TWI879074B - Operating method for electronic apparatus for processing information and electronic apparatus supporting thereof - Google Patents

Abstract

According to the present invention, an information processing method is disclosed, which processes request information by an electronic device, and includes the following steps: setting a request information processing model related to the processing of request information obtained by a service; and processing the request information obtained by the above-mentioned service based on at least one processing model included in the above-mentioned request information processing model.

Description

Operation method of electronic device for processing information and electronic device supporting the same

The present invention relates to a method and device for processing information, and more specifically, to a method and electronic device for processing request information obtained through a service.

With the development of electronic technology, e-commerce has become a field of shopping. Customers can buy items online even if they do not go directly to shopping malls or markets. Items purchased online will be delivered to the delivery location requested by the customer.

In the field of e-commerce, since the processing of detailed and accurate information about products will have a significant impact on service satisfaction, various solutions for more detailed and accurate information processing are being discussed.

For related content, please refer to previous documents such as KR101756594B1 or KR101500849B1.

According to the method of the present invention, the electronic device can process the request information obtained through the service by setting the request information processing model.

The technical topics that this invention intends to achieve are not limited to the above-mentioned technical topics. People with common sense in the technical field to which this invention belongs can clearly understand other technical topics not mentioned based on the following description.

Various embodiments may provide an operation method of an electronic device for information processing and an electronic device supporting the same.

An information processing method of various embodiments, which processes request information by an electronic device, includes: setting a request information processing model related to the processing of request information obtained by a service; and processing the request information obtained by the service based on at least one processing model included in the request information processing model, and the request information processing model may include the following models: a first processing model, which limits the number of request information to be processed per unit time to less than a first critical number in each server included in one or more servers associated with the service; a second processing model, which corresponds to a plurality of APIs (Application Programming Interfaces) corresponding to the service. A specific API group in a plurality of first API groups classified by importance according to application programming interfaces (APIs) limits the number of request information to be processed per unit time in each of the above servers to less than a second critical number; and a third processing model, which corresponds to each API group included in a plurality of second API groups classified by resource usage according to the above plurality of APIs, limits the number of request information to be processed to less than each critical number set for each of the above API groups.

In the exemplary embodiment, the request information processing model may include the following models: The fourth processing model corresponds to the user of the above service and limits the number of request information to be processed per unit time to less than the third critical number.

In the exemplary embodiment, the number of request information obtained from the above-mentioned user per unit time can be confirmed by an external cache corresponding to the above-mentioned one or more servers.

In the exemplary embodiment, the number of request information obtained from the user per unit time can be confirmed based on the identification information of the user and the information of the API being used by the user.

In the exemplary embodiment, the above information processing method may further include the following steps: confirming the information of the above API by using the API identifier.

In the exemplary embodiment, the request information processing model may include the following models: The fifth processing model, which interrupts the processing of all request information obtained through the above service.

In the exemplary embodiment, the following request information may be refused to be processed: the number of request information exceeding the critical number limited by each processing model included in the above request information processing model.

In the exemplary embodiment, the information processing method may further include the following steps: setting each processing model state identification information corresponding to each processing model included in the request information processing model; and based on the each processing model state identification information, confirming the number of request information rejected for processing according to each processing model.

In the exemplary embodiment, the at least one processing model can be selected based on the first input of the administrator corresponding to the electronic device.

In the exemplary embodiment, the first critical number, the second critical number, and the critical numbers for each of the API groups can be set based on the second input of the administrator corresponding to the electronic device.

In the exemplary embodiment, the first critical number, the second critical number, and the critical numbers for each of the API groups can be set based on the environmental parameter information related to the service.

In an exemplary embodiment, the environmental parameter information may include at least one of information about the number of the one or more servers, information about the total resource capacity used for the service, and information about whether to conduct promotions on the service for which the request information is expected to increase or decrease.

In the exemplary embodiment, the information processing method further includes the following steps: setting a layer structure corresponding to the request information processing model; and based on the layer structure, the request information processing model can be applied to the algorithm used for the action of the electronic device.

A non-transitory computer-readable recording medium of various embodiments records a program for executing an information processing method in a computer, wherein the information processing method comprises the following steps: setting a request information processing model related to processing of request information obtained through a service; and processing the request information obtained through the service based on at least one processing model included in the request information processing model; and the request information processing model may include the following models: a first processing model, which limits the number of request information to be processed per unit time to less than a first critical number in each server included in one or more servers associated with the service; a second processing model, which corresponds to a plurality of APIs (Application Programming Interfaces) corresponding to the service. Interfaces) according to the importance of a specific API group in the first plurality of API groups, in each of the above servers, limiting the number of request information to be processed per unit time to less than the second critical number; and a third processing model, corresponding to each API group included in the second plurality of API groups classified according to the resource usage of the above plurality of APIs, limiting the number of request information to be processed to less than each critical number set for each of the above API groups.

An electronic device of various embodiments, which processes request information, includes: a processor; and one or more memories storing one or more instructions; when the one or more instructions are executed, the processor is controlled to perform the following steps: setting a request information processing model related to the processing of request information obtained through a service; and based on the request information At least one processing model included in the processing model processes the request information obtained by the above service; the above request information processing model may include the following models: a first processing model, which limits the number of request information to be processed per unit time to less than a first critical number in each server included in one or more servers associated with the above service; a second processing model, which corresponds to a plurality of APIs (Application Programming Interfaces) corresponding to the above service. Programming Interfaces) classifies the above-mentioned multiple APIs according to the importance of a specific API group in the first API group, and limits the number of request information to be processed per unit time in each of the above-mentioned servers to less than the second critical number; and a third processing model, which corresponds to each API group included in the second API group that classifies the above-mentioned multiple APIs according to the resource usage, and limits the number of each request information to be processed to less than each critical number set for each of the above-mentioned API groups.

The various embodiments of the present invention described above are only part of the preferred embodiments of the present invention. People with common sense in the technical field can derive and understand various embodiments reflecting the technical features of the various embodiments of the present invention based on the detailed descriptions described below.

The present invention proposes a method for an electronic device to process request information obtained through a service by setting a request information processing model, which has the technical effect of efficiently implementing the processing of request information.

The effects that can be obtained in this invention are not limited to the above effects. People with common sense in the technical field to which this invention belongs can clearly understand other technical effects not mentioned based on the following description.

100: Electronic devices

200: User device

210: Input/output department

220: Communications Department

230: Storage

240:Processor

300: Server device

301: Communication equipment

303: Control Department

305:Memory

401:Action

403:Action

500: Request information received from multiple users of the service is processed by one or more servers associated with the service

600: The request information obtained from multiple users using the service is divided into the request information obtained corresponding to the API group with higher importance on the service and the request information obtained corresponding to the API group with lower importance, and the request information obtained corresponding to each API group can be processed by one or more servers associated with the service

700: Classify request information obtained from multiple users using the service into request information corresponding to an API group with higher resource usage, request information corresponding to an API group with medium to high resource usage, and request information corresponding to an API group with lower resource usage, and process the request information corresponding to each API group by one or more servers associated with the service

800: Separate request information obtained from multiple users using the service into request information corresponding to each user, and process the request information corresponding to each user by one or more servers associated with the service

801: The number of request messages corresponding to specific users distinguished by identification information shall not exceed 20 per minute

803: Set up an external cache that corresponds to more than one server

900: Prevent all request information obtained through the service from being processed by each server.

1001: Setting the 1st to 5th processing models

1003: Set the display layer (Facade Layer) structure that can apply the above-mentioned first processing model to the above-mentioned fifth processing model

1005: Bucket4J core algorithm

1101: Set the 5th processing model to off

1103-1: The number of request messages that need to be processed every minute is more than 100,000

1103-2: Limit the number of request messages to be processed per minute to less than 10,000

1201: Set the 5th processing model to off

1203-1: Limit the number of request messages to be processed per minute to 10,000.

1203-2: Limit the number of request messages to be processed per minute to 10,000.

1205-1: The number of request information obtained from users is more than 20 per minute, or the number of inputs used for request information obtained from users is more than 20 per minute

1205-2: Limit the number of request messages to be processed per minute for this user to less than 20.

1301: Set the 5th processing model to off

1303-1: Limit the number of request messages to be processed per minute to 10,000.

1303-2: Limit the number of request messages to be processed per minute to 10,000.

1305-1: Limit the number of request messages to be processed per minute for this user to less than 20.

1305-2: Limit the number of request messages to be processed per minute for this user to less than 20.

1307-1: Deemed excessive

1307-2: Limit the number of request information to be processed per unit time to less than 8,000. For API groups with higher importance, each server can process 2,000 request information per unit time.

1401: Set the 5th processing model to off

1403-1: Limit the number of request messages to be processed per minute to 10,000.

1403-2: Limit the number of request messages to be processed per minute to 10,000.

1405-1: Limit the number of request messages to be processed per minute for this user to less than 20.

1405-2: Limit the number of request messages to be processed per minute for this user to less than 20.

1407-1: Limit the number of request information to be processed per unit time to less than 8,000. For API groups with higher importance, each server can process 2,000 request information per unit time.

1407-2: Limit the number of request information to be processed per unit time to less than 8,000. For API groups with higher importance, each server can process 2,000 request information per unit time.

1409-1: Determined to have exceeded the resource capacity allocated to the API group with higher resource usage

1409-2: Based on the third processing model, for the resource capacity allocated to the API group with higher resource usage, the request information processing of the API group is limited to a critical number of processable request information within 1,000. For the API group with higher resource usage, a maximum of 1,000 request information can be processed.

FIG1 is a diagram of an information processing system for illustrating the operation method of an electronic device for information processing that can implement various embodiments.

FIG2 is a diagram showing the configuration of device nodes of various embodiments.

FIG3 is a structural diagram of an electronic device for implementing the information processing method proposed by the present invention.

FIG. 4 is a diagram showing the operation method of the electronic device for information processing in various embodiments.

FIG5 is a diagram showing an example of the first processing model included in the setting request information processing model.

FIG6 is a diagram showing an example of a second processing model included in the setting request information processing model.

FIG. 7 is a diagram showing an example of a third processing model included in the setting request information processing model.

FIG8 is a diagram showing an example of the fourth processing model included in the setting request information processing model.

FIG. 9 is a diagram showing an example of the fifth processing model included in the setting request information processing model.

FIG. 10 is a diagram showing an example of a layer structure for applying the request information processing model to an algorithm for the operation of the electronic device 100.

Figures 11 to 14 are diagrams showing an example of processing request information based on a request information processing model including the first processing model to the fifth processing model.

The following embodiments combine the components and features of various embodiments in a specific form. Unless otherwise explicitly stated, each component or feature can be considered to be optional. Each component or feature can be implemented in a form that is not combined with other components or features. In addition, some components and features can be combined to form various embodiments. The order of the actions described in various embodiments can be changed. Some components or features of a certain embodiment can be included in other embodiments, or can replace the corresponding components or features of other embodiments.

In the description of the drawings, no procedures or steps are described that may confuse the main points of various embodiments, nor are any procedures or steps that can be understood by a person with common sense in the technical field.

Throughout the specification, when a certain component is described as "comprising or including" a certain component, if there is no special content to the contrary, it means that other components can be further included, but other components are not excluded. In addition, the terms "...part", "...device", "module" and the like described in the specification refer to a unit that processes at least one function or action, which can be implemented by hardware, software, or a combination of hardware and software. In addition, in the text describing various embodiments (especially in the scope of the invention application below), if there is no other indication in this specification or no clear rebuttal in the text, "a (or an)", "one (one)", "the (the)" and similar related words can be used in a meaning including both the singular and the plural.

Below, with reference to the attached drawings, the preferred implementation methods of various embodiments are described in detail. The detailed description disclosed below together with the attached drawings is an explanation of the exemplary implementation methods of various embodiments, and is not intended to represent the only implementation method.

In addition, the specific terms used in various embodiments are provided to help understand the various embodiments. The use of such specific terms can be changed into other forms without departing from the technical ideas of the various embodiments.

FIG. 1 is a diagram of an information processing system for illustrating the operation method of an electronic device for information processing that can implement various embodiments.

Referring to FIG. 1 , the information processing system of various embodiments can be implemented in various types of devices. For example, the information processing system can be implemented in an electronic device 100 related to the service, a user device 200 capable of utilizing the service, and a server device 300 used for the service. In other words, the electronic device 100 related to the service, the user device 200, and the server device 300 can implement the actions of various embodiments of the present invention based on the information processing system implemented in each device. On the other hand, the information processing system of various embodiments is not limited to that shown in FIG. 1 above, but can also be implemented in more diverse devices.

The electronic device 100 of various embodiments may correspond to the following device, which implements the information processing method proposed in the present invention related to the service and manages the processing of information sent and received between the user device 200, the server device 300 and the service. In the present invention, the electronic device 100 may be configured to include the functions of the user device 200 or the server device 300.

The user device 200 of various embodiments may be a device that can be used by a personal user, such as a desktop computer, a tablet computer, a mobile terminal, etc. In addition, other devices that implement similar functions may also be used as the user device 200.

The server device 300 of various embodiments may be a device that performs wireless and wired communication with a plurality of user devices 200 and includes a storage device with a large unit of storage capacity. For example, the server device 300 may include a cloud device connected to a plurality of user devices 200.

The information processing system of various embodiments may include various modules for actions. The modules included in the information processing system may be computer codes or one or more instructions for a specified action that can be performed by a physical device (e.g., electronic device 100, user device 200, and server device 300) that implements the information processing system (or, included in the physical device). In other words, the physical device that implements the information processing system stores multiple modules in the form of computer codes in the memory, and when executing the multiple modules stored in the memory, the multiple modules can be implemented by the physical device to perform the specified actions corresponding to the multiple modules.

FIG2 is a diagram showing the configuration of device nodes of various embodiments.

The device node of FIG. 2 may include an electronic device 100, a user device 200, and a server device 300 constituting the information processing system of FIG. 1, and the device node of FIG. 2 may include an input/output unit 210, a communication unit 220, a storage unit 230, and a processor 240.

The input/output unit 210 may be various interfaces or ports for receiving user input or outputting information to the user. The input/output unit 210 may include an input module and an output module, and the input module receives user input from the user. User input can be implemented in various forms such as key input, touch input, and voice input. Examples of input modules that can receive such user input include traditional keypads or keyboards, mice, touch sensors that sense user touch, microphones that receive sound signals, cameras that recognize gestures by image recognition, proximity sensors that include at least one of an illumination sensor or an infrared sensor that senses user approach, motion sensors that recognize user movements by means of an accelerometer or a gyroscope sensor, and various forms of input mechanisms that sense or receive other forms of user input. The input module of the embodiments of the present invention may include at least one of the devices listed above. Here, the touch sensor can be implemented in the following ways, that is, a piezoelectric or electrostatic touch sensor that senses touch by a touch panel or touch film attached to a display panel, an optical touch sensor that senses touch by an optical method, etc. In addition, the input module can also be implemented in the form of an input interface (USB (Universal Serial Bus) port, PS/2 (Personal System 2) port, etc.) connected to an external input device that receives user input, thereby replacing a device that senses user input itself. In addition, the output module can output various information. The output module may include at least one of a display for outputting images, a speaker for outputting sounds, a tactile device for generating vibrations, and other output mechanisms of various forms. Furthermore, the output module can also be implemented in the form of a port-type output interface that connects the above-mentioned output mechanisms.

For example, an output module in the form of a display can display text, static images, and videos. The display may include a liquid crystal display (LCD), a light emitting diode (LED), an organic light emitting diode (OLED), a flat panel display (FPD), a transparent display, a curved display, a flexible display, a three-dimensional display (3D Display), a holographic display, a projector, and at least one of various types of devices that can implement image output functions. Such a display may also be in the form of a touch display that is integrally formed with a touch sensor of an input module.

The communication unit 220 can communicate with other devices. Therefore, the device nodes associated with the service can send and receive information with other devices through the communication unit. For example, the device nodes can use the communication unit to communicate with each other or with other devices.

Here, communication means the sending and receiving of data which can be realized by wired or wireless. For this purpose, the communication unit can be constituted as: a wired communication module connected to the Internet via a LAN (Local Area Network), a mobile communication module connected to a mobile communication network via a mobile communication base station to send and receive data, a short-range communication module using a WLAN (Wireless Local Area Network) system communication method such as Wireless Fidelity (Wi-Fi) or a WPAN (Wireless Personal Area Network) system communication method such as Bluetooth or Zigbee, a satellite communication module using a GNSS (Global Navigation Satellite System) such as GPS (Global Positioning System), or a combination thereof.

The memory 230 can store various information. The memory 230 can store data temporarily or semi-permanently. For example, the memory 230 of the device node can store data related to the operating system (OS) used to drive the device node, data used to host the website, or programs or applications used to generate Braille (for example, website applications). In addition, the memory 230 can store modules in the form of computer code as described above.

Examples of the memory 230 include: a hard disk drive (HDD), a solid state drive (SSD), a flash memory, a read-only memory (ROM), a random access memory (RAM), etc. Such a memory 230 can be provided in a built-in type or a removable type.

The processor 240 controls the overall operation of the device node. To this end, the processor 240 can perform various information calculations and processing, and control the operation of each component of the device node. For example, the processor 240 can execute programs and applications for information processing. The processor 240 can be implemented by a computer or a similar device based on hardware, software, or a combination thereof. In terms of hardware, the processor 240 can be implemented in the form of a circuit that processes electrical signals and performs control functions, and in terms of software, it can be implemented in the form of a program that drives the hardware processor 240. On the other hand, in the case where no specific mention is made in the following description, the action of the device node can be interpreted as being performed by the control of the processor 240. That is, it can be interpreted as when executing the module implemented in the above-mentioned information processing system, the module controls the processor 240 to make the device node perform the following actions.

In short, various embodiments can be implemented by various mechanisms. For example, various embodiments can be implemented by hardware, firmware, software, or a combination thereof.

In the case of hardware implementation, the methods of various embodiments may be implemented by one or more ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), processors, controllers, microcontrollers, microprocessors, etc.

When implemented by firmware or software, the methods of various embodiments may be implemented in the form of modules, programs, or functions that implement the functions or actions described below. For example, the software code may be stored in a memory and driven by a processor. The memory may be located inside or outside the processor and may exchange data with the processor through various known mechanisms.

Below, various embodiments are described in more detail based on the above technical ideas. The various embodiments described below can apply the above content. For example, actions, functions, terms, etc. that are not defined in the various embodiments described below can be implemented and explained based on the content of the above description.

In the following description, various embodiments are described based on the premise that the service-related electronic device 100 implements actions used in the information processing method.

FIG3 is a structural diagram of an electronic device for implementing the information processing method proposed by the present invention.

In FIG3 , the electronic device 100 implementing the information processing method may include a communication device 301, a control unit 303, and a memory 305. Each component included in the electronic device 100 of FIG3 may correspond to the structure of the device node of FIG2 , or the electronic device 100 of FIG3 may include the structure of the device node of FIG2 . As an example, the communication device 301 included in the electronic device 100 of FIG3 may correspond to the communication unit 220 included in the structure of the device node of FIG2 .

The electronic device 100 in FIG. 3 may have the following functions: communicating with other devices via the communication device 301.

The control unit 303 can control the electronic device 100 to implement the information output method of various embodiments including Figures 4 to 14 described below. As an example, the control unit 303 can control the electronic device 100 to implement the various actions 401 to 403 of Figure 4 described below, and control the electronic device 100 to store and send and receive various information required to implement the actions 401 to 403 of Figure 4.

The memory 305 can be a volatile memory or a non-volatile memory, so that the control unit 303 can store the program code required to execute the program for implementing the information output method in the memory 305.

In the present invention, the electronic device 100 for implementing the information output method is not limited to the structure shown in FIG. 3, and in addition to the various components shown in FIG. 3, the electronic device 100 of the present invention may also include other common components.

FIG. 4 is a diagram showing the operation method of the electronic device for information processing in various embodiments.

According to FIG. 4 , the electronic device 100 can perform an action of processing request information in order to process request information, can set a request information processing model 401 related to the processing of request information obtained through a service, and can process request information 403 obtained through a service based on at least one processing model included in the request information processing model.

According to FIG. 4 , the electronic device 100 may set a request information processing model and process request information for a service related to the electronic device 100, and the service may correspond to a service in which a plurality of users utilizing the service order and purchase a plurality of items sold in the service. The plurality of items sold in the service may include various types or categories of items registered by the seller for the purpose of selling items, and are not limited to the types or categories of items.

According to various embodiments, in action 401, the electronic device 100 may set a request information processing model related to the processing of request information obtained through the service.

For example, the request information processing model set by the electronic device 100 according to action 401 may include a first processing model, which limits the number of request information to be processed per unit time to less than a first critical number in each server included in one or more servers associated with the service. Hereinafter, the one or more servers or each server described below may be understood as a concept corresponding to the server device 300 in FIG. 1

The first processing model described above is equivalent to a processing model for preventing a load from being generated when processing request information in each server included in one or more servers associated with a service, and the first processing model can be set to be applied according to the selection input of the administrator who applies the first processing model. As an example, when the number of request information to be processed per unit time by one or more servers is confirmed to be greater than a fixed number, and the administrator of the electronic device 100 determines that the number of request information to be processed per unit time in each server is too large, the administrator can select input to apply the first processing model. By applying the first processing model using the administrator's selection input, the number of request information to be processed per unit time in each server can be limited to less than the first critical number.

Alternatively, in addition to the administrator's selection input, the electronic device 100 can also be set in the following manner: the first processing model is applied when a certain condition is met. As an example, the number of request information to be processed by one or more servers per unit time can be set to a condition of more than a fixed number and used in the first processing model. The electronic device 100 can be managed in the following manner: when the above conditions are met, the first processing model is automatically applied to limit the number of request information to be processed per unit time in each server to less than the first critical number.

Here, the first critical number set for the first processing model may be a value set by the administrator's input.

FIG5 is a diagram showing an example of the first processing model included in the setting request information processing model.

In FIG. 5 , the electronic device 100 is managed as follows: request information obtained from a plurality of users utilizing the service is processed by one or more servers associated with the service ( 500 ). At this time, the first processing model can be applied in the same form as 501 , and the first processing model limits the number of request information to be processed per unit time in each server to within a specific critical number.

In FIG. 5 , by applying the first processing model, the number of request information to be processed by each server per minute can be limited to within 10,000, and this first processing model can also be set by administrator selection input or automatic application based on the following situation: the number of request information to be processed by one or more servers per minute is confirmed to be more than 30,000.

For example, the request information processing model set by the electronic device 100 according to action 401 may include a second processing model, which corresponds to a specific API group in a plurality of first API groups that classify a plurality of APIs (Application Programming Interfaces) corresponding to the service according to importance, and limits the number of request information to be processed per unit time in each of the above servers to less than the second critical number.

The second processing model described above corresponds to a processing model for preventing a load from being generated when processing request information corresponding to an API group having a specific importance in each server included in one or more servers associated with the service, and the second processing model can be set to be applied according to the selection input of an administrator who applies the second processing model.

Various APIs on the service may have different importance from each other, and it is very important for the electronic device 100 to manage in such a way that request information obtained by APIs with higher importance can be mainly processed. Therefore, the electronic device 100 is divided into an API group with higher importance and an API group with lower importance according to the importance of various APIs on the service, and the processing of request information obtained corresponding to the API group with lower importance can be limited so that request information obtained corresponding to the API group with higher importance can be mainly processed.

For example, when the number of request information to be processed per unit time by one or more servers corresponding to an API group with a lower importance is confirmed to be greater than a fixed number, and the administrator of the electronic device 100 determines that the number of request information processed in each server corresponding to the API group with a lower importance has increased, thereby generating a load in the processing of request information corresponding to the API group with a higher importance, the administrator can make a selection input to apply the second processing model. By using the administrator's selection input to apply the second processing model, the number of request information to be processed per unit time corresponding to the API group with a lower importance in each server can be limited to below the second critical number. By applying this second processing model, a processing capacity per unit time of a certain level or more for request information corresponding to an API group with a higher importance can be ensured in each server.

Alternatively, in addition to the administrator's selection input, the electronic device 100 can also be set in the following manner: the second processing model is applied when a certain condition is met. As an example, the number of request information to be processed by one or more servers per unit time can be set to a fixed number or more for the second processing model corresponding to the API group with lower importance. The electronic device 100 can be managed in the following manner: when the above conditions are met, the second processing model is automatically applied, and the number of request information to be processed per unit time is limited to less than the second critical number corresponding to the API group with lower importance in each server.

Here, the second critical number set for the second processing model may be a value set by the administrator's input. Furthermore, for the second processing model, the electronic device 100 may confirm and manage information about the importance of each API in advance, and may also perform the following actions based on the information about the importance of each API, that is, to divide various APIs on the service into an API group with a higher importance and an API group with a lower importance.

Regarding the second processing model, examples of APIs with higher importance include APIs for providing a checkout page when purchasing items, APIs for adding items to a shopping cart, etc. Examples of APIs with lower importance include APIs for the checkout mechanism to confirm users, APIs for requesting fresh-keeping bags when ordering items, etc.

FIG6 is a diagram showing an example of a second processing model included in the setting request information processing model.

In FIG. 6 , the electronic device 100 can manage the request information obtained from multiple users using the service in the following manner: the request information obtained corresponding to the API group with higher importance on the service and the request information obtained corresponding to the API group with lower importance can be divided, and the request information obtained corresponding to each API group can be processed by one or more servers associated with the service ( 600 ). At this time, the second processing model can be applied in the same form as 601 , and the second processing model limits the number of request information to be processed per unit time to within a specific critical number corresponding to the API group with lower importance in each server.

In FIG. 6, by applying the second processing model, the number of request information to be processed per minute in each server corresponding to the API group with lower importance can be limited to within 8,000, and this second processing model can also be set based on the administrator's selection input or automatic application based on the following situation: the number of request information to be processed per minute in one or more servers corresponding to the API group with lower importance is confirmed to be more than 24,000. By applying the same second processing model as 601, a processing capacity per unit time of more than a certain level for request information corresponding to the API group with higher importance can be ensured in each server.

For example, the request information processing model set by the electronic device 100 according to action 401 may include a third processing model, which corresponds to each API group included in a plurality of second API groups that classify a plurality of APIs (Application Programming Interfaces) according to resource usage, and limits the number of each request information to be processed to less than each critical number set for each of the above API groups.

The third processing model described above is equivalent to a processing model for preventing the remaining resource capacity of each managed API group from being 0 in the process of processing request information corresponding to a plurality of second API groups classified according to resource usage in each server included in one or more servers associated with the service, and the third processing model can be set to be applied according to the selection input of the administrator who applies the third processing model.

Various APIs on the service may consume different resource usages, and it may be very important for the electronic device 100 to manage in a manner that does not exceed the resource usage used for each API. Therefore, the electronic device 100 can manage in the following manner: the various APIs on the service are divided into an API group with a higher resource usage, an API group with a medium resource usage, and an API group with a lower resource usage according to their resource usage, a fixed resource capacity can be allocated corresponding to the API group, and the request information obtained corresponding to each API group can be mainly processed within the range of not exceeding the allocated resource capacity.

For example, 1) a fixed resource capacity may be allocated to an API group with a high resource usage, and a critical number 1 of request information that can be processed based on the allocated resource capacity may be determined; 2) a fixed resource capacity may be allocated to an API group with a medium resource capacity, and a critical number n of request information that can be processed based on the allocated resource capacity may be determined; 3) a fixed resource capacity may be allocated to an API group with a low resource usage, and a critical number m of request information that can be processed based on the allocated resource capacity may be determined. When the administrator of the electronic device 100 wants to manage the resource capacity allocated to each API group, the administrator can select input to apply the third processing model. By using the administrator's selection input to apply the third processing model, the number of processed request information can be limited to within the critical number of each API group that has been confirmed.

Here, each critical number set for the third processing model can be a value set by the administrator's input. In addition, for the third processing model, the electronic device 100 can confirm and manage the information about the resource usage of each API in advance, and can also perform the following actions based on the information about the resource usage of each API, that is, to classify various APIs on the service into an API group with higher resource usage, an API group with medium resource usage, and an API group with lower resource usage.

Regarding the third processing model, examples of APIs with high resource usage may include landing APIs, purchase APIs corresponding to purchase button inputs, etc., and examples of APIs with medium resource usage may include APIs for setting schedules such as delivery schedule dates, etc. In addition, examples of APIs with low resource usage may include APIs for changing delivery addresses, APIs for inputting personal pass codes related to overseas direct purchases, etc.

FIG. 7 is a diagram showing an example of a third processing model included in the setting request information processing model.

In FIG. 7 , the electronic device 100 can manage the request information obtained from multiple users using the service in the following manner: the request information obtained corresponding to the API group with higher resource usage, the request information obtained corresponding to the API group with medium and high resource usage, and the request information obtained corresponding to the API group with lower resource usage on the service, and the request information obtained corresponding to each API group is processed by one or more servers associated with the service ( 700 ). At this time, the third processing model can be applied in the same form as 701, and the third processing model limits the number of request information to be processed corresponding to each API group to within the critical number set for each API group.

In FIG. 7, by applying the third processing model, the number of request information to be processed for the API group with high resource usage can be limited to within 1,000, the number of request information to be processed for the API group with medium resource usage can be limited to within 5,000, and the number of request information to be processed for the API group with low resource usage can be limited to within 10,000. Therefore, the resource capacity for each API group can be managed in a manner that cannot be zero. In addition, this third processing model can be set to be applied by the administrator's selection input.

For example, the request information processing model set by the electronic device 100 according to action 401 may include a fourth processing model, which limits the number of request information to be processed per unit time to less than the third critical number corresponding to the user of the service.

The fourth processing model described above is equivalent to a processing model for preventing a load from being generated by excessive request information being obtained in a short period of time due to repeated input from a specific user in each of the one or more servers associated with the service, and the fourth processing model can be set to be applied according to the selection input of the administrator who applies the fourth processing model.

On the service, users can use various APIs to perform various inputs, generate request information corresponding to the user's input, and each server processes it. However, if the user repeatedly clicks or touches, or uses macros to generate a large amount of request information in a short period of time, even if the server is allowed to process all of them, it will generate unnecessary load. Therefore, it may be very important to manage the electronic device 100 in a way to avoid the same problem. Therefore, the electronic device 100 can be managed in the following way: corresponding to each user on the service, confirm the number of request information obtained per unit time, and limit the number of request information to be processed per unit time of each user to less than the third critical number when necessary.

Here, the third critical number set for the fourth processing model can be a value set by the administrator's input.

For example, the number of request information obtained from a user per unit time can be confirmed by an external cache that corresponds to one or more servers associated with the service. That is, unlike caches that are set separately in each server included in one or more servers when applying other processing models, in the case of the fourth processing model, an external cache that corresponds to one or more servers is set, so that the number of request information obtained from a user can be easily tracked.

For example, the number of request information obtained from a user per unit time can be confirmed based on the user's identification information and the information of the API that the user is using. That is, since a large amount of request information generated by the user through repeated input is likely to be an action implemented in a specific API, the electronic device 100 can effectively use the user's identification information and the information of the API that the user is using to track the request information confirmed by the same user's action.

For example, the electronic device 100 can confirm the information of the API that the user is using by the same API identifier as above. The definitions of terms used in each API, information processing paths, event names, etc. may be different, so the electronic device 100 can set an identifier to identify each API, and use the set identifier to track the information of the API that the user is using.

FIG8 is a diagram showing an example of the fourth processing model included in the setting request information processing model.

In FIG. 8 , the electronic device 100 can manage in the following manner: request information obtained from a plurality of users utilizing the service can be divided into request information corresponding to each user, and the request information corresponding to each user is processed by one or more servers associated with the service (800).

In FIG8 , by applying the fourth processing model, management is performed in the following manner, that is, the number of request information corresponding to a specific user distinguished by identification information does not exceed 20 per minute (801), and in order to confirm the request information obtained per unit time for each user, an external cache (803) corresponding to one or more servers can be set. This fourth processing model can be set in a manner that is applied according to the administrator's selection input.

For example, the request information processing model set by the electronic device 100 according to action 401 may include a fifth processing model, which interrupts the processing of all request information obtained through the service.

The fifth processing model described above is equivalent to interrupting the processing model for processing all request information when a problem occurs in processing request information by one or more servers associated with the service, and the fifth processing model can be set to be applied according to the selection input of the administrator who applies the fifth processing model.

The fifth processing model can be set as follows: instructing each server unit to interrupt the processing of request information so as not to process the request information in each server, or instructing the front end to interrupt the processing of request information before the request information is transmitted to each server so as not to process the request information in each server.

FIG9 is a diagram showing an example of the fifth processing model included in the setting request information processing model.

In FIG. 9 , the electronic device 100 can be managed by the fifth processing model in the following manner, that is, preventing each server from processing all request information obtained by the service (900), and this fifth processing model can be set to be applied according to the administrator's selection input.

For example, you may refuse to process a request message that exceeds a critical number of restrictions imposed by each processing model included in the request message processing model.

For example, the electronic device 100 can confirm the number of request information that is rejected according to each processing model included in the request information processing model. Specifically, the electronic device 100 can set each processing model state identification information corresponding to each processing model included in the request information processing model, and based on each processing model state identification information, confirm the number of request information that is rejected according to each processing model.

According to various embodiments, in action 403, the electronic device 100 may process the request information obtained through the service based on at least one processing model included in the request information processing model.

For example, according to action 403, the electronic device 100 can effectively utilize at least one processing model for processing request information, which is selected by the first input of the administrator of the electronic device 100 from the first processing model to the fifth processing model. That is, the administrator of the electronic device 100 can select the processing model to be applied for processing request information according to the situation.

For example, according to action 403, the electronic device 100 can set the critical number of restrictions in each processing model included in the request information processing model set for processing the request information based on the second input of the administrator of the electronic device 100. That is, the administrator of the electronic device 100 can set the critical number of request information processing used for each processing model according to the situation.

For example, according to action 403, the electronic device 100 can set the critical numbers of restrictions in each processing model included in the request information processing model set for processing the request information based on the environmental parameter information related to the service. That is, the electronic device 100 can be managed in the following manner: the administrator of the electronic device 100 does not set the critical number of request information processing for each processing model, but sets the critical number of request information processing for each processing model based on the environmental parameter information related to the service.

For example, the environmental parameter information as described above may include at least one of the information of parameters that can affect the request information processing of the server, such as information on the number of the above-mentioned one or more servers, information on the total resource capacity used for the above-mentioned service, and/or information on whether to conduct promotions on the above-mentioned service for which the request information is expected to increase or decrease.

On the other hand, the electronic device 100 can also set a layer structure to apply the request information processing model set according to FIG. 4 for processing request information to a general algorithm. That is, the electronic device 100 can set a layer structure corresponding to the request information processing model, and according to the set layer structure, the request information processing model can be applied to the general algorithm used for the action of the electronic device 100.

FIG. 10 is a diagram showing an example of a layer structure for applying the request information processing model to an algorithm for the operation of the electronic device 100.

In FIG. 10 , when the electronic device 100 sets the first to fifth processing models to process request information (1001), a facade layer structure (1003) that can apply the first to fifth processing models can be set in Bucket4J core algorithm 1005, which is an example algorithm among algorithms used for the operation of the electronic device 100.

As shown in Figure 10, the first processing model corresponds to "Server Rate Limit", the second processing model corresponds to "Reserved Rate Limit", the third processing model corresponds to "Concurrent Rate Limit", the fourth processing model corresponds to "API+Client Rate Limit", and the fifth processing model corresponds to "Kill Switch".

Needless to say, according to FIGS. 4 to 10 , each information set or processed by the electronic device 100 in the process of implementing the action method for information processing can be combined in various forms.

Figures 11 to 14 are diagrams showing an example of processing request information based on a request information processing model including the first processing model to the fifth processing model. For example, the examples of Figures 11 to 14 can process request information generated in response to input from the user device 200 in the server device 300, and can implement the various embodiments described in the following figures based on the actions of the above-mentioned electronic device 100 in Figures 4 to 10.

Specifically, each embodiment described in the following figures can be implemented in the following form: when the user device 200 receives input information from the user and transmits request information related to the input information to the server device 300, the server device 300 can process the request information based on the action of the electronic device 100 in Figures 4 to 10. However, each embodiment described in the following figures is not limited to this form, and can be implemented in all forms that can implement each embodiment.

FIG. 11 is a diagram showing an example of processing request information based on a request information processing model of various embodiments.

In FIG. 11 , it can be confirmed that the fifth processing model equivalent to the "self-destruct switch" and the first processing model equivalent to the "server rate limit" are applied based on the request information processing model. The administrator corresponding to the electronic device 100 sets the fifth processing model to off (1101), and can set it to on again when it is necessary to interrupt the processing of all request information.

In addition, in FIG. 11 , the administrator corresponding to the electronic device 100 can confirm that the processing of request information in each server will generate a load. For example, when the number of request information to be processed per minute is more than 100,000 (1103-1), based on the first processing model, the number of request information to be processed per minute in each server can be limited to less than 10,000 (1103-2).

At this time, the application of each processing model as described above is not limited to the order shown in FIG. 11 , and each processing model can be applied according to the input of the administrator corresponding to the electronic device 100 or whether each processing model meets the preset conditions.

FIG. 12 is a diagram showing another example of processing request information based on the request information processing model of various embodiments. For convenience, the example of FIG. 12 shows the fourth processing model added to the example of FIG. 11, but the application form of the fourth processing model is not limited to FIG. 12, and the fourth processing model can be applied alone or in combination with various other processing models.

In FIG12, it can be confirmed that the fifth processing model equivalent to the "self-destruct switch", the first processing model equivalent to the "server rate limit", and the fourth processing model equivalent to the "API+client rate limit" are applied based on the request information processing model. As described in FIG11, the administrator corresponding to the electronic device 100 in FIG12: 1) sets the fifth processing model to off (1201), 2) corresponding to the situation where the number of request information to be processed per minute is more than 100,000, the number of request information to be processed per minute in each server can be limited to within 10,000 according to the first processing model (1203-1, 1203-2).

Furthermore, in FIG. 12 , when the number of request information obtained from the user by the administrator corresponding to the electronic device 100 is more than 20 per minute, or the input for the request information obtained from the user is more than 20 times per minute (1205-1), based on the fourth processing model, the number of request information to be processed per minute corresponding to the user can be limited to less than 20 (1205-2).

At this time, the application of each processing model as described above is not limited to the order shown in FIG. 12 , and each processing model can be applied according to the input of the administrator corresponding to the electronic device 100 or whether each processing model meets the preset conditions.

FIG. 13 is a diagram showing another example of processing request information based on the request information processing model of various embodiments. For convenience, the example of FIG. 13 shows the second processing model added to the example of FIG. 12, but the application form of the second processing model is not limited to FIG. 13, and the second processing model can be applied alone or in combination with various other processing models.

In FIG. 13 , it can be confirmed that based on the request information processing model, the fifth processing model equivalent to the “self-destruct switch”, the first processing model equivalent to the “server rate limit”, the fourth processing model equivalent to the “API+client rate limit”, and the second processing model equivalent to the “retention rate limit” are applied. As described in FIG. 12 , the administrator corresponding to the electronic device 100 in FIG. 13 : 1) sets the fifth processing model to off ( 1301 ), 2) when the number of request information to be processed per minute is more than 100,000, according to the first processing model, the number of request information to be processed per minute in each server is limited to within 10,000 ( 1 303-1, 1303-2), 3) When the number of request information obtained from the user is more than 20 per minute, or the input for the request information obtained from the user is more than 20 times per minute, based on the fourth processing model, the number of request information to be processed per minute corresponding to the user can be limited to less than 20 (1305-1, 1305-2).

Furthermore, in FIG. 13 , the administrator corresponding to the electronic device 100 can manage in the following manner: when the multiple APIs (Application Programming Interfaces) corresponding to the service are classified into an API group with a higher importance and an API group with a lower importance according to the importance, since the number of request information processed corresponding to the API group with a lower importance is more than 8,000, it is judged that it is excessive (1307-1). Based on the second processing model, the number of request information to be processed per unit time in each server can be limited to less than 8,000 corresponding to the API group with a lower importance, and 2,000 request information can be processed per unit time in each server corresponding to the API group with a higher importance (1307- 2).

At this time, the application of each processing model as described above is not limited to the order shown in FIG. 13 , and each processing model can be applied according to the input of the administrator corresponding to the electronic device 100 or whether each processing model meets the preset conditions.

FIG. 14 is a diagram showing another example of processing request information based on the request information processing model of various embodiments. For convenience, the example of FIG. 14 shows the third processing model added to the example of FIG. 13, but the application form of the third processing model is not limited to FIG. 14, and the third processing model can be applied alone or in combination with various other processing models.

In FIG. 14 , it can be confirmed that based on the request information processing model, the 5th processing model equivalent to the “self-destruct switch”, the 1st processing model equivalent to the “server rate limit”, the 4th processing model equivalent to the “API+client rate limit”, the 2nd processing model equivalent to the “retention rate limit” and the 3rd processing model equivalent to the “concurrent limit” are applied. Similar to the description in FIG. 13 , the administrator corresponding to the electronic device 100 in FIG. 14 : 1) sets the fifth processing model to off (1401); 2) when the number of request information to be processed per minute is more than 100,000, the number of request information to be processed per minute can be limited to 10,000 or less in each server according to the first processing model (1403-1, 1403-2); 3) when the number of request information obtained from the user is more than 20 per minute, or the input of the request information obtained from the user is more than 20 times per minute, based on the fourth processing model, the number of request information to be processed per minute corresponding to the user can be limited to less than 20 (1405-1, 1405-2). Furthermore, the administrator corresponding to the electronic device 100 can manage as follows: 4) When it is confirmed that the number of request information processed corresponding to the API group with lower importance is more than 8,000, according to the second processing model, the number of request information to be processed per unit time in each server corresponding to the API group with lower importance is limited to less than 8,000, and the number of request information to be processed per unit time in each server corresponding to the API group with higher importance is limited to 2,000 (1407-1, 1407-2).

In addition, in FIG. 14 , the administrator corresponding to the electronic device 100 can manage the following manner: according to the resource usage, the multiple APIs (Application Programming When the API groups (Application Programming Interfaces) are classified into API groups with high resource usage, API groups with medium resource usage, and API groups with low resource usage, the number of request messages processed corresponding to the API groups with high resource usage is judged to exceed the resource capacity allocated to the API groups with high resource usage (1409-1). Based on the third processing model, the resource capacity allocated to the API groups with high resource usage is used to limit the request message processing of the API groups to a critical number of 1,000 request messages that can be processed. For the API groups with high resource usage, a maximum of 1,000 request messages can be processed (1409-2).

At this time, the application of each processing model as described above is not limited to the order shown in FIG. 14 , and each processing model can be applied according to the input of the administrator corresponding to the electronic device 100 or whether each processing model meets the preset conditions.

The examples of Figures 11 to 14 can be implemented in association with the actions of the electronic device 100 described in Figures 4 to 10. The examples of Figures 11 to 14 are used to disclose an example of the present invention. Various embodiments of the present invention are not limited to the example forms of Figures 11 to 14, and can be implemented according to all forms of various embodiments that can implement the present invention.

The embodiments of the present invention disclosed in this specification and drawings are only used to easily explain the technical content of the present invention and help understand the specific examples of the present invention, and are not intended to limit the scope of the present invention. That is, for those with common sense in the technical field to which the present invention belongs, it is clear that other variations based on the technical ideas of the present invention can be implemented. In addition, each of the above embodiments can be combined and used as needed. For example, among all the embodiments of the present invention, some can be combined with each other and implemented through the system.

Furthermore, the system and methods of the present invention can be implemented in the form of program commands executed by various computer mechanisms and recorded in computer-readable media.

As described above, in certain aspects, various embodiments of the present invention may be implemented as computer readable code in a computer readable recording medium. A computer readable recording medium is any data storage device capable of storing data that can be read by a computer system. Examples of computer readable recording media may include: read only memory (ROM), random access memory (RAM), compact disk-read only memory (CD-ROM), magnetic tape, floppy disk, optical data storage device, and carrier wave (data transmission via the Internet, etc.). The computer-readable recording medium can also be distributed through computer systems connected to a network, thereby storing and executing computer-readable codes in a distributed manner. In addition, the functional programs, codes, and segments used to implement various embodiments of the present invention can be easily explained by skilled programmers in the field of application of the present invention.

Furthermore, it is known that the apparatus and methods of various embodiments of the present invention can be implemented in the form of hardware, software, or a combination of hardware and software. Such software can be stored, for example, in a volatile or non-volatile storage device such as a ROM, or a memory such as a RAM, a memory chip, a device or an integrated circuit, or a storage medium such as a compact disk (CD), a DVD (Digital Versatile Disc), a disk or a tape that can be recorded optically or magnetically and can be read by a machine (such as a computer), regardless of whether it can be deleted or recorded again. It is known that the methods of various embodiments of the present invention can be implemented by a computer including a control unit and a memory or a vehicle including the memory or computer as described above, and such a memory is an example of a storage medium that includes a program for implementing the commands of the embodiments of the present invention or can be read by a machine suitable for storing the program.

Therefore, the present invention includes: a program of code for implementing the device or method described in the scope of the invention application of this specification, and a storage medium that can be read by a machine (computer, etc.) storing such a program. In addition, such a program can be electronically transferred through any medium such as a communication signal transmitted by a wired or wireless connection, and the present invention appropriately includes its equivalents.

In addition, it can be understood that the embodiments of the present invention described above are only examples, and those with common sense in the field can realize various variations and equivalent embodiments based on them. Therefore, the true technical protection scope of the present invention should be defined according to the following invention patent application scope.

401:Action

403:Action

Claims (15)

An information processing method for processing request information by an electronic device comprises the following steps: setting a request information processing model related to the processing of request information obtained by a service; and processing the request information obtained by the service based on at least one processing model included in the request information processing model; the request information processing model comprises the following models: a first processing model, which limits the number of request information to be processed per unit time to a first critical number in each server included in one or more servers associated with the service. The second processing model corresponds to a specific API group in the plurality of first API groups that classify the plurality of APIs corresponding to the above service according to importance, and limits the number of request information to be processed per unit time in each of the above servers to less than the second critical number; and the third processing model corresponds to each API group included in the plurality of second API groups that classify the plurality of APIs corresponding to the above service according to resource usage, and limits the number of each request information to be processed to less than each critical number set for each of the above API groups. The information processing method of claim 1, wherein the request information processing model includes the following models: the fourth processing model, which corresponds to the user of the above service and limits the number of request information to be processed per unit time to less than the third critical number. The information processing method of request item 2, wherein the number of request information obtained from the above-mentioned user per unit time is confirmed by an external cache corresponding to the above-mentioned one or more servers. The information processing method of request item 2, wherein based on the identification information of the above user and the information of the API being used by the above user, the number of request information obtained from the above user per unit time is confirmed. The information processing method of claim 4 further includes the following steps: confirming the information of the above API by using the API identifier. The information processing method of request item 1, wherein the request information processing model includes the following models: the fifth processing model, which interrupts the processing of all request information obtained through the above service. The information processing method of request item 1, wherein the following request information is refused to be processed: exceeding the critical number limited by each processing model included in the above request information processing model. The information processing method of request item 1 further includes the following steps: setting each processing model state identification information corresponding to each processing model included in the above-mentioned request information processing model; and based on the above-mentioned each processing model state identification information, confirming the number of request information that is rejected for processing according to the above-mentioned each processing model. An information processing method as claimed in claim 1, wherein the at least one processing model is selected based on a first input from a manager corresponding to the electronic device. The information processing method of claim 1, wherein the first critical number, the second critical number, and the critical numbers for each of the API groups are set based on the second input of the administrator corresponding to the electronic device. The information processing method of claim 1, wherein the first critical number, the second critical number, and the critical numbers for each of the API groups are set based on the environment parameter information related to the service. The information processing method of claim 11, wherein the environmental parameter information includes at least one of information about the number of the one or more servers, information about the total resource capacity used for the service, and information about whether to conduct promotions on the service for which the request information is expected to increase or decrease. The information processing method of claim 1 further includes the following steps: setting a layer structure corresponding to the above-mentioned request information processing model; and based on the above-mentioned layer structure, the above-mentioned request information processing model is applied to the algorithm used for the action of the above-mentioned electronic device. A non-transitory computer-readable recording medium records a program for executing an information processing method in a computer, the information processing method comprising the following steps: setting a request information processing model related to the processing of request information obtained through a service; and processing the request information obtained through the service based on at least one processing model included in the request information processing model; the request information processing model comprises the following models: a first processing model that, in each of the one or more servers associated with the service, processes the request information to be processed per unit time. The number is limited to be below the first critical number; the second processing model corresponds to a specific API group in the first API groups in which the plurality of APIs corresponding to the above service are classified according to importance, and the number of request information to be processed per unit time in each of the above servers is limited to be below the second critical number; and the third processing model corresponds to each API group included in the second API groups in which the plurality of APIs corresponding to the above service are classified according to resource usage, and the number of each request information to be processed is limited to be below the critical number set for each of the above API groups. An electronic device for processing request information, comprising: a processor; and one or more memories storing one or more instructions; when the one or more instructions are executed, the processor is controlled to perform the following steps: setting a request information processing model related to the processing of request information obtained through a service; and processing the request information obtained through the service based on at least one processing model included in the request information processing model; the request information processing model includes the following models: a first processing model, in each server included in one or more servers associated with the service, The number of request information to be processed per unit time is limited to less than the first critical number; the second processing model corresponds to a specific API group in a plurality of first API groups in which the plurality of APIs corresponding to the above service are classified according to importance, and the number of request information to be processed per unit time in each of the above servers is limited to less than the second critical number; and the third processing model corresponds to each API group included in a plurality of second API groups in which the plurality of APIs corresponding to the above service are classified according to resource usage, and the number of each request information to be processed is limited to less than each critical number set for each of the above API groups.