Business management method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a business management method and device, equipment, a storage medium and a program product. Belongs to the technical field of computers. According to the method, a plurality of edge nodes correspondingly obtain a unified and standard business management file issued by a cloud node based on respective subscribed target business algorithm services, and a plurality of target business algorithms are executed according to respective collaborative scheduling rules. Namely, the cloud uniformly manages a plurality of edge nodes through the business management file with the uniform standard, so that the problem of low business management efficiency of the edge nodes in the related technology can be solved, and the business management efficiency of the edge nodes can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a business management method, device, equipment, storage medium and program product. Background Art

[0002] The new power system is supported by the interaction between source, grid, load and storage and the complementarity of multiple energies, and has the basic characteristics of clean and low-carbon, safe and controllable, flexible and efficient, intelligent and friendly, and open and interactive. In this scenario, the traditional locally deployed integrated energy management system of enterprises is difficult to interact with the new power system, or enterprises interact with the new power system through the establishment of high-cost digital teams, and the return on investment of enterprises is low.

[0003] As a result, the integrated energy management system will evolve towards cloud computing. However, the integrated energy management system for cloud computing does not have the security and stability of local deployment when regulating equipment. Therefore, the new integrated energy management system is deployed locally by private cloud edge computing, which is responsible for the management and control of equipment. The public cloud is responsible for the interaction with the market and the power system, and is deployed on cloud nodes. The collaboration of cloud-edge software is completed through the upgrade technology of Over-the-Air Technology (OTA).

[0004] When facing enterprise-side business scenarios, there are differentiated business needs. When facing thousands of edge nodes, traditional solutions are more often carried out in the form of maintenance projects, which requires a lot of time and manpower costs. In addition, when responding to customer business needs, the cycle is long and the time cost is very high, which brings uncertainty to customers' business operation plans and makes it difficult to keep up with market trends, resulting in low business management efficiency of edge nodes. Summary of the invention

[0005] The present invention provides a service management method, device, equipment, storage medium and program product, which can improve the service management efficiency of edge nodes.

[0006] In the first aspect, an embodiment of the present disclosure provides a business management method, which is applied to edge nodes, including: multiple edge nodes subscribe to a target business algorithm service in a cloud node respectively; the multiple edge nodes receive a business management file sent by the cloud node based on the target business algorithm service they subscribe to; the business management file is composed of multiple target business algorithms and collaborative scheduling rules corresponding to the target business algorithm service; the multiple edge nodes respectively execute their respective multiple target business algorithms in accordance with their respective collaborative scheduling rules.

[0007] In the second aspect, the embodiments of the present disclosure provide a business management method, which is applied to cloud nodes, including: pre-registering multiple business algorithms to an algorithm service management pool; based on the target business algorithm services subscribed by multiple edge nodes in the algorithm service management pool, screening multiple target business algorithms corresponding to each of the multiple edge nodes; combining the multiple target business algorithms and collaborative scheduling rules corresponding to each edge node into a business management file corresponding to each edge node; and respectively sending the business management files corresponding to each of the multiple edge nodes to the corresponding edge nodes.

[0008] In the third aspect, the embodiment of the present disclosure also provides a business management device, which is applied to the edge node, including: a target business algorithm service subscription module, which is used for multiple edge nodes to subscribe to the target business algorithm service in the cloud node respectively; a business management file receiving module, which is used for the multiple edge nodes to receive the business management files sent by the cloud node based on the target business algorithm service they subscribe to; the business management file is composed of multiple target business algorithms and collaborative scheduling rules corresponding to the target business algorithm service; a target business algorithm execution module, which is used for the multiple edge nodes to execute their respective multiple target business algorithms according to their respective collaborative scheduling rules.

[0009] In the fourth aspect, the embodiments of the present disclosure also provide a business management device, which is applied to a cloud node, including: a business algorithm registration module, which is used to pre-register multiple business algorithms to an algorithm service management pool; a screening module, which is used to screen multiple target business algorithms corresponding to each of the multiple edge nodes based on the target business algorithm services subscribed by the multiple edge nodes in the algorithm service management pool; a business management file composition module, which is used to combine the multiple target business algorithms and collaborative scheduling rules corresponding to each edge node into a business management file corresponding to each edge node; and a business management file distribution module, which is used to distribute the business management files corresponding to each of the multiple edge nodes to the corresponding edge nodes respectively.

[0010] In the fifth aspect, an embodiment of the present disclosure further provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the business management method as described in the embodiment of the present disclosure.

[0011] In a sixth aspect, an embodiment of the present disclosure further provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the business management method as described in the embodiment of the present disclosure.

[0012] In a seventh aspect, an embodiment of the present disclosure further provides a computer program product, including a computer program, which, when executed by a processor, implements the business management method as described in the embodiment of the present disclosure.

[0013] According to the technical solution of the disclosed embodiment, multiple edge nodes subscribe to the target business algorithm service in the cloud node respectively; the multiple edge nodes receive the business management files sent by the cloud node based on the target business algorithm service they subscribe to; the business management files are composed of multiple target business algorithms and collaborative scheduling rules corresponding to the target business algorithm service; the multiple edge nodes execute their respective multiple target business algorithms according to their respective collaborative scheduling rules. In the disclosed embodiment, multiple edge nodes obtain the unified standard business management files issued by the cloud node based on the target business algorithm service they subscribe to, and execute multiple target business algorithms according to their respective collaborative scheduling rules, that is, the cloud manages multiple edge nodes uniformly through unified standard business management files, which can solve the problem of low business management efficiency of edge nodes in related technologies and improve the business management efficiency of edge nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0015] Figure 1 A schematic diagram of a business management method flow provided by an embodiment of the present invention;

[0016] Figure 2 A schematic diagram of another service management method flow provided by an embodiment of the present invention;

[0017] Figure 3 A schematic diagram of the structure of a service management device provided by an embodiment of the present invention;

[0018] Figure 4 A schematic diagram of the structure of another service management device provided by an embodiment of the present invention;

[0019] Figure 5 The present invention is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0021] It should be understood that the various steps recorded in the method implementation of the present disclosure can be performed in different orders and / or in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect. The term "including" and its variations used herein are open inclusions, that is, "including but not limited to". It should be noted that the concepts of "first", "second", etc. mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units. It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative and not restrictive, and those skilled in the art should understand that unless otherwise clearly stated in the context, it should be understood as "one or more". It is understandable that the data involved in the present technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of the corresponding laws, regulations and relevant provisions.

[0022] Figure 1 The present invention provides a flow chart of a service management method, which is applied to edge nodes. The present invention is applicable to the situation of managing services of edge nodes. The method can be executed by a service management device applied to edge nodes. The device can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, which can be a mobile terminal, a PC or a server. Figure 1 As shown, the method includes:

[0023] S110. Multiple edge nodes subscribe to target business algorithm services at cloud nodes respectively.

[0024] Among them, the target business algorithm service can be understood as the business algorithm service that the edge node has subscribed to in the cloud node. The business algorithm service can be understood as a service that is developed in advance according to the user's business needs, deployed in the cloud, and available for users to subscribe or use. The business algorithm service can also be expanded or adjusted according to the user's business needs. In this embodiment, there is no restriction on the business algorithm service, for example, it may include peak-valley arbitrage algorithm service, energy storage control algorithm service, photovoltaic power generation monitoring algorithm service, cold and hot control algorithm service, demand response algorithm service, photovoltaic absorption algorithm service, demand optimization algorithm service, anti-backflow algorithm service, etc.

[0025] In this embodiment, the target business algorithm service subscribed by each edge node may be the same or different. If the subscribed target business algorithm service is the same, the specific parameter data corresponding to the target business algorithm may be different, and the corresponding algorithm and logical relationship may be the same. That is, the corresponding target business algorithm may also be obtained according to the target business algorithm service and the identity information of the edge node and the existing business-related information.

[0026] S120. The multiple edge nodes receive the business management file sent by the cloud node based on the target business algorithm service to which they are subscribed.

[0027] In this embodiment, each target business algorithm service corresponds to a business process, and each business process includes at least one target business algorithm and a collaborative scheduling rule. Different target business algorithm services have different corresponding target business algorithms and corresponding collaborative scheduling rules. That is, different target business algorithm services have different corresponding business management files. In this embodiment, each edge node can subscribe to at least one target business algorithm service, and each edge node corresponds to at least one business management file, and each business management file is different.

[0028] In this embodiment, the cloud node can combine multiple target business algorithms and collaborative scheduling rules of each edge node into a business management file in a unified file format. In this embodiment, there is no restriction on the file format, for example, it can be xml format, json format, csv format, etc. Among them, the business management file can be composed of multiple target business algorithms corresponding to the target business algorithm service and collaborative scheduling rules. Collaborative scheduling rules can be used to dynamically coordinate scheduling of multiple target business algorithms to improve the execution efficiency and accuracy of each target business algorithm and improve user experience. Collaborative scheduling rules may include rules for collaborative scheduling of multiple target business algorithms, the scheduling frequency of each target business algorithm, the scheduling order between multiple target business algorithms, etc.

[0029] S130. The multiple edge nodes respectively execute the multiple target service algorithms according to their respective collaborative scheduling rules.

[0030] In this embodiment, after each edge node obtains its own service management file, it executes its own multiple target service algorithms according to its own collaborative scheduling rules. For each edge node, in the process of executing multiple target service algorithms according to the collaborative scheduling rules, each target service algorithm cooperates and influences each other, that is, each target service algorithm is collaboratively scheduled.

[0031] Optionally, multiple edge nodes respectively execute their respective multiple target business algorithms according to their respective collaborative scheduling rules, including: for each edge node, dividing the corresponding multiple target business algorithms into multiple levels; determining the control result corresponding to the target business algorithm of the current level based on the control result corresponding to the target business algorithm of the previous level; wherein the control result is the output result in the process of executing the target business algorithm; and adjusting the target business algorithm of the previous level according to the control result corresponding to the target business algorithm of the current level.

[0032] In this embodiment, the specific process of each edge node executing its own multiple target business algorithms according to its own collaborative scheduling rules is similar. For example, for any edge node, the corresponding multiple target business algorithms are divided into multiple levels. In this embodiment, there is no restriction on the specific number of multiple levels, which can be determined according to the number of target business algorithms, and each target business algorithm can correspond to one level. The target business algorithm used to generate target instructions can be placed in the first layer, and the target business algorithm that affects the results of the target business algorithm of the first layer can be placed in the subsequent layers. The target business algorithm of the next layer is responsible for regulating the target business algorithm of the previous layer, and the regulation result of the target business algorithm of the previous layer affects the regulation result of the target business algorithm of the next layer.

[0033] In this embodiment, after each target business algorithm is divided into corresponding levels, if the current level is not the first level, the control result corresponding to the target business algorithm of the current level is determined based on the control result corresponding to the target business algorithm of the previous level; wherein the control result is the output result in the process of executing the target business algorithm; the target business algorithm of the previous level is adjusted according to the control result corresponding to the target business algorithm of the current level. If the current level is the first level, the control result corresponding to the target business algorithm of the current level is directly obtained (the control result at this time can be understood as the target instruction generated by the target business algorithm of the first level), and the target business algorithm of the first level is adjusted according to the control result of the target business algorithm of at least one subsequent level.

[0034] Exemplarily, the target business algorithm service takes the peak-valley arbitrage algorithm service as an example, and the corresponding multiple target business algorithms may include the peak-valley arbitrage algorithm, the remaining power (State Of Charge, SOC) upper and lower limit algorithm and the overload protection algorithm. The corresponding collaborative scheduling rules may include the scheduling frequencies corresponding to the peak-valley arbitrage algorithm, the SOC upper and lower limit algorithm and the overload protection algorithm, for example, the peak-valley arbitrage algorithm is scheduled once every 5 minutes, the SOC upper and lower limit algorithm is scheduled once every minute, and the overload protection algorithm is scheduled once every second. The peak-valley arbitrage algorithm can be placed in the first layer, the SOC upper and lower limit algorithm can be placed in the second layer, and the overload protection algorithm can be placed in the third layer.

[0035] Exemplarily, the target charge and discharge power instruction generated by the peak-valley arbitrage algorithm may affect the remaining power SOC protected by the SOC upper and lower limit algorithm, and may also affect the loop load protected by the overload protection algorithm. The SOC upper and lower limit algorithm is used to ensure that the remaining power SOC of the battery is within the set power range by limiting the charge and discharge power to ensure the safety of the battery. Among them, the set power range consists of the upper limit value of the SOC and the lower limit value of the SOC. The overload protection algorithm is used to ensure that the load avoids overload by monitoring the load condition. The specific steps are as follows: Obtain the target charge and discharge power in the target charge and discharge power instruction generated by the peak-valley arbitrage algorithm through measuring point A. Obtain the remaining power SOC of the battery monitored by the SOC upper and lower limit protection algorithm by measuring B. Set the safety factor of a certain loop through the overload protection algorithm. If the target charge and discharge power generated by the peak-valley arbitrage algorithm causes the remaining power SOC of the battery monitored by the SOC upper and lower limit protection algorithm to be not within the set power range, the peak-valley arbitrage algorithm is adjusted according to the remaining power SOC so that the remaining power SOC is within the set power range. The control result of the SOC upper and lower limit protection algorithm is the remaining power SOC, and the control result of the peak-valley arbitrage algorithm is the target charge and discharge power. If the target charge and discharge power generated by the peak-valley arbitrage algorithm causes the load monitored by the overload protection algorithm to exceed the set safety factor (such as exceeding 80% of the transformer load), the peak-valley arbitrage algorithm is adjusted according to the monitored load so that the monitored load is less than the set safety factor. The control result of the overload protection algorithm is the load monitored by the overload protection algorithm. After adjusting the peak-valley arbitrage algorithm, the control results corresponding to the peak-valley arbitrage algorithm, the SOC upper and lower limit algorithm, and the overload protection algorithm will change. The control result of the SOC upper and lower limit algorithm changes according to the change of the control result of the peak-valley arbitrage algorithm, and the control result of the overload protection algorithm changes according to the change of the control result of the peak-valley arbitrage algorithm and the control result of the SOC upper and lower limit algorithm.

[0036] In this embodiment, multiple target business algorithms of each edge node are divided into multiple levels, and the control results of the target business algorithm of the current level are obtained according to the control results corresponding to the target business algorithm of the previous level. The target business algorithm of the previous level is adjusted based on the control results of the target business algorithm of the current level. This method can coordinately schedule multiple target business algorithms and improve the execution efficiency and accuracy of the target business algorithms.

[0037] Optionally, multiple edge nodes respectively execute their respective multiple target business algorithms according to their respective collaborative scheduling rules, including: for each edge node, if the current utilization rate of computing resources is greater than a set utilization rate threshold, then executing the multiple target business algorithms according to the collaborative scheduling rules and time period.

[0038] The current computing resources include at least one of the following: memory, central processing unit, and disk. In this embodiment, there is no restriction on setting the usage rate threshold, which can be determined according to the actual situation. The usage rate threshold corresponding to each computing resource can be the same or different. For example, the usage rate threshold for memory can be 90%, 80%, etc., the usage rate threshold for central processing unit can be 90%, 95%, etc., and the usage rate threshold for disk can be 90%, 85%, etc.

[0039] In this embodiment, there is no restriction on the time period. For example, one hour, two hours, one day, etc. can be used as the time period.

[0040] In this embodiment, each edge node, in the process of executing its own multiple target business algorithms according to its own collaborative scheduling rules, if the current computing resource usage is less than or equal to the set usage threshold, then it can continue to execute its own multiple target business algorithms according to its own collaborative scheduling rules. If the current computing resource (at least one of the memory, central processing unit, and disk) usage is greater than the corresponding set usage threshold, then the respective multiple target business algorithms are executed according to the respective collaborative scheduling rules and time periods, that is, the collaborative scheduling rules are combined in the process of executing multiple target business algorithms according to the time period. The explanation for executing multiple target business algorithms according to the time period can be: for the current time period, among the multiple target business algorithms, the target business algorithm required for the current time period can be executed, and for other target business algorithms, they can be placed in the corresponding time period for execution.

[0041] In this embodiment, when the current utilization rate of computing resources is greater than the set utilization rate threshold, multiple target business algorithms are executed according to collaborative scheduling rules and time periods, which can save computing resource space and at the same time ensure the integrity and correctness of the target business algorithms, ensuring that all target business algorithms can be successfully executed.

[0042] Optionally, executing the multiple target business algorithms according to the collaborative scheduling rules and time periods includes: pre-acquiring the target business algorithm corresponding to the current time period; determining the target planning business algorithm based on the multiple target business algorithms and the target business algorithm corresponding to the current time period; wherein the multiple target business algorithms are composed of the target planning business algorithm and the target business algorithm of the current time period; before the current time period, deleting or trimming the target planning business algorithm; within the current time period, executing the target business algorithm corresponding to the current time period according to the collaborative scheduling rules; and correspondingly installing or adding the target planning business algorithm to obtain the target business algorithm corresponding to the next time period.

[0043] In this embodiment, after receiving multiple target business algorithms, each edge node installs and executes the multiple target business algorithms. When the current computing resource usage rate is greater than the set usage rate threshold, the target business algorithm corresponding to the current time period is obtained in advance; before the current time period, the target planning business algorithm is deleted or trimmed. In this embodiment, there is no limit on the number of target planning algorithms, which can be determined according to actual conditions, for example, 10 or 20. In the current time period, the target business algorithm corresponding to the current time period is executed according to the collaborative scheduling rules. Correspondingly, the target planning business algorithm is installed or added to obtain the target business algorithm corresponding to the next time period, and so on, in a rolling installation, addition, deletion, and trimming manner to enable edge nodes to complete the execution of target business algorithms within limited computing resources.

[0044] Exemplarily, take 20 algorithms as an example for multiple target business algorithms, take 10 as an example for the number of target business algorithms required for the current time period, and the remaining 10 target business algorithms are used as target planning business algorithms. Take the time period as an example of one hour. If the usage rate of any current computing resource among the current memory, the current central processing unit and the current disk is greater than the set usage threshold, then the 10 target planning business algorithms will be deleted or trimmed before the current time period, and the required 10 target business algorithms will be executed in the current time period. At the 50th minute in the current time period, 10 target planning business algorithms are installed or added to obtain the target business algorithms required for the next time period.

[0045] For another example, take 100 algorithms as an example for multiple target business algorithms and one day as an example for the time period. If 50 algorithms need to be run in one day, then the corresponding 50 target business algorithms can be deployed in the corresponding time period.

[0046] In this embodiment, by deleting or trimming the target planning business algorithm before the current time period; executing the target business algorithm corresponding to the current time period according to the collaborative scheduling rules during the current time period; and installing or adding the target planning business algorithm to obtain the target business algorithm corresponding to the next time period, the edge node can effectively complete the execution of the target business algorithm within limited computing resources, thereby saving the hardware resource cost of the edge node.

[0047] According to the technical solution of the disclosed embodiment, multiple edge nodes subscribe to the target business algorithm service in the cloud node respectively; the multiple edge nodes receive the business management files sent by the cloud node based on the target business algorithm service they subscribe to; the business management files are composed of multiple target business algorithms and collaborative scheduling rules corresponding to the target business algorithm service; the multiple edge nodes execute their respective multiple target business algorithms according to their respective collaborative scheduling rules. In the disclosed embodiment, multiple edge nodes obtain the unified standard business management files issued by the cloud node based on the target business algorithm service they subscribe to, and execute multiple target business algorithms according to their respective collaborative scheduling rules, that is, the cloud manages multiple edge nodes uniformly through unified standard business management files, which can solve the problem of low business management efficiency of edge nodes in related technologies and improve the business management efficiency of edge nodes.

[0048] The technical solution of the disclosed embodiment is a method of uniformly managing multiple edge nodes in the cloud through a unified standard business management file. Compared with the method of initializing or prefabricating all algorithms at the edge nodes in traditional technologies, it is more flexible and convenient, and has more advantages in terms of time and labor costs when upgrading the algorithms of each edge node.

[0049] Figure 2 This is a flow chart of another service management method provided by an embodiment of the present invention, which is applied to a cloud node. The method can be executed by a service management device applied to a cloud node. The device can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, which can be a mobile terminal, a PC or a server. The specific steps are as follows:

[0050] S210. Register multiple business algorithms to the algorithm service management pool in advance.

[0051] In this embodiment, multiple business algorithms corresponding to all business algorithm services that have been written can be pre-registered in the algorithm service management pool through the cloud node. Specifically, the cloud node is responsible for automatically managing the file upload process of the business algorithm through the preset algorithm automatic publishing interface. When the business algorithm file is received, the corresponding docker file (used to define the build process of the Docker image) and the necessary startup scripts or configuration files are automatically generated. Subsequently, by executing these scripts, the corresponding Docker image is automatically built, and the Docker container is started based on the image. These containers will then be registered and added to the algorithm service management pool of the cloud node. At the same time, the collaborative scheduling rules corresponding to all business algorithm services are pre-set in the cloud node.

[0052] S220: Based on the target business algorithm services subscribed by the multiple edge nodes in the algorithm service management pool, screen the multiple target business algorithms corresponding to the multiple edge nodes.

[0053] In this embodiment, each edge node subscribes to the required business algorithm service in the cloud node, and uses the subscribed business algorithm service as the corresponding target business algorithm service. The algorithm service management pool of the cloud node selects multiple business algorithms related to the target business algorithm service from multiple business algorithms corresponding to all business algorithm services as multiple target business algorithms. And selects the collaborative scheduling rules related to the target business algorithm service from the collaborative scheduling rules corresponding to all business algorithm services.

[0054] S230: Combining the multiple target service algorithms and collaborative scheduling rules corresponding to each edge node into a service management file corresponding to each edge node.

[0055] In this embodiment, for each edge node, corresponding multiple target service algorithms and corresponding collaborative scheduling rules may be combined into a service management file.

[0056] S240: Send the service management files corresponding to each of the multiple edge nodes to the corresponding edge nodes respectively.

[0057] In this embodiment, after receiving the business management file, each edge node will automatically execute the preset script to generate the corresponding Docker image according to the business management file. Subsequently, based on the Docker image, the edge node will start the Docker container. After starting, the Docker container will be registered in the algorithm service management pool of the respective edge node and synchronized with the corresponding collaborative scheduling rules, so that multiple edge nodes can respectively execute their respective multiple target business algorithms according to their respective collaborative scheduling rules.

[0058] The technical solution of the disclosed embodiment is to pre-register multiple business algorithms to the algorithm service management pool; based on the target business algorithm services subscribed by multiple edge nodes in the algorithm service management pool, screen the multiple target business algorithms corresponding to each of the multiple edge nodes; group the multiple target business algorithms and collaborative scheduling rules corresponding to each edge node into a business management file corresponding to each edge node; and send the business management files corresponding to each of the multiple edge nodes to the corresponding edge nodes respectively. In the disclosed embodiment, the cloud node screens the corresponding multiple target business algorithms for each edge node according to the target business algorithm services subscribed by the multiple edge nodes, and combines the corresponding collaborative scheduling rules to form a unified standard business management file corresponding to each edge node, and synchronizes the business management file to each edge node, that is, the cloud manages multiple edge nodes uniformly through a unified standard business management file, which can solve the problem of low business management efficiency of edge nodes in related technologies and improve the business management efficiency of edge nodes.

[0059] Figure 3 A schematic diagram of the structure of a service management device provided in an embodiment of the present disclosure, which is applied to an edge node, such as Figure 3 As shown, the device includes: a target business algorithm service subscription module 310, a business management file receiving module 320 and a target business algorithm execution module 330;

[0060] The target business algorithm service subscription module 310 is used for multiple edge nodes to subscribe to the target business algorithm service in the cloud node respectively;

[0061] A business management file receiving module 320 is used for the multiple edge nodes to receive business management files sent by the cloud node based on the target business algorithm service they subscribe to; the business management file is composed of multiple target business algorithms corresponding to the target business algorithm service and collaborative scheduling rules;

[0062] The target service algorithm execution module 330 is used for the multiple edge nodes to respectively execute the multiple target service algorithms according to their respective collaborative scheduling rules.

[0063] The technical solution of the disclosed embodiment is that multiple edge nodes subscribe to the target business algorithm service on the cloud node respectively through the target business algorithm service subscription module; the multiple edge nodes receive the business management files sent by the cloud node based on the target business algorithm service they subscribe to through the business management file receiving module; the business management file is composed of multiple target business algorithms and collaborative scheduling rules corresponding to the target business algorithm service; the multiple edge nodes execute their respective multiple target business algorithms according to their respective collaborative scheduling rules through the target business algorithm execution module. In the disclosed embodiment, multiple edge nodes obtain the unified standard business management files issued by the cloud node based on the target business algorithm service they subscribe to, and execute multiple target business algorithms according to their respective collaborative scheduling rules, that is, the cloud manages multiple edge nodes uniformly through the unified standard business management files, which can solve the problem of low business management efficiency of edge nodes in related technologies and improve the business management efficiency of edge nodes.

[0064] Optionally, the target business algorithm execution module is specifically used to: for each edge node, divide the corresponding multiple target business algorithms into multiple levels; determine the control result corresponding to the target business algorithm of the current level based on the control result corresponding to the target business algorithm of the previous level; wherein the control result is the output result in the process of executing the target business algorithm; adjust the target business algorithm of the previous level according to the control result corresponding to the target business algorithm of the current level.

[0065] Optionally, the target business algorithm execution module is also used to: for each edge node, if the current computing resource utilization rate is greater than the set utilization rate threshold, execute the multiple target business algorithms according to the collaborative scheduling rules and time period; wherein the current computing resources include at least one of the following: memory, central processing unit, and disk.

[0066] Optionally, the target business algorithm execution module is also used to: pre-acquire the target business algorithm corresponding to the current time period; determine the target planning business algorithm based on the multiple target business algorithms and the target business algorithm corresponding to the current time period; wherein the multiple target business algorithms are composed of the target planning business algorithm and the target business algorithm of the current time period; before the current time period, delete or trim the target planning business algorithm; within the current time period, execute the target business algorithm corresponding to the current time period according to the collaborative scheduling rules; and install or add the target planning business algorithm to obtain the target business algorithm corresponding to the next time period.

[0067] The business management device provided in the embodiments of the present disclosure can execute the business management method provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0068] Figure 4 A schematic diagram of another business management device structure provided by an embodiment of the present disclosure, which is applied to a cloud node, such as Figure 4 As shown, the device includes: a business algorithm registration module 410, a screening module 420, a business management file composition module 430 and a business management file distribution module 440;

[0069] The business algorithm registration module 410 is used to pre-register multiple business algorithms to the algorithm service management pool;

[0070] A screening module 420, configured to screen a plurality of target service algorithms corresponding to each of the plurality of edge nodes based on the target service algorithm services subscribed by the plurality of edge nodes in the algorithm service management pool;

[0071] A service management file composition module 430, configured to compose the plurality of target service algorithms and collaborative scheduling rules corresponding to each edge node into a service management file corresponding to each edge node;

[0072] The service management file sending module 440 is used to send the service management files corresponding to the multiple edge nodes to the corresponding edge nodes respectively.

[0073] The business management device provided in the embodiments of the present disclosure can execute the business management method provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0074] The technical solution of the disclosed embodiment is to pre-register multiple business algorithms to the algorithm service management pool through the business algorithm registration module; to screen multiple target business algorithms corresponding to each of the multiple edge nodes based on the target business algorithm services subscribed by multiple edge nodes in the algorithm service management pool through the screening module; to form the multiple target business algorithms and collaborative scheduling rules corresponding to each edge node into a business management file corresponding to each edge node through the business management file composition module; and to send the business management files corresponding to each of the multiple edge nodes to the corresponding edge nodes through the business management file distribution module. In the disclosed embodiment, the cloud node screens the corresponding multiple target business algorithms for each edge node according to the target business algorithm services subscribed by the multiple edge nodes, and forms a unified standard business management file corresponding to each edge node in combination with the corresponding collaborative scheduling rules, and synchronizes the business management file to each edge node, that is, the cloud manages multiple edge nodes uniformly through a unified standard business management file, which can solve the problem of low business management efficiency of edge nodes in related technologies and improve the business management efficiency of edge nodes.

[0075] Figure 5A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0076] like Figure 5 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0077] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0078] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as method business management.

[0079] In some embodiments, the method business management may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method business management described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method business management in any other appropriate manner (e.g., by means of firmware).

[0080] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0081] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0082] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0083] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0084] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0085] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0086] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the service management method provided in any embodiment of the present application.

[0087] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0088] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A business management method, characterized in that: Applied to edge nodes, including: Multiple edge nodes subscribe to the target business algorithm service in the cloud node respectively; The multiple edge nodes receive a service management file sent by a cloud node based on the target service algorithm service they subscribe to; the service management file is composed of multiple target service algorithms corresponding to the target service algorithm service and a collaborative scheduling rule; The multiple edge nodes respectively execute the multiple target service algorithms according to their respective collaborative scheduling rules.

2. The method according to claim 1, characterized in that The multiple edge nodes respectively execute the multiple target service algorithms according to their respective collaborative scheduling rules, including: For each edge node, dividing the corresponding multiple target service algorithms into multiple levels; Determine the control result corresponding to the target business algorithm of the current level based on the control result corresponding to the target business algorithm of the previous level; wherein the control result is the output result in the process of executing the target business algorithm; The target business algorithm of the previous level is adjusted according to the control result corresponding to the target business algorithm of the current level.

3. The method according to claim 1, characterized in that The multiple edge nodes respectively execute the multiple target service algorithms according to their respective collaborative scheduling rules, including: For each edge node, if the current computing resource usage is greater than a set usage threshold, the multiple target business algorithms are executed according to the collaborative scheduling rules and time period; wherein the current computing resources include at least one of the following: memory, central processing unit, and disk.

4. The method according to claim 3, characterized in that Executing the multiple target service algorithms according to the collaborative scheduling rules and time periods includes: Pre-acquire the target business algorithm corresponding to the current time period; Determine a target planning business algorithm based on the multiple target business algorithms and the target business algorithm corresponding to the current time period; wherein the multiple target business algorithms are composed of the target planning business algorithm and the target business algorithm of the current time period; Before the current time period, deleting or trimming the target planning business algorithm; During the current time period, executing the target service algorithm corresponding to the current time period according to the collaborative scheduling rule; The target planning business algorithm is installed or added accordingly to obtain the target business algorithm corresponding to the next time period.

5. A business management method, characterized in that: Applied to cloud nodes, including: Register multiple business algorithms to the algorithm service management pool in advance; Based on the target business algorithm services subscribed by the multiple edge nodes in the algorithm service management pool, screening the multiple target business algorithms corresponding to the multiple edge nodes respectively; Combining the multiple target service algorithms and collaborative scheduling rules corresponding to each edge node into a service management file corresponding to each edge node; The service management files corresponding to each of the multiple edge nodes are respectively sent to the corresponding edge nodes.

6. A service management device, characterized in that: Applied to edge nodes, including: The target business algorithm service subscription module is used for multiple edge nodes to subscribe to the target business algorithm service in the cloud node respectively; A business management file receiving module, used for the multiple edge nodes to receive business management files sent by the cloud node based on the target business algorithm service they subscribe to; the business management file consists of multiple target business algorithms corresponding to the target business algorithm service and collaborative scheduling rules; The target service algorithm execution module is used for the multiple edge nodes to respectively execute the multiple target service algorithms according to their respective collaborative scheduling rules.

7. A service management device, characterized in that: Applied to cloud nodes, including: The business algorithm registration module is used to pre-register multiple business algorithms to the algorithm service management pool; A screening module, configured to screen a plurality of target business algorithms corresponding to each of the plurality of edge nodes based on the target business algorithm services subscribed by the plurality of edge nodes in the algorithm service management pool; A service management file composition module, used to compose the multiple target service algorithms and collaborative scheduling rules corresponding to each edge node into a service management file corresponding to each edge node; The service management file sending module is used to send the service management files corresponding to each of the multiple edge nodes to the corresponding edge nodes respectively.

8. An electronic device, characterized in that: The electronic device comprises: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the business management method as described in any one of claims 1-5.

9. A storage medium comprising computer executable instructions, wherein the computer executable instructions are used to execute the service management method according to any one of claims 1 to 5 when executed by a computer processor.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the service management method according to any one of claims 1 to 5.

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