Real-time data collaboration strategy control system, method and device based on cloud edge collaboration scene, computer equipment, storage medium and computer program product

Abstract

The embodiment of the invention provides a real-time data collaboration strategy control system, method and device based on a cloud edge collaboration scene, computer equipment, a storage medium and a computer program product, and relates to the technical field of cloud computing. The system comprises a cloud server, an edge server, a strategy collection terminal and a strategy collection server, wherein the strategy collection server receives a data rule conversion strategy from the strategy collection terminal and sends the data rule conversion strategy to the cloud server; the cloud server receives the data rule conversion strategy and sends the data rule conversion strategy to the edge server; and the edge server collects the electric power collection data and obtains the electric power data to be transmitted according to the data rule conversion strategy and the electric power collection data. According to the system, the power collection data is screened and filtered according to the data rule conversion strategy to obtain the power data to be transmitted, so that bandwidth waste is reduced, the data transmission efficiency is improved, and the transmission cost is reduced.

Description

Technical Field

[0001] The present application relates to the field of cloud computing technology, and in particular to a real-time data collaboration strategy control system, method, apparatus, computer equipment, storage medium and computer program product based on a cloud-edge collaboration scenario. Background Art

[0002] In the cloud-edge collaboration scenario, usually, the edge database needs to upload the real-time power collection data to the corresponding cloud server.

[0003] In the current real-time data collaborative strategy control technology based on cloud-edge collaborative scenarios, the power collection data collected by the edge server is generally synchronized in full to the corresponding cloud server. A considerable portion of the synchronized data is non-required data, resulting in a waste of bandwidth and low data transmission efficiency. Summary of the invention

[0004] Based on this, it is necessary to provide a real-time data collaborative strategy control system, method, device, computer equipment, storage medium and computer program product based on cloud-edge collaborative scenarios to address the above technical problems.

[0005] In a first aspect, the present application provides a real-time data collaboration strategy control system based on a cloud-edge collaboration scenario. The system includes:

[0006] Cloud server, edge server, policy collection terminal and policy collection server; wherein:

[0007] The policy collection server is used to receive the data rule conversion policy from the policy collection terminal and send the data rule conversion policy to the cloud server;

[0008] The cloud server is used to receive the data rule conversion strategy and send the data rule conversion strategy to the edge server;

[0009] The edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

[0010] In one of the embodiments, the edge server includes: a collection service module and a data conversion module; the collection service module is used to collect the power collection data and send the power collection data to the data conversion module; the data conversion module is used to receive the power collection data and filter the power data to be transmitted from the power collection data according to the data rule conversion strategy.

[0011] In one of the embodiments, the data conversion module is further used to: obtain an extraction field rule in the data rule conversion strategy; use the extraction field rule to filter out field data corresponding to the extraction field rule in the power collection data, and determine the field data as the power data to be transmitted.

[0012] In one of the embodiments, the cloud server is further used to store the data rule conversion strategy in a cloud database.

[0013] In one of the embodiments, the cloud server includes: a policy management service module; the policy management service module is used to obtain the data rule conversion policy in the cloud database according to a preset trigger condition, and broadcast the data rule conversion policy to the edge server.

[0014] In a second aspect, the present application provides a real-time data collaborative strategy control method based on a cloud-edge collaborative scenario, which is applied to a cloud server of a real-time data collaborative strategy control system based on a cloud-edge collaborative scenario. The method includes:

[0015] Receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database;

[0016] In response to a preset trigger condition, the data rule conversion strategy is obtained in the cloud database, and the data rule conversion strategy is broadcast to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

[0017] In a third aspect, the present application provides a real-time data collaborative strategy control device based on a cloud-edge collaborative scenario, which is applied to a cloud server of a real-time data collaborative strategy control system based on a cloud-edge collaborative scenario. The device includes:

[0018] An acquisition module is used to receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database;

[0019] The sending module is used to obtain the data rule conversion strategy in the cloud database in response to a preset trigger condition, and broadcast the data rule conversion strategy to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

[0020] In a fourth aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0021] Receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database;

[0022] In response to a preset trigger condition, the data rule conversion strategy is obtained in the cloud database, and the data rule conversion strategy is broadcast to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

[0023] In a fifth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0024] Receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database;

[0025] In response to a preset trigger condition, the data rule conversion strategy is obtained in the cloud database, and the data rule conversion strategy is broadcast to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

[0026] In a sixth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0027] Receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database;

[0028] In response to a preset trigger condition, the data rule conversion strategy is obtained in the cloud database, and the data rule conversion strategy is broadcast to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

[0029] In the above-mentioned real-time data collaborative policy control system, method, device, computer equipment, storage medium and computer program product based on the cloud-edge collaborative scenario, the system includes: a cloud server, an edge server, a policy collection terminal and a policy collection server; wherein: the policy collection server is used to receive the data rule conversion policy from the policy collection terminal and send the data rule conversion policy to the cloud server; the cloud server is used to receive the data rule conversion policy and send the data rule conversion policy to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion policy and the power collection data. In the system provided by the embodiment of the present application, the data rule conversion policy is introduced into the cloud-edge collaborative system, and the data rule conversion policy set by the user can be obtained. Then, the edge server can filter the real-time collected power collection data according to the data rule conversion policy to obtain the power data to be transmitted, thereby reducing the amount of transmitted data, reducing bandwidth waste, improving data transmission efficiency, and reducing transmission costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 A schematic diagram of the structure of a real-time data collaboration strategy control system based on a cloud-edge collaboration scenario provided in an embodiment of the present application;

[0032] Figure 2 A structural diagram of another real-time data collaboration strategy control system based on a cloud-edge collaboration scenario provided in an embodiment of the present application;

[0033] Figure 3 A flowchart of a real-time data collaboration strategy control method based on a cloud-edge collaboration scenario provided in an embodiment of the present application;

[0034] Figure 4 A structural block diagram of a real-time data collaboration strategy control device based on a cloud-edge collaboration scenario provided in an embodiment of the present application;

[0035] Figure 5 An internal structure diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0037] In an exemplary embodiment, Figure 1 As shown, a real-time data collaborative policy control system based on a cloud-edge collaborative scenario is provided, the system comprising: a cloud server, an edge server, a policy collection terminal and a policy collection server; wherein: the policy collection server is used to receive the data rule conversion policy from the policy collection terminal, and send the data rule conversion policy to the cloud server; the cloud server is used to receive the data rule conversion policy, and send the data rule conversion policy to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion policy and the power collection data.

[0038] Among them, in the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, a cloud server, an edge server, a policy collection terminal and a policy collection server may be included. The policy collection terminal may be, but is not limited to, various personal computers, laptops, smart phones, tablets, IoT devices and portable wearable devices. IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The policy collection server may be implemented with an independent server or a server cluster consisting of multiple servers. The policy collection terminal may communicate with the policy collection server through a network. The user can register and log in to the policy collection platform of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario on the policy collection terminal. The policy collection terminal displays the policy collection page in response to the login operation triggered by the user; the user can trigger the filling of the data rule conversion policy for the power data to be transmitted on the policy collection page; the policy collection terminal can send the data rule conversion policy for the power data to be transmitted to the policy collection server in response to the filling operation triggered by the user on the policy collection page; the policy collection server can send the data rule conversion policy to the cloud server, and the cloud server can store the received data rule conversion policy for the power data to be transmitted in the cloud database. The cloud database can store multiple data rule conversion policies. There is a corresponding relationship between the data rule conversion policy and the power data to be transmitted. The power data to be transmitted can be the power data that the user needs to obtain and needs to be transmitted from the edge server to the cloud server. The data rule conversion policy can be the screening condition for the corresponding power data to be transmitted. The data rule conversion strategy can be used to filter out the corresponding power data to be transmitted in the real-time collected power collection data. The cloud server can obtain the data rule conversion strategy in the cloud database according to the preset trigger condition, and broadcast the data rule conversion strategy to at least one edge server by using the cloud-edge collaborative channel. After the edge server collects the power collection data in real time, it can use the data rule conversion strategy to filter out the power data to be transmitted corresponding to the data rule conversion strategy in the power collection data; the preset trigger condition can be a pre-set condition for obtaining the power data to be transmitted and transmitting the power data to be transmitted from the edge server to the cloud server. For example, a trigger period can be set to achieve regular triggering.

[0039] In the system of this embodiment, the system includes: a cloud server, an edge server, a policy collection terminal and a policy collection server; wherein: the policy collection server is used to receive the data rule conversion policy from the policy collection terminal and send the data rule conversion policy to the cloud server; the cloud server is used to receive the data rule conversion policy and send the data rule conversion policy to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion policy and the power collection data. In the system provided by the embodiment of the present application, the data rule conversion policy is introduced into the cloud-edge cooperation system, and the data rule conversion policy set by the user can be obtained. Then, the edge server can filter the real-time collected power collection data according to the data rule conversion policy to obtain the power data to be transmitted, thereby reducing the amount of transmitted data, reducing bandwidth waste, improving data transmission efficiency, and reducing transmission costs.

[0040] In an exemplary embodiment, Figure 2 As shown, the edge server includes: a collection service module and a data conversion module; the collection service module is used to collect power collection data and send the power collection data to the data conversion module; the data conversion module is used to receive the power collection data and filter the power data to be transmitted in the power collection data according to the data rule conversion strategy.

[0041] Among them, the collection service module can collect various types of power data in real time, that is, power collection data, such as power equipment operation data and power plant status data, etc. Next, the collection service module can push the real-time collected power collection data to the data conversion module of the edge server according to the preset interface specification. Furthermore, after receiving the power collection data, the data conversion module can filter the power collection data according to the data rule conversion strategy corresponding to the power collection data received by the broadcast, and obtain the power data to be transmitted corresponding to the data rule conversion strategy.

[0042] In an exemplary embodiment, the data conversion module is also used to: obtain the extraction field rule in the data rule conversion strategy; use the extraction field rule to filter out the field data corresponding to the extraction field rule in the power collection data, and determine the field data as the power data to be transmitted.

[0043] Among them, the data conversion module can use the parsing library or parsing algorithm to parse the content of the data rule conversion strategy, and extract the rule information about field extraction and filtering, that is, the extraction field rule. For example, the detailed rules of the field name list, filtering conditions (for example, specific numerical range, specific character matching, etc.) and data conversion operations (for example, data type conversion, etc.) to be extracted are parsed. In addition, the data conversion module can also perform format conversion on the power acquisition data so that the data format of the power acquisition data matches the data format of the data rule conversion strategy and the extraction field rule. Next, the data conversion module traverses each field in the input power acquisition data, extracts the value of the field in the extraction field list, and organizes it into a new data structure in a predetermined order. For example, if the data rule conversion strategy stipulates that the three fields of equipment number, temperature value and operating status are extracted, the data conversion module finds the corresponding field value from the power acquisition data and constructs a new data object, which only contains these three fields and their corresponding values. Further, for each extracted data object, the data conversion module can make a judgment one by one according to the filtering conditions in the data rule conversion strategy. If the data object meets all the filtering conditions, the data object is retained; if the data object does not meet at least one of the filtering conditions, the data object is discarded. For example, if the filtering conditions are that the temperature value is greater than 50 degrees Celsius and the operating status is "normal", only data objects that meet both conditions will be retained and continue to be processed. Furthermore, the power data to be transmitted can be screened and stored according to business needs, for example, in a local database, or packaged and uploaded to a cloud server or other target location at a certain time interval or data volume threshold.

[0044] In the system of this embodiment, the real-time collected power collection data can be screened and filtered according to the data rule conversion strategy to obtain the power data to be transmitted, thereby reducing the amount of transmitted data, reducing bandwidth waste, improving data transmission efficiency, and reducing transmission costs.

[0045] In an exemplary embodiment, the cloud server is also used to store the data rule conversion strategy in the cloud database.

[0046] In an exemplary embodiment, the cloud server includes: a policy management service module; the policy management service module is used to obtain a data rule conversion policy in a cloud database according to a preset trigger condition, and broadcast the data rule conversion policy to an edge server.

[0047] Among them, the preset trigger condition can be a pre-set condition for obtaining the power data to be transmitted and transmitting the power data to be transmitted from the edge server to the cloud server. For example, a trigger period can be set to achieve regular triggering. In one possible implementation, the policy management service module of the cloud server can set a timed task mechanism, for example, automatically triggering the policy acquisition operation at a certain time interval (for example, 5 minutes, 10 minutes, etc., which can be adjusted according to actual business needs). In another possible implementation, the policy management service module of the cloud server can set a specific trigger condition. For example, when it is detected that the policy data in the database is updated (through the database change notification mechanism, such as the trigger function provided by some databases or the API for monitoring data changes), or when a manual trigger instruction from the administrator is received (through the management interface or a specific command interface), the policy acquisition operation is started. When the preset trigger conditions are met, the policy management service module can use the database connection component to establish a connection with the cloud database that stores the data rule conversion policy, and obtain the latest data rule conversion policy from the cloud database table according to the pre-defined query statement. The query statement is designed according to the database structure to accurately retrieve the corresponding data rule conversion policy information. The data rule conversion policy information includes but is not limited to the rule content, scope of application and version information of the data rule conversion policy. Furthermore, the data rule conversion policy can be broadcast to the edge server in the form of a broadcast.

[0048] In the system of this embodiment, the data rule conversion strategy existing in the cloud database can be utilized, and when the preset trigger conditions are met, the policy management service module can call the data rule conversion strategy and send it to the edge server, so as to facilitate the subsequent use of the data rule conversion strategy to screen and filter the power collection data to obtain the power data to be transmitted, thereby improving data transmission efficiency.

[0049] In an exemplary embodiment, Figure 3 As shown, a real-time data collaborative strategy control method based on a cloud-edge collaborative scenario is provided. Taking the real-time data collaborative strategy control method based on a cloud-edge collaborative scenario as an example, the method is applied to a cloud server of a real-time data collaborative strategy control system based on a cloud-edge collaborative scenario. The method may include:

[0050] Step 302: Receive a data rule conversion policy sent by a policy collection server of a real-time data collaborative policy control system based on a cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database.

[0051] Among them, in the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, a cloud server, an edge server, a policy collection terminal and a policy collection server may be included. The policy collection terminal may be, but is not limited to, various personal computers, laptops, smart phones, tablets, IoT devices and portable wearable devices. IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The policy collection server may be implemented with an independent server or a server cluster consisting of multiple servers. The policy collection terminal may communicate with the policy collection server through a network. The user can register and log in to the policy collection platform of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario on the policy collection terminal. The policy collection terminal displays the policy collection page in response to the login operation triggered by the user; the user can trigger the filling of the data rule conversion policy for the power data to be transmitted on the policy collection page; the policy collection terminal can send the data rule conversion policy for the power data to be transmitted to the policy collection server in response to the filling operation triggered by the user on the policy collection page; the policy collection server can send the data rule conversion policy to the cloud server, and the cloud server can store the received data rule conversion policy for the power data to be transmitted in the cloud database. The cloud database can store multiple data rule conversion policies. There is a corresponding relationship between the data rule conversion policy and the power data to be transmitted. The power data to be transmitted can be the power data that the user needs to obtain and needs to be transmitted from the edge server to the cloud server. The data rule conversion policy can be the corresponding screening condition for the power data to be transmitted.

[0052] Step 304 , in response to a preset trigger condition, obtain a data rule conversion strategy in the cloud database, and broadcast the data rule conversion strategy to the edge server.

[0053] The edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data. The cloud server can obtain the data rule conversion strategy in the cloud database according to the preset trigger condition, and broadcast the data rule conversion strategy to at least one edge server. After the edge server collects the power collection data in real time, it can use the data rule conversion strategy to filter out the power data to be transmitted corresponding to the data rule conversion strategy in the power collection data; the preset trigger condition can be a pre-set condition for obtaining the power data to be transmitted and transmitting the power data to be transmitted from the edge server to the cloud server. For example, a trigger period can be set to achieve regular triggering.

[0054] In the method of this embodiment, a data rule conversion strategy is introduced into the cloud-edge cooperation system, and the data rule conversion strategy set by the user can be obtained. Then, the edge server can filter the real-time collected power collection data according to the data rule conversion strategy to obtain the power data to be transmitted, thereby reducing the amount of transmitted data, reducing bandwidth waste, improving data transmission efficiency, and reducing transmission costs.

[0055] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0056] Based on the same inventive concept, the embodiment of the present application also provides a real-time data collaborative policy control device based on a cloud-edge collaborative scenario for implementing the real-time data collaborative policy control method based on a cloud-edge collaborative scenario involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more embodiments of the real-time data collaborative policy control device based on a cloud-edge collaborative scenario provided below can refer to the limitations of the real-time data collaborative policy control method based on a cloud-edge collaborative scenario above, and will not be repeated here.

[0057] In one embodiment, Figure 4 As shown, a real-time data collaboration strategy control device based on a cloud-edge collaboration scenario is provided, including: an acquisition module 402 and a sending module 404, wherein:

[0058] An acquisition module 402 is used to receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database;

[0059] The sending module 404 is used to obtain the data rule conversion strategy in the cloud database in response to a preset trigger condition, and broadcast the data rule conversion strategy to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

[0060] Each module in the above-mentioned real-time data collaborative strategy control device based on cloud-edge collaborative scenarios can be implemented in whole or in part by software, hardware, and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0061] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store real-time data collaborative strategy control related data based on a cloud-edge collaborative scenario. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a real-time data collaborative strategy control method based on a cloud-edge collaborative scenario is implemented.

[0062] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0063] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0064] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0065] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0066] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0067] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0068] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0069] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A real-time data collaborative strategy control system based on cloud-edge collaborative scenarios, characterized in that: The system comprises: Cloud server, edge server, policy collection terminal and policy collection server; wherein: The policy collection server is used to receive the data rule conversion policy from the policy collection terminal and send the data rule conversion policy to the cloud server; The cloud server is used to receive the data rule conversion strategy and send the data rule conversion strategy to the edge server; The edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

2. The system according to claim 1, characterized in that The edge server includes: a collection service module and a data conversion module; the collection service module is used to collect the power collection data and send the power collection data to the data conversion module; the data conversion module is used to receive the power collection data and filter the power data to be transmitted from the power collection data according to the data rule conversion strategy.

3. The system according to claim 2, characterized in that The data conversion module is further used to: obtain an extraction field rule in the data rule conversion strategy; use the extraction field rule to filter out field data corresponding to the extraction field rule in the power collection data, and determine the field data as the power data to be transmitted.

4. The system according to claim 1, characterized in that The cloud server is also used to store the data rule conversion strategy in a cloud database.

5. The method according to claim 4, characterized in that The cloud server includes: a policy management and control service module; the policy management and control service module is used to obtain the data rule conversion policy in the cloud database according to a preset trigger condition, and broadcast the data rule conversion policy to the edge server.

6. A real-time data collaboration strategy control method based on cloud-edge collaboration scenario, characterized in that: A cloud server applied to a real-time data collaborative strategy control system based on a cloud-edge collaborative scenario; the method comprises: Receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database; In response to a preset trigger condition, the data rule conversion strategy is obtained in the cloud database, and the data rule conversion strategy is broadcast to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

7. A real-time data collaboration strategy control device based on cloud-edge collaboration scenario, characterized in that: A cloud server applied to a real-time data collaborative strategy control system based on a cloud-edge collaborative scenario; the device comprises: An acquisition module is used to receive a data rule conversion policy sent by a policy collection server of the real-time data collaborative policy control system based on the cloud-edge collaborative scenario, and store the data rule conversion policy in a cloud database; The sending module is used to obtain the data rule conversion strategy in the cloud database in response to a preset trigger condition, and broadcast the data rule conversion strategy to the edge server; the edge server is used to collect power collection data, and obtain the power data to be transmitted according to the data rule conversion strategy and the power collection data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to claim 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claim 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to claim 6 are implemented.

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