rule, JSON data is also generated; wherein the attributes of the JSON data include but are not limited to: alarm device IP, alarm rule type , Alarm details.

Preferably, if the alarm sending module receives the JSON data, it will send a notification by means including but not limited to email or short message WeChat.

Preferably, the step S102 includes: S1021. Determine the collection range. If it is a region or a group, retrieve the IPs of all the plant side equipment in the plant information database, and according to the site to be monitored The type of the side equipment determines the specific equipment IP; if it is the IP list of the plant side equipment, it is stored under the local IP list file to provide inquiries; S1022, according to the collection frequency and time in the operation data collection parameters Interval and running data type stitching start command.

Preferably, the step S103 includes: reading the local IP list file through the task scheduling module of the central platform, traversing the IPs therein, and transmitting the running data collection script to the factory station corresponding to the IP In the specified directory of the side device.

In a second aspect, the present application also provides a computer device, including a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein, when the processor executes the computer program, the The steps of the method described above.

In a third aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method are implemented.

This application has at least the following advantages:

In the first aspect, by transmitting an independent running data collection script to the plant-side equipment, through the preset running data collection parameters, a start command of the running data collection script is generated, and the running data collection script on the plant-side equipment is remotely started , the running data collection script can use the commands and environment that come with the operating system to realize the collection of corresponding running data without integrating the collection function into the application software of the plant side equipment; therefore, by reporting the running data collection to the service and application Software decoupling expands the range of operating data acquisition target devices, and enables customization of reporting requirements, enabling flexible expansion of operating data collection types and logic;

In the second aspect, according to the operating data threshold and trend alarm rules, the operating data collection and reporting service is decoupled from the application software to ensure the correct evaluation of system capabilities, timely identification of equipment weaknesses, indicating the direction of optimization, and finding out the existence of problems in the software. issues and verify stability and reliability.

Description of drawings

FIG. 1 is an application environment diagram showing a method for collecting data based on situational awareness equipment operation in an embodiment;

FIG. 2 is a schematic flow diagram showing a method for collecting operation data based on a situational awareness device in an embodiment;

Fig. 3 is a schematic flow diagram showing the startup command for generating and running the data collection script in step S102 in one embodiment;

Fig. 4 is a trend diagram showing the memory usage of the plant side equipment in operation in one embodiment;

Fig. 5 is a trend diagram showing the CPC usage rate when the station side equipment is running in one embodiment;

Fig. 6 is a schematic block diagram of a computer device in one embodiment.

Detailed ways

It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprising" and/or "comprising" are used in this specification, it indicates There are features, steps, operations, means, components and/or combinations thereof.

In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in each embodiment of the application, many technical details are provided for readers to better understand the application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in this application can also be realized. The division of the following embodiments is for the convenience of description, and should not constitute any limitation to the specific implementation of the present application. The embodiments can be combined and referred to each other on the premise of no contradiction.

For ease of understanding, the system to which this application applies is described first. A method for collecting operation data of equipment based on situational awareness provided by the present application can be applied to the system architecture shown in FIG. 1 . The system includes: a user space file server 103 and a terminal device 101, and the terminal device 101 communicates with the user space file server 103 through the network. Wherein, the user space file server 103 can be a file server based on the NFSv3\v4 protocol, running under the environment of Linux, and NFS (Network File System) is a network abstraction on the file system, which can be allowed to run on the terminal device 101 The remote client of the file system is accessed through the network in a similar manner to the local file system. The terminal device 101 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, etc., and the user space file server 103 may be implemented by an independent server or a server cluster composed of multiple servers.

FIG. 2 is a schematic flowchart of a method for collecting operation data based on situational awareness devices provided by an embodiment of the present application. The method can be executed by a user space file server in the system shown in FIG. 1 . As shown in Figure 2, the method may include the following steps:

S101. Based on the operation data collection requirements of the plant side equipment, preset operation data collection parameters, wherein the operation data collection parameters include but not limited to: region, group, IP list, equipment type, collection frequency, time interval, Types of operating data;

S102. Based on the preset operation data collection parameters, generate a startup command for the operation data collection script;

S103. Upload the running data collection script to the plant side equipment;

S104. Remotely start the operation data collection script according to the startup command, and the operation data collection script collects the operation data of the plant side equipment according to the received command.

In this embodiment, according to the operation data collection requirements of the plant side equipment, the operation data collection parameters can be preset in advance, and the preset operation data collection parameters include region, group, IP list, equipment type, collection frequency, time interval, Types of running data, etc., and according to these preset running data collection parameters, the startup command of the running data collection script can be generated, so by transmitting an independent collection script to the plant side equipment, and then remotely start the plant side equipment Run the data collection script, and the running data collection script can use the commands and environment that come with the operating system to realize the collection of corresponding running data without integrating the collection function into the application software of the plant side equipment, thus realizing the running data collection The reporting service is decoupled from the application software, which expands the range of target equipment for operating data collection, so that the collection method can realize the customization of reporting requirements, and realize the flexible expansion of the types and logic of operating data collection.

The following is a detailed description of each step:

As shown in Figure 2, S101, based on the operation data collection requirements of the plant side equipment, preset operation data collection parameters, wherein the operation data collection parameters include but are not limited to: region, group, IP list, equipment type, collection frequency , time interval, type of operation data;

In this embodiment, it should be noted that the operating data of the current plant side equipment may include hardware performance data when the equipment is running, such as CPU, memory, disk occupancy, etc.; it may also include operating system and business application operating status data , such as file index node occupancy, number of database connections, data processing throughput, application service running status, etc. Therefore, in the embodiment of this application, the user can preset the operation data collection parameters based on the operation data collection requirements of the plant side equipment, where the operation data collection parameters include but are not limited to: region, group, IP list, equipment type, collection frequency, Time interval, type of operation data, etc. For example, when the collection frequency is preset, the data acquisition device in the station side platform will collect the operation data of the station side equipment according to the preset collection frequency and report it in time.

As shown in Fig. 2, S102, based on the preset operation data collection parameters, generate a startup command for the operation data collection script;

In this embodiment, it should be noted that the task scheduling module in the center-side platform is used to generate the startup command of the running data collection script, and the task scheduling module generates the startup command of the running data collection script based on the running data collection parameters preset by the user. Order.

After the task scheduling module receives the preset operation data collection parameters, the steps to generate the start command are as follows:

As shown in Figure 3, S1021, determine the collection range, if it is a region or a group, then retrieve the IPs of all plant side equipment in the plant information database, and determine the specific device IP according to the type of plant side equipment to be monitored; If it is the IP list of the plant side equipment, it will be stored in the local IP list file to provide query.

In this embodiment, it needs to be explained that, firstly, there are multiple stations, and multiple stations will have various types of station-side equipment such as the main platform, standby platform, etc., and each station-side device has There is a corresponding device IP. When the user defines the collection range, he can choose a certain region or a certain device under a certain group. At this time, first search all the plant sides in the region or group selected by the user in the plant information database. The device IP of the device, and then determine the specific device IP according to the device type of the plant side device to be monitored. Or the user can also directly provide the IP list of the plant side equipment, and store it in the local IP list file to provide query.

As shown in FIG. 3 , S1022 , splicing start commands according to the collection frequency, time interval, and type of operation data in the operation data collection parameters.

In this embodiment, it should be noted that, after determining the device IP of the station-side device to be monitored, the task scheduling module in the center-side platform will then collect the data according to the collection frequency, time interval, and type of operation data in the operation data collection parameters. Wait to splice the start command, the start command is mainly used to remotely start and run the data collection script to collect data from the plant side equipment.

As shown in Figure 2, S103, upload the running data collection script to the plant side equipment;

In this embodiment, it should be noted that after the task scheduling module generates the startup command of the running data collection script, it uploads the running data collection script to the plant side equipment, and the main content is that the task scheduling module reads the local IP list file , traverse the IPs in it, and transfer the running data collection script to the specified directory of the plant side equipment corresponding to the IP through the scp (secure copy) command. The scp command is a command for safely copying files to a remote system and copying files from a remote system to the local through the SSH protocol.

As shown in FIG. 2, S104. Remotely start the running data collection script according to the startup command, and the running data collection script collects the running data of the plant side equipment according to the received command.

In this embodiment, it should be noted that when the task scheduling module transmits the running data collection script to the specified directory of the plant side equipment corresponding to the IP, the task scheduling module will remotely execute the startup command generated in step S102, Remotely start the running data collection script through the start command, and collect the running data of the plant side equipment after the running data collection script receives the command.

Wherein, the task scheduling module executes the ssh (Secure Shell) command with the startup command of the running data collection script generated in step S102 as a parameter, and remotely starts the running data collection script transmitted to the factory station side equipment.

In this embodiment, it also needs to be explained that the running data collection script uses the generator mode, which can separate the running data collection results from the collection logic, so as to achieve more fine-grained control over the data collection process, and also improve the running data collection process. Flexible expansion capabilities for collection types and collection logic. The running data acquisition script includes four modules, the running data module, the builder module, the recorder module and the startup module. The running data module is used to define and store different types of running data of the plant side equipment. The builder module is used to calculate or extract the real running data according to the command output to be parsed. The recorder module is used to record the Info class generated by the Director, and upload the collection results to the data processing module of the center-side platform according to the collection frequency. The start-up module is used to start the collection of operation data of the plant side equipment, mainly to start operation data collection according to the preset collection frequency, time interval, operation data type parameters, etc. in step S101.

As shown in Figure 2, the collection method in this embodiment also includes: S105, the running data collection script uploads the collection results to the data processing module of the center side platform according to the collection frequency in the running data collection parameters;

S106. The data processing module generates alarm information according to the operation data alarm rules according to the collection results; wherein the operation data alarm rules include operation data alarm threshold rules and operation data alarm trend rules, and the operation data alarm threshold rules include but are not limited to: The value is higher than the preset value n times or lower than the preset value n times; the operating data alarm trend rules include but are not limited to: the operating value of the operating data increases for n consecutive times or decreases for n consecutive times or the growth rate is higher than the preset value Or the reduction rate is lower than the preset value.

In this embodiment, it should be noted that the running data collection script performs data collection according to the collection frequency in the preset running data parameters and simultaneously uploads the collection results to the data processing module of the central platform, that is to say, the running data collection The script executes the rsync command regularly according to the preset collection frequency in step S101, and uploads the collection result files stored in the specified directory of the plant side equipment to the data processing module.

After the data processing module receives the collection results, it matches the uploaded collection results according to the operation data alarm rules, and generates custom alarm information; the operation data alarm rules include the operation data alarm threshold rules and the operation data alarm trend rules, and the operation data alarm Threshold rules include but are not limited to: the operating value of the operating data is higher than the preset value n times or lower than the preset value n times. For example, if the CPU usage rate is higher than 90% for three consecutive times, those skilled in the art may define different thresholds according to various data, which is not specifically limited in this embodiment. The operation data alarm trend rules include but are not limited to: the operation value of the operation data increases continuously for n times or decreases for n times in a row, or the growth rate is higher than a preset value or the decrease rate is lower than a preset value. For example, if the number of database connections increases ten times in a row, those skilled in the art may define different trend rules according to various types of data, which is not specifically limited in this embodiment.

As shown in FIG. 2 , it also includes: S107 , the data processing module generates an operation trend graph according to the collection result.

In this embodiment, it should be noted that the data processing module generates the running data trend graph according to the collection results, wherein the generating method of the running data trend graph is: according to the running data reported to the specified directory of the plant side equipment in step S104, Use pyecharts to generate the html code of the running data trend graph of the equipment on the plant side.

In this embodiment, it should also be noted that if the operation data alarm threshold rule or the operation data alarm trend rule is triggered, a piece of JSON (JavaScript Object Notation) data will also be generated, wherein the attributes of the JSON data include but are not limited to: alarm Device IP, alarm rule type, alarm details, etc., where the alarm details are threshold/trend rule, actual value/actual trend.

As shown in Figure 2, it also includes: S108, the data processing module pushes the generated alarm information to the alarm sending module of the center side platform and pushes the generated operation trend graph to the report display module of the center side platform, and the alarm sending module sends an alarm The information and report display module displays the operation trend graph of the plant side equipment through the web page.

In this embodiment, it should be noted that the data processing module pushes the generated alarm information to the alarm sending module of the central platform, and the alarm sending module sends the alarm information in various ways; if the JSON data sent in step S107 is received Notifications will also be made via e-mail, SMS, WeChat, etc.

The data processing module also pushes the generated running data trend graph to the report display module of the center side platform, and the report display module displays the running data trend graph of the factory station side equipment through the Web page, according to the operation of the factory station side equipment generated in step S107 The html code of the data trend graph uses react technology to write the web page framework, introduces and displays the html code that runs the data trend graph. Among them, React technology is mainly used to build the user interface (User Interface, referred to as UI). As shown in Figure 4, it shows the trend graph of memory usage. At 2022-11-29T01:13:50, the occupied memory usage is 17424MB; as shown in Figure 5, it shows the trend graph of CPU usage, at 2022-11-29T02 :40: 33.38% CPU usage at :52.

Therefore, through the operation data alarm threshold and alarm trend rules, the real-time performance of operation problem discovery is improved, and the accuracy of business personnel in locating operation problems is improved through the centralized display of operation data trend graphs.

According to the embodiment of the present application, the present application also provides a computer device and a computer-readable storage medium.

As shown in FIG. 6 , it is a block diagram of a computer device according to an embodiment of the present application. Computing equipment is intended to mean any form of digital computer or mobile device. Wherein digital computers may include desktop computers, laptop computers, workstations, personal digital assistants, servers, mainframe computers, and other suitable computers. Mobile devices may include tablets, smartphones, wearable devices, and the like.

As shown in Figure 6, device 600 includes computing unit 601, ROM 602, RAM 603, bus 604 and input/output (I/O) interface 605, and computing unit 601, ROM 602 and RAM 603 are connected to each other through bus 604. An input/output (I/O) interface 605 is also connected to the bus 604 .

The computing unit 601 can execute various processes in the method embodiments of the present application according to computer instructions stored in the read-only memory (ROM) 602 or loaded from the storage unit 608 into the random access memory (RAM) 603 . The computing unit 601 may be various general-purpose and/or special-purpose processing components having processing and computing capabilities. The computing unit 601 may include, but not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors ( DSP), and any suitable processor, controller, microcontroller, etc. In some embodiments, the methods provided in the embodiments of the present application may be implemented as computer software programs, which are tangibly included in computer-readable storage media, such as the storage unit 608 .

The RAM 603 can also store various programs and data necessary for the operation of the device 600. Part or all of the computer program can be loaded and/or installed on the device 600 via the ROM 602 and/or the communication unit 609.

The input unit 606 , output unit 607 , storage unit 608 and communication unit 609 in the device 600 may be connected to the I/O interface 605 . Wherein, the input unit 606 may be such as a keyboard, mouse, touch screen, microphone, etc.; the output unit 607 may be such as a display, a speaker, an indicator light, and the like. The device 600 is capable of exchanging information, data, and the like with other devices through the communication unit 609 .

It should be noted that the device may also include other components necessary for normal operation. It is also possible to include only the components necessary to realize the solution of the present application, instead of all the components shown in the figure.

Various implementations of the systems and techniques described herein can be implemented in digital electronic circuitry, systems integrated circuits, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips system (SOC), load programmable logic device (CPLD), computer hardware, firmware, software, and/or a combination thereof.

Computer instructions for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer instructions may be provided to the computing unit 601, so that when the computer instructions are executed by the computing unit 601 such as a processor, various steps involved in the method embodiments of the present application are executed.

The computer-readable storage medium provided in the present application may be a tangible medium, which may contain or store computer instructions for executing the steps involved in the method embodiments of the present application. Computer-readable storage media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, and other forms of storage media.

The above specific implementation methods are not intended to limit the protection scope of the present application. It should be apparent to those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of this application shall be included within the protection scope of this application.

Claims (10)

1. A method for collecting data based on situation awareness equipment operation, characterized in that, comprising the following steps: S101. Based on the operation data collection requirements of the plant side equipment, preset operation data collection parameters, wherein the operation data collection parameters include but not limited to: region, group, IP list, equipment type, collection frequency, time interval, Types of operating data; S102. Based on the preset operation data collection parameters, generate a startup command for the operation data collection script; S103. Upload the running data collection script to the plant side equipment; S104. Remotely start the operation data collection script according to the startup command, and the operation data collection script collects the operation data of the plant side equipment according to the received command. 2. The method for collecting data based on situational awareness equipment operation according to claim 1, further comprising the steps of: S105. The operation data collection script uploads the collection results to the data processing module of the center side platform according to the collection frequency in the operation data collection parameters; S106. The data processing module generates alarm information according to the operation data alarm rules according to the collection results; wherein the operation data alarm rules include operation data alarm threshold rules and operation data alarm trend rules, and the operation data alarm threshold rules include but are not limited to It is: the operating value of the operating data is higher than the preset value n times or lower than the preset value n times; the operating data alarm trend rule includes but not limited to: the operating value of the operating data increases for n consecutive times or decreases for n consecutive times Either the growth rate is higher than the preset value or the decrease rate is lower than the preset value. 3. The method for collecting data based on situational awareness equipment operation according to claim 2, further comprising the steps of: S107. The data processing module generates an operation trend graph according to the collection result. 4. The method for collecting data based on situational awareness equipment operation according to claim 3, further comprising the steps of: S108. The data processing module pushes the generated alarm information to the alarm sending module of the center-side platform and pushes the generated operation trend graph to the report display module of the center-side platform, and the alarm sending module sends the alarm information , the report display module displays the operation trend chart of the plant side equipment through a webpage. 5. The method for collecting operation data based on situational awareness equipment according to claim 4, wherein if the collection result satisfies the operation data alarm threshold rule or the operation data alarm trend rule, JSON data is also generated; wherein The attributes of the JSON data include but are not limited to: alarm device IP, alarm rule type, and alarm details. 6. The method for collecting data based on situational awareness equipment operation according to claim 5, wherein if the alarm sending module receives the JSON data, it sends the data by including but not limited to e-mail, short message WeChat notify. 7. The method for collecting operation data based on situational awareness equipment according to any one of claims 1-6, wherein the step S102 includes: S1021. Determine the collection range. If it is a region or a group, retrieve the IPs of all the plant side equipment in the plant information database, and determine the specific device IP according to the type of the plant side equipment to be monitored; if it is The IP list of the plant side equipment is stored under the local IP list file to provide inquiries; S1022. Splicing start commands according to the collection frequency, time interval, and type of operation data in the operation data collection parameters. 8. The method for collecting operation data based on situational awareness equipment according to claim 7, wherein the step S103 includes: Read the local IP list file through the task scheduling module of the central platform, traverse the IPs therein, and transmit the running data collection script to the specified directory of the plant side equipment corresponding to the IP. 9. A computer device, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, characterized in that, when the processor executes the computer program, any one of claims 1 to 8 is realized. A step of said method. 10. A computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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