Cloud computer configuration method, device and equipment and readable storage medium

Abstract

The invention discloses a cloud computer configuration method, device and equipment and a readable storage medium, first user attribute information of a sensing user is obtained, the first user attribute information comprises a first cloud computer use scene corresponding to the sensing user, a sensing task corresponding to the first cloud computer use scene is distributed to sensing equipment corresponding to the sensing user, and the sensing task is sent to the sensing equipment corresponding to the sensing user. The sensing task is used for indicating the sensing equipment to obtain sensing data for the cloud computer configuration information, receiving the sensing data returned by the sensing equipment in response to the sensing task, and establishing a mapping relation between the first user attribute information and the cloud computer configuration information under the condition of determining that the sensing user is satisfied with the cloud computer configuration information according to the sensing data. According to the embodiment, the crowd sensing technology is utilized to obtain the cloud computer configuration information which senses that the user meets the configuration requirement in the specific use scene, the corresponding mapping relation is established, and on the basis, the cloud computer configuration information which meets the requirement of the user can be distributed to the user in the specific use scene according to the mapping relation.

Description

Technical Field

[0001] The present application belongs to the technical field of cloud computer configuration, and in particular, relates to a cloud computer configuration method, device, equipment and readable storage medium. Background Art

[0002] With the continuous growth of the national economy and the continuous innovation of science and technology, the Internet has been widely used in various industries and fields, creating a lot of current value. Cloud computers have broad application prospects and can meet the requirements of high performance, low cost, high reliability and high scalability put forward by users in big data industries such as finance, telecommunications, public security, transportation, health, radio and television. It will also promote the widespread application of information technology in big data application fields such as the Internet of Things, smart cities, smart grids, smart transportation, smart medical care, and food safety. The emergence of cloud computers can improve the utilization rate of computing resources and thus reduce user costs. For some lightweight office scenarios, cloud computers can provide more convenient multi-person collaboration, office services and other functions, thereby improving office efficiency. In the fields of corporate office, government affairs processing, software development, etc., cloud computers have very broad application prospects.

[0003] At present, the configuration of cloud computers is often realized by manufacturers providing a standard package, and users can only choose a relatively available product according to their needs to complete their tasks. However, this method has a relatively poor interactive experience for users, and users can only passively accept it, which cannot meet their actual needs. Summary of the invention

[0004] The embodiments of the present application provide a cloud computer configuration method, apparatus, device and readable storage medium, which can determine cloud computer configuration information that meets the actual needs of users.

[0005] In a first aspect, an embodiment of the present application provides a cloud computer configuration method, comprising:

[0006] Acquire first user attribute information of a perceived user, where the first user attribute information includes a first cloud computer usage scenario corresponding to the perceived user;

[0007] Allocating a perception task corresponding to the first cloud computer usage scenario to a perception device corresponding to the perception user, where the perception task is used to instruct the perception device to obtain perception data of the cloud computer configuration information;

[0008] receiving sensing data returned by the sensing device in response to the sensing task;

[0009] When it is determined based on the perception data that the perceived user is satisfied with the cloud computer configuration information, a mapping relationship between the first user attribute information and the cloud computer configuration information is established.

[0010] In a second aspect, an embodiment of the present application provides a cloud computer configuration device, including:

[0011] An acquisition module, used to acquire first user attribute information of a perceived user, where the first user attribute information includes a first cloud computer usage scenario corresponding to the perceived user;

[0012] A task assignment module, used to assign a perception task corresponding to the first cloud computer usage scenario to a perception device corresponding to the perception user, wherein the perception task is used to instruct the perception device to obtain perception data of the cloud computer configuration information;

[0013] A sensing data receiving module, used for receiving the sensing data returned by the sensing device in response to the sensing task;

[0014] The mapping module is used to establish a mapping relationship between the first user attribute information and the cloud computer configuration information when the perceived user is determined to be satisfied with the cloud computer configuration information according to the perception data.

[0015] In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising: a processor and a memory storing computer program instructions;

[0016] When the processor executes the computer program instructions, the cloud computer configuration method of the first aspect is implemented.

[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the cloud computer configuration method of the first aspect is implemented.

[0018] The cloud computer configuration method, apparatus, device and readable storage medium of the embodiment of the present application obtains the first user attribute information of the perceived user, the first user attribute information includes the first cloud computer usage scenario corresponding to the perceived user, and assigns the perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perceived user, the perception task is used to instruct the perception device to obtain the perception data of the cloud computer configuration information, and receives the perception data returned by the perception device in response to the perception task. When it is determined based on the perception data that the perceived user is satisfied with the cloud computer configuration information, a mapping relationship between the first user attribute information and the cloud computer configuration information is established. According to this embodiment, the cloud computer configuration information that meets the configuration requirements of the perceived user in a specific usage scenario is obtained by using the crowd intelligence perception technology, and a corresponding mapping relationship is established. Based on this, the cloud computer configuration information that meets the requirements of the user in the specific usage scenario can be assigned to the user according to the mapping relationship. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 It is a flowchart of the cloud computer configuration method provided in the embodiment of the present application;

[0021] Figure 2 It is a flowchart of a simulated annealing algorithm provided in an embodiment of the present application;

[0022] Figure 3 It is a system structure topology diagram provided in an embodiment of the present application;

[0023] Figure 4 It is a schematic diagram of the process of configuring a cloud computer by a cloud computer configuration device provided in an embodiment of the present application;

[0024] Figure 5 It is a schematic diagram of a process of matching user attribute information of a requesting user with cloud computer configuration information provided in an embodiment of the present application;

[0025] Figure 6 It is a schematic diagram of relevant information of the cloud computer configuration provided in the embodiment of the present application;

[0026] Figure 7 It is a structural diagram of a cloud computer configuration device provided in an embodiment of the present application;

[0027] Figure 8 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0029] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0030] See also Figure 1 , is a flow chart of a cloud computer configuration method provided in an embodiment of the present application, the method is applied to a cloud computer configuration device for managing cloud computer configuration information, such as Figure 1 As shown, the method may include the following steps:

[0031] S11. Obtain first user attribute information of the perceived user, where the first user attribute information includes a first cloud computer usage scenario corresponding to the perceived user.

[0032] The cloud computer configuration method provided in this embodiment is applied to a cloud computer configuration device, which is implemented based on Mobile Crowd Sensing (MCS) technology. MCS refers to collecting user-contributed data by utilizing smart mobile device sensors in physical space and mobile social networks in cyberspace.

[0033] In this embodiment, the aware user refers to a user who can contribute data to the cloud computer configuration device.

[0034] The first user attribute information of the perceived user may include not only the first cloud computer usage scenario, but also gender, age and other information, which is not specifically limited in this embodiment.

[0035] In actual applications, the first user attribute information of the perceived user can be uploaded by the perceived user to the cloud computer configuration device.

[0036] S12. Assign a perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user, where the perception task is used to instruct the perception device to obtain perception data on the cloud computer configuration information.

[0037] The sensing device corresponding to the sensing user may be a device with sensing capabilities used by the sensing user, including but not limited to smart phones equipped with sensors, various smart wearable devices, vehicle-mounted smart sensing devices, etc.

[0038] In crowd perception, perception users use mobile devices such as smartphones, various smart wearable devices, and in-vehicle smart perception devices as basic perception units, which can form a new type of mobile perception network that is different from traditional fixed sensor networks. In this network, mobile perception nodes can be carried around the physical world by moving people or cars, making it easier to achieve large-scale coverage of the entire physical world and extensive information collection. Through collaboration on the mobile Internet, perception task distribution and perception data collection and utilization can be achieved, and ultimately large-scale and complex social perception tasks can be completed. In short, crowd perception plays the characteristic of "strength in numbers", uniting a large number of perception users to form a perception system that is anytime, anywhere, pervasive, and closely related to people's lives. Work that previously required a lot of manpower and material resources, such as road traffic situation monitoring and large-scale wireless signal surveys, can now be completed through the crowd perception model.

[0039] The purpose of this embodiment is to use the crowd-sensing model to obtain the relatively optimal solution for the relevant software and hardware configuration of the cloud computer in a specific usage scenario.

[0040] Usually, users have different configuration requirements for cloud computers in different usage scenarios, and they pay attention to different configuration items. For example, cloud computers are suitable for usage scenarios including but not limited to games, office, education, scientific research, etc. Cloud computer configuration information includes but is not limited to configuration information of graphics card, memory, disk, cloud disk, CPU, broadband and other configuration items. In the game scenario, users usually need higher definition pictures, faster response speed, etc., so the configuration items they pay attention to are mainly graphics card, CPU and broadband, etc., while in the office scenario, users usually need larger storage space, so the configuration items they pay attention to are mainly memory, disk, cloud disk, etc. Therefore, in order to determine the cloud computer configuration information that is more in line with the user's corresponding usage scenario, when assigning perception tasks to the perception user, the perception task corresponding to the first cloud computer usage scenario is assigned to the perception device corresponding to the perception user, so that the perception device can return the perception data corresponding to the first cloud computer usage scenario.

[0041] Among them, the perception data may include subjective information and objective information. The subjective information may include the perceived user's subjective usage experience of the cloud computer, and the objective information may include considerations of objective capabilities such as bit rate, frame rate, resolution, backup, exclusivity, bandwidth, cloud protection, etc.

[0042] Based on subjective and objective information, the perceived user's satisfaction with the cloud computer configuration information can be accurately analyzed.

[0043] S13. Receive the perception data returned by the perception device in response to the perception task.

[0044] After receiving the perception task, the perception device can collect data, obtain corresponding perception data, and upload the perception data to the cloud computer configuration device. In this way, the cloud computer configuration device can receive the perception data returned by the perception device.

[0045] In order to avoid data leakage and protect data security, when uploading the perception data to the cloud computer configuration device, the perception device can perform privacy protection processing on the collected perception data before uploading it to the cloud computer configuration device. For example, the perception data can be processed for privacy protection in an encrypted manner, and accordingly, after receiving the encrypted perception data, the cloud computer configuration device can decrypt it in a corresponding decryption manner. The encryption method and the decryption method can be pre-set according to the actual situation.

[0046] S14. When the perceived user is determined to be satisfied with the cloud computer configuration information based on the perception data, a mapping relationship between the first user attribute information and the cloud computer configuration information is established.

[0047] After acquiring the perception data, the satisfaction score corresponding to the perception data can be determined according to the preset scoring rules for scoring the perception data, and by comparing the satisfaction score with the preset satisfaction threshold, it is determined whether the perception user is satisfied with the cloud computer configuration information. The satisfaction scoring rules can be set according to actual conditions, and this embodiment does not specifically limit this.

[0048] The satisfaction threshold may be preset and stored by an administrator of the cloud computer configuration device.

[0049] Furthermore, in order to ensure data security and prevent the satisfaction threshold from being tampered with, the satisfaction threshold can be stored in the blockchain.

[0050] As an example, the administrator of the cloud computer configuration device can set the satisfaction threshold as the judgment condition of the smart contract corresponding to the blockchain, and upload it to the blockchain to store the satisfaction threshold on the blockchain. When the satisfaction threshold is needed, the satisfaction threshold is obtained from the blockchain.

[0051] When determining whether the perceived user is satisfied with the cloud computer configuration information by comparing the satisfaction score with a preset satisfaction threshold, if the satisfaction score is greater than or equal to the satisfaction threshold, it is determined that the perceived user is satisfied with the cloud computer configuration information; if the satisfaction score is less than the satisfaction threshold, it is determined that the perceived user is dissatisfied with the cloud computer configuration information.

[0052] When it is determined that the perceived user is satisfied with the cloud computer configuration information, it is determined that the cloud computer configuration information meets the configuration requirements of the first cloud computer usage scenario, thereby establishing a mapping relationship between the first user attribute information and the cloud computer configuration information. In this way, the cloud computer configuration information that has a mapping relationship with the first user attribute information can be found later.

[0053] The cloud computer configuration method provided in this embodiment obtains the first user attribute information of the perceived user, the first user attribute information includes the first cloud computer usage scenario corresponding to the perceived user, and assigns a perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perceived user, the perception task is used to instruct the perception device to obtain perception data of the cloud computer configuration information, and receives the perception data returned by the perception device in response to the perception task. When it is determined based on the perception data that the perceived user is satisfied with the cloud computer configuration information, a mapping relationship between the first user attribute information and the cloud computer configuration information is established. According to this embodiment, the cloud computer configuration information that meets the configuration requirements of the perceived user in a specific usage scenario is obtained by using the crowd intelligence perception technology, and a corresponding mapping relationship is established. Based on this, the cloud computer configuration information that meets the requirements of the user in the specific usage scenario can be assigned based on the mapping relationship.

[0054] In some embodiments, in order to ensure data security, before sending the perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user, the perception user may be authenticated first, wherein the identity authentication method may include:

[0055] Obtaining authentication information of the perceived user;

[0056] Determine whether the perceived user is a legitimate user based on the authentication information.

[0057] Accordingly, when it is determined that the perceived user is a legitimate user, the perceived task corresponding to the first cloud computer usage scenario is sent to the perceived device corresponding to the perceived user. When it is determined that the perceived user is not a legitimate user, the perceived task corresponding to the first cloud computer usage scenario is not sent to the perceived device corresponding to the perceived user.

[0058] Among them, the method of authenticating the perceived user can be set according to actual conditions.

[0059] As an example, an asymmetric key can be used to authenticate the perception user. The administrator of the cloud computer configuration device can pre-issue an authorization key to the cloud computer configuration device. The authorization key includes an authorization public key and an authorization private key. The cloud computer configuration device can assign the authorization key to the authorized perception device. Based on this, after the cloud computer configuration device obtains the first user attribute information of the perception user, it can send a random number to the perception user. After receiving the random number, the perception user uses the authorization public key to encrypt the random number, and returns the encrypted ciphertext as authentication information to the cloud computer configuration device. After receiving the ciphertext, the cloud computer configuration device uses the authorization private key to decrypt it. If the decrypted content is the above random number, the perception user is determined to be a legal user, otherwise the perception user is determined to be an illegal user.

[0060] Furthermore, in order to prevent the authorization key from being tampered with, the administrator of the cloud computer configuration device can upload the authorization key to the blockchain for storage and obtain it from the blockchain when needed.

[0061] Through the above methods, the security of perceived data can be improved, and the reliability of various security and privacy issues such as perceived user privacy leakage, privacy measurement, data quality and privacy protection can be improved.

[0062] In some embodiments, in crowd perception, there are many factors that affect the quality of perception data, among which the most direct influencing factor is the participant who provides the perception data, that is, the perception user. In the data perception stage, the perception user must collect matching perception data in combination with the scene attributes of the perception task. The identity, location, time, context and other information attributes of the perception user change dynamically throughout the process, and the perception user has different levels of cognition and participation attitudes for the perception task. When the perception user obtains a bad interactive experience when using the device, it will inevitably cause high perception costs or poor participation enthusiasm, resulting in poor perception data quality.

[0063] In view of this, when allocating perception tasks, the will of the perception user can be fully and accurately analyzed, so as to allocate a perception task that matches the will of the perception user to the perception device corresponding to the perception user.

[0064] Through the above methods, the efficiency of task allocation can be effectively improved while improving the quality of perception data.

[0065] In some embodiments, after receiving the sensing data returned by the sensing device in response to the sensing task, the following steps may also be performed:

[0066] When it is determined based on the perception data that the perceived user is dissatisfied with the cloud computer configuration information, adjusting the cloud computer configuration information;

[0067] After each adjustment, returning to the step of sending a perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user;

[0068] Until it is detected that the user is satisfied with the cloud computer configuration information, the adjustment of the cloud computer configuration information is stopped.

[0069] When the perceived user's satisfaction with the cloud computer configuration information in the first cloud computer usage scenario is low, it means that the cloud computer configuration cannot meet the configuration requirements of the perceived user in the first cloud computer usage scenario. At this time, the configuration information of one or more configuration items of the cloud computer is adjusted, and the perception tasks are reassigned to the perception devices corresponding to the perceived users according to the adjusted configuration items for iterative processing until the cloud computer configuration information that satisfies the perceived user is obtained. In this way, cloud computer configuration information that meets the user's configuration requirements in the usage scenario can be obtained.

[0070] In some embodiments, a simulated annealing algorithm may be used to adjust the cloud computer configuration information.

[0071] The simulated annealing algorithm is essentially a probabilistic search algorithm. In each iteration, the algorithm chooses a solution outside the search neighborhood with a certain probability. That is, the algorithm can always jump out of the local optimal solution with a certain probability. If this solution is better than the historical optimal solution, the algorithm will concentrate on searching near this solution until a better solution is found with a certain probability.

[0072] See also Figure 2 , is a flowchart of the simulated annealing algorithm, according to Figure 2 It can be seen that the idea of ​​the simulated fire-breathing algorithm is to start from a relatively high initial temperature and gradually reduce the temperature until the temperature is reduced to meet the thermal equilibrium condition. At each temperature, n rounds of search are performed, and in each round of search, random perturbations are added to the old solutions to generate new solutions, and the new solutions are accepted according to certain rules.

[0073] By adjusting the cloud computer configuration information through the simulated annealing algorithm, different configuration items can be adjusted for different usage scenarios, providing better configuration items in the process of allocating perception tasks, and realizing "teaching students in accordance with their aptitude" for different usage scenarios.

[0074] Currently, data faces complex data security threats and privacy leakage risks such as false data attacks, Sybil attacks, location attacks, and task association attacks. In view of this, in order to improve data security, in some embodiments, after establishing the mapping relationship between user information and cloud computer configuration information, the following steps can also be performed:

[0075] Store the mapping relationship in the blockchain.

[0076] The content on the blockchain requires complex calculations using cryptographic principles before it can be recorded on the chain. Moreover, on the blockchain, the content of the latter block will include the content of the previous block, which makes it very difficult and costly to tamper with the information.

[0077] As an example, when storing the mapping relationship on the blockchain, the mapping relationship can be hashed to generate a summary, and the summary can be digitally signed using a preset encryption algorithm to obtain digital signature information, and the digital signature information and the mapping relationship can be uploaded and stored on the blockchain. When saving the corresponding data on the blockchain, it is necessary to use digital fingerprint technologies such as MD5 (Message-Digest Algorithm) and SHA (Secure Hash Algorithm) to perform trusted data signature processing on the summary to obtain the corresponding digital signature information.

[0078] Through the above methods, data security can be improved.

[0079] In actual applications, the cloud computer configuration device can obtain multiple sets of perception data through multiple perception users. Each perception user can perceive multiple cloud computer usage scenarios separately. In this way, the mapping relationship between multiple user attribute information and cloud computer configuration information can be finally obtained. Based on this, after the mapping relationship between user attribute information and cloud computer configuration information is stored in the blockchain, the following steps can also be performed:

[0080] Obtaining second user attribute information of the requesting user sent by the service provider;

[0081] Obtaining candidate cloud computer configuration information that has a mapping relationship with the second user attribute information from the blockchain;

[0082] Determine target configuration information from candidate configuration information;

[0083] The target configuration information is sent to the service provider so that the service provider can configure the cloud computer based on the target configuration information.

[0084] The service provider is the provider of the cloud computer. The requesting user can be any subscriber of the service provider. When a subscriber of the service provider needs to use the cloud computer, the subscriber is used as the requesting user.

[0085] To facilitate distinction from the user attribute information of the perceiving user, the user attribute information corresponding to the requesting user is referred to as second user attribute information.

[0086] After obtaining the second user attribute information and service scope authority of the requesting user, the cloud computer configuration device searches for the cloud computer configuration information corresponding to the second user attribute information on the blockchain as the candidate cloud computer configuration information, determines a configuration information from the candidate configuration information as the target configuration information, and sends the target configuration information to the service provider, so that the service provider can configure the cloud computer based on the target configuration information

[0087] Because the number of perceived users is usually large, a mapping relationship between user attribute information and cloud computer configuration information can usually be established for one perceived user, and the user attribute information of different perceived users may be the same. Therefore, for the second user attribute information, multiple backup cloud computer configuration information with a mapping relationship may be determined. Based on this, any cloud computer configuration information in the alternative cloud computer configuration information can be used as the target cloud computer configuration information, or the cloud computer configuration information that meets specific conditions can be used as the target cloud computer configuration information, where the specific conditions can be set according to actual conditions.

[0088] Through the above method, the target cloud computer configuration that meets the usage scenario can be provided to the requesting user.

[0089] In some embodiments, when determining the target configuration information from the candidate configuration information, the following steps may be included:

[0090] Determine the service scope authority corresponding to the requesting user according to the second user attribute information, where the service scope authority is used to indicate the service scope that the service provider can provide to the requesting user;

[0091] Determine the optimal configuration information that matches the service scope authority among the candidate configuration information;

[0092] The optimal configuration information is determined as the target configuration information.

[0093] Generally, for the same cloud computer usage scenario, different users may have different corresponding service scope permissions. In view of this, in order to provide the requesting user with cloud computer configuration information that better meets its needs, the service scope permissions of the requesting user are determined. The service scope permissions corresponding to the requesting user can be obtained from a preset access control policy based on the second user attribute information. The access control policy may include a correspondence between user attribute information and service scope permissions.

[0094] The access control policy can be preset by the administrator of the cloud computer configuration device according to the actual situation and distributed to the cloud computer configuration device. In order to prevent the access control policy from being tampered with, the cloud computer configuration device can store the access control policy in the blockchain. Based on this, after obtaining the second user attribute information, the cloud computer configuration device can obtain the service scope authority corresponding to the second user attribute information stored in the access control policy from the blockchain. The service scope authority is used to indicate the service scope that the service provider can provide to the requesting user, including but not limited to the authority level of bandwidth, graphics card, CPU performance, etc.

[0095] After determining the candidate configuration information, the resource list and capability rights provided by the service provider can be compared to determine whether each candidate cloud computer configuration information is within the service scope authority corresponding to the requesting user, search for the optimal configuration information available under the service scope authority, and determine the optimal configuration information as the target configuration information. The optimal configuration information can be the configuration information with the best performance of the corresponding cloud computer.

[0096] Through the above method, the optimal cloud computer configuration that meets the usage scenario can be provided to the requesting user.

[0097] The cloud computer configuration method provided in the embodiment of the present application is described below in conjunction with application scenarios.

[0098] See also Figure 3 , which is a system structure topology diagram applicable to the cloud computer configuration method provided in the embodiment of the present application, Figure 3 As shown, the system may include: a cloud computer configuration device, an administrator, a perceiving user, a service provider, a requesting user and a blockchain.

[0099] Among them, the system can mainly realize the following processing:

[0100] Pre-release access control policy processing: managers release relevant access control policies and authorization keys to the cloud computer configuration device, set satisfaction thresholds as the judgment conditions of the smart contract, and package and store this information in the blockchain to realize the storage of policy information on the blockchain.

[0101] Authorized access processing, based on the user attribute information of the perceived user, including but not limited to: permission level, gender, age, usage scenario, etc., can be determined by searching and matching on the blockchain to determine whether the perceived user belongs to the authorized access user recorded in the administrator's preset access control policy. If the determination is successful, the user will be regarded as an authorized perceived user of the cloud computer configuration device.

[0102] For service information feedback processing, the service provider first passes the user attribute information of the requesting user to the cloud computer configuration information. The cloud computer configuration information obtains the service scope permissions stored in the access control policy of the user attribute information from the blockchain. The service scope permissions include but are not limited to the permission levels of bandwidth, graphics card, CPU performance, etc., and are optimally matched based on comprehensive factors such as the scenario. The service provider provides services to the requesting user through the transmitted encrypted sampling data.

[0103] Satisfaction iteration training processing, based on the satisfaction threshold preset by the cloud computer configuration information manager, as the first satisfaction information, with the help of the smart contract strategy set on the blockchain to improve the reliability of the sampled data, and at the same time determine the second satisfaction information of the cloud computer configuration information in the process of perceiving the user to collect the perception data, this information includes but is not limited to: the subjective usage experience of the perceiving user and the consideration of objective capabilities such as bit rate, frame rate, resolution, backup, exclusive, bandwidth, cloud protection, etc. When the second satisfaction information score obtained by the cloud computer configuration in a specific scenario is low, one or more configuration information of the cloud computer will be adjusted, and the perception tasks will be reallocated for iterative processing, so as to "teach students in accordance with their aptitude" for different scenarios.

[0104] The following uses the game scenario as an example to describe the process of configuring the cloud computer by the cloud computer configuration device. Figure 3 As shown, the cloud computer configuration device can include the following four modules: user attribute module, group intelligence perception module, configuration allocation module and overall coordination module. The overall process diagram is as follows Figure 4 As shown, it mainly includes the following steps:

[0105] Step 1: The perception user initiates an authorization application, the cloud computer configuration device queries the authorization key on the blockchain, authenticates the perception user based on the authorization key, and sends the user attribute information of the perception user to the user attribute module of the cloud computer configuration device after successful authentication;

[0106] Step 2: After the user completes the identity authentication, the user attribute module saves the user attribute information and notifies the crowd-sensing module to realize the allocation, coordination and participation of the sensing task;

[0107] Step 3: After the perception user receives the perception task assigned by the group intelligence perception module, it collects data and uploads the collected perception data to the cloud computer configuration device after privacy protection processing. After receiving the uploaded perception data, the cloud computer configuration device determines the perception user's satisfaction with the cloud computer configuration information based on the satisfaction information in the perception data. When the satisfaction is less than the set satisfaction threshold, the simulated annealing algorithm is used to find better cloud computer configuration information, and the perception task is reallocated, and the perception data is collected again. When the satisfaction is greater than the set satisfaction threshold, step 4 is performed.

[0108] Step 4: The cloud computer configuration device obtains the user attribute information in the user attribute module and the perception data collected in the group intelligence perception module, establishes a corresponding mapping relationship between the user attribute information and the cloud computer configuration information, and stores the mapping relationship on the chain, thereby realizing a fine-grained division of the user attribute information and the cloud computer configuration data;

[0109] Step 5: The requesting user visits the service provider to apply for a service of a specific usage scenario. After receiving the request from the requesting user, the service provider interacts with the cloud computer configuration device to initiate an application to the cloud computer configuration device, obtains the cloud computer configuration information under the user attribute information of the requesting user, and waits for a response from the cloud computer configuration device;

[0110] Step 6: The configuration allocation module receives the request from the service provider, verifies the user attribute information of the requesting user, confirms the service scope and authority, and then passes the relevant request to the overall coordination module;

[0111] Step 7: After receiving the configuration allocation request, the overall coordination module searches for the cloud computer configuration information corresponding to the relevant user attribute information on the blockchain, compares the resource list and capability rights provided by the service provider, determines whether it is within the authority permitted by the service scope authority and confirms it, searches for the optimal configuration information available under the service scope authority, and returns the confirmation information to the configuration allocation module;

[0112] Step 8: The configuration allocation module returns the optimal configuration information to the service provider. The service provider sets up the cloud computer according to the optimized hardware and software configuration, puts the cloud computer in standby mode for the requesting user, and sends feedback information.

[0113] Step 9: After receiving the feedback, the requesting user can use the cloud computer device with relevant configuration, and the process ends.

[0114] The cloud computer configuration device encrypts the mapping relationship between user attribute information and cloud computer configuration information and uploads it to the blockchain. Since the hash of the previous block is required to calculate the hash of the current block in the blockchain, if a third party needs to add malicious devices to the blockchain, the cost will be very high. When saving the corresponding data on the blockchain, trusted data signature processing is required, and digital fingerprint technologies such as MD5 and SHA are used to obtain the corresponding signature value, which improves the security of the data.

[0115] The cloud computer configuration device uses the crowd intelligence perception module to allocate the perception tasks to the corresponding perception users with the greatest adaptability. The crowd intelligence perception module first allocates the authentication information stored on the blockchain to the corresponding perception user, and the perception user uses this information to complete the identity authentication on the perception platform. At the same time, the perception users can include the platform preset testers, the platform actual users, etc. After successful verification, the crowd intelligence perception module will allocate and coordinate the MCS perception tasks to the corresponding users. The perception users interact with the cloud computer configuration device through the mobile Internet and 5G / 6G network, and upload the collected perception data to the cloud computer configuration device after privacy protection according to the usage scenario.

[0116] The cloud computer configuration device uses smart contracts to search for the corresponding cloud computer configuration information on the blockchain, and verifies user attributes at the same time to achieve the optimal allocation of user attribute information and cloud computer configuration information. In layman's terms, the cloud computer configuration device can be regarded as a "container black box" that associates and selects user attributes and configuration information. According to the description of user attributes, the cloud computer configuration device selects the iteratively optimized software and hardware configuration from the mapping relationship reported and stored on the blockchain node, and provides relevant services to the service provider's subscribers within the available service range. The process of requesting the user's user attribute information to match the cloud computer configuration information is as follows: Figure 5 shown.

[0117] The cloud computer configuration device serves as an intermediary between the perception user and the service provider. It is composed of one or more data micro-centers of perception devices close to the perception user. The cloud computer configuration device can be hosted by a fog node or an edge computing node, and a reasonable incentive mechanism can be used to encourage more perception users to participate in the task. The cloud computer configuration device can classify, aggregate, and model the perception data uploaded by the perception user, and finally provide the processed perception data to the cloud service provider to obtain a task reward that matches the data quality. The service provider can be hosted by a cloud server, and mine the value information based on the perception data set obtained from the exchange with the perception platform, and then serve the social organization or individual that initiated the perception service request. Relevant information about cloud computer configuration is as follows: Figure 6 shown.

[0118] This embodiment adopts a crowd-sensing solution to obtain the optimal solution for cloud computer configuration, and introduces blockchain for verification and confirmation, which improves the security and reliability of the perceived data reported by the perceived user, and greatly increases the cost of third-party malicious devices joining. At the same time, the cloud computer configuration device receives the user attribute information uploaded by the perceived user, uses the key to authenticate the user's identity, realizes the reporting of perceived data and the distribution and sharing of cloud computer configuration information, and improves the reliability of various security and privacy issues such as privacy leakage, privacy measurement, data quality and privacy protection of the perceived user during the entire life cycle of the perceived data.

[0119] This embodiment proposes to combine blockchain technology with access control, and designs and implements a method for intelligent allocation of configuration information based on crowd intelligence perception. First, the perception user is used as the source of perception data, and the corresponding access control policy is set. When the perception user passes the identity authentication, the platform will upload the perception data to the blockchain and declare the existence of the cloud computer configuration information configured with the user attribute information of the perception user.

[0120] When the user requesting the service provider needs to use the cloud computer, the user attribute module verifies the identity attribute information of the requesting user and grants the corresponding service scope authority. The service provider searches for the cloud computer configuration information mapped to the user attribute information based on the perception data provided by the crowd intelligence perception module, and customizes the adaptation device for the user, providing a good interactive experience.

[0121] The workflow of this embodiment is jointly processed by four modules: user attribute module, group intelligence perception module, configuration allocation module, and overall coordination module. Each module works together to process user requests. Through the policy processing of smart contracts, a fully automated process can be adopted without any human participation. As long as the requirements listed in the smart contract code are met, it can greatly save time and reduce costs. It cannot be changed, effectively ensuring the security of the overall process and user privacy information.

[0122] This embodiment proposes to use iterative training to improve the reliability of the perception data of cloud computer configuration information. The perception data reported by the perception user is compared with the set satisfaction threshold to decide whether to record the mapping relationship or adjust the configuration information to reacquire the perception data. When the perception data satisfaction is low, the simulated annealing algorithm is used to find the optimal solution, which greatly improves the authenticity and adaptability of the reported perception data clustering, and facilitates the scheduling of perception users and perception platforms.

[0123] Based on the cloud computer configuration method provided in the above embodiment, the present application also provides a specific implementation of a cloud computer configuration device. Please refer to the following embodiment.

[0124] See also Figure 7The cloud computer configuration device provided in the embodiment of the present application includes the following units:

[0125] An acquisition unit 701 is used to acquire first user attribute information of a perception user, where the first user attribute information includes a first cloud computer usage scenario corresponding to the perception user;

[0126] A task allocation unit 702 is used to allocate a perception task corresponding to the first cloud computer usage scenario to a perception device corresponding to the perception user, where the perception task is used to instruct the perception device to obtain perception data of the cloud computer configuration information;

[0127] The sensing data receiving unit 703 is used to receive the sensing data returned by the sensing device in response to the sensing task;

[0128] The mapping unit 704 is used to establish a mapping relationship between the first user attribute information and the cloud computer configuration information when it is determined based on the perception data that the perceived user is satisfied with the cloud computer configuration information.

[0129] The cloud computer configuration device of the embodiment of the present application obtains the first user attribute information of the perceived user, the first user attribute information includes the first cloud computer usage scenario corresponding to the perceived user, and assigns a perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perceived user, the perception task is used to instruct the perception device to obtain the perception data of the cloud computer configuration information, receives the perception data returned by the perception device in response to the perception task, and establishes a mapping relationship between the first user attribute information and the cloud computer configuration information when it is determined based on the perception data that the perceived user is satisfied with the cloud computer configuration information. According to this embodiment, the cloud computer configuration information that meets the configuration requirements of the perceived user in a specific usage scenario is obtained by using the crowd intelligence perception technology, and a corresponding mapping relationship is established. Based on this, the cloud computer configuration information that meets the requirements of the user in the specific usage scenario can be assigned to the user according to the mapping relationship.

[0130] In some embodiments, the apparatus may further include: an adjustment unit, configured to:

[0131] After receiving the perception data returned by the perception device in response to the perception task, if it is determined according to the perception data that the perception user is not satisfied with the cloud computer configuration information, adjusting the cloud computer configuration information;

[0132] After each adjustment, returning to the step of sending a perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user;

[0133] Until it is detected that the user is satisfied with the cloud computer configuration information, the adjustment of the cloud computer configuration information is stopped.

[0134] In some embodiments, the adjusting unit is configured to:

[0135] The simulated annealing algorithm is used to adjust the cloud computer configuration information.

[0136] In some embodiments, the apparatus may further include: a verification unit, configured to:

[0137] Before sending the perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user, obtaining the authentication information of the perception user;

[0138] Determining whether the perceived user is a legitimate user based on the authentication information;

[0139] The task allocation unit 702 is used to:

[0140] When it is determined that the perceived user is a legitimate user, a perception task corresponding to the first cloud computer usage scenario is sent to a perception device corresponding to the perceived user.

[0141] In some embodiments, the apparatus may further include: a storage unit configured to:

[0142] After establishing the mapping relationship between user information and cloud computer configuration information, the mapping relationship is stored in the blockchain.

[0143] In some embodiments, the apparatus may further include: a configuration unit configured to:

[0144] Obtaining second user attribute information of the requesting user sent by the service provider;

[0145] Obtaining candidate cloud computer configuration information that has a mapping relationship with the second user attribute information from the blockchain;

[0146] Determine target configuration information from candidate configuration information;

[0147] The target configuration information is sent to the service provider so that the service provider can configure the cloud computer based on the target configuration information.

[0148] In some embodiments, the configuration unit may be used to:

[0149] Determine the service scope authority corresponding to the requesting user according to the second user attribute information, where the service scope authority is used to indicate the service scope that the service provider can provide to the requesting user;

[0150] Determine the optimal configuration information that matches the service scope authority among the candidate configuration information;

[0151] The optimal configuration information is determined as the target configuration information.

[0152] The cloud computer configuration device provided in the embodiment of the present application can achieve Figures 1 to 6 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0153] Figure 8 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0154] The electronic device may include a processor 801 and a memory 802 storing computer program instructions.

[0155] Specifically, the processor 801 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0156] The memory 802 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 802 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory 802 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 802 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 802 is a non-volatile solid-state memory. The memory 802 may include a read-only memory (ROM), a random access memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Therefore, typically, the memory 802 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer executable instructions, and when the software is executed (e.g., by one or more processors), it may perform the operations described in any one of the cloud computer configuration methods in the above embodiments.

[0157] The processor 801 implements any one of the cloud computer configuration methods in the above embodiments by reading and executing computer program instructions stored in the memory 802.

[0158] In one example, the electronic device may further include a communication interface 803 and a bus 810. Figure 8 As shown, the processor 801, the memory 802, and the communication interface 803 are connected via a bus 810 and communicate with each other.

[0159] The communication interface 803 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0160] Bus 810 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 810 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0161] In addition, in combination with the cloud computer configuration method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the cloud computer configuration methods in the above embodiment is implemented.

[0162] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0163] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0164] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0165] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0166] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A cloud computer configuration method, characterized in that: include: Acquire first user attribute information of a perceived user, where the first user attribute information includes a first cloud computer usage scenario corresponding to the perceived user; Allocating a perception task corresponding to the first cloud computer usage scenario to a perception device corresponding to the perception user, wherein the perception task is used to instruct the perception device to obtain perception data of the cloud computer configuration information; receiving the sensing data returned by the sensing device in response to the sensing task; When it is determined according to the perception data that the perception user is satisfied with the cloud computer configuration information, a mapping relationship between the first user attribute information and the cloud computer configuration information is established.

2. The method according to claim 1, characterized in that: After receiving the perception data returned by the perception device in response to the perception task, the method further includes: In the case where it is determined according to the perception data that the perception user is not satisfied with the cloud computer configuration information, adjusting the cloud computer configuration information; After each adjustment, returning to the step of sending the perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user; Until the perceived user is satisfied with the cloud computer configuration information, stop adjusting the cloud computer configuration information.

3. The method according to claim 2, characterized in that The adjusting the cloud computer configuration information includes: The cloud computer configuration information is adjusted using a simulated annealing algorithm.

4. The method according to claim 1, characterized in that: Before sending the perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user, the method further includes: Obtaining authentication information of the sensing user; Determining whether the perceived user is a legitimate user based on the authentication information; The sending the perception task corresponding to the first cloud computer usage scenario to the perception device corresponding to the perception user includes: When it is determined that the perceived user is a legitimate user, a perception task corresponding to the first cloud computer usage scenario is sent to a perception device corresponding to the perceived user.

5. The method according to claim 1, characterized in that After establishing the mapping relationship between the user information and the cloud computer configuration information, the method further includes: The mapping relationship is stored in the blockchain.

6. The method according to claim 5, characterized in that After storing the mapping relationship in the blockchain, the method further includes: Obtaining second user attribute information of the requesting user sent by the service provider; Acquire candidate cloud computer configuration information that has a mapping relationship with the second user attribute information from the blockchain; Determine target configuration information from the candidate configuration information; The target configuration information is sent to the service provider so that the service provider configures the cloud computer based on the target configuration information.

7. The method according to claim 6, characterized in that The determining target configuration information from the candidate configuration information includes: Determine the service scope authority corresponding to the requesting user according to the second user attribute information, where the service scope authority is used to indicate the service scope that the service provider can provide to the requesting user; Determining optimal configuration information among the candidate configuration information that matches the service scope authority; The optimal configuration information is determined as the target configuration information.

8. A cloud computer configuration device, characterized in that: include: An acquisition unit, configured to acquire first user attribute information of a perceiving user, wherein the first user attribute information includes a first cloud computer usage scenario corresponding to the perceiving user; A task allocation unit, configured to allocate a perception task corresponding to the first cloud computer usage scenario to a perception device corresponding to the perception user, wherein the perception task is used to instruct the perception device to obtain perception data of the cloud computer configuration information; a sensing data receiving unit, configured to receive the sensing data returned by the sensing device in response to the sensing task; A mapping unit is used to establish a mapping relationship between the first user attribute information and the cloud computer configuration information when it is determined according to the perception data that the perception user is satisfied with the cloud computer configuration information.

9. An electronic device, characterized in that: The electronic device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the cloud computer configuration method as described in any one of claims 1-7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by the processor, the cloud computer configuration method according to any one of claims 1 to 7 is implemented.

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