WO2017166644A1

WO2017166644A1 - Data acquisition method and system

Info

Publication number: WO2017166644A1
Application number: PCT/CN2016/096968
Authority: WO
Inventors: 王孝庆; 刘永华
Original assignee: 乐视控股（北京）有限公司; 乐视云计算有限公司
Priority date: 2016-03-31
Filing date: 2016-08-26
Publication date: 2017-10-05
Also published as: CN105912587A

Abstract

A data acquisition method and system. The method comprises: storing log information about at least one service by means of distributed storage (101); configuring a data acquisition task rule according to corresponding service requirements, wherein the data acquisition task rule corresponds to information about at least one feature (102); acquiring target data from the stored log information according to the data acquisition task rule (103); and storing a target data acquisition result (104). A data centre platform can be enriched, and a more humanized service can be provided for a user according to a data acquisition result, and a service platform is further improved.

Description

Data acquisition method and system

The present application claims priority to Chinese Patent Application No. 2016102028782, entitled "A Data Collection Method and System", filed on March 31, 2016, the entire contents of which is incorporated herein by reference. In the application.

Technical field

The present disclosure relates to the field of data processing, for example, to a data acquisition method and system.

Background technique

With the development of modern science and technology, data acquisition technology has penetrated into all walks of life and various technical fields.

The log is an event record called log generated by the network device, system, and service program at runtime; each log records the description information of the date, time, user, and action. The log records the life cycle of the system. By checking the log, you can know the status of the system at a certain moment. By analyzing the logs and collecting useful data, you can get the user's usage information and access statistics for the service system. Provide evidence for optimization and prevention of cybersecurity issues.

However, related data collection methods can only collect structured data from databases and network files, but ignore the collection of unstructured data in log information covering a large amount of user behavior data, so the data collected about user behavior is not enough. rich.

Summary of the invention

The embodiments of the present disclosure provide a data collection method and system, which are used to solve the problem that the data collected by the related data collection method is not rich enough for the user behavior, and can enrich the data center platform, and can provide users with more humanization according to the data collection result. The service and the more perfect business platform.

Embodiments of the present disclosure provide a data collection method, including:

Collecting log information of at least one service in a distributed storage manner;

Configuring a data collection task rule according to the corresponding service requirement; wherein the data collection task rule corresponds to at least one feature information;

Collecting target data from the stored log information according to the data collection task rule;

The target data collection result is stored.

The embodiment of the present disclosure provides a data collection system, including: a log information storage module, a data collection task configuration module, a log data collection module, and a target data storage module;

The log information storage module is configured to store log information of at least one service in a distributed storage manner;

The data collection task configuration module is configured to configure a data collection task rule according to the corresponding service requirement; wherein the data collection task rule corresponds to at least one feature information;

The log data collection module is configured to collect target data from the log information stored in the log information storage module according to the data collection task rule; and

The target data storage module is configured to store the target data output by the log data collection module.

Embodiments of the present disclosure provide a non-transitory computer readable storage medium storing computer executable instructions that, when executed by an electronic device, cause the electronic device to perform the data collection method described above.

Embodiments of the present disclosure provide a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, when the program instructions are executed by a computer Causing the computer to perform the data acquisition method described above.

An embodiment of the present disclosure provides an electronic device including at least one processor and a memory communicatively coupled to the at least one processor, the memory for storing instructions executable by the at least one processor, the instructions being The at least one processor, when executed, causes the at least one processor to perform the data acquisition method described above.

The embodiments of the present disclosure provide a data collection method and system. On the one hand, storing log information in a distributed storage manner can effectively reduce the performance requirements of a single CPU and resources, and reduce the cost of data collection; The disclosed embodiment can be configured by parsing log information The data collection task rule collects the target data from the analysis result. Since a large amount of log information contains a large amount of user data, user operation behavior data and business data, the collection result not only enriches the data center platform, but also enables The data collection results effectively analyze the user's behavior habits and business operations to better understand the user's needs, thus providing users with more humanized services and better improving the business platform.

BRIEF abstract

The one or more embodiments are exemplified by the accompanying drawings in the accompanying drawings, and FIG. The figures in the drawings do not constitute a scale limitation unless otherwise stated.

1 is a flow chart of steps of a first embodiment of a data collection method according to the present disclosure;

2 is a schematic diagram of a user activity map of the present disclosure;

3 is a flow chart of steps of a second embodiment of a data collection method according to the present disclosure;

4 is a schematic structural diagram of Embodiment 1 of a data collection system according to the present disclosure;

FIG. 5 is a schematic structural diagram of Embodiment 2 of a data collection system according to the present disclosure;

FIG. 6 is a schematic structural diagram of Embodiment 3 of a data collection system according to the present disclosure;

FIG. 7 is a schematic diagram showing the hardware structure of an electronic device for data acquisition according to the present disclosure.

Embodiments of the invention

The technical solutions in the embodiments of the present disclosure will be clearly and completely described in conjunction with the drawings in the embodiments of the present disclosure. Some embodiments are disclosed, rather than all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present disclosure without departing from the inventive scope are the scope of the disclosure.

Method embodiment 1

Referring to FIG. 1 , a flow chart of steps of a first embodiment of a data collection method of the present disclosure is shown. include:

Step 101: Store log information of at least one service in a distributed storage manner.

The log information of the service in the embodiment of the disclosure may be stored in a distributed storage manner, that is, the log file is evenly distributed to multiple data servers for storage, and the resources of the data servers are uniformly managed and allocated to the user. A file system access interface is provided, and a large number of log information files that can be effectively solved by the distributed storage method occupy too many resources, resulting in high requirements for multiple storage resources and CPU performance, and can effectively solve log information. Limitations on file size, number of log information files, number of open log information files, etc.

In the embodiment of the present disclosure, the log information may include the user behavior habits and the service information data in the embodiment of the disclosure. For example, the downloading time, the environment initialization time, the source detection time, and the source detection time are included in the transcoded log information. The key frame scan time, the slicing time, the file transcoding time, the audio processing, the subtitle processing time, the finished product detection time, and the like. For example, the media file log information (MediaInfo file) stored in the distributed file system may include: Data information such as code rate, frame rate, size, video duration, audio duration, video format, audio format, number of channels, video bit rate, audio bit rate, and the like.

It can be understood that the above-mentioned transcoding log information and the media file log information are only an example of the log information of the embodiment of the present disclosure, and are not to be understood as the limitation of the log information in the embodiment of the present disclosure. In fact, the log information may include the user. The user-related log information generated by the operation, and the service-related log information generated during the service processing process, the log information is not limited in the embodiment of the present disclosure.

In the embodiment of the present disclosure, the process of performing the distributed storage of the log information may refer to the process of the related distributed storage file information, which is not limited in the embodiment of the present disclosure.

Step 102: Configure a data collection task rule according to the corresponding service requirement, where the data collection task rule corresponds to at least one feature information;

In the embodiment of the present disclosure, the data collection task rule may be pre-defined according to requirements, and the corresponding data collection task rule may be formulated according to the pre-acquired target data and the feature information corresponding to the target data, because the pre-acquired target data may involve one or more Feature information, so the corresponding data collection task rule corresponds to one or more feature information, for example, the target data is the total number of videos successfully uploaded by the Shanghai node within the last month, and the feature information involved includes: regional characteristics The information is: Shanghai, the time range characteristic information is: the most recent month (for example: 2015/10/01 to 2015/11/01), the video upload status characteristic information is: three characteristics information are successfully obtained, and the data collection task rules are corresponding of Corresponding to the three feature information, the corresponding data collection task rule can be: the video with the geographical feature information is Shanghai, and the video upload time is between 2015/10/01 and 2015/11/01, and the video upload status is successful. quantity;

In the embodiment of the present disclosure, the user may configure the data collection task rule on the user interaction interface. For example, the service needs to count the total amount of videos successfully uploaded by the Shanghai node within the last month, that is, the target data is the latest one. Within the month, the total number of videos successfully uploaded by the Shanghai node video is configured on the user interaction interface. The above data collection task rule is the statistical geographical feature information for Shanghai, and the video upload time is from 2015/10/01 to 2015/11/ 01, and the video upload status is the number of successful videos, correspondingly, you can configure the feature information: the regional feature information is: Shanghai, the time range feature information is: the most recent month (for example: 2015/10/01 to 2015/11 /01), the video upload status feature information is: success.

It can be understood that the configuration of the data collection task rule by using the user interaction interface is only one way of configuring the data collection task rule in the embodiment of the present disclosure, and is not understood as a kind of configuration data collection task rule in the embodiment of the present disclosure. The configuration of the data collection task rule is not limited by the configuration of the data collection task rule in the embodiment of the present disclosure.

Step 103: Collect target data from the stored log information according to the data collection task rule.

In an optional embodiment of the present disclosure, the step 103 of collecting the target data from the stored log information according to the data collection task rule may include:

Step A1: Obtain target log information of the corresponding service from the stored log information.

Step A2: Parse the target log information to collect the target data from the parsing result according to the data collection task rule. due to

In the embodiment of the present disclosure, the log information storage server may store log information of multiple services, such as an upload task, a download task, a storage task, and a transcoding task, etc., therefore, the empty page extracts the target of the corresponding service according to the service type. Log information, for example, if the service type is uploaded, the log information corresponding to the upload task in the log information storage server is the target log information.

In the embodiment of the present disclosure, the log information is obtained by parsing the log information, for example, the obtained log information corresponding to the upload service is: 2015-10-20 10:00:30 User=1001upload a file IP=10.80.25.32 success, the parsing result obtained by parsing the log information is: upload date: 2015-10-20; upload time: 10:00:30; user: 1001; IP: 10.80.25.32 Upload status: success; and collect the target data from the parsing result according to the data collection task rule, that is, analyze the parsing result according to the data task collection rule to collect the target data, for example, the data collection task rule is a statistical regional feature. If the number of videos whose video upload date is from 2015/10/01 to 2015/11/01 and the video upload status is successful, you can perform traversal analysis on the analysis result of the obtained log information, and the statistics meet the IP. The address corresponds to Shanghai, and the upload date is between 2015/10/01 and 2015/11/01, and the number of log messages with the status of success is the result of collecting the final target data.

It can be understood that the foregoing data collection task rule is that the number of videos whose statistical geographical feature information is Shanghai and the video upload date is between 2015/10/01 and 2015/11/01 and the video upload status is successful is only as an embodiment of the present disclosure. An example of the data collection task rule is not understood as a limitation on the data collection task rule in the embodiment of the present disclosure. In fact, the data collection task rule can be set by a person in the field according to business requirements, for example, a service. You need to collect the number of failed video uploads in user B. The corresponding data collection task rule is: the user feature information is user A, and the time range feature information is time period B, and the upload status is failed log information. Total; embodiments of the present disclosure do not define data collection task rules herein.

Step 104: Store the target data collection result.

In an optional embodiment of the present disclosure, the embodiment of the present disclosure may further include:

Receiving log information uploaded by at least one service; and/or,

Reading log information from the at least one service.

That is, the embodiment of the present disclosure may access the service log information storage medium of the service, and read the log information from the service log information storage medium; or receive the log information uploaded by the service through the API interface. The disclosed embodiment does not limit the manner in which the log information is acquired.

In the embodiment of the present disclosure, data can be collected from the log information, and the collected result can cover the data of the user, the content, the production process, and the research and development index, and then analyze the data to obtain more detailed data analysis, such as Obtaining user activity map analysis, user refinement operation, and the like. For example, referring to FIG. 2, a schematic diagram of a user activity map in the embodiment of the present disclosure is shown, which uses an application according to the collected data for a certain user. All log information generated is collected and analyzed.

In summary, a data collection method provided in an embodiment of the present disclosure, on the one hand, uses a distributed storage manner to store log information, which can effectively reduce performance requirements for a single CPU and resources, and reduce the cost of data collection; In an aspect, the embodiment of the present disclosure can collect the target data according to the configured data collection task rule by parsing the log information. Since a large amount of log information includes a large amount of user data, user operation behavior data, and service data, the collection result is collected. It not only enriches the data center platform, but also enables effective analysis of user behavior habits and business operations based on data collection results to better understand user needs, thereby providing users with more personalized services and better improving the service platform. .

Method embodiment two

Referring to FIG. 3, a flow chart of the steps of the second embodiment of the data collection method of the present disclosure is shown, which may include:

Step 301: Store log information of at least one service in a distributed storage manner.

Step 302: Configure a data collection task rule according to the corresponding service requirement; the data collection task rule corresponds to at least one feature information; wherein the data collection task further includes: data collection interface information;

Step 303: Collect target data from the stored log information according to the data collection task rule.

Step 304: Collect target data from the database according to the data collection task rule; and/or

Collecting target data from the text file according to the data collection task rule;

Step 305: Store the target data collection result.

With respect to the first embodiment of the present disclosure, a step 304 is added in the embodiment of the present disclosure, in which the target data can be collected from a database, and/or a text file, that is, the data may be based on multiple data sources in the embodiment of the present disclosure. Data collection and data collection results are more abundant.

In the embodiment of the present disclosure, the data collection interface information may include: a name of the data source, a data storage manner, and a data storage format, where the data storage manner may include: a storage type and a storage location of the data, and the storage type may include: a database Type, for example: My sql, Oracle, etc., text type, such as: txt, syslog, etc., log information, such as: web log, operating system log, etc.; for database type data, the data collection interface information can also indicate the database where Host IP address, Database name, user name, password; for text type data, the data collection interface information may also indicate the storage path of the file; the data storage format refers to the format of the data itself, and for the database data, the above database storage format includes the data to be read. Data table name, field name, primary key information; for the text type, the above database storage format mainly includes the file name, and keyword information.

In the following, by way of example, in the embodiment of the present disclosure, data is collected from a database to illustrate:

For example, the business needs to collect the source data from the production database, that is, the data collection interface information may include: data source: production database, data storage type: My sql, data storage location: upload task table and other information, from the above The source data uploading data is collected in the uploading task table of the production database, and the data may include: file size, file name, uploading user, uploading client IP, starting uploading time, uploading completion time, storage node, and the like.

In the embodiment of the present disclosure, the data source of the current data collection task may be determined according to the data collection interface information as a database, or a text file, or log information.

In an optional embodiment of the disclosure, the foregoing method may further include:

Storing database data information of at least one service in a distributed storage manner; and/or

The distributed storage mode is used to store text file information of at least one service.

That is, in the embodiment of the present disclosure, the data information and the text file stored in the database may also be stored in a distributed storage manner, so that the requirements for the performance of the CPU and resources of the single machine can be reduced, thereby saving the cost of data collection.

For the method embodiments, for the sake of brevity, they are all described as a series of action combinations, but those skilled in the art should understand that the embodiments of the present application are not limited by the described action sequence, because the embodiment according to the present application Some steps can be performed in other orders or at the same time. Secondly, those skilled in the art should also understand that the actions involved in the embodiments described in the specification are not necessarily required in the embodiments of the present application.

Device embodiment 1

Referring to FIG. 4, a schematic structural diagram of Embodiment 1 of a data collection system of the present disclosure is shown, which may include: a log information storage module 401, a data collection task configuration module 402, a log data collection module 403, and a target data storage module 404. ;

The log information storage module 401 can be configured to store log information of at least one service in a distributed storage manner.

The data collection task configuration module 402 can be configured to configure a data collection task rule according to the corresponding service requirement; wherein the data collection task rule corresponds to at least one feature information;

The log data collection module 403 may be configured to collect target data from the log information stored in the log information storage module 401 according to the data collection task rule; and

The target data storage module 304 may be configured to store the target data output by the log data collection module.

Device embodiment 2

Referring to FIG. 5, a schematic structural diagram of Embodiment 1 of a data collection system according to the present disclosure is shown, which may include: a log information storage module 501, a data collection task configuration module 502, a log data collection module 503, and a target data storage module 504. ;

The log information storage module 501 can be configured to store log information of at least one service in a distributed storage manner.

The data collection task configuration module 502 can be configured to configure a data collection task rule according to the corresponding service requirement; wherein the data collection task rule corresponds to at least one feature information;

The log data collection module 503 may be configured to collect target data from the log information stored in the log information storage module 501 according to the data collection task rule; and

The target data storage module 504 can be configured to store the target data output by the log data collection module.

The log data collection module 503 may include: a log information obtaining submodule 4031 and a log information parsing submodule 5032;

The log information obtaining sub-module 5031 may be configured to obtain target log information of the corresponding service from the log information storage module.

The log information parsing sub-module 5032 may be configured to parse the target log information acquired by the log information obtaining sub-module to collect the target data from the parsing result according to the data collecting task rule.

Device embodiment three

Referring to FIG. 6, a schematic structural diagram of a third embodiment of a data collection system according to the present disclosure is shown, which may include: a log information storage module 601, a data collection task configuration module 602, and a log data collection module. 603, a database data collection module 604, a text file data collection module 605, and a target data storage module 606,

The log information storage module 601 can be configured to store log information of at least one service in a distributed storage manner.

The data collection task configuration module 602 can be configured to configure a data collection task rule according to the corresponding service requirement; wherein the data collection task rule corresponds to at least one feature information;

The log data collection module 603 may be configured to collect target data from the log information stored in the log information storage module 601 according to the data collection task rule;

The target data storage module 606 may be configured to store the target data output by the log data collection module;

The database data collection module 604 can be configured to collect target data from the database according to the data collection task rule; and

The text file data collection module 605 may be configured to collect target data from the text file according to the data collection task rule;

The data storage module 606 is further configured to store the database data collection module 604 and the target data output by the text file data collection module 605.

a database data storage module, configured to store database data information of at least one service in a distributed storage manner; and/or

The text file data storage module can be configured to store the text file information of at least one service in a distributed storage manner.

For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

The embodiment of the present application provides a non-transitory computer storage medium, where the computer storage medium stores computer executable instructions for performing the data collection method in any of the embodiments of the present application.

7 is a schematic diagram showing the hardware structure of an electronic device for data acquisition according to the present disclosure, as shown in FIG. The electronic device includes:

One or more processors 710 and memory 720, one processor 710 is taken as an example in FIG.

The apparatus for performing the data collection method may further include: an input device 730 and an output device 740.

The processor 710, the memory 720, the input device 730, and the output device 740 may be connected by a bus or other means, as exemplified by a bus connection in FIG.

The memory 720 is used as a non-transitory computer readable storage medium, and can be used for storing a non-transitory software program, a non-transitory computer executable program, and a module, such as a program instruction corresponding to the data collection method in the embodiment of the present application. / Module (for example, each module shown in Figures 4-6). The processor 710 executes various functional applications and data processing of the server by running non-transitory software programs, instructions, and modules stored in the memory 720, that is, implementing the data acquisition method of the above method embodiment.

The memory 720 may include a storage program area and an storage data area, wherein the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created according to usage of the data collection device, and the like. Moreover, memory 720 can include high speed random access memory, and can also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 720 can optionally include memory remotely located relative to processor 710, which can be connected to the data collection device over a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

Input device 730 can receive input numeric or character information and generate key signal inputs related to user settings and function control of the data collection device. The output device 740 can include a display device such as a display screen.

The one or more modules are stored in the memory 720, and when executed by the one or more processors 710, perform the data collection method in any of the above method embodiments.

The above products can perform the methods provided by the embodiments of the present application, and have the corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the method provided by the embodiments of the present application.

The electronic device of the embodiment of the present application exists in various forms, including but not limited to:

(1) Mobile communication devices: These devices are characterized by mobile communication functions and are mainly aimed at providing voice and data communication. Such terminals include: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones.

(2) Ultra-mobile personal computer equipment: This type of equipment belongs to the category of personal computers, has computing and processing functions, and generally has mobile Internet access. Such terminals include: PDAs, MIDs, and UMPC devices, such as the iPad.

(3) Portable entertainment devices: These devices can display and play multimedia content. Such devices include: audio, video players (such as iPod), handheld game consoles, e-books, and smart toys and portable car navigation devices.

(4) Server: A device that provides computing services. The server consists of a processor, a hard disk, a memory, a system bus, etc. The server is similar to a general-purpose computer architecture, but because of the need to provide highly reliable services, processing power and stability High reliability in terms of reliability, security, scalability, and manageability.

(5) Other electronic devices with data interaction functions.

The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, ie may be located A place, or it can be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of the embodiment. Those of ordinary skill in the art can understand and implement without deliberate labor.

Through the description of the above embodiments, those skilled in the art can clearly understand the implementations. The method can be implemented by means of software plus a general hardware platform, and of course, also through hardware. Based on such understanding, the above technical solutions may be embodied in the form of software products in essence or in the form of software products, which may be stored in a computer readable storage medium such as a ROM/RAM or a disk. , an optical disk, etc., includes instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) to perform the methods described in the various embodiments or portions of the various embodiments described above.

The above embodiments are only used to illustrate the technical solutions of the present disclosure, and are not intended to be limiting; although the present disclosure has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that The technical solutions are described as being modified, or equivalent to some of the technical features are replaced; and such modifications or substitutions do not depart from the scope of the technical solutions of the embodiments of the present disclosure.

Industrial applicability

The present application solves the problem that the data collected by the related data collection method is not rich enough for the user behavior, can enrich the data center platform, and can provide users with more humanized services according to the data collection results, and further improve the service platform.

Claims

A data collection method is applied to an electronic device, and the method includes:

Collecting log information of at least one service in a distributed storage manner;

Configuring a data collection task rule according to the corresponding service requirement; wherein the data collection task rule corresponds to at least one feature information;

Collecting target data from the stored log information according to the data collection task rule;

The target data collection result is stored.
The method of claim 1, wherein the collecting target data from the stored log information according to the data collection task rule comprises:

Obtaining target log information of the corresponding service from the stored log information;

Parsing the target log information to collect the target data from the parsing result according to the data collection task rule.
The method of claim 1, wherein the data collection task further comprises: data collection interface information; and the method further comprises:

Collecting target data from the database according to the data collection task rule; and/or

The target data is collected from the text file according to the data collection task rule.
The method of claim 3, wherein the method further comprises:

Storing database data information of at least one service in a distributed storage manner; and/or

The distributed storage mode is used to store text file information of at least one service.
The method of claim 1 wherein the method further comprises:

Receiving log information uploaded by at least one service; and/or,

Reading log information from the at least one service.
A data collection system, comprising: a log information storage module, a data collection task configuration module, a log data collection module, and a target data storage module;

The log information storage module is configured to store log information of at least one service in a distributed storage manner;

The data collection task configuration module is configured to configure a data collection task rule according to the corresponding service requirement; wherein the data collection task rule corresponds to at least one feature information;

The log data collection module is configured to collect target data from the log information stored in the log information storage module according to the data collection task rule; and

The target data storage module is configured to store the target data output by the log data collection module.
The system of claim 6, wherein the log data collection module comprises: a log information acquisition submodule and a log information parsing submodule;

The log information obtaining sub-module is configured to obtain target log information of the corresponding service from the log information storage module;

The log information parsing sub-module is configured to parse the target log information acquired by the log information obtaining sub-module to collect the target data from the parsing result according to the data collecting task rule.
The system of claim 6, wherein the data collection task further comprises: data collection interface information; and the system further comprises: a database data acquisition module, and/or a text file data acquisition module;

The database data collection module is configured to collect target data from the database according to the data collection task rule; and/or

The text file data collection module is configured to learn from the text according to the data collection task rule The target data is collected in this document;

The data storage module is further configured to store the database data collection module, and/or the target data output by the text file data collection module.
The system of claim 8 wherein said system further comprises:

a database data storage module configured to store database data information of at least one service in a distributed storage manner; and/or

The text file data storage module is configured to store the text file information of the at least one service in a distributed storage manner.
The system of claim 6 wherein said apparatus further comprises:

Receiving a log information module, configured to receive log information uploaded by at least one service; and/or,

Reading a log information module, configured to read log information from the at least one service.
A non-transitory computer readable storage medium storing computer executable instructions that, when executed by an electronic device, cause the electronic device to perform the method of any of claims 1-5.
A computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, when the program instructions are executed by a computer, causing the computer The method of any of claims 1-5.
An electronic device comprising at least one processor and a memory communicatively coupled to the at least one processor, the memory for storing instructions executable by the at least one processor, the instructions being processed by the at least one When executed, the at least one processor is caused to perform the method of any of claims 1-5.