CN117768463A - Method and device for simulating cloud mobile phone, electronic equipment and storage medium - Google Patents

Abstract

The disclosure provides a method, a device, electronic equipment and a storage medium for simulating a cloud mobile phone, relates to the technical field of data processing, and particularly relates to the fields of big data, cloud computing and cloud service. The specific implementation scheme is as follows: in response to receiving a simulation request from a target device and detecting that historical simulation parameters for the target device are not stored in a database, selecting a plurality of first parameters corresponding to a plurality of first categories in a first set of categories to be simulated from the database; generating a plurality of second parameters according to a plurality of preset generation rules corresponding to a plurality of second categories in a second category set to be simulated; determining target simulation parameters according to the first parameters and the second parameters; and outputting the target simulation parameters so as to simulate the target device as a cloud mobile phone based on the target simulation parameters.

Description

Method and device for simulating cloud mobile phone, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of data processing technology, and in particular, to the field of big data, cloud computing, and cloud service, and more particularly, to a method, an apparatus, an electronic device, a storage medium, and a computer program product for simulating a cloud mobile phone.

Background

The cloud mobile phone is a mobile phone which applies a cloud computing technology to network terminal services. In practical application, some application programs can detect whether the equipment running the application program is a real mobile phone, and if the equipment is detected to be a non-real mobile phone, the situations of blocking the account of the application program, stopping running the application program and the like can occur.

Therefore, some protection means are needed to simulate the relevant parameters of the equipment, so that the application program normally runs in the equipment.

Disclosure of Invention

The present disclosure provides a method, apparatus, electronic device, storage medium, and computer program product for simulating a cloud mobile phone.

According to an aspect of the present disclosure, there is provided a method of simulating a cloud mobile phone, including: in response to receiving a simulation request from a target device and detecting that historical simulation parameters for the target device are not stored in a database, selecting a plurality of first parameters corresponding to a plurality of first categories in a first set of categories to be simulated from the database; generating a plurality of second parameters according to a plurality of preset generation rules corresponding to a plurality of second categories in a second category set to be simulated; determining target simulation parameters according to the first parameters and the second parameters; and outputting the target simulation parameters so as to simulate the target device as a cloud mobile phone based on the target simulation parameters.

According to another aspect of the present disclosure, there is provided an apparatus for simulating a cloud mobile phone, including: the device comprises a first determining module, a second determining module and an output module. The first determining module is used for responding to the simulation request from the target equipment, detecting that the historical simulation parameters for the target equipment are not stored in the database, and selecting a plurality of first parameters corresponding to a plurality of first categories in a first category set to be simulated from the database; and generating a plurality of second parameters according to a plurality of preset generation rules corresponding to a plurality of second categories in the second category set to be simulated. The second determining module is used for determining target simulation parameters according to the first parameters and the second parameters. The output module is used for outputting the target simulation parameters so as to simulate the target equipment into the cloud mobile phone based on the target simulation parameters.

According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the methods provided by the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method provided by the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method provided by the present disclosure.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

fig. 1 is an application scenario schematic diagram of a method and apparatus for simulating a cloud handset according to an embodiment of the disclosure;

FIG. 2 is a schematic flow chart of a method of emulating a cloud handset according to an embodiment of the disclosure;

FIG. 3 is a schematic flow chart of a method of emulating a cloud handset according to an embodiment of the disclosure;

FIG. 4 is a schematic diagram of a method of emulating a cloud handset, according to an embodiment of the disclosure;

FIG. 5 is a schematic block diagram of an apparatus for emulating a cloud handset, according to an embodiment of the present disclosure; and

Fig. 6 is a block diagram of an electronic device for implementing a method of emulating a cloud handset according to an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In some embodiments, a worker can manually configure relevant parameters of the cloud mobile phone according to actual requirements, so as to realize a simulation process. However, in practical applications, a large number of cloud mobile phones are sometimes required to be used, and parameters of each cloud mobile phone need to be different, otherwise, parameters of a plurality of cloud mobile phones are completely the same and can be identified as non-real mobile phones by application programs. The staff configures the relevant parameters of each cloud mobile phone one by one, so that the simulation efficiency is low.

The present disclosure is directed to a method of simulating a cloud handset, the method selecting some first parameters from a database, generating some second parameters based on predetermined rules, and determining target simulation parameters based on the first parameters and the second parameters. And then, the cloud end transmits the target simulation parameters to the equipment, and a simulation process can be realized. The method can simulate parameters such as a system layer, an application layer and the like of the equipment, and send the simulated target simulation parameters to the equipment, so that the cloud mobile phone and the true mobile phone can be operated indiscriminately. In addition, the method can also perform batch simulation of the cloud mobile phones, and the parameters of each cloud mobile phone do not need to be manually configured one by one, so that the efficiency can be improved.

The technical solutions provided by the present disclosure will be described in detail below with reference to the accompanying drawings and specific embodiments.

Fig. 1 is an application scenario schematic diagram of a method and apparatus for simulating a cloud handset according to an embodiment of the disclosure.

It should be noted that fig. 1 is only an example of a system architecture to which embodiments of the present disclosure may be applied to assist those skilled in the art in understanding the technical content of the present disclosure, but does not mean that embodiments of the present disclosure may not be used in other devices, systems, environments, or scenarios.

As shown in fig. 1, a system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and/or wireless communication links, and the like.

The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. The terminal devices 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.

The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result to the terminal device, for example, generate the target simulation parameters according to the simulation request sent by the device 101, and feed back the target simulation parameters to the device 101.

It should be noted that, the method for simulating a cloud mobile phone provided in the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the device for simulating a cloud mobile phone provided by the embodiments of the present disclosure may be generally disposed in the server 105. The method of simulating a cloud handset provided by the embodiments of the disclosure may also be performed by a server or cluster of servers other than the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the apparatus for simulating a cloud mobile phone provided by the embodiments of the present disclosure may also be provided in a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.

It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Fig. 2 is a schematic flow chart of a method of emulating a cloud handset according to an embodiment of the disclosure.

As shown in fig. 2, the method 200 of simulating a cloud mobile phone may include operations S210 to S230, where the method may be performed by a server, and the server may be deployed in a cloud, for example.

In response to receiving the simulation request from the target device and detecting that the historical simulation parameters for the target device are not stored in the database, selecting a plurality of first parameters corresponding to a plurality of first categories in a first set of categories to be simulated from the database in operation S210; and generating a plurality of second parameters according to a plurality of preset generation rules corresponding to a plurality of second categories in the second category set to be simulated.

In operation S220, a target simulation parameter is determined according to the plurality of first parameters and the plurality of second parameters.

In operation S230, the target simulation parameters are output so as to simulate the target device as a cloud handset based on the target simulation parameters.

For example, the historical simulation parameters may represent simulation parameters that have been previously sent to the target device. The database can store the historical simulation parameters of a plurality of devices, can also store the corresponding relation between the historical simulation parameters and the device identifiers, and can judge whether the historical simulation parameters aiming at the target device are stored in the database or not based on the corresponding relation and the device identifiers in the simulation request.

For example, the simulation parameters may include system parameters, kernel parameters, identification parameters, list parameters, setup parameters, and the like. The system parameters may include vendor, model, motherboard model, operating system name, operating system version, processor (CPU), subscriber identity card (SIM card) card slot number, screen size, etc. The kernel parameters may include an initial stack size of the virtual memory, a stack growth limit of the virtual memory, a stack maximum value, and the like. The identification parameters may include a mobile equipment identification code (MEID), an international mobile subscriber identification code (IMSI), an integrated circuit card identification code (ICCD), a mobile phone serial number (IMEI), an anonymous device identifier (OAID), a Serial Number (SN), a bluetooth MAC, etc. The list parameters may include wifi lists, application lists, and the like. The setting parameters may include volume, lock time, alarm clock, power, etc.

In one example, the first set of categories may be preconfigured. The first class of simulation parameters (i.e., first parameters) are simulation parameters that need to be read from the database, for example, vendor, model, motherboard model, application list, etc. may be the first parameters.

For example, one first category is "vendor", another first category is "screen size", simulation data of a plurality of "vendor" categories such as "vendor a", "vendor B", "vendor C", "vendor D" and the like may be stored in the database, simulation data of a plurality of "screen size" categories such as "4 inch", "4.7 inch", "5.5 inch", "6.2 inch" and the like may be also stored, and "vendor a" and "6.2 inch" may be randomly selected from the database as the first parameter.

In one example, a second set of categories may be preconfigured, where the simulation parameters of the second category (i.e., second parameters) are simulation parameters that need to be generated based on a predetermined generation rule, e.g., identification parameters, volume, power, etc. may be second parameters. The predetermined generation rule is determined based on the real handset data.

For example, the predetermined generation rule corresponding to the electric quantity and the volume is to randomly generate a number in the range of 10-90, and the generated electric quantity may be 88, and the electric quantity value 88 is a second parameter.

For another example, the identification parameters may include numbers and case letters, each identification parameter corresponding to a predetermined generation rule defining the number of characters and character categories for each location of the identification parameter, the number of characters may be 15-17, and the character categories may include numbers 0-9, uppercase letters a-Z, lowercase letters a-Z. For example, a certain predetermined generation rule is: generating 10-bit characters, wherein the first 5 bits are numbers, the last 2 bits are uppercase letters, the middle 3 bits are lowercase letters, and the characters can be randomly generated based on the preset generation rule, and the generated identification parameter is a second parameter.

After the first parameter and the second parameter are obtained, the first parameter and the second parameter may be taken as target simulation parameters. In other embodiments, the first parameter and the second parameter may be further filled into a predetermined template, so as to obtain the target simulation parameter, where the template may perform format conversion on the first parameter and the second parameter, so as to facilitate the target device to analyze the target simulation parameter.

After obtaining the target simulation parameters, the server can send the target simulation parameters to the target device, and then when an application program running on the target device detects whether the target device is a real mobile phone, the target device can feed back the target simulation parameters to the application program, so that the normal running of the application program is ensured.

The technical scheme provided by the embodiment of the disclosure selects some first parameters from the database, generates some second parameters based on a predetermined rule, and can determine target simulation parameters based on the first parameters and the second parameters. And then, the server transmits the target simulation parameters to the equipment, so that the simulation process can be realized. The method can simulate parameters such as a system layer, an application layer and the like of the target equipment, and send the simulated target simulation parameters to the target equipment, so that the cloud mobile phone and the true mobile phone can operate indiscriminately. In addition, the method can also perform batch simulation of the cloud mobile phones, and the parameters of each cloud mobile phone do not need to be manually configured one by one, so that the efficiency can be improved.

In another embodiment of the present disclosure, the process of selecting the first parameter may include: the order of the target devices is determined based on the order in which the simulation requests were received, and a plurality of target data sets having categories consistent with the plurality of first categories are also determined from the plurality of data sets. A plurality of first parameters is then determined from the plurality of target data sets according to the order of the target devices and the order of the plurality of simulation parameters in each target data set.

For example, the database stores a plurality of data sets, each data set including a plurality of simulation parameters corresponding to the same first class. For example, the database includes a "vendor" data set and a "screen size" data set, the "vendor" data set including "vendor A", "vendor B", "vendor C", "vendor D". The plurality of simulation parameters in the database have an order. It should be noted that, the simulation parameters in the data set in the database are determined based on the real mobile phone data, for example, data related to a plurality of real mobile phones are summarized and counted, and then common data are used as the simulation parameters in the database.

For example, in the event that a simulation request is received and it is determined that historical simulation parameters for the target device are not stored in the database, the target device is assigned a number that characterizes the order of the target devices, after which the first parameter may be selected from the database in order. For example, the number of a certain target device is number 3, and the third simulation parameter in the "vendor" data set and the "screen size" data set may be used as the first parameter selected.

According to the method and the device, the first parameters are selected from the database according to the numbers of the devices and the sequence of the simulation parameters in the database, so that the selected first parameters have diversity, large-scale repetition is avoided, and the risk that the target device is identified as an abnormal device by an application program is further reduced. In addition, in the process of actually constructing the database, relevant parameters of common real equipment in the market can be summarized based on big data analysis, such as sales, usage and the like of various equipment, and simulation parameters in the database are ordered according to the quantity, for example, if the equipment of a manufacturer A in the market is more than the equipment of a manufacturer B, the simulation parameter 'manufacturer A' in the database is positioned before 'manufacturer B', so that in the process of batch simulation, target equipment can preferentially obtain simulation parameters consistent with the parameters of the common real equipment, and the safety is further improved.

In another embodiment of the present disclosure, the process of generating the second parameter may include: the target number is determined according to a predetermined number range corresponding to the second parameter, and then divided into a first number and a second number. The first number of sub-parameters is then generated according to a predetermined generation rule defining characters in at least one predetermined position of the first number of sub-parameters, and the second number of sub-parameters is also randomly generated. And then determining the first number of sub-parameters and the second number of sub-parameters as the same second parameter.

Taking the second parameter to be generated as the wifi list as an example, a predetermined number range corresponding to the wifi list may be preconfigured to be 10-20, and then the target number is randomly determined to be 15, for example, the 15 may be randomly or according to a predetermined proportion divided into 5 and 10. Then 5 sub-parameters may be generated according to a predetermined generation rule, for example, prefix 1111 or 222 of the 5 sub-parameters, and 5-7 bits of other characters are randomly generated after the prefix. Furthermore, 10 sub-parameters may also be randomly generated, which 10 sub-parameters may be completely random and not generated based on a predetermined generation rule. Thus, 15 sub-parameters representing 15 wifi names can be obtained, and then the 15 sub-parameters can be used as a wifi list.

According to the embodiment of the disclosure, a part of the subparameters are generated based on the preset generation rule, and a part of the subparameters are also generated randomly, so that the second parameter has a certain rule and a certain randomness, the risk that the target equipment is identified as abnormal equipment by the application program is reduced, and the safety is improved.

Fig. 3 is a schematic flow chart of a method of emulating a cloud handset according to an embodiment of the disclosure.

As shown in fig. 3, the method 300 of simulating a cloud mobile phone may include operations S311 to S313 and operations S320 to S350, where operations S310 to S313, operations S320 to S330 may refer to the above, and the description of this embodiment is omitted.

In operation S311, in response to receiving the simulation request from the target device, it is determined whether historical simulation parameters for the target device are stored in the database. If not, operation S312 is entered. If so, operation S350 is entered.

For example, the historical simulation parameters for the target device include a historical dynamic simulation parameter and/or a historical static simulation parameter, and the number of the historical dynamic simulation parameters and the historical static simulation parameters is not limited in this embodiment.

In operation S312, a plurality of first parameters corresponding to a plurality of first categories in a first set of categories to be emulated are selected from a database.

In operation S313, a plurality of second parameters are generated according to a plurality of predetermined generation rules corresponding to a plurality of second classes in a second class set to be simulated.

In operation S320, a target simulation parameter is determined according to the plurality of first parameters and the plurality of second parameters.

In operation S330, the target simulation parameters are output so as to simulate the target device as a cloud handset based on the target simulation parameters.

In operation S340, the target simulation parameters are determined as historical simulation parameters for the target device and stored in the database, so that after receiving the simulation request of the target device again, new target simulation parameters can be determined based on the historical simulation parameters.

In operation S350, the target simulation parameters are determined according to the historical simulation parameters.

It should be noted that, for example, the simulation parameters may include a system parameter, a kernel parameter, an identification parameter, a list parameter, a setting parameter, and the like. The system parameters may include vendor, model, motherboard model, operating system name, operating system version, processor (CPU), SIM card slot number, screen size, etc. The kernel parameters may include an initial stack size of the virtual memory, a stack growth limit of the virtual memory, a stack maximum value, and the like. The identification parameters may include a mobile equipment identification code (MEID), an International Mobile Subscriber Identity (IMSI), ICCD, IMEI, OAID, SN, bluetooth MAC, etc. The list parameters may include wifi lists, application lists, and the like. The setting parameters may include volume, lock time, alarm clock, power, etc.

The above-mentioned respective simulation parameters may be divided into static simulation parameters and dynamic simulation parameters in a manner of whether they are changed or not. The static simulation parameters may represent parameters that are no longer changed after the determination, e.g., vendor, model, motherboard model, MEID, etc., may be static simulation parameters. The dynamic simulation parameters may represent parameters that need to be changed periodically or in real time after the determination, for example, wifi list, application list, electric quantity, etc. may be dynamic simulation parameters.

For example, for the historical static simulation parameters, the historical static simulation parameters for the target device may be read from the database according to the device identification of the target device, and then the historical static simulation parameters are determined as the target simulation parameters.

The problem that the target device is identified as an abnormal device by the application program is easily caused by changing the simulation parameters of the model, manufacturer, and the like of the target device. In the embodiment, the static simulation parameters do not need to be adjusted, and the historical static simulation parameters which are determined before and sent to the target equipment are directly used as the target static simulation parameters in the target simulation parameters, so that the static simulation parameters of the target equipment are prevented from being changed, and the safety is improved. In addition, the static simulation parameters are directly read, and the method does not need to be determined again, so that the computing resources can be saved.

For another example, for historical dynamic simulation parameters, at least one historical dynamic simulation parameter for the target device may be read from a database based on the device identification of the target device. And then generating the target dynamic simulation parameters in the target simulation parameters according to the values of the historical dynamic simulation parameters, the preset generation rules corresponding to the categories of the historical dynamic simulation parameters and the preset updating rules corresponding to the categories of the historical dynamic simulation parameters for each historical dynamic simulation parameter.

Taking electric quantity as an example, the electric quantity value of the historical dynamic simulation parameter is 80, and the predetermined generation rule is as follows: and generating an electric quantity value within 10-90, wherein the generated electric quantity value and the last electric quantity value are smaller than a set threshold value, and the set threshold value can be 2. Predetermined update rules: the amount of electricity is increased. The generated electrical quantity value may be 81, and the electrical quantity value 81 is the target dynamic simulation parameter.

It should be noted that, the dynamic simulation parameters such as the electric quantity of the target device do not change for a long time, which easily causes the problem that the target device is identified as an abnormal device by the application program. The embodiment can adjust the dynamic simulation parameters, thereby improving the safety.

Fig. 4 is a schematic diagram of a method of emulating a cloud handset according to an embodiment of the disclosure.

As shown in fig. 4, in this embodiment, the database 405 may be constructed in advance. For example, system parameters, kernel parameters, identification parameters, list parameters, setting parameters, etc. are analyzed and summarized to obtain effective parameters, which may represent parameters possessed by real devices commonly found in the market. The database 405 may be updated periodically by a worker or by an automatic update program. The staff can also configure information such as a predetermined generation rule, a predetermined update rule, correspondence between each rule and simulation parameter category, and the like.

The plurality of target devices 4011, 4012 may each send a simulation request to the server, taking the target device 4011 as an example. After receiving the emulation request sent by the target device 4011, the server can determine whether a number has been assigned to the target device 4011 based on the number processing logic 402.

If the simulation request of the target device 4011 is received for the first time, the number is allocated to the target device 4011, and the correspondence between the number and the target device 4011 is stored in the storage area 403, and the same physical memory may be used for the storage area 403 and the database 405. Target simulation parameters may also be generated based on the predetermined processing logic 404. Specific implementations of the predetermined processing logic may refer to the above, for example, the above procedure of selecting the first parameter from the database and generating the second parameter based on the predetermined generation rule. After obtaining the target simulation parameters, the server needs to send the target simulation parameters to the target device 4011. In addition, the server may store the generated target simulation parameters to the database 405, and use the target simulation parameters as historical simulation parameters for the target device 4011.

If the server receives the simulation request of the target device 4011 again, the corresponding relationship between the number and the target device 4011 can be queried, and the number allocated to the target device 4011 can be determined. The historical simulation parameters may then be read from the database 405 based on the number, where the historical simulation parameters include a historical static simulation parameter and a historical dynamic simulation parameter, where the historical static simulation parameter is not adjusted and is sent to the target device 4011 again, and the historical dynamic simulation parameter needs to be adjusted based on a predetermined update rule and then sent to the target device 4011. In addition, the historical simulation parameters for the target device 4011 in the database 405 need to be updated.

In addition, the server may send parameter pulling interval information and log reporting interval information to the target device 4011, where the parameter pulling interval information indicates how often the target device 4011 needs to request the target simulation parameters from the server at intervals, and the log reporting interval information indicates how often the target device 4011 needs to report its own log to the server at intervals.

Fig. 5 is a schematic block diagram of an apparatus for simulating a cloud handset according to an embodiment of the disclosure.

As shown in fig. 5, the apparatus 500 for simulating a cloud handset may include a first determining module 510, a second determining module 520, and an output module 530.

The first determining module 510 is configured to, in response to receiving a simulation request from a target device, and detecting that no historical simulation parameters for the target device are stored in the database, select a plurality of first parameters corresponding to a plurality of first categories in a first set of categories to be simulated from the database; and generating a plurality of second parameters according to a plurality of preset generation rules corresponding to a plurality of second categories in the second category set to be simulated.

The second determining module 520 is configured to determine the target simulation parameter according to the plurality of first parameters and the plurality of second parameters.

The output module 530 is configured to output the target simulation parameters so as to simulate the target device as a cloud mobile phone based on the target simulation parameters.

In this embodiment, the database includes a plurality of data sets, each data set including a plurality of simulation parameters corresponding to the same first class. The first determination module includes: an order determination sub-module, a target data set determination sub-module, and a first parameter determination sub-module. The order determination submodule is used for determining the order of the target devices according to the order of the received simulation requests. The target data set determination submodule is used for determining a plurality of target data sets with the category consistent with a plurality of first categories from the plurality of data sets. The first parameter determination sub-module is used for determining a plurality of first parameters from a plurality of target data sets according to the order of the target devices and the order of the plurality of simulation parameters in each target data set.

In this embodiment, the first determining module includes: the device comprises a range determination sub-module, a dividing sub-module, a first sub-parameter determination sub-module, a second sub-parameter determination sub-module and a second parameter determination sub-module. The range determination sub-module is used for determining the target number according to a predetermined number range corresponding to the second parameter. The dividing submodule is used for dividing the target quantity into a first quantity and a second quantity. The first sub-parameter determination sub-module is used for generating a first number of sub-parameters according to a predetermined generation rule, and the predetermined generation rule is used for limiting characters at least one predetermined position in the first number of sub-parameters. The second sub-parameter determination sub-module is configured to randomly generate a second number of sub-parameters. The second parameter determination submodule is used for determining the first number of subparameters and the second number of subparameters as the same second parameter.

In this embodiment, the apparatus further includes: and the third determining module is used for determining the target simulation parameters according to the historical simulation parameters under the condition that the historical simulation parameters aiming at the target equipment are stored in the determining database.

In this embodiment, the historical simulation parameters for the target device include at least one historical dynamic simulation parameter. The third determination module includes: a first reading sub-module and a generating sub-module. The first reading sub-module is used for reading at least one historical dynamic simulation parameter aiming at the target equipment from the database according to the equipment identification of the target equipment. The generation sub-module is used for generating target dynamic simulation parameters in the target simulation parameters according to the values of the historical dynamic simulation parameters, the preset generation rules corresponding to the categories of the historical dynamic simulation parameters and the preset updating rules corresponding to the categories of the historical dynamic simulation parameters for each historical dynamic simulation parameter.

In this embodiment, the historical simulation parameters for the target device include static and dynamic simulation parameters. Determining the target simulation parameters from the historical simulation parameters includes: the second reading sub-module and the determining sub-module. The second reading submodule is used for reading the historical static simulation parameters aiming at the target equipment from the database according to the equipment identification of the target equipment. The determining submodule is used for determining the historical static simulation parameters as target simulation parameters.

In this embodiment, the apparatus further includes: and the storage module is used for determining the target simulation parameters as historical simulation parameters for the target equipment and storing the historical simulation parameters into the database.

According to an embodiment of the present disclosure, the present disclosure also provides an electronic device including at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of emulating a cloud handset described above.

According to an embodiment of the present disclosure, there is also provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of emulating a cloud phone described above.

According to an embodiment of the present disclosure, there is also provided a computer program product comprising a computer program which, when executed by a processor, implements the method of emulating a cloud handset described above.

Fig. 6 is a block diagram of an electronic device for implementing a method of emulating a cloud handset according to an embodiment of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 6, the apparatus 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 may also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other by a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

Various components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, mouse, etc.; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as a method of emulating a cloud handset. For example, in some embodiments, the method of emulating a cloud handset may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into RAM603 and executed by computing unit 601, one or more steps of the method of emulating a cloud handset described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the method of emulating a cloud handset by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.

In the technical scheme of the disclosure, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the personal information of the user accord with the regulations of related laws and regulations, and the public order colloquial is not violated.

In the technical scheme of the disclosure, the authorization or consent of the user is obtained before the personal information of the user is obtained or acquired.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims (17)

1. A method of emulating a cloud handset, comprising:

in response to receiving a simulation request from a target device, and detecting that no historical simulation parameters for the target device are stored in a database,

selecting a plurality of first parameters corresponding to a plurality of first categories in a first category set to be simulated from the database;

generating a plurality of second parameters according to a plurality of preset generation rules corresponding to a plurality of second categories in a second category set to be simulated;

Determining target simulation parameters according to the first parameters and the second parameters; and

and outputting the target simulation parameters so as to simulate the target equipment into a cloud mobile phone based on the target simulation parameters.

2. The method of claim 1, wherein the database comprises a plurality of data sets, each data set comprising a plurality of simulation parameters corresponding to a same first class; the selecting, from the database, a plurality of first parameters corresponding to a plurality of first categories according to the plurality of first categories in the set of first categories to be simulated includes:

determining the order of the target devices according to the order in which the simulation requests are received;

determining a plurality of target data sets having a category consistent with the plurality of first categories from the plurality of data sets; and

the plurality of first parameters is determined from the plurality of target data sets according to the order of the target devices and the order of the plurality of simulation parameters in each target data set.

3. The method of claim 1, wherein the generating a plurality of second parameters according to a plurality of predetermined generation rules corresponding to a plurality of second classes of the second class set to be emulated comprises:

Determining a target number according to a predetermined number range corresponding to the second parameter;

dividing the target number into a first number and a second number;

generating the first number of sub-parameters according to a predetermined generation rule, wherein the predetermined generation rule is used for limiting characters at least one predetermined position in the first number of sub-parameters;

randomly generating a second number of sub-parameters; and

and determining the first number of sub-parameters and the second number of sub-parameters as the same second parameter.

4. A method according to any one of claims 1 to 3, further comprising:

in the event that it is determined that historical simulation parameters for the target device have been stored in the database, determining target simulation parameters from the historical simulation parameters.

5. The method of claim 4, wherein the historical simulation parameters for the target device comprise at least one historical dynamic simulation parameter; determining the target simulation parameters according to the historical simulation parameters comprises:

reading at least one historical dynamic simulation parameter for the target device from the database according to the device identification of the target device; and

And generating target dynamic simulation parameters in the target simulation parameters according to the values of the historical dynamic simulation parameters, the preset generation rules corresponding to the categories of the historical dynamic simulation parameters and the preset updating rules corresponding to the categories of the historical dynamic simulation parameters aiming at each historical dynamic simulation parameter.

6. The method of claim 4, wherein the historical simulation parameters for the target device comprise static dynamic simulation parameters; determining the target simulation parameters according to the historical simulation parameters comprises:

according to the equipment identification of the target equipment, reading historical static simulation parameters aiming at the target equipment from the database; and

and determining the historical static simulation parameters as the target simulation parameters.

7. The method of claim 1, further comprising:

and determining the target simulation parameters as historical simulation parameters for the target equipment, and storing the historical simulation parameters into the database.

8. An apparatus for emulating a cloud handset, comprising:

a first determination module for, in response to receiving a simulation request from a target device, detecting that no historical simulation parameters for the target device are stored in a database,

Selecting a plurality of first parameters corresponding to a plurality of first categories in a first category set to be simulated from the database;

generating a plurality of second parameters according to a plurality of preset generation rules corresponding to a plurality of second categories in a second category set to be simulated;

the second determining module is used for determining target simulation parameters according to the first parameters and the second parameters; and

and the output module is used for outputting the target simulation parameters so as to simulate the target equipment into a cloud mobile phone based on the target simulation parameters.

9. The apparatus of claim 8, wherein the database comprises a plurality of data sets, each data set comprising a plurality of simulation parameters corresponding to a same first class; the first determining module includes:

an order determining submodule, configured to determine an order of the target device according to an order in which the simulation requests are received;

a target data set determination submodule for determining a plurality of target data sets with the category consistent with the plurality of first categories from the plurality of data sets; and

a first parameter determination sub-module for determining the plurality of first parameters from the plurality of target data sets according to the order of the target devices and the order of the plurality of simulation parameters in each target data set.

10. The apparatus of claim 8, wherein the first determination module comprises:

a range determination submodule, configured to determine a target number according to a predetermined number range corresponding to the second parameter;

dividing the target quantity into a first quantity and a second quantity by a sub-module;

a first sub-parameter determination sub-module for generating the first number of sub-parameters according to a predetermined generation rule for defining characters in at least one predetermined position in the first number of sub-parameters;

the second sub-parameter determining sub-module is used for randomly generating a second number of sub-parameters; and

and the second parameter determination submodule is used for determining the first number of subparameters and the second number of subparameters as the same second parameter.

11. The apparatus of any of claims 8 to 10, further comprising:

and the third determining module is used for determining target simulation parameters according to the historical simulation parameters when the historical simulation parameters for the target equipment are stored in the database.

12. The apparatus of claim 11, wherein the historical simulation parameters for the target device comprise at least one historical dynamic simulation parameter; the third determination module includes:

A first reading submodule, configured to read at least one historical dynamic simulation parameter for the target device from the database according to the device identifier of the target device; and

the generation sub-module is used for generating target dynamic simulation parameters in the target simulation parameters according to the values of the historical dynamic simulation parameters, the preset generation rules corresponding to the categories of the historical dynamic simulation parameters and the preset updating rules corresponding to the categories of the historical dynamic simulation parameters for each historical dynamic simulation parameter.

13. The apparatus of claim 11, wherein the historical simulation parameters for the target device comprise static dynamic simulation parameters; determining the target simulation parameters according to the historical simulation parameters comprises:

the second reading submodule is used for reading historical static simulation parameters aiming at the target equipment from the database according to the equipment identification of the target equipment; and

and the determining submodule is used for determining the historical static simulation parameters as the target simulation parameters.

14. The apparatus of claim 8, further comprising:

and the storage module is used for determining the target simulation parameters as historical simulation parameters aiming at the target equipment and storing the historical simulation parameters into the database.

15. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 7.

16. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1 to 7.

17. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.