Cross-cloud resource recommendation method and apparatus, and computer-readable storage medium

Abstract

The present disclosure relates to the field of cloud computing. Disclosed are a cross-cloud resource recommendation method and apparatus, and a computer-readable storage medium. The cross-cloud resource recommendation method comprises: performing abstraction on a plurality of resources from a plurality of cloud service providers, so as to generate a plurality of types of resource pools, and determining the types of the resource pools on the basis of resources in the resource pools; determining the type and scale of a resource required by a user; on the basis of the type of the resource required by the user, determining a resource pool for providing resources to the user; on the basis of the usage situations of the resources of the plurality of cloud service providers and the scale of the resource required by the user, selecting a resource from the resource pool for providing the resources to the user; and recommending the selected resource to the user.

Description

Cross-cloud resource recommendation method, device, and computer-readable storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is based on and claims priority to an application filed in China with application number 202311108125.1 and filing date August 30, 2023. The disclosed content of the Chinese application is hereby introduced as a whole into this application. Technical Field

[0003] The present disclosure relates to the field of cloud computing, and in particular to a method, device, and computer-readable storage medium for recommending cross-cloud resources. Background Art

[0004] There are currently a variety of cloud service providers on the market, but each provider offers different cloud service strengths and resources, and there's no unified API (Application Programming Interface) for interconnection. This makes data transfer and mobility between different cloud services very difficult. To address this, users must select a cloud service provider based on their needs, handle API call incompatibilities between different cloud services, and determine the suitability of resources.

[0005] Summary of the Invention

[0006] According to a first aspect of some embodiments of the present disclosure, a method for recommending cross-cloud resources is provided, including: abstracting multiple resources from multiple cloud service providers to generate multiple types of resource pools, and determining the type of resource pool based on the resources in the resource pool; determining the type and scale of resources required by the user; determining the resource pool that provides resources to the user based on the type of resources required by the user; selecting resources from the resource pool that provides resources to the user based on the usage of resources of multiple cloud service providers and the scale of resources required by the user; and recommending the selected resources to the user.

[0007] In some embodiments, abstracting multiple resources from multiple cloud service providers to generate multiple resource pools includes: calculating the similarity between every two resources from the multiple cloud service providers; and abstracting multiple resources based on the similarity to generate multiple types of resource pools.

[0008] In some embodiments, the similarity between each two resources is determined based on text similarity and word order similarity between the description texts of each two resources.

[0009] In some embodiments, the similarity between each two resources is determined according to a weighted sum of text similarity and word order similarity between the description texts of each two resources.

[0010] In some embodiments, determining the type and scale of resources required by the user includes: receiving resource demand information sent by the user through a unified interface; and parsing the resource demand information to determine the type and scale of resources required by the user.

[0011] In some embodiments, determining the resource pool that provides resources to the user based on the type of resources required by the user includes: obtaining information of each resource pool in multiple resource pools through a unified interface for heterogeneous resources; and determining the resource pool that provides resources to the user based on the type of resources required by the user and the information of each resource pool.

[0012] In some embodiments, based on the usage of resources of multiple cloud service providers and the scale of resources required by the user, selecting resources from a resource pool that provides resources to the user includes: selecting unused resources from the resource pool that provides resources to the user that meet the scale of resources required by the user.

[0013] In some embodiments, recommending the selected resource to the user includes: sending at least one piece of information of the selected resource's name, its cloud service provider, and its scale to the user.

[0014] In some embodiments, recommending the selected resource to the user includes: sending a resource pool corresponding to the selected resource to the user.

[0015] According to a second aspect of some embodiments of the present disclosure, a cross-cloud resource recommendation device is provided, including: an abstraction module, configured to abstract multiple resources from multiple cloud service providers to generate multiple types of resource pools, and determine the resource type of the resource pool based on the resources in the resource pool; a user demand determination module, configured to determine the type and scale of resources required by the user; a user resource pool determination module, configured to determine the resource pool that provides resources to the user based on the type of resources required by the user; a resource selection module, configured to select resources from the resource pool that provides resources to the user based on the usage of resources of multiple cloud service providers and the scale of resources required by the user; and a recommendation module, configured to recommend the selected resources to the user.

[0016] According to a third aspect of some embodiments of the present disclosure, a cross-cloud resource recommendation device is provided, comprising: a memory; and a processor coupled to the memory, the processor being configured to execute any one of the aforementioned cross-cloud resource recommendation methods based on instructions stored in the memory.

[0017] According to a fourth aspect of some embodiments of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the program is executed by a processor, any one of the aforementioned cross-cloud resource recommendation methods is implemented.

[0018] According to a fifth aspect of some embodiments of the present disclosure, a computer program is provided, comprising: instructions, which, when executed by a processor, cause the processor to execute any one of the aforementioned cross-cloud resource recommendation methods.

[0019] Other features and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments of the present disclosure with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0021] FIG1 shows a schematic flow chart of a method for recommending cross-cloud resources according to some embodiments of the present disclosure.

[0022] FIG2 shows a schematic diagram of a network architecture for cross-cloud resource recommendation according to some embodiments of the present disclosure.

[0023] FIG3 shows a schematic structural diagram of a device for recommending cross-cloud resources according to some embodiments of the present disclosure.

[0024] FIG4 shows a schematic structural diagram of a device for recommending cross-cloud resources according to other embodiments of the present disclosure.

[0025] FIG5 shows a schematic structural diagram of a device for recommending cross-cloud resources according to yet other embodiments of the present disclosure. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is in no way intended to limit the present disclosure and its application or use. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0027] Unless specifically stated otherwise, the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure.

[0028] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0029] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0030] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0031] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0032] The market includes heterogeneous services provided by a variety of cloud service providers. For example, cloud service provider 1 can implement data desensitization at a low cost, and cloud service provider 2 can quickly implement artificial intelligence (AI) computing power services. Users need to use desensitized data to train machine learning models. The lowest cost and most efficient method is to perform data desensitization on cloud service provider 1, and then use cloud service provider 2 for rapid model training. Therefore, how to achieve collaborative resource scheduling across different cloud service providers is an important challenge faced. The present disclosure provides a cross-cloud resource recommendation method, device, and computer-readable storage medium that can solve the above problems.

[0033] Figure 1 shows a flow chart of a method for recommending cross-cloud resources according to some embodiments of the present disclosure. As shown in Figure 1 , the method for recommending cross-cloud resources in this embodiment includes steps S102 to S110.

[0034] In step S102, multiple resources from multiple cloud service providers are abstracted to generate multiple types of resource pools, and the type of the resource pool is determined based on the resources in the resource pool, such as data storage services, data computing services, encryption services, data desensitization services, AI model training services and other service types. Each cloud service provider can provide one or more resources, that is, one or more types of services. Since the same resource pool contains relatively similar resources, the type of the resource pool can be determined based on the commonalities of the various resources in the resource pool. When abstracting multiple resources, since the resources of each cloud service provider are abstracted together, the same resource pool includes resources from one or more cloud service providers, and the resources of each cloud service provider can also be distributed in one or more resource pools.

[0035] In some embodiments, the similarity between each pair of resources from multiple cloud service providers is calculated. Based on the similarity, the multiple resources are abstracted to generate various types of resource pools. In other words, the resource similarity is used as the "distance" between different resources during abstraction for abstraction calculation. This allows for the grouping of identical or similar resources into the same resource pool.

[0036] In some embodiments, the similarity between every two resources is determined based on the text similarity and word order similarity between the description texts of every two resources. The description text includes, for example, the name, introduction, type, important parameters, etc. of the resource, such as "providing a neural network model for training structured data" and "providing simple data preprocessing services". Text similarity refers to the similarity of the words used in the two description texts, and word order similarity refers to the similarity of the arrangement order of the words used in the two description texts with a similarity higher than a threshold. By using these two aspects to measure the similarity of the description texts, similar resources can be determined more accurately. In some embodiments, the similarity between every two resources is determined based on the weighted sum of the text similarity and word order similarity between the description texts of every two resources, and the sum of the weight of the text similarity and the weight of the word order similarity is equal to 1.

[0037] An example of an abstract operation on resources is clustering. Each cluster generated by clustering can correspond to a resource pool of a certain type. The following describes the process of clustering resource description text using the K-means algorithm as an example:

[0038] Step 1: Randomly select k resources from all resources provided by all cloud service providers as the initial centroid resources;

[0039] Step 2: Calculate the similarity between each resource and the centroid resource, and divide each resource into the cluster corresponding to the centroid resource with the greatest similarity;

[0040] Step 3: Calculate the mean similarity between all resources in each cluster and update the centroid resource in the cluster based on the mean;

[0041] Step 4: Repeat steps 2-3 until one of the convergence conditions is met. The convergence conditions include: ① the position change of the centroid resource is less than the specified threshold; ② the maximum number of iterations is reached.

[0042] Those skilled in the art may also adopt other clustering methods as needed, which will not be described in detail here.

[0043] Through the above embodiments, heterogeneous resources provided by different cloud service providers can be classified, so that homogeneous resources with high similarity can be formed in each cluster.

[0044] In step S104, the type and size of the resources required by the user are determined. The type and size may be included in the resource requirement information submitted by the user. The type and size of the resources required by the user may be determined by parsing the resource requirement description text submitted by the user. Alternatively, fields for the type and size of the resources may be provided on the front-end page for the user to fill in or select from a number of options. After the user submits the form on the page, the content in the corresponding fields may be obtained by parsing the form.

[0045] Because the embodiments of this disclosure integrate the resources of various cloud service providers, users no longer need to submit requests to the interfaces provided by each cloud service provider one by one. Instead, they can submit resource demand information through a unified interface, which then analyzes the resource demand to determine the type and scale of resources required by the user. The unified interface can be regarded as the entry point for users to request the use of heterogeneous resources from various cloud service providers, eliminating the need to consider the differences in access, accessibility, and usage between different cloud service providers when submitting resource requests.

[0046] In step S106, a resource pool that provides resources to the user is determined based on the type of resources required by the user.

[0047] The type of resource required by the user can be one of the types in multiple resource pools. Alternatively, the similarity between the type of resource required by the user and the type of each resource pool can be calculated, and the resource pool corresponding to the type with the highest similarity is selected as the resource pool providing resources to the user.

[0048] In some embodiments, a unified heterogeneous resource interface is used to obtain information about each of the multiple resource pools. Based on the type of resources required by the user and the information about each resource pool, the resource pool that provides the resources to the user is determined. The unified heterogeneous resource interface allows users to retrieve the type of each resource pool and, of course, to query parameters such as the status of resources in each resource pool.

[0049] In step S108, resources are selected from the resource pool providing resources to the user based on the resource usage of multiple cloud service providers and the scale of resources required by the user. The scale of the resources can be determined, for example, by the amount of storage space occupied. By monitoring the resource usage and resource availability of each cloud service provider, it is possible to help manage global heterogeneous resources across multiple cloud service providers.

[0050] In some embodiments, unused resources that meet the scale of resources required by the user are selected from a resource pool providing resources for the user. Unused resources that meet the scale of resources required by the user are, for example, idle resources that occupy more space than the space required by the user.

[0051] In step S110, the selected resource is recommended to the user. The recommendation may be a recommendation of information about the selected resource or a recommendation of an access method.

[0052] In some embodiments, at least one of the following information, including the name of the selected resource, the cloud service provider to which it belongs, and the scale, is sent to the user for reference and confirmation. 5G data storage services, cloud service providers 4G data desensitization service and cloud service provider AI model training service that takes up 4GB of space.

[0053] After the user confirms, the access method can be further sent to the user, or the user can connect to various cloud service providers on his own to access the recommended resources.

[0054] In some embodiments, the resource pool corresponding to the selected resource is sent to the user, for example, the access method of the resource pool is sent to the user. The access method can be an access address, interface, etc., so that the user does not need to obtain the access method of each cloud service provider on his own.

[0055] The above-described embodiments abstract the heterogeneous resources provided by various cloud service providers to generate homogeneous resources across multiple resource pools. Furthermore, when users wish to use heterogeneous resources, they no longer need to consider the resource selection strategies of each cloud service provider; resource recommendations are automatically generated and presented to the user. Consequently, the disclosed embodiments can automatically implement coordinated resource scheduling across different cloud service providers, improving user resource utilization efficiency.

[0056] The following describes the process of providing resource recommendation services to users in conjunction with the exemplary network architecture provided in some embodiments of the present disclosure.

[0057] Figure 2 shows a schematic diagram of the network architecture for cross-cloud resource recommendation according to some embodiments of the present disclosure. As shown in Figure 2, cloud service providers 1, 2...n each have multiple resources, and the same or similar resources are represented by the same letters. For example, cloud service provider 1 provides resources A, B..., cloud service provider 2 provides resources C, A..., and cloud service provider n provides resources B, D... By abstracting the resources provided by these cloud service providers, similar resources are divided into the same resource pool. The resource pool isomorphic resource module shows the categories corresponding to each resource pool after abstraction. The cross-cloud heterogeneous resource collaboration module can obtain information about various resource pools through the unified interface of heterogeneous resources. User 1, user 2 to user m all access the cross-cloud heterogeneous resource collaboration module through the unified interface to obtain the recommendation results of the module. The cross-cloud heterogeneous resource collaboration module is, for example, used to at least implement the aforementioned steps S104 to S110.

[0058] As can be seen from the above architecture diagram, users do not need to worry about which cloud service provider to obtain the required resources from. Through the cross-cloud heterogeneous resource collaboration module and unified interface, they can obtain automatically generated recommendation results.

[0059] An embodiment of the cross-cloud resource recommendation apparatus disclosed herein will be described below with reference to FIG3 to FIG5 .

[0060] Figure 3 shows a schematic diagram of the structure of a cross-cloud resource recommendation device according to some embodiments of the present disclosure. As shown in Figure 3, the cross-cloud resource recommendation device 30 includes: an abstraction module 310, configured to abstract multiple resources from multiple cloud service providers to generate multiple types of resource pools, and determine the type of resource pool based on the resources in the resource pool; a user demand determination module 320, configured to determine the type and scale of resources required by the user; a user resource pool determination module 330, configured to determine the resource pool that provides resources to the user based on the type of resources required by the user; a resource selection module 340, configured to select resources from the resource pool that provides resources to the user based on the usage of resources of multiple cloud service providers and the scale of resources required by the user; and a recommendation module 350, configured to recommend the selected resources to the user.

[0061] The above-described embodiments abstract the heterogeneous resources provided by various cloud service providers to generate homogeneous resources across multiple resource pools. Furthermore, when users wish to use heterogeneous resources, they no longer need to consider the resource selection strategies of each cloud service provider; resource recommendations are automatically generated and presented to the user. Consequently, the disclosed embodiments can automatically implement coordinated resource scheduling across different cloud service providers, improving user resource utilization efficiency.

[0062] In some embodiments, the abstraction module 310 is further configured to calculate the similarity between every two resources from a plurality of cloud service providers; and abstract the plurality of resources based on the similarity to generate resource pools of various types.

[0063] In some embodiments, the similarity between each two resources is determined based on text similarity and word order similarity between the description texts of each two resources.

[0064] In some embodiments, the similarity between each two resources is determined according to a weighted sum of text similarity and word order similarity between the description texts of each two resources.

[0065] In some embodiments, the user demand determination module 320 is further configured to receive resource demand information sent by the user through the unified interface; and parse the resource demand information to determine the type and scale of resources required by the user.

[0066] In some embodiments, the user resource pool determination module 330 is further configured to obtain information about each resource pool in multiple resource pools through a unified interface for heterogeneous resources; and determine the resource pool that provides resources to the user based on the type of resources required by the user and the information of each resource pool.

[0067] In some embodiments, the resource selection module 340 is further configured to select unused resources that meet the scale of resources required by the user from a resource pool providing resources for the user.

[0068] In some embodiments, the recommendation module 350 is further configured to send at least one of the following information: the name of the selected resource, the cloud service provider to which it belongs, and the scale to the user.

[0069] In some embodiments, the recommendation module 350 is further configured to send the resource pool corresponding to the selected resource to the user.

[0070] Figure 4 shows a schematic diagram of the structure of a cross-cloud resource recommendation apparatus according to other embodiments of the present disclosure. As shown in Figure 4, the cross-cloud resource recommendation apparatus 40 of this embodiment includes: a memory 410 and a processor 420 coupled to the memory 410. The processor 420 is configured to execute the cross-cloud resource recommendation method of any of the aforementioned embodiments based on instructions stored in the memory 410.

[0071] The memory 410 may include, for example, a system memory, a fixed non-volatile storage medium, etc. The system memory may store, for example, an operating system, application programs, a boot loader, and other programs.

[0072] FIG5 shows a schematic diagram of the structure of a cross-cloud resource recommendation device according to some other embodiments of the present disclosure. As shown in FIG5 , the cross-cloud resource recommendation device 50 of this embodiment includes: a memory 510 and a processor 520, and may also include an input / output interface 530, a network interface 540, a storage interface 550, and the like. These interfaces 530, 540, 550 and the memory 510 and the processor 520 can be connected, for example, via a bus 560. Among them, the input / output interface 530 provides a connection interface for input / output devices such as a display, mouse, keyboard, and touch screen. The network interface 540 provides a connection interface for various networked devices. The storage interface 550 provides a connection interface for external storage devices such as SD cards and USB flash drives.

[0073] An embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is configured to implement any of the aforementioned cross-cloud resource recommendation methods when executed by a processor.

[0074] Those skilled in the art will appreciate that embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable non-transient storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0075] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0076] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0078] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A cross-cloud resource recommendation method, comprising: Abstracting multiple resources from multiple cloud service providers to generate multiple types of resource pools, and determining the type of the resource pool according to the resources in the resource pool; Determine the type and size of resources required by users; Determine a resource pool that provides resources to the user according to the type of resources required by the user; Selecting resources from a resource pool providing resources for the user according to the usage of the resources of the multiple cloud service providers and the scale of resources required by the user; The selected resources are recommended to the user.

2. The recommendation method according to claim 1, wherein: The abstraction of multiple resources from multiple cloud service providers to generate multiple resource pools includes: Calculating the similarity between every two resources among the multiple resources from the multiple cloud service providers; The multiple resources are abstracted based on the similarities to generate multiple types of resource pools.

3. The recommendation method according to claim 2, wherein: The similarity between each two resources is determined according to the text similarity and word order similarity between the description texts of each two resources.

4. The recommendation method according to claim 3, wherein: The similarity between each two resources is determined according to the weighted sum of the text similarity and the word order similarity between the description texts of each two resources.

5. The recommendation method according to any one of claims 1 to 4, wherein: Determining the type and size of resources you will need includes: Receiving resource demand information sent by the user through a unified interface; The resource demand information is parsed to determine the type and scale of resources required by the user.

6. The recommendation method according to any one of claims 1 to 5, wherein: The determining, according to the type of resources required by the user, a resource pool that provides resources for the user comprises: Obtaining information of each resource pool in the multiple resource pools through a unified interface for heterogeneous resources; A resource pool that provides resources for the user is determined according to the type of resources required by the user and information about each resource pool.

7. The recommendation method according to any one of claims 1 to 6, wherein: The selecting a resource from a resource pool providing resources for the user according to the usage of the resources of the multiple cloud service providers and the scale of the resources required by the user includes: Selecting unused resources that meet the scale of resources required by the user from a resource pool that provides resources for the user.

8. The recommendation method according to any one of claims 1 to 7, wherein: The recommending the selected resource to the user comprises: At least one of the following information: the name of the selected resource, the cloud service provider to which it belongs, and the scale is sent to the user.

9. The recommendation method according to any one of claims 1 to 8, wherein: The recommending the selected resource to the user comprises: The resource pool corresponding to the selected resource is sent to the user.

10. A cross-cloud resource recommendation device, comprising: an abstraction module configured to abstract multiple resources from multiple cloud service providers to generate multiple types of resource pools, and determine the resource type of the resource pool according to the resources in the resource pool; A user demand determination module configured to determine the type and size of resources required by the user; A user resource pool determination module, configured to determine a resource pool that provides resources for the user according to the type of resources required by the user; A resource selection module, configured to select resources from a resource pool providing resources for the user according to the usage of the resources of the multiple cloud service providers and the scale of the resources required by the user; The recommendation module is configured to recommend the selected resource to the user.

11. A cross-cloud resource recommendation device, comprising: Memory; as well as A processor coupled to the memory, the processor being configured to execute a command based on instructions stored in the memory. command, executing the cross-cloud resource recommendation method as described in any one of claims 1 to 9.

12. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for recommending cross-cloud resources according to any one of claims 1 to 9.

13. A computer program comprising: The instructions, when executed by a processor, cause the processor to execute the cross-cloud resource recommendation method according to any one of claims 1 to 9.

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