CN115002810B

CN115002810B - Resource configuration method, private network control method, edge cloud server and equipment

Info

Publication number: CN115002810B
Application number: CN202210918137.XA
Authority: CN
Inventors: 杨光
Original assignee: Alibaba Damo Institute Hangzhou Technology Co Ltd
Current assignee: Alibaba Cloud Computing Ltd
Priority date: 2022-08-01
Filing date: 2022-08-01
Publication date: 2023-01-13
Anticipated expiration: 2042-08-01
Also published as: CN115002810A

Abstract

The embodiment of the application provides a resource configuration method, a private network control method, an edge cloud server and equipment. The resource configuration method is applied to an edge cloud server deployed in an exclusive network; the resource allocation method comprises the following steps: acquiring a resource allocation request; determining preset reference equipment in communication connection with the edge cloud server and reference resources of the preset reference equipment; and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain the edge resource corresponding to the edge cloud server, wherein the edge resource is the same as the reference resource. According to the technical scheme, the edge cloud server is configured based on the resource configuration request and the reference resource, the edge resource which is the same as the reference resource is obtained, the edge resource framework of the edge cloud server is effectively unified with the reference resource framework of the preset reference device, and unified management and maintenance operation of the preset reference device and the edge cloud server by a user are facilitated.

Description

Resource configuration method, private network control method, edge cloud server and equipment

Technical Field

The present application relates to the field of network technologies, and in particular, to a resource configuration method, a private network management and control method, an edge cloud server, and a device.

Background

For a 5G network system, an existing 5G network architecture often includes a general server for implementing basic data processing operations and an acceleration server for implementing acceleration data processing operations, and for the general server for implementing basic data processing operations, different manufacturers may produce general servers of different specifications, resources such as hardware specifications of different general servers are often different, and the general servers of different hardware specifications often correspond to different software logics, so that for a user, complexity of operation and maintenance management on the servers is increased.

Disclosure of Invention

The embodiment of the application provides a resource configuration method, a private network management and control method, an edge cloud server and equipment, so that resource configuration of the edge cloud server is realized based on reference resources of preset reference equipment, and the configured edge resources are the same as the reference resources, so that a user can perform unified management and maintenance operation on the edge cloud server.

In a first aspect, an embodiment of the present application provides a resource configuration method, which is applied to an edge cloud server deployed in an exclusive network; the method comprises the following steps:

acquiring a resource allocation request;

determining preset reference equipment in communication connection with the edge cloud server and reference resources of the preset reference equipment;

and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge resource corresponding to the edge cloud server, wherein the edge resource is the same as the reference resource.

In a second aspect, an embodiment of the present application provides an edge cloud server, which is deployed in an exclusive network; the edge cloud server includes:

a first obtaining module, configured to obtain a resource configuration request;

the first determining module is used for determining preset reference equipment in communication connection with the edge cloud server and reference resources of the preset reference equipment;

a first processing module, configured to configure the edge cloud server based on the resource configuration request and a reference resource, and obtain an edge resource corresponding to the edge cloud server, where the edge resource is the same as the reference resource.

In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the resource configuration method of the first aspect.

In a fourth aspect, an embodiment of the present invention provides a computer storage medium for storing a computer program, where the computer program is used to enable a computer to implement the resource allocation method shown in the first aspect when executed.

In a fifth aspect, an embodiment of the present invention provides a computer program product, including: computer program, which, when executed by a processor of an electronic device, causes the processor to perform the steps of the resource allocation method according to the first aspect.

In a sixth aspect, an embodiment of the present invention provides a private network control method, including:

acquiring a network control request through a dedicated network;

processing the network control request by using an edge cloud server deployed in the dedicated network to obtain network control information corresponding to the dedicated network, wherein the network control request is processed by using edge resources corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, and the edge resources are the same as the reference resources of the preset reference equipment;

controlling the dedicated network based on the network control information.

In a seventh aspect, an embodiment of the present invention provides a private network management and control device, including:

the second acquisition module is used for acquiring the network control request through the exclusive network;

the second processing module is configured to process the network control request by using an edge cloud server deployed in the dedicated network to obtain network control information corresponding to the dedicated network, where the network control request is processed through an edge resource corresponding to the edge cloud server, the edge cloud server is communicatively connected with a preset reference device, and the edge resource is the same as a reference resource of the preset reference device;

and the second control module is used for controlling the exclusive network based on the network control information.

In an eighth aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor; wherein the memory is configured to store one or more computer instructions, and when the one or more computer instructions are executed by the processor, the method for managing and controlling a private network according to the sixth aspect is implemented.

In a ninth aspect, an embodiment of the present invention provides a computer storage medium, configured to store a computer program, where the computer program is configured to, when executed, implement the private network management and control method according to the sixth aspect.

In a tenth aspect, an embodiment of the present invention provides a computer program product, including: a computer program, which, when executed by a processor of an electronic device, causes the processor to execute the steps in the private network management and control method according to the sixth aspect.

In an eleventh aspect, an embodiment of the present invention provides a data processing method, including:

acquiring a data processing request corresponding to the augmented reality terminal through a dedicated network;

processing the data processing request by using an edge cloud server deployed in the exclusive network to obtain a data processing result corresponding to the augmented reality terminal, wherein the data processing request is processed by using edge resources corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, and the edge resources are the same as the reference resources of the preset reference equipment;

and controlling the augmented reality terminal based on the data processing result.

In a twelfth aspect, an embodiment of the present invention provides a data processing apparatus, including:

the third acquisition module is used for acquiring a data processing request corresponding to the augmented reality terminal through an exclusive network;

a third processing module, configured to process the data processing request by using an edge cloud server deployed in the dedicated network, and obtain a data processing result corresponding to the augmented reality terminal, where the data processing request is processed through an edge resource corresponding to the edge cloud server, the edge cloud server is communicatively connected with a preset reference device, and the edge resource is the same as a reference resource of the preset reference device;

and the third control module is used for controlling the augmented reality terminal based on the data processing result.

In a thirteenth aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the data processing method of the eleventh aspect.

In a fourteenth aspect, an embodiment of the present invention provides a computer storage medium for storing a computer program, where the computer program is configured to enable a computer to implement the data processing method shown in the eleventh aspect when executed.

In a fifteenth aspect, an embodiment of the present invention provides a computer program product, including: a computer program, which, when executed by a processor of an electronic device, causes the processor to carry out the steps of the data processing method according to the eleventh aspect.

According to the resource configuration method, the private network control method, the edge cloud server and the device, the preset reference device in communication connection with the edge cloud server and the reference resource of the preset reference device are determined by obtaining the resource configuration request, the edge cloud server is configured based on the resource configuration request and the reference resource pair, the edge resource same as the reference resource is obtained, the edge resource framework (including the framework of the infrastructure) of the edge cloud server is effectively unified with the framework of the preset reference device, and therefore the user can conveniently conduct unified management and maintenance operation on the preset reference device and the edge cloud server.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a schematic diagram of a resource allocation method according to an embodiment of the present application;

fig. 2 is a schematic flowchart of a resource allocation method according to an embodiment of the present application;

fig. 3 is a schematic flowchart of another resource allocation method according to an embodiment of the present application;

fig. 4 is a schematic flowchart of another resource allocation method according to an embodiment of the present application;

fig. 5 is a schematic flowchart of a resource allocation method according to an embodiment of the present application;

fig. 6 is a schematic architecture diagram of a resource allocation system according to an embodiment of the present application;

fig. 7 is a schematic flowchart of a private network control method according to an embodiment of the present application;

fig. 8 is a schematic flowchart of a data processing method according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of an edge cloud server according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of an electronic device corresponding to the edge cloud server shown in fig. 9;

fig. 11 is a schematic structural diagram of a private network control apparatus according to an embodiment of the present application;

fig. 12 is a schematic structural diagram of an electronic device corresponding to the private network control apparatus shown in fig. 11;

fig. 13 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;

fig. 14 is a schematic structural diagram of an electronic device corresponding to the data processing apparatus shown in fig. 13.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and "a" and "an" typically include at least two, but do not exclude the inclusion of at least one.

It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of additional like elements in a commodity or system that comprises the element.

In addition, the sequence of steps in each method embodiment described below is only an example and is not strictly limited.

In order to facilitate those skilled in the art to understand the technical solutions provided in the embodiments of the present application, the following description is provided for the related technologies:

for a 5G network system, an existing 5G network architecture often includes a general-purpose server for implementing basic data processing operations and an acceleration server for implementing accelerated data processing operations, specifically, the general-purpose server may implement a central unit function (CU), an operation and maintenance management (OAM) function, and an interface function of a 5G base station (RAN), and the acceleration server may implement accelerated data processing operations, and the implementation manner of the acceleration server may include a hardware Distribution Unit (DU), a radio frequency unit (RU), and so on.

In the actual use process, for the universal server for realizing the basic data processing operation, different manufacturers can produce the universal servers with different hardware specifications, and the universal servers with different hardware specifications often correspond to different software logics, so that the problem that the hardware specifications of the universal servers are not uniform, the supported specifications are different, and the software and the hardware of the universal servers are often bound with each other, so that for a user, the complexity of operation and maintenance management of the servers is increased, and the unified management and control and scheduling of resources are not facilitated.

In addition, when the general-purpose server performs data processing operation, the data processing operation is often performed by using local resources of the general-purpose server, so that the local resources of the general-purpose server need to be maintained, and the advantages of the general-purpose server in the aspects of virtualization management and the like cannot be exerted; in addition, the calculation operation and the storage operation of the data are often implemented in the same area or the same space, which results in that the data storage and the data calculation are relatively mixed in the architecture, and the quality and the reliability of the data processing are easily reduced; in addition, the general server is often only in communication connection with the 5G core network, and is not connected with the application on the cloud through a public cloud link, so that the application scene and the application range of the architecture are limited.

In order to solve the above technical problem, this embodiment provides a resource allocation method, a vehicle control method, an edge cloud server and a device, where an execution subject of the resource allocation method may be a resource allocation apparatus, and specifically, refer to fig. 1 as follows:

the resource configuration device may refer to any computing device with a certain resource configuration capability, and in the specific implementation, the resource configuration device may be implemented as a mobile phone, a tablet computer, a set application program, a robot, a cluster server, a conventional server, a cloud host, a virtual center, and the like, and in the specific implementation, the resource configuration device may be implemented as an edge cloud server, and the edge cloud server is deployed in an exclusive network, and the resource configuration method in this case may be applied to the edge cloud server deployed in the exclusive network; in addition, the basic structure of the resource configuration apparatus may include: at least one processor. The number of processors depends on the configuration and type of the requesting end. The resource configuration device may also include a Memory, which may be volatile, such as RAM, or non-volatile, such as Read-Only Memory (ROM), flash Memory, or both. The memory typically stores an Operating System (OS), one or more application programs, and may also store program data and the like. Besides the processing unit and the memory, the resource configuration device also includes some basic configurations, such as a network card chip, an IO bus, a display component, and some peripheral devices. Alternatively, some peripheral devices may include, for example, a keyboard, a mouse, a stylus, a printer, and the like. Other peripheral devices are well known in the art and will not be described in detail herein.

In this embodiment of the application, the resource configuration device is configured to obtain a resource configuration request, where the resource configuration request includes identification information of an edge cloud server that is to perform resource configuration operation, and specifically, the resource configuration operation of the edge cloud server may include at least one of the following: the resource allocation request can correspond to different types to realize the allocation operation of different resource information.

After the resource configuration request is obtained, a preset reference device in communication connection with the edge cloud server and a reference resource of the preset reference device may be determined based on the resource configuration request, where the reference resource may include at least one of: after the reference resources of the preset reference device are obtained, the edge resources of the edge cloud server can be configured to be the same as the reference resources of the preset reference device, so that the edge cloud server can be configured based on the resource configuration request and the reference resources after the reference resources are obtained, the edge resources which are the same as the reference resources can be obtained, and the resource configuration operation of the edge cloud server is realized.

According to the technical scheme provided by the embodiment, the preset reference equipment in communication connection with the edge cloud server and the reference resource of the preset reference equipment are determined by obtaining the resource configuration request, the edge cloud server is configured based on the resource configuration request and the reference resource, the edge resource identical to the reference resource is obtained, the edge resource framework (including the framework of infrastructure) of the edge cloud server and the framework of the preset reference equipment are unified effectively, so that the unified management and maintenance operation of the preset reference equipment and the edge cloud server by a user are facilitated, and the framework of the server is universal, so that various different software logics can be adapted, the practicability of the method is improved, and the popularization and application of the market are facilitated.

The resource allocation method, the vehicle control method, the edge cloud server and the device provided by the embodiments of the present application are specifically described below through an exemplary application scenario. The features of the embodiments and examples described below may be combined with each other without conflict between the embodiments.

Fig. 2 is a schematic flowchart of a resource allocation method according to an embodiment of the present application; referring to fig. 2, in this embodiment, an execution main body of the method may be a resource configuration device, where the resource configuration device may be implemented as software, or a combination of software and hardware, and when the resource configuration device is implemented specifically, the resource configuration device may be implemented as an edge cloud server deployed in an exclusive network, that is, the resource configuration method may be applied to the edge cloud server deployed in the exclusive network, and the edge cloud server may be in communication connection with all IT devices at a site level to implement corresponding data processing operations. Specifically, the resource allocation method may include:

step S201: and acquiring a resource configuration request.

Step S202: and determining a preset reference device in communication connection with the edge cloud server and a reference resource of the preset reference device.

Step S203: and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain the edge resource corresponding to the edge cloud server, wherein the edge resource is the same as the reference resource.

The following describes the implementation process of the above steps in detail:

step S201: and acquiring a resource allocation request.

When a user has a resource configuration demand on the edge cloud server, the resource configuration device can implement resource configuration operation, at this time, the resource configuration device can obtain a resource configuration request, and the resource configuration information can implement configuration operation on at least one of network resources, a computing kernel, storage resources and large-page memory information of the edge cloud server. In addition, the specific obtaining manner of the resource allocation request in this embodiment is not limited, and in some examples, the resource allocation request may be obtained based on an execution operation input by a user, and at this time, obtaining the resource allocation request may include: displaying a display interface for carrying out interactive operation with a user; the method includes the steps of obtaining execution operation input by a user in a display interface, and obtaining a resource configuration request based on the execution operation, wherein the resource configuration request may include identification information corresponding to an edge cloud server and resource information to be configured. In other examples, the resource allocation request may be obtained by the third device, and in this case, obtaining the resource allocation request may include: acquiring a third device in communication connection with the resource allocation device; the resource configuration request is obtained actively or passively by the third device.

The edge cloud server can be in communication connection with preset reference equipment, the preset reference equipment can manage and control the edge cloud server, unified management of the edge cloud server and the preset reference equipment is facilitated for a user, when resource configuration is performed on the edge cloud server, reference resources of the preset reference equipment can be referred to, specifically, when a resource configuration request is obtained, the preset reference equipment in communication connection with the edge cloud server can be determined based on the resource configuration request, and reference resources corresponding to the preset reference equipment are determined, and the reference resources can comprise at least one of the following: generally, after the architecture of the preset reference device is determined, the reference resource corresponding to the preset reference device can be determined.

Step S203: and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge resource corresponding to the edge cloud server, wherein the edge resource is the same as the reference resource.

In order to enable the resource architecture of the edge cloud server to be the same as or substantially the same as the resource architecture of the preset reference device, after the resource configuration request and the reference resource are obtained, a resource configuration operation may be performed on the edge cloud server based on the resource configuration request and the reference resource, so that an edge resource that is the same as the reference resource may be obtained, where the edge resource corresponds to the edge cloud server.

Specifically, the specific implementation manner of configuring the edge cloud server is not limited in this embodiment, and in some examples, the resource configuration operation may be implemented by a machine learning model trained in advance, at this time, configuring the edge cloud server based on the resource configuration request and the reference resource, and obtaining the edge resource corresponding to the edge cloud server may include: the method comprises the steps of obtaining a pre-trained machine learning model, inputting a resource configuration request and a reference resource into the machine learning model after obtaining the resource configuration request and the reference resource, and thus obtaining an edge resource output by the machine learning model, wherein the edge resource is the same as the reference resource and corresponds to an edge cloud server.

In other examples, since the types of the reference resources may include a plurality of types, and different types of reference resources often have different characteristics, in order to ensure the quality and effect of the resource configuration operation, the resource configuration operations corresponding to the different types of resources may be the same and independent, for example, when the reference resources include central network resources; configuring the architecture of the edge cloud server based on the resource configuration request and the reference resource, and obtaining the edge resource corresponding to the edge cloud server may include: and configuring the edge cloud server based on the resource configuration request and the central network resource to obtain the edge network resource corresponding to the edge cloud server, wherein the edge network resource is the same as the central network resource.

As another example, where the reference resource includes a central compute kernel; configuring the edge cloud server based on the resource configuration request and the reference resource, and obtaining the edge resource corresponding to the edge cloud server may include: and configuring the edge cloud server based on the resource configuration request and the central network resource to obtain an edge computing kernel corresponding to the edge cloud server, wherein the edge computing kernel is the same as the central computing kernel.

As another example, where the reference resource comprises a central storage resource; configuring the edge cloud server based on the resource configuration request and the reference resource, and obtaining the edge resource corresponding to the edge cloud server may include: and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge storage resource corresponding to the edge cloud server, wherein the edge storage resource is the same as the central storage resource. It should be noted that the resource configuration operations corresponding to the different types of resources may be performed synchronously or asynchronously.

In still other examples, in order to solve the problem that data operation and data storage are mixed when a resource configuration device (or an edge cloud server) performs data processing operations, so that reliability of data processing may be reduced, this embodiment further provides a technical solution for separately managing different types of edge resources, where after obtaining edge resources corresponding to the edge cloud server, the method in this embodiment may further include: determining attribute information of the edge resources; and managing and controlling the edge resources based on the attribute information, wherein the management and control operations of the edge resources corresponding to different attribute information are mutually independent.

When the types of the edge resources are multiple, in order to perform separate management operations on different types of edge resources, attribute information of the edge resources may be determined first, where the attribute information is used to identify the types and functional roles of the edge resources, and when the edge resources are specifically implemented, the attribute information may be implemented as a resource identifier corresponding to the edge resources, and different edge resources may correspond to different resource identifiers, for example; the edge resources may include at least one of: the edge storage resource is used for realizing storage operation on data, the edge computing resource is used for realizing operation on the data, and the edge network resource is used for realizing transmission of the data, wherein the edge storage resource corresponds to a resource identifier 1, the edge computing resource corresponds to a resource identifier 2, the edge network resource corresponds to a resource identifier 0, and the like. Alternatively, the attribute information may be implemented as a data format corresponding to the edge resource, and different edge resources may correspond to different data formats, for example; the edge resources may include at least one of: the edge storage resources are used for realizing storage operation on data, the edge computing resources are used for realizing operation on the data, and the edge network resources are used for realizing transmission of the data.

Because the attribute information can identify the type and the functional role of the edge resource, after the attribute information is obtained, the edge resource can be managed and controlled based on the attribute information, specifically, management and control operations of the edge resource corresponding to different attribute information are mutually independent, for example, the edge resource includes: when the edge storage resources, the edge computing resources and the edge network resources are used, the separate management and control operation on the edge storage resources, the edge computing resources and the edge network resources can be realized by respectively utilizing different communication links, storage spaces or access paths and the like, so that the situation that data operation and data storage are mixed with each other can be effectively avoided, the accuracy and the reliability of data processing operation are further ensured, and the practicability of the method is improved.

According to the resource configuration method provided by the embodiment, the preset reference device in communication connection with the edge cloud server and the reference resource of the preset reference device are determined by obtaining the resource configuration request, the edge cloud server is configured based on the resource configuration request and the reference resource, the edge resource same as the reference resource is obtained, and the edge resource framework (including the framework of infrastructure) of the edge cloud server and the framework of the preset reference device are unified effectively.

Fig. 3 is a schematic flowchart of another resource allocation method according to an embodiment of the present application; on the basis of the foregoing embodiment, referring to fig. 3, because the edge cloud server is in communication connection with the preset reference device, and the preset reference device can manage and control the edge cloud server, at this time, in order to improve flexible reliability of the method for use, this embodiment further provides an implementation scheme that can flexibly schedule resources of the edge cloud server according to a requirement of the preset reference device, and at this time, the method in this embodiment may further include:

step S301: and acquiring the resource calling request through preset reference equipment.

Step S302: schedulable resources in the edge cloud server are determined based on the resource invocation request.

Step S303: and sending the schedulable resource to preset reference equipment to realize resource scheduling operation.

When the preset reference device performs data processing operation, in order to ensure stable operation of the data processing operation, the preset reference device may selectively call edge resources in the edge cloud server according to a requirement, for example: when the reference resources in the preset reference device cannot meet the data processing requirement, the edge resources in the edge cloud server can be called. When the preset reference device needs to call the edge resources of the edge cloud server, the preset reference device may generate a resource call request, because one preset reference device may be communicatively connected with a plurality of edge cloud servers, at this time, in order to ensure normal operation of resource scheduling, the resource call request may include a server identifier of the edge cloud server to be called, and then the resource call request may be sent to the resource configuration device.

After acquiring the resource calling request, in order to enable a resource scheduling operation, a schedulable resource in the edge cloud server may be determined based on the resource calling request, and the schedulable resource may be at least a part of an edge resource in the edge cloud server. It should be noted that, in order to ensure that the edge cloud server can perform normal data processing operations, when determining schedulable resources, a currently required resource of the edge cloud server may be determined first, and then a difference value between the edge resource in the edge cloud server and the currently required resource may be determined as the schedulable resource. Or after the current required resource is obtained, a resource lower limit value used for ensuring normal operation of basic data processing operation in the edge cloud server can be determined, then the current required resource is analyzed and compared with the resource lower limit value, and when the current required resource is larger than the resource lower limit value, a difference value between the edge resource and the current required resource can be directly determined as a schedulable resource. When the current required resource is less than or equal to the resource lower limit value, the difference value between the edge resource and the resource lower limit value can be determined as the schedulable resource, so that the stable data processing operation of the edge cloud server can be effectively ensured.

After the schedulable resource is determined, the schedulable resource may be sent to the preset reference device, so that the preset reference device may perform a data processing operation based on the schedulable resource, thereby implementing a resource scheduling operation.

In the embodiment, the resource calling request is obtained through the preset reference device, the schedulable resource in the edge cloud server is determined based on the resource calling request, and the schedulable resource is sent to the preset reference device, so that the resource scheduling operation is effectively realized, a user can flexibly select whether the resource scheduling operation needs to be carried out according to the requirement, the utilization rate of the edge resource is improved, and the flexible reliability of the method is also improved.

Fig. 4 is a schematic flowchart of another resource allocation method according to an embodiment of the present application; on the basis of the foregoing embodiment, referring to fig. 4, in order to further improve the practicability and the application range of the method, the method in this embodiment may further include an implementation scheme for performing application configuration based on an edge cloud server, and specifically, the method in this embodiment may further include:

step S401: function configuration information corresponding to a preset function is acquired.

Step S402: and performing configuration operation of a preset function based on the function configuration information so as to enable the edge cloud server to realize the preset function.

The edge cloud server can perform function configuration operation according to user requirements, and at the moment, the edge cloud server can acquire function configuration information which is used for achieving configuration operation of a certain application program or loading operation of a certain preset function through the edge cloud server. Specifically, when a user wants to implement a certain preset function (e.g., an image processing function, a video processing function, a fault location function, etc.), and the edge cloud server does not have the preset function and can support the preset function, a function configuration operation of the preset function may be performed through the edge cloud server, at this time, the resource configuration device (e.g., the edge cloud server) may obtain function configuration information (the function configuration information may include a function configuration file, a function attribute, etc.) corresponding to the preset function, a specific obtaining manner of the function configuration information is similar to a specific obtaining manner of the resource configuration request, which may specifically refer to the above statements and is not described again.

After the function configuration information is acquired, configuration operation of a preset function can be performed based on the function configuration information, so that the edge cloud server can realize the preset function; for example: enabling the edge cloud server to realize an image processing function based on the function configuration information; enabling the edge cloud server to realize a video processing function based on the function configuration information; fault handling functions and the like may be implemented by the edge cloud server based on the functional configuration information.

It should be noted that, the technical solution in this embodiment can perform the function configuration operation not only based on the requirement of the user, but also based on the requirement of the user and the current network situation or communication situation, for example: when the current network condition (the network bandwidth is less than or equal to the first bandwidth threshold, or the network rate is less than or equal to the first rate threshold) or the communication condition (the number of visiting users is less than or equal to the preset number) is the network state 1, the preset function 1 meeting the network state 1 can be configured based on the requirements of the users; when the current network condition (the network bandwidth is greater than the first bandwidth threshold, or the network rate is greater than the first rate threshold) or the communication condition (the number of visiting users is greater than the preset number) is the network state 2, the preset function 2 meeting the network state 2 can be configured based on the requirements of the users, which is beneficial to ensuring the implementation quality and effect of the configured preset function.

In the embodiment, function configuration information corresponding to a preset function is acquired; and then, configuration operation of the preset function is carried out based on the function configuration information, so that the edge cloud server can realize the preset function, the configuration operation of the preset function which can be realized by the edge cloud server can be effectively realized according to the requirement of a user, the personalized requirements of different users can be met, and the flexibility and the reliability of the method are further improved.

In still other examples, in order to solve the problem that the edge cloud server in the prior art is only in communication connection with a 5G core network, but is not in communication connection with an on-cloud application through a public cloud link, which effectively limits an application range of the edge cloud server, since the edge cloud server in this embodiment may be in communication connection with a preset reference device, and may invoke the on-cloud application through the preset reference device, specifically, the method in this embodiment may further include:

step S401': and acquiring an application calling request corresponding to a preset application, wherein the preset application is deployed on a preset reference device.

Step S402': and sending the application calling request to preset reference equipment so as to call the preset application through the preset reference equipment to perform data processing operation.

When a user wants to implement a certain preset function (for example, an image processing function, a video processing function, a fault location function, and the like), and the edge cloud server does not have the preset function and cannot support the preset function, the preset function cannot be implemented by performing configuration operation on the edge cloud server. After the application calling request is obtained, the application calling request can be sent to the preset reference device so that the preset application can be called through the preset reference device to perform data processing operation, and therefore stability and reliability of the data processing operation are guaranteed.

In the embodiment, an application calling request corresponding to a preset application is obtained; and then sending the application calling request to the cloud server so as to call the preset application through the preset reference equipment to perform data processing operation, wherein at the moment, the edge cloud server and the preset reference equipment are communicated with each other, so that the preset application on the cloud can be effectively called by a user according to the requirement, the personalized requirements of different users can be met, the stable operation of the data processing operation is ensured, and the flexible reliability of the method is further improved.

Fig. 5 is a schematic flowchart of a resource allocation method according to an embodiment of the present application; on the basis of any one of the above embodiments, referring to fig. 5, after obtaining the edge resource corresponding to the edge cloud server, the data processing operation may be performed based on the edge resource, specifically, the method in this embodiment may include:

step S501: and acquiring a data processing request.

Step S502: a resource requirement corresponding to the data processing request is determined.

Step S503: and when the edge resource does not meet the resource requirement, performing containerization processing on the edge resource based on the data processing request to obtain the containerization resource meeting the resource requirement.

When a user has a data processing requirement, the resource configuration device (or the edge cloud server) may obtain a data processing request, where a specific obtaining manner of the data processing request is similar to a specific obtaining manner of the resource configuration request, and the above statements may be specifically referred to, and details are not described here again. To enable data processing operations, after the data processing request is obtained, the data processing request may be analyzed to determine a resource requirement corresponding to the data processing request, where the resource requirement may include at least one of: network resource requirements, computing resource requirements, storage resource requirements, and the like.

After the resource demand is obtained, the edge resource and the resource demand may be analyzed and compared, and when the edge resource cannot meet the resource demand, it is indicated that the edge resource provided by the edge cloud server is not adapted to the resource demand, for example: the number of network interfaces is not adapted, the number of compute cores is not adapted, the number of storage spaces is not adapted, etc. In this case, in order to meet the resource demand, the resource information may be subjected to containerization processing based on the resource demand, so that a plurality of containerized resources meeting the resource demand may be obtained. Specifically, the specific implementation manner of the containerization process is not limited in this embodiment, in some examples, the containerization process operation may be automatically implemented by a machine learning model, at this time, the machine learning model for implementing the containerization process is trained in advance, and after the resource demand and the edge resource are obtained, the resource demand and the edge resource may be input into the machine learning model, so that a plurality of containerization resources output by the machine learning model may be obtained, and the plurality of containerization resources are adapted to the resource demand.

In other instances, since edge resources have different types of behavior, for example: the edge resources may include edge storage resources, edge computing kernels, edge network resources, and the like, and different edge resources often correspond to different containerization processing manners, and in order to ensure normal operation of containerization processing, different processing manners may be adopted to process different edge resources, and at this time, performing containerization processing on resource information based on a data processing request may include: the method comprises the steps of determining an information type corresponding to resource information, determining an implementation mode for containerizing the resource information based on the information type and the resource requirement, and containerizing the resource information based on the implementation mode, so that a plurality of containerized resources meeting the resource requirement can be obtained.

In specific implementation, when the edge resource includes an edge network resource, the edge network resource at this time may mainly refer to a network interface or a network port; containerizing the edge resource based on the data processing request, and obtaining the containerized resource satisfying the resource requirement may include: acquiring address information for identifying edge network resources; and performing containerization processing on the address information based on the resource demand to obtain a plurality of virtualized network resources corresponding to the resource demand, wherein the address information corresponding to different virtualized network resources is different.

When the edge network resource includes an edge network port or an edge network port, the number of edge network interfaces provided by the hardware resource is often fixed, for example: the number of edge network interfaces provided by the edge cloud server may be 1 or 2, while the number of network interfaces required for different data processing requests may be different, for example: the number of the network interfaces required by the data processing request can be 3, 4, 5 or 6, and the like, and the edge network resources which can be provided by the edge cloud server cannot meet the resource requirement, so that the edge network resources can be subjected to containerization processing. Because the address information corresponding to the edge network resource is often pre-configured, and different network interfaces may correspond to different address information, containerization processing may be performed based on the address information. Specifically, address information for identifying the edge network resource may be obtained, for example: the address information corresponding to a certain edge network resource is 211.138.176.0 to 211.138.176.255, the address information corresponding to a certain edge network resource is 210.76.208.0 to 210.76.208.255, and so on. Because the address information or address information corresponding to different edge network interfaces is often different, after the address information is obtained, containerization processing can be performed on the address information based on resource requirements, so that a plurality of virtualized network resources can be obtained.

For example, the address information corresponding to a certain edge network resource is 211.138.176.0 to 211.138.176.255, the number of network interfaces at this time is 1, and the number of network interfaces corresponding to resource requirements is 3, at this time, an implementation manner may automatically perform containerization processing using a machine learning model, at this time, a machine learning model trained in advance may be obtained, and then the obtained resource requirements, address information, and network resources are input to the machine learning model, so that three virtualized network interfaces output by the machine learning model may be obtained. Another implementation manner is to divide the address information, and then obtain three virtualized network interfaces based on the result after division, at this time, after obtaining the address information, the address information may be subjected to trisection processing or non-trisection processing based on resource requirements, and three pieces of sub-address information are obtained, for example, the three pieces of sub-address information may be: 211.138.176.0-211.138.176.84, 211.138.176.85-211.138.176.169, 211.138.176.170-211.138.255, then virtualizing three corresponding virtual network ports based on the sub-address information, and the address information corresponding to different virtual network ports is different, thereby effectively implementing the virtualization operation of network resources.

In addition, when the edge resource includes an edge computing kernel, performing containerization processing on the edge resource based on resource requirements, and obtaining the containerization resource meeting the resource requirements may include: acquiring the number of kernels of an edge computing kernel; and performing containerization processing on the computing kernel based on the resource demand and the kernel quantity to obtain a plurality of virtualized kernels corresponding to the resource demand, wherein the resources corresponding to different virtualized kernels are different.

When the edge resource includes an edge computing kernel, since the computing kernel of the edge cloud server is configured after the network architecture of the edge cloud server is determined, the number of the computing kernels of the edge cloud server is often fixed, for example: the number of computing cores provided by the edge cloud server is 1, 2, or 3, and so on, and the number of edge computing cores required for different data processing requests may be different, for example: the number of the computing cores required by the data processing request 1 may be 5, 6, or 8, and the like, and the edge computing cores that can be provided by the edge cloud server at this time cannot meet the resource requirement, so that containerization processing may be performed on the edge computing cores, and thus, a plurality of virtualized cores corresponding to the resource requirement may be obtained. For example, the number of computing cores provided by the edge cloud server is 2, and the number of computing cores required by the resource requirement is 6, and then the edge computing cores may be subjected to virtualization partition processing based on the resource requirement, for example: one edge computing kernel can be virtualized into 3, so that 6 virtualized kernels corresponding to resource requirements can be obtained, resources corresponding to different virtualized kernels can be different, and the operation of containerization processing on the computing kernels is effectively realized.

Further, when the edge resource comprises an edge storage resource; performing containerization processing on the edge resource based on the resource demand, and obtaining the containerized resource meeting the resource demand may include: acquiring a storage space for identifying edge storage resources; and performing containerization processing on the storage space based on the resource demand to obtain a plurality of virtualized spaces corresponding to the resource demand, wherein the space addresses corresponding to different virtualized spaces are different.

When the edge resources include edge storage resources, since the storage space of the edge cloud server is configured after the network architecture is determined, the number of the storage spaces is often fixed, for example: the storage space provided by the edge cloud server is 1, 2 or 3, and so on, and the storage space required by different data processing requests may be different, for example: the storage space required by the data processing request can be 5, 6 or 8, and the edge storage resource which can be provided by the edge cloud server at the moment cannot meet the resource requirement, so that the edge storage resource can be subjected to containerization processing.

In the embodiment, after the edge resources corresponding to the edge cloud server are obtained, the resource requirements corresponding to the data processing requests are determined by obtaining the data processing requests, and when the edge resources do not meet the resource requirements, the edge resources are subjected to containerization processing based on the data processing requests to obtain the containerized resources meeting the resource requirements, so that various data processing requests can be effectively adapted to various types of resources, namely, decoupling among a hardware layer, a virtual layer and a software layer is realized, the network architecture is more flexible and convenient to adjust, in addition, a user can arrange and manage the network architecture through a resource configuration device at any time based on the requirements, the operation is simple and reliable, the difficulty of network maintenance and management is further reduced, the flexible reliability of the use of the method is effectively improved, and the popularization and the application of the market are facilitated.

In specific application, referring to fig. 6, taking a central cloud server as a preset reference device and a central resource as a reference resource as an example, the present application embodiment provides a cloud infrastructure architecture for a 5G base station, where the cloud infrastructure architecture is mainly used for a 5G private network, and the cloud infrastructure architecture optimizes a general server, so as to realize transformation of the cloud infrastructure architecture, and significantly improve management, operation and maintenance and resource utilization efficiency of the 5G network architecture, and specifically, the cloud infrastructure architecture may include:

the 5G private network core network is in communication connection with the edge cloud server and is used for providing a network connection function;

the edge cloud server (i.e., a general server) is deployed in the 5G private network, is in communication connection with a core network of the 5G private network, and is used for implementing general data processing operations, and specifically, the edge cloud server may implement a central unit CU function, an operation maintenance management OMA function, and a preset interface function (e.g., an N2 interface function, an N3 interface function) of the 5G base station.

The special hardware (special server) is deployed in the 5G private network, is in communication connection with a core network of the 5G private network, and is used for realizing accelerated data processing operation, wherein the implementation manner of the special hardware may include a hardware distribution unit DU or a radio frequency unit RU, and the special hardware may perform custom configuration operation according to user requirements.

In addition, an edge cloud server in the cloud infrastructure architecture may be communicatively connected to a central cloud server, and the edge cloud server (i.e., the field-level cloud infrastructure) may define or configure resource information such as hardware resources, computing resources (ECS), storage resources (EBS), network resources (VPC), and the like, where the resource information of the types described above may be managed and maintained independently, and the edge cloud server may reuse the same architecture in the central cloud server (or a public cloud server), that is, the edge cloud server may be deployed with reference to the architecture of the central cloud server, so that a user may perform uniform management and maintenance on the edge cloud server and the central cloud server, and in addition, the edge cloud server may load a 5G base station function, where the 5G core network function may be selected arbitrarily according to a user requirement.

In a specific implementation, a large amount of application products in a public cloud form may be deployed in the central cloud server, for example: the system comprises a load balancing application for realizing load balancing operation, a container service application for realizing container operation, a big data development platform EMR application for realizing big data analysis and processing, a relational database service RDS, a function computing application, a cloud desktop application and the like, and similar to a central cloud server, the edge cloud server can also deploy corresponding application products according to requirements, so that the practicability of the framework can be expanded.

Similarly, the central cloud server may also deploy multiple tools that implement different functions, such as: the system comprises an access control tool, a cloud management and control tool, an elastic telescopic tool, a resource arrangement tool, an operation auditing tool, an EMS tool and the like, wherein different functional operations can be realized by the different tools, and the edge cloud server can call the required tool to perform corresponding data processing operation through the central cloud server, so that different processing requirements of users can be met, and the flexibility and the reliability of the use of the framework are further improved.

The cloud infrastructure architecture provided by the application embodiment effectively unifies resource architectures of the central cloud server and the edge cloud servers, for example: the hardware specifications of the central cloud server and the edge cloud server are uniformly operated, so that the edge cloud server can reuse the scale of the central cloud server with other network applications, and a user can conveniently and uniformly control and schedule the resources of the central cloud server and the edge cloud server; in addition, the edge cloud server can call the application (such as management and control and data analysis) on the cloud of the public cloud, so that different use requirements of different users can be met; it should be noted that the data storage operation and the calculation operation in the architecture are independent from each other, which is beneficial to improving the stability and reliability of data processing; moreover, the framework realizes unified containerization service, can shield the requirement of bottom hardware, is more universal, has wider application range and scenes, further improves the practicability of the framework, and is beneficial to popularization and application in the market.

Fig. 7 is a schematic flowchart of a private network management and control method according to an embodiment of the present application; referring to fig. 7, in the embodiment, an execution main body of the method may be a private network management and control device, it can be understood that the private network management and control device may be implemented as software or a combination of software and hardware, when the method is implemented specifically, the private network management and control device may be deployed in a private network, the private network may be deployed in different application scenes or application areas, the areas may include a factory area (smart factory), a park area (smart park, residential park, etc.), a mine area, etc., and when the area is a factory area, the private network management and control method in the embodiment may implement flexible control operation on the private networks corresponding to different factory areas; when the area is a park area, the private network control method in the embodiment can realize flexible control operation on the private networks corresponding to different park areas; when the area is a mine area, the private network control method in the embodiment can realize flexible control operation on devices in different mine areas. Specifically, the private network management and control method may include:

step S701: the network control request is obtained through a proprietary network.

Step S702: processing the network control request by using an edge cloud server deployed in the dedicated network to obtain network control information corresponding to the dedicated network, wherein the network control request is processed by using edge resources corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, and the edge resources are the same as the reference resources of the preset reference equipment.

Step S703: controlling the dedicated network based on the network control information.

Specifically, when the dedicated network is used for performing corresponding data processing operation, a user can control the dedicated network according to requirements, specifically, in order to accurately and effectively control the dedicated network, a network control request can be acquired through the dedicated network, in order to perform stable control operation on the dedicated network, the network control request can be processed by using a marginal cloud server deployed in the dedicated network, and network control information corresponding to the dedicated network is acquired, and the network control information can include information for controlling a network operation state of the dedicated network, information for controlling storage data of the dedicated network, information for controlling computing resources of the dedicated network, and the like, and then the dedicated network can be controlled based on the network control information, so that the practicability of the method is further improved.

It should be noted that the method in this embodiment may also include the method in the embodiment shown in fig. 1 to fig. 6, and for the part not described in detail in this embodiment, reference may be made to the related description of the embodiment shown in fig. 1 to fig. 6. The implementation process and technical effect of the technical solution refer to the descriptions in the embodiments shown in fig. 1 to 6, and are not described herein again.

Similarly, the embodiment may also provide a vehicle control method, where an execution subject of the method may be a vehicle control device, and it is understood that the vehicle control device may be implemented as software, or a combination of software and hardware, and when implemented specifically, the vehicle control device may be deployed in a dedicated network to implement a control operation on a vehicle. Specifically, the vehicle control method may include:

step S701': and acquiring a vehicle control request corresponding to the vehicle to be controlled through a dedicated network.

Step S702': the method comprises the steps that a vehicle control request is processed by an edge cloud server deployed in an exclusive network, vehicle control information corresponding to a vehicle to be controlled is obtained, wherein the vehicle control request is processed through edge resources corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, and the edge resources are the same as the reference resources of the preset reference equipment.

Step S703': and controlling the vehicle to be controlled based on the vehicle control information.

In particular, a vehicle to be controlled may correspond to one or more dedicated networks, such as: a certain enterprise may include a factory floor a located in an area a and a factory floor B located in an area B, the factory floor a corresponds to the private network a, the factory floor B corresponds to the private network B, and the private network a and the private network B both belong to the certain enterprise, at this time, a registered vehicle of an employee of the enterprise may correspond to the private network a and the private network B, and when the registered vehicle travels to the area a or the area B, the registered vehicle is allowed to pass and parking operation may be guided.

Therefore, in the process of driving the vehicle to be controlled (an unmanned vehicle or a manned vehicle), in order to accurately and effectively control the vehicle to be controlled, a vehicle control request corresponding to the vehicle to be controlled can be acquired through the dedicated network, in order to perform stable control operation on the vehicle to be controlled in the dedicated network, a sensor can be arranged on the vehicle to be controlled, and the running state data corresponding to the vehicle to be controlled can be quickly acquired through the sensor, and can include at least one of the following: the vehicle driving method comprises the steps of obtaining the current vehicle speed, the driving direction and the environment information of a vehicle, wherein the environment information comprises the distribution position of surrounding objects, the vehicle speed of the vehicle in front of the vehicle and the road speed limit of the road where the vehicle is located. In some examples, the sensors may include an image acquisition sensor, a radar sensor, and a global positioning system GPS, and in particular, the operating state data corresponding to the vehicle to be controlled is determined by the image acquisition sensor, the radar sensor, and the global positioning system GPS.

After the vehicle control request is obtained, the vehicle control request can be processed by using the edge cloud server deployed in the exclusive network, vehicle control information corresponding to the vehicle to be controlled is obtained, the vehicle control information can be used for assisting the vehicle to be controlled to stop in a preset area or assisting the vehicle to be controlled to pass through the preset area, and the like, and then the vehicle to be controlled can be controlled based on the vehicle control information, so that the practicability of the method is further improved.

It should be noted that, as for the vehicle control device, the vehicle control device may be provided on the vehicle, or the vehicle control device may be provided independently of the vehicle, in which case the vehicle control device may be communicatively connected to the vehicle CPU.

In addition, the vehicle control device can be adjusted according to different vehicles, that is, algorithm modules included in the vehicle control device are different according to different vehicle types, and in this case, the vehicle control device can implement not only control operation of automatic driving of the vehicle, but also other operations. For example, different vehicle control devices may be involved for a logistics vehicle, a public service vehicle, a medical service vehicle, and a terminal service vehicle. Algorithm modules included in the vehicle control device are exemplified below for the four kinds of autonomous vehicles, respectively:

wherein, the logistics vehicle refers to the vehicle that uses in the logistics scene, for example: the logistics vehicle with the automatic sorting function, the refrigeration and heat preservation function and the measurement function can be used. These logistics vehicles may involve different algorithm modules.

For example, the logistics vehicles can be provided with an automatic sorting device which can automatically take out, convey, sort and store the goods after the logistics vehicles reach the destination. This relates to an algorithm module for goods sorting, which mainly implements logic control of goods taking out, carrying, sorting, storing and the like.

For another example, in a cold chain logistics scenario, the logistics vehicle may further include a refrigeration and insulation device, and the refrigeration and insulation device may implement refrigeration or insulation of transported fruits, vegetables, aquatic products, frozen foods, and other perishable foods, so that the transportation environment is in a proper temperature environment, and the long-distance transportation problem of perishable foods is solved. The algorithm module is mainly used for dynamically and adaptively calculating the proper temperature of cold meal or heat preservation according to the information such as the property, the perishability, the transportation time, the current season, the climate and the like of food (or articles), and automatically adjusting the cold-storage heat preservation device according to the proper temperature, so that a transport worker does not need to manually adjust the temperature when the vehicle transports different foods or articles, the transport worker is liberated from the complicated temperature regulation and control, and the efficiency of cold-storage heat preservation transportation is improved.

For another example, in most logistics scenarios, the fee is charged according to the volume and/or weight of the parcel, but the number of the logistics parcels is very large, and the measurement of the volume and/or weight of the parcel by only depending on a courier is very inefficient and has high labor cost. Therefore, in some logistics vehicles, a measuring device is added, so that the volume and/or the weight of the logistics packages can be automatically measured, and the cost of the logistics packages can be calculated. This relates to an algorithm module for logistics package measurement, which is mainly used to identify the type of logistics package, determine the measurement mode of logistics package, such as volume measurement or weight measurement or combined measurement of volume and weight, and can complete the measurement of volume and/or weight according to the determined measurement mode and complete the cost calculation according to the measurement result.

The public service vehicle refers to a vehicle providing some public service, for example: can be a fire truck, an ice removing vehicle, a watering cart, a snow clearer, a garbage disposal vehicle, a traffic command vehicle and the like. These public service vehicles may involve different algorithm modules.

For example, in the case of an automatically driven fire fighting vehicle, the main task is to perform a reasonable fire fighting task on the fire scene, which involves an algorithm module for the fire fighting task, which at least needs to implement logic such as identification of the fire situation, planning of the fire fighting scheme, and automatic control of the fire fighting device.

For another example, for an ice removing vehicle, the main task is to remove ice and snow on the road surface, which involves an algorithm module for ice removal, the algorithm module at least needs to realize the recognition of the ice and snow condition on the road surface, formulate an ice removal scheme according to the ice and snow condition, such as which road sections need to be deiced, which road sections need not to be deiced, whether a salt spreading manner, the salt spreading gram number, and the like are adopted, and the logic of automatic control of a deicing device under the condition of determining the ice removal scheme.

The medical service vehicle is an automatic driving vehicle capable of providing one or more medical services, the vehicle can provide medical services such as disinfection, temperature measurement, dispensing and isolation, and the algorithm module relates to algorithm modules for providing various self-service medical services, the algorithm modules mainly realize identification of disinfection requirements and control of a disinfection device so that the disinfection device can disinfect patients, or identify the positions of the patients, control the temperature measurement device to automatically press close to the forehead and the like of the patients to measure the temperature of the patients, or is used for realizing judgment of symptoms, giving out prescriptions according to judgment results and realizing identification of medicine/medicine containers and control of a medicine taking manipulator so that the medicine taking manipulator can grab medicines for the patients according to the prescriptions, and the like. The terminal service vehicle refers to a self-service automatic driving vehicle which can replace some terminal devices to provide some convenient service for users, for example, the vehicles can provide services such as printing, attendance checking, scanning, unlocking, payment and retail for the users.

For example, in some application scenarios, a user often needs to go to a specific location to print or scan a document, which is time consuming and labor intensive. Therefore, a terminal service vehicle capable of providing printing/scanning service for a user appears, the service vehicles can be interconnected with user terminal equipment, the user sends a printing instruction through the terminal equipment, the service vehicle responds to the printing instruction, documents required by the user are automatically printed, the printed documents can be automatically sent to the position of the user, the user does not need to queue at a printer, and the printing efficiency can be greatly improved. Or, the scanning instruction sent by the user through the terminal equipment can be responded, the scanning vehicle is moved to the position of the user, the user finishes scanning on the scanning tool of the service vehicle on which the document to be scanned is placed, queuing at the printing/scanning machine is not needed, and time and labor are saved. This involves an algorithm module providing print/scan services that needs to identify at least the interconnection with the user terminal equipment, the response to print/scan instructions, the positioning of the user's location, and travel control.

For another example, as new retail scenes are developed, more and more electronic stores sell goods to large office buildings and public areas by means of self-service vending machines, but the self-service vending machines are placed at fixed positions and are not movable, and users need to go by the self-service vending machines to purchase needed goods, so that the convenience is poor. Therefore, self-service driving vehicles capable of providing retail services appear, the service vehicles can carry commodities to move automatically and can provide corresponding self-service shopping APP or shopping entrances, a user can place an order for the self-service driving vehicles providing retail services through the APP or shopping entrances by means of a terminal such as a mobile phone, the order comprises names and numbers of commodities to be purchased, and after the vehicle receives an order placement request, whether the current remaining commodities have the commodities purchased by the user and whether the quantity is sufficient can be determined. This involves algorithm modules that provide retail services that implement logic primarily to respond to customer order requests, order processing, merchandise information maintenance, customer location, payment management, etc.

It should be noted that the method in this embodiment may also include the method in the embodiment shown in fig. 1 to fig. 6, and for the part of this embodiment that is not described in detail, reference may be made to the relevant description of the embodiment shown in fig. 1 to fig. 6. The implementation process and technical effect of the technical solution refer to the descriptions in the embodiments shown in fig. 1 to 6, and are not described herein again.

Fig. 8 is a schematic flowchart of a data processing method according to an embodiment of the present application; referring to fig. 8, the embodiment provides a data processing method, an execution subject of the method may be a data processing device, it may be understood that the data processing device may be implemented as software, or a combination of software and hardware, and when the data processing device is implemented specifically, the data processing device may be deployed in a dedicated network to implement a control operation on an augmented reality terminal. Specifically, the data processing method may include:

step S801: and acquiring a data processing request corresponding to the augmented reality terminal through the dedicated network.

The Augmented Reality terminal may be implemented as a head mounted display Device (HMD for short) in the field of Augmented Reality (AR), virtual Reality (VR for short), or Mixed Reality (MR for short), or video Reality (CR for short), and may be in communication connection with the cloud platform, so as to implement an Augmented Reality game scene, an Augmented Reality conference scene, and the like based on the Augmented Reality terminal.

During specific application, the augmented reality terminal may be located in a certain area, and a certain dedicated network may be deployed in the area, at this time, in order to increase the entertainment and the extensibility of the augmented reality terminal, the registered user may access the dedicated network through the augmented reality terminal, and may call some application programs located in the dedicated network, for example: the method comprises the steps that an application program A, an application program B and an application program C are deployed in an exclusive network, an extended reality terminal accesses the exclusive network and passes validity verification, the extended reality terminal can call the application program A, the application program B and the application program C, the application range of the extended reality terminal is effectively expanded, in order to enable the extended reality terminal to stably run the application program, a data processing request corresponding to the extended reality terminal can be obtained through the exclusive network, the data processing request can comprise an identity of the extended reality terminal, and validity verification operation is conducted on the extended reality terminal.

Step S802: the data processing method comprises the steps that a data processing request is processed by an edge cloud server deployed in an exclusive network, and a data processing result corresponding to an augmented reality terminal is obtained, wherein the data processing request is processed through edge resources corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, and the edge resources are the same as the reference resources of the preset reference equipment.

Step S803: and controlling the augmented reality terminal based on the data processing result.

After the data processing request is acquired, the data processing request may be processed by the edge cloud server to obtain a data processing result, and the augmented reality terminal may be controlled based on the data processing result, for example: the display interface or the display content in the augmented reality terminal can be controlled or adjusted, so that the augmented reality terminal can stably perform data processing operations, for example: an application program located in a dedicated network can be stably run, and the like.

In other examples, after the augmented reality terminal is controlled based on the data processing result, the virtual scene information in the augmented reality terminal can be acquired, and the data processing result is displayed or run in the virtual scene information, so that the user can know the data processing result in time, and the experience of the user in using the augmented reality terminal is improved.

It should be noted that the method in this embodiment may also include the method in the embodiment shown in fig. 1 to fig. 6, and for the part not described in detail in this embodiment, reference may be made to the relevant description of the embodiment shown in fig. 1 to fig. 6. The implementation process and technical effect of the technical solution refer to the descriptions in the embodiments shown in fig. 1 to 6, and are not described herein again.

Similar to the foregoing implementation, the augmented reality terminal may be replaced by a conference participating device, and at this time, the data processing method in this embodiment may include:

step S801': acquiring a data processing request corresponding to the conference participating equipment through an exclusive network;

step S802': processing a data processing request by using an edge cloud server deployed in an exclusive network to obtain a data processing result corresponding to a participated device, wherein the data processing request is processed by using an edge resource corresponding to the edge cloud server, the edge cloud server is in communication connection with a preset reference device, and the edge resource is the same as the reference resource of the preset reference device;

step S803': and controlling the conference participating equipment based on the data processing result.

Wherein, controlling the conferencing device based on the data processing result may include: carrying out validity verification operation on the conference participating equipment based on the data processing result, and generating validity prompt information when the conference participating equipment is determined to be legal equipment; and when the participated equipment is determined to be illegal equipment, generating illegal prompt information. In other examples, controlling the conference participating device based on the data processing result may further include: and performing check-in operation and the like on the conference participating equipment based on the data processing result, thereby effectively improving the practicability of the method.

Fig. 9 is a schematic structural diagram of an edge cloud server according to an embodiment of the present application; referring to fig. 9, the present embodiment provides an edge cloud server, which may perform the resource allocation method shown in fig. 2, and the edge cloud server may be deployed in a dedicated network; specifically, the edge cloud server includes:

a first obtaining module 11, configured to obtain a resource configuration request;

the first determining module 12 is configured to determine a preset reference device in communication connection with the edge cloud server and a reference resource of the preset reference device;

the first processing module 13 is configured to configure the edge cloud server based on the resource configuration request and the reference resource, and obtain an edge resource corresponding to the edge cloud server, where the edge resource is the same as the reference resource.

In some examples, the reference resource comprises a central network resource; when the first processing module 13 configures the architecture of the edge cloud server based on the resource configuration request and the reference resource, and obtains an edge resource corresponding to the edge cloud server, the first processing module 13 is configured to perform: and configuring the edge cloud server based on the resource configuration request and the central network resource to obtain the edge network resource corresponding to the edge cloud server, wherein the edge network resource is the same as the central network resource.

In some examples, the reference resource includes a central computing kernel; when the first processing module 13 configures the edge cloud server based on the resource configuration request and the reference resource, and obtains an edge resource corresponding to the edge cloud server, the first processing module 13 is configured to perform: and configuring the edge cloud server based on the resource configuration request and the central network resource to obtain an edge computing kernel corresponding to the edge cloud server, wherein the edge computing kernel is the same as the central computing kernel.

In some examples, the reference resource comprises a central storage resource; when the first processing module 13 configures the edge cloud server based on the resource configuration request and the reference resource, and obtains an edge resource corresponding to the edge cloud server, the first processing module 13 is configured to perform: and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge storage resource corresponding to the edge cloud server, wherein the edge storage resource is the same as the central storage resource.

In some examples, the first obtaining module 11, the first determining module 12 and the first processing module 13 in this embodiment are configured to perform the following steps:

a first obtaining module 11, configured to obtain a resource calling request through a preset reference device;

a first determining module 12, configured to determine schedulable resources in an edge cloud server based on the resource calling request;

the first processing module 13 is configured to send the schedulable resource to a preset reference device, so as to implement a resource scheduling operation.

In some examples, after obtaining the edge resource corresponding to the edge cloud server, the first determining module 12 and the first processing module 13 in this embodiment are configured to perform the following steps:

a first determining module 12, configured to determine attribute information of an edge resource;

the first processing module 13 is configured to manage and control edge resources based on the attribute information, where management and control operations of the edge resources corresponding to different attribute information are independent of each other.

In some examples, the first obtaining module 11 and the first processing module 13 are configured to perform the following steps:

a first obtaining module 11, configured to obtain function configuration information corresponding to a preset function;

the first processing module 13 is configured to perform configuration operation of a preset function based on the function configuration information, so that the edge cloud server can implement the preset function.

In some examples, the first obtaining module 11 and the first processing module 13 in this embodiment are configured to perform the following steps:

the first obtaining module 11 is configured to obtain an application call request corresponding to a preset application, where the preset application is deployed on a cloud server;

the first processing module 13 is configured to send an application call request to a cloud server, so as to call the preset application through the preset reference device to perform data processing operation.

In some examples, after obtaining the edge resource corresponding to the edge cloud server, the first obtaining module 11, the first determining module 12, and the first processing module 13 in this embodiment are configured to perform the following steps:

a first obtaining module 11, configured to obtain a data processing request;

a first determining module 12, configured to determine a resource requirement corresponding to the data processing request;

the first processing module 13 is configured to, when the edge resource does not meet the resource requirement, perform containerization processing on the edge resource based on the data processing request to obtain a containerized resource meeting the resource requirement.

The edge cloud server shown in fig. 9 may execute the method of the embodiment shown in fig. 1 to fig. 6, and reference may be made to the related description of the embodiment shown in fig. 1 to fig. 6 for a part not described in detail in this embodiment. The implementation process and technical effect of the technical solution refer to the descriptions in the embodiments shown in fig. 1 to 6, and are not described herein again.

In one possible design, the architecture of the edge cloud server shown in fig. 9 may be implemented as an electronic device. As shown in fig. 10, the electronic device may include: a first processor 21 and a first memory 22. Wherein the first memory 22 is used for storing programs for corresponding electronic devices to execute the resource configuration method provided in the embodiments shown in fig. 1-6, and the first processor 21 is configured for executing the programs stored in the first memory 22.

The program comprises one or more computer instructions, wherein the one or more computer instructions, when executed by the first processor 21, are capable of performing the steps of: acquiring a resource allocation request; determining preset reference equipment in communication connection with the edge cloud server and reference resources of the preset reference equipment; and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain the edge resource corresponding to the edge cloud server, wherein the edge resource is the same as the reference resource.

Further, the first processor 21 is also used for executing all/part of the steps in the embodiments shown in fig. 1-6. The electronic device may further include a first communication interface 23, which is used for the electronic device to communicate with other devices or a communication network.

In addition, an embodiment of the present invention provides a computer storage medium for storing computer software instructions for an electronic device, which includes a program for executing the resource allocation method in the method embodiments shown in fig. 1 to fig. 6.

Furthermore, an embodiment of the present invention provides a computer program product, including: computer program, which, when being executed by a processor of an electronic device, causes the processor to carry out the method of resource allocation in the method embodiments shown in fig. 1-6.

Fig. 11 is a schematic structural diagram of a private network management and control device according to an embodiment of the present application; referring to fig. 11, in this embodiment, a private network management and control apparatus is provided, where the private network management and control apparatus is configured to execute the private network management and control method shown in fig. 7, specifically, the private network management and control apparatus may include:

a second obtaining module 31, configured to obtain a network control request through a dedicated network;

the second processing module 32 is configured to process a network control request by using an edge cloud server deployed in the dedicated network, and obtain network control information corresponding to the dedicated network, where the network control request is processed through an edge resource corresponding to the edge cloud server, the edge cloud server is communicatively connected to a preset reference device, and the edge resource is the same as a reference resource of the preset reference device;

the second control module 33 is configured to control the dedicated network based on the network control information.

The private network management and control apparatus shown in fig. 11 may execute the method shown in the embodiment shown in fig. 7, and reference may be made to the related description of the embodiment shown in fig. 7 for a part not described in detail in this embodiment. The implementation process and technical effect of the technical solution are described in the embodiment shown in fig. 7, and are not described herein again.

In one possible design, the structure of the private network management and control apparatus shown in fig. 11 may be implemented as an electronic device. As shown in fig. 12, the electronic device may include: a second processor 41 and a second memory 42. The second memory 42 is used for storing a program of the corresponding electronic device for executing the private network management and control method provided in the embodiment shown in fig. 7, and the second processor 41 is configured to execute the program stored in the second memory 42.

The program comprises one or more computer instructions, wherein the one or more computer instructions, when executed by the second processor 41, are capable of performing the steps of: acquiring a network control request through a dedicated network; processing a network control request by using an edge cloud server deployed in an exclusive network to obtain network control information corresponding to the exclusive network, wherein the network control request is processed by edge resources corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, and the edge resources are the same as the reference resources of the preset reference equipment; the proprietary network is controlled based on the network control information.

Further, the second processor 41 is also used to execute all or part of the steps in the embodiment shown in fig. 7. The electronic device may further include a second communication interface 43 for communicating with other devices or a communication network.

In addition, an embodiment of the present invention provides a computer storage medium for storing computer software instructions for an electronic device, which includes a program for executing the vehicle control method in the method embodiment shown in fig. 7.

Furthermore, an embodiment of the present invention provides a computer program product, including: a computer program which, when executed by a processor of an electronic device, causes the processor to carry out the vehicle control method in the method embodiment shown in fig. 7.

Fig. 13 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application; referring to fig. 13, the present embodiment provides a data processing apparatus for executing the data processing method shown in fig. 8, and specifically, the data processing apparatus may include:

a third obtaining module 51, configured to obtain, through an exclusive network, a data processing request corresponding to the augmented reality terminal;

the third processing module 52 is configured to process a data processing request by using an edge cloud server deployed in an exclusive network, to obtain a data processing result corresponding to the augmented reality terminal, where the data processing request is processed through an edge resource corresponding to the edge cloud server, the edge cloud server is communicatively connected with a preset reference device, and the edge resource is the same as a reference resource of the preset reference device;

and a third control module 53, configured to control the augmented reality terminal based on the data processing result.

The data processing apparatus shown in fig. 13 can execute the method of the embodiment shown in fig. 8, and reference may be made to the related description of the embodiment shown in fig. 8 for a part of this embodiment that is not described in detail. The implementation process and technical effect of the technical solution refer to the description in the embodiment shown in fig. 8, and are not described herein again.

In one possible design, the structure of the data processing apparatus shown in fig. 13 may be implemented as an electronic device. As shown in fig. 14, the electronic device may include: a third processor 61 and a third memory 62. Wherein the third memory 62 is used for storing programs for executing the data processing method provided in the embodiment shown in fig. 8, and the third processor 61 is configured for executing the programs stored in the third memory 62.

The program comprises one or more computer instructions, wherein the one or more computer instructions, when executed by the third processor 61, are capable of performing the steps of: acquiring a data processing request corresponding to the augmented reality terminal through a dedicated network; processing a data processing request by using an edge cloud server deployed in an exclusive network to obtain a data processing result corresponding to an augmented reality terminal, wherein the data processing request is processed through an edge resource corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, and the edge resource is the same as the reference resource of the preset reference equipment; and controlling the augmented reality terminal based on the data processing result.

Further, the third processor 61 is also used for executing all or part of the steps in the embodiment shown in fig. 7. The electronic device may further include a third communication interface 63 for communicating with other devices or a communication network.

In addition, an embodiment of the present invention provides a computer storage medium for storing computer software instructions for an electronic device, which includes a program for executing the data processing method in the method embodiment shown in fig. 7.

Furthermore, an embodiment of the present invention provides a computer program product, including: the computer program, when executed by a processor of the electronic device, causes the processor to perform the data processing method in the method embodiment shown in fig. 7.

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course, can also be implemented by a combination of hardware and software. With this understanding in mind, the above-described technical solutions and/or portions thereof that contribute to the prior art may be embodied in the form of a computer program product, which may be embodied on one or more computer-usable storage media having computer-usable program code embodied therein (including but not limited to disk storage, CD-ROM, optical storage, etc.).

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and these modifications or substitutions do not depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A resource allocation method is characterized in that the method is applied to an edge cloud server deployed in an exclusive network; the method comprises the following steps:

acquiring a resource allocation request;

and configuring the edge cloud server based on the resource configuration request and a reference resource to obtain an edge resource corresponding to the edge cloud server, wherein the edge resource is the same as the reference resource, so that the resource architecture of the edge cloud server is the same as the resource architecture of the preset reference equipment.

2. The method of claim 1, wherein the reference resource comprises a central network resource; configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge resource corresponding to the edge cloud server, including:

and configuring the edge cloud server based on the resource configuration request and a central network resource to obtain an edge network resource corresponding to the edge cloud server, wherein the edge network resource is the same as the central network resource.

3. The method of claim 1, wherein the reference resource comprises a central computing kernel; configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge resource corresponding to the edge cloud server, including:

configuring the edge cloud server based on the resource configuration request and central network resources to obtain an edge computing kernel corresponding to the edge cloud server, wherein the edge computing kernel is the same as the central computing kernel.

4. The method of claim 1, wherein the reference resource comprises a central storage resource; configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge resource corresponding to the edge cloud server, including:

and configuring the edge cloud server based on the resource configuration request and the reference resource to obtain an edge storage resource corresponding to the edge cloud server, wherein the edge storage resource is the same as the central storage resource.

5. The method of claim 1, further comprising:

acquiring a resource calling request through the preset reference equipment;

determining schedulable resources in the edge cloud server based on the resource invocation request;

and sending the schedulable resource to the preset reference equipment to realize resource scheduling operation.

6. The method of claim 1, wherein after obtaining the edge resource corresponding to the edge cloud server, the method further comprises:

determining attribute information of the edge resource;

and managing and controlling the edge resources based on the attribute information, wherein the management and control operations of the edge resources corresponding to different attribute information are mutually independent.

7. The method of claim 1, further comprising:

acquiring function configuration information corresponding to a preset function;

and performing configuration operation of a preset function based on the function configuration information so that the edge cloud server can realize the preset function.

8. The method of claim 1, further comprising:

acquiring an application calling request corresponding to a preset application, wherein the preset application is deployed on the preset reference device;

and sending the application calling request to the preset reference equipment so as to call the preset application to perform data processing operation through the preset reference equipment.

9. The method of any of claims 1-8, wherein after obtaining the edge resource corresponding to the edge cloud server, the method further comprises:

acquiring a data processing request;

determining a resource requirement corresponding to the data processing request;

and when the edge resource does not meet the resource requirement, performing containerization processing on the edge resource based on the data processing request to obtain the containerization resource meeting the resource requirement.

10. A private network control method is characterized by comprising the following steps:

acquiring a network control request through a dedicated network;

processing the network control request by using an edge cloud server deployed in the dedicated network to obtain network control information corresponding to the dedicated network, wherein the network control request is processed by using edge resources corresponding to the edge cloud server, the edge cloud server is in communication connection with preset reference equipment, a resource architecture of the edge cloud server is the same as that of the preset reference equipment, and the edge resources are the same as that of the preset reference equipment;

controlling the dedicated network based on the network control information.

11. An edge cloud server, deployed in a proprietary network; the edge cloud server includes:

the first acquisition module is used for acquiring a resource configuration request;

the first processing module is configured to configure the edge cloud server based on the resource configuration request and a reference resource, and obtain an edge resource corresponding to the edge cloud server, where the edge resource is the same as the reference resource, so that a resource architecture of the edge cloud server is the same as a resource architecture of the preset reference device.

12. An electronic device, comprising: a memory, a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the resource configuration method of any of claims 1-9.