Application remote arrangement method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to an application remote arrangement method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a dynamic resource topology network and the priority of a to-be-deployed application; acquiring historical load data and predicted load data of each edge node; determining a target edge node according to the priority of the to-be-deployed application, the historical load data of each edge node and the predicted load data; the target edge node is used for deploying the to-be-deployed application; and issuing a deployment instruction to the target edge node, wherein the deployment instruction is used for indicating the target edge node to deploy the to-be-deployed application. By adopting the method, the data transmission timeliness can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart grid, and in particular to an application remote arrangement method and device, computer equipment, computer readable storage medium and computer program product. BACKGROUND

[0002] With the rapid development of smart grid technology, in more and more use of various application adaptation power grid system in daily use scene, for example, using application to realize the operation of electricity fee query, payment, etc.

[0003] And the power grid scene covers power generation, power transmission, power transformation, power distribution and power utilization, etc. Multiple links, involving massive equipment monitoring, data acquisition and analysis, and real-time control and other complex tasks, so the power grid system puts forward higher requirements for the deployment and operation of various applications.

[0004] In related technologies, the deployment of various applications is realized by adopting a centralized architecture form of centralized deployment of applications in a cloud data center. However, this centralized architecture has a large geographical span, and data needs to be transmitted over a long distance, which can easily cause data transmission delay and is not conducive to real-time data transmission. SUMMARY

[0005] Therefore, it is necessary to provide an application remote arrangement method, device, computer equipment, computer readable storage medium and computer program product capable of improving data transmission timeliness for the above technical problems.

[0006] In a first aspect, the present application provides an application remote arrangement method, comprising:

[0007] Obtaining a dynamic resource topology network and a priority of an application to be deployed; the dynamic resource topology network comprises at least one edge node;

[0008] Obtaining historical load data and predicted load data of each edge node;

[0009] According to the priority of the application to be deployed, the historical load data and the predicted load data of each edge node, a target edge node is determined; the target edge node is used to deploy the application to be deployed;

[0010] The deployment instruction is used to instruct the target edge node to deploy the application to be deployed.

[0011] In one embodiment, before obtaining the dynamic resource topology network, the application of the remote arrangement method further comprises: obtaining real-time running state data of the edge nodes, inputting the real-time running state data into a node health assessment model, and obtaining real-time health data of the edge nodes output by the node health assessment model; obtaining the communication relationship between each edge node and the geographical position of each edge node, and constructing a network physical logic topology graph according to the communication relationship between each edge node and the geographical position of each edge node; generating the dynamic resource topology network according to the real-time health data of the edge nodes and the network physical logic topology graph.

[0012] In one of the embodiments, the target edge node is determined according to the priority of the application to be deployed, historical load data and predicted load data of each edge node, which comprises: obtaining historical load data of each edge node in a preset time period; inputting the historical load data into a node load prediction model, and obtaining load data of each edge node in a target time period output by the node load prediction model; determining the target edge node according to the priority of the application to be deployed, load data of each edge node in the target time period and real-time health data of the edge nodes.

[0013] In one optional embodiment, after the target edge node is determined according to the priority of the application to be deployed, historical load data and predicted load data of each edge node, the application of the remote arrangement method further comprises: sending a security verification instruction to the target edge node; receiving an application running security verification report sent by the target edge node, and verifying the application running security report by using a preset security verification standard; when the application running security verification report is verified, the step of issuing a deployment instruction to the target edge node is continued.

[0014] In one exemplary embodiment, after the target edge node is determined according to the priority of the application to be deployed, historical load data and predicted load data of each edge node, the application of the remote arrangement method further comprises: obtaining a security attribute of the application to be deployed; when the security attribute represents that the application to be deployed needs to be kept secret, generating an application legality verification pass report, and sending the legality verification pass report to the target edge node; receiving verification pass feedback information sent by the target edge node, and continuing to execute the step of sending a deployment instruction to the target edge node; the verification pass feedback information is feedback information generated by the target edge node after verifying that the application legality verification pass report is passed.

[0015] In one embodiment, after the deployment instruction is issued to the target edge node, the application of the remote arrangement method comprises: monitoring the network connection state of the target edge node in real time; when it is determined that the target edge node has a network interruption event according to the network connection state, obtaining a backup target node; transferring the task of the target edge node to the backup node.

[0016] In a second aspect, the application further provides a remote arrangement device, comprising:

[0017] a first data acquisition module, configured to acquire a dynamic resource topology network and a priority of an application to be deployed, wherein the dynamic resource topology network comprises at least one edge node;

[0018] a second data acquisition module, configured to acquire historical load data and predicted load data of each edge node;

[0019] a target node determination module, configured to determine a target edge node according to the priority of the application to be deployed, the historical load data and the predicted load data of each edge node, wherein the target edge node is used to deploy the application to be deployed;

[0020] an instruction issuing module, configured to issue a deployment instruction to the target edge node, wherein the deployment instruction is used to instruct the target edge node to deploy the application to be deployed.

[0021] In a third aspect, the application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method embodiments when executing the computer program.

[0022] In a fourth aspect, the application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the above-mentioned method embodiments when executed by a processor.

[0023] In a fifth aspect, the application further provides a computer program product, comprising a computer program, and the computer program implements the steps of the above-mentioned method embodiments when executed by a processor.

[0024] The above-mentioned remote arrangement method, device, computer device, computer readable storage medium and computer program product use the priority of the application to be deployed, the historical load data and the predicted load data of each edge node to determine a target edge node, and deploy the application to be deployed on the target edge node, so that different priorities of the application to be deployed can be distinguished, and the application to be deployed with high priority can be deployed on the edge node, thereby improving the timeliness of data transmission. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the application or the related art, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the application or the related art. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0026] Figure 1An application environment diagram for applying the remote arrangement method in an embodiment;

[0027] Figure 2 A flowchart diagram for applying the remote arrangement method in an embodiment;

[0028] Figure 3 A block diagram of the structure of an apparatus for applying the remote arrangement method in an embodiment;

[0029] Figure 4 An internal structure diagram of a computer device in an embodiment. DETAILED DESCRIPTION

[0030] In order to make the purposes, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application in combination 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.

[0031] The application remote arrangement method provided by the embodiments of the present application can be applied in an application environment as shown in Figure 1 . The terminal 102 communicates with the server 104 through a network. The data storage system can store data required to be processed by the server 104. The data storage system can be integrated on the server 104, or placed on a cloud or other network server. The server 104 acquires a dynamic resource topology network and a priority of an application to be deployed; acquires historical load data and predicted load data of each edge node; determines a target edge node according to the priority of the application to be deployed, the historical load data of each edge node and the predicted load data; the target edge node is used to deploy the application to be deployed; and the server 104 issues a deployment instruction to the target edge node, the deployment instruction being used to instruct the target edge node to deploy the application to be deployed. The edge node can be a terminal. The terminal 102 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle device, a projection device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The head-mounted device can be a virtual reality (VR) device, an augmented reality (AR) device, smart glasses, etc. The server 104 can be a stand-alone physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0032] In an exemplary embodiment, as shown in Figure 2 , a remote arrangement method is provided, and the method is applied in Figure 1Taking the server in the example, the explanation includes the following steps 202 to 208. Wherein:

[0033] Step 202: Obtain the dynamic resource topology network and the priority of the applications to be deployed.

[0034] In one embodiment, the dynamic resource topology network includes, but is not limited to, at least one edge node and the communication connections between edge nodes.

[0035] In one embodiment, the dynamic resource topology network can be adjusted based on the network physical logical topology diagram. Optionally, a network physical logical topology diagram is generated based on at least one edge node and the communication connection relationships between the edge nodes, and the network physical logical topology diagram is adjusted based on the operating status parameters of at least one edge node to generate the dynamic resource topology network. For example, if the operating status parameters of the edge node determine that the current edge node is in a communication disconnected state or is in an unhealthy operating state, the edge node is deleted from the network physical logical topology diagram to update the network physical logical topology diagram and obtain the dynamic resource topology network.

[0036] In one embodiment, an edge node being in an unhealthy operating state could be due to factors such as excessively high edge node temperature or excessively high CPU usage.

[0037] The priority of the application to be deployed is used to determine whether the application to be deployed is a critical application.

[0038] In one embodiment, the priority of the application to be deployed can be used to determine the target edge node.

[0039] In one embodiment, edge nodes have attribute information used to classify them. For example, edge nodes may be determined as critical nodes or as ordinary nodes based on the attribute information.

[0040] In one embodiment, the attribute information of the edge node may include, but is not limited to, the edge node's latency, CPU utilization, and / or memory utilization.

[0041] In one exemplary embodiment, if the priority of the application to be deployed determines that the application to be deployed is a critical application, the application to be deployed can be deployed on a critical edge node; if the priority of the application to be deployed determines that the application to be deployed is a non-critical application, the application to be deployed can be deployed on a non-critical edge node.

[0042] In one exemplary embodiment, if the priority of the application to be deployed determines that the application to be deployed is a non-critical application, the application to be deployed can be deployed on a cloud server.

[0043] In one embodiment, the business data corresponding to the to-be-deployed application is acquired, and when the business data indicates that the to-be-deployed application involves a critical business, the to-be-deployed application is considered as a critical application; when the business data indicates that the to-be-deployed application involves a non-critical business, the to-be-deployed application is considered as a non-critical application. Exemplarily, when the business data of the to-be-deployed application is core business data, the to-be-deployed application can be considered as a critical application; when the business data of the to-be-deployed application is auxiliary business data, the to-be-deployed application can be considered as a critical application.

[0044] In one embodiment, the to-be-deployed application includes at least one application module, the data flow of the to-be-deployed application during running and the data dependency relationship between the application modules are acquired, the priority and the data sensitivity of each application module are determined according to the data flow of the to-be-deployed application during running and the data dependency relationship between the application modules, the priority of each application module is determined according to the priority and the data sensitivity of each application module, and it is determined whether the application module is a critical application module or a non-critical application module according to the priority of each application module, the application module is deployed on a critical edge node when the application module is a critical application module, and the application module is deployed on a non-critical edge node or a cloud server when the application module is a non-critical application module. The data sensitivity is used to represent the severity when the data of the application module is leaked.

[0045] In one embodiment, a priority threshold is set, the to-be-deployed application is considered as a critical application when the priority of the to-be-deployed application is greater than or equal to the priority threshold, and the to-be-deployed application is considered as a non-critical application when the priority of the to-be-deployed application is less than the priority threshold.

[0046] In one embodiment, the priority of the to-be-deployed application can include a first priority and a second priority, the first priority is used to represent that the to-be-deployed application is a critical application, and the second priority is used to represent that the to-be-deployed application is a non-critical application.

[0047] In one embodiment, for a critical application, the to-be-deployed application can be arranged on a critical edge node. Alternatively, for a non-critical application, the to-be-deployed application can be arranged on a non-critical edge node or a cloud server.

[0048] In an optional embodiment, the dynamic resource topology network can be pre-generated, for example, real-time running state data of the edge nodes is acquired, the real-time running state data is input into a node health assessment model, and real-time health data of the edge nodes output by the node health assessment model is acquired; a communication relationship between the edge nodes and geographical positions of the edge nodes are acquired, and a network physical logical topology graph is constructed according to the communication relationship between the edge nodes and the geographical positions of the edge nodes; and the dynamic resource topology network is generated according to the real-time health data of the edge nodes and the network physical logical topology graph.

[0049] The real-time running state data is used to represent current running data of the edge nodes. For example, the real-time running state data includes but is not limited to CPU utilization, memory occupancy, network export bandwidth, round-trip delay to the core network, and historical failure times of the nodes.

[0050] In an embodiment, a data collection program is arranged in the edge nodes to realize collection of real-time state data of the edge nodes.

[0051] In an embodiment, the data collection program realizes acquisition of the real-time state data by calling an operating system kernel interface and a network interface function of the edge nodes.

[0052] In an embodiment, after the data collection program acquires the real-time state data, the data collection program encapsulates the collected real-time state data into a data packet in a unified format, and sends the compressed packet to the server through an encrypted channel after compressing the data packet.

[0053] In an embodiment, the acquisition of the real-time running state data of the edge nodes can also be that a data telemetry module is arranged on the edge nodes that realize data exchange, the data telemetry module is used to realize acquisition of specified type data, and the acquired specified type data is transmitted to the server according to a data transmission protocol. For example, the specified type data can include but is not limited to port flow and delay jitter. For example, the data transmission protocol can include but is not limited to a gNMI protocol, and the gNMI protocol can be used to realize pushing of interface flow data at a frequency of 100 ms.

[0054] In an embodiment, the obtaining of the real-time running state data of the edge node can further comprise setting a real-time running state data obtaining module, the real-time running state data obtaining module periodically sending a data obtaining instruction to a data obtaining node, the data obtaining node sending a data probe packet to other edge nodes, and other edge nodes returning corresponding data according to the required upload data set in the data probe packet after obtaining the data probe packet. Optionally, the data probe packet sent by the data obtaining node to other edge nodes can be an ICMP or UDP probe packet. Optionally, the required upload data set in the data probe packet can be network connectivity, time delay and / or packet loss rate between the edge nodes, etc. Optionally, other edge nodes are provided with a data monitoring module for monitoring the real-time running state data thereof and uploading the monitored real-time running state data when required.

[0055] The node health assessment model is a model for assessing whether the edge node is running healthily.

[0056] Optionally, the node health assessment model can be pre-generated by training historical data.

[0057] In an embodiment, the pre-generation process of the node health assessment model can comprise collecting multi-dimensional running state data of the edge node during normal operation as a training set, training an unsupervised anomaly detection module by using the training set, and generating the node health assessment model. Optionally, the multi-dimensional running state data can include, but is not limited to, CPU utilization, memory occupancy, network export bandwidth, round-trip time to the core network, and historical failure times of the node. Optionally, the anomaly detection module can be a self-encoder network.

[0058] In an embodiment, after obtaining the real-time running state data of the edge node, the real-time running state data is input into the node health assessment model, and result data corresponding to the real-time running state data output by the node health assessment model is obtained, and the real-time health state of the edge node is determined according to the result data.

[0059] In an embodiment, the determination of the real-time health state of the edge node can further comprise obtaining real-time running state data of the edge node and weight values corresponding to each real-time running state data, determining a real-time health state value according to the real-time running state data and the weight values corresponding to each real-time running state data, and determining the real-time health state of the edge node according to the real-time health state value. Optionally, the real-time running state data is normalized data. Optionally, the weight values corresponding to each real-time running state data can be pre-set.

[0060] In an optional embodiment, when the real-time health status value is calculated according to the real-time running status data and the weight value corresponding to each real-time running status data, the process of quantifying the real-time running status data is included.

[0061] For example, the continuous input data such as the CPU occupancy rate of the node and the network delay are fuzzified into variables such as "low", "medium" and "high" through the membership function.

[0062] For example, an expert knowledge base is established, which contains a plurality of fuzzy rules in the form of "IF... THEN... ", such as "IF the CPU occupancy rate is 'high' AND the network delay is 'high', THEN the node health degree is 'poor'".

[0063] The communication relationship is used to represent whether the edge nodes communicate with each other.

[0064] Optionally, the geographical position of the edge node can be represented by the latitude and longitude.

[0065] In an embodiment, after the communication relationship between the edge nodes and the geographical position of each edge node are determined, the network physical logical topology graph is constructed according to the communication relationship between the edge nodes and the geographical position of each edge node.

[0066] For example, according to the geographical position of each edge node, candidate edge nodes are determined from the edge nodes, and the candidate edge nodes having the communication relationship are connected to generate the network physical logical topology graph.

[0067] Optionally, the candidate edge nodes can be determined according to the geographical position of each edge node, that is, the edge nodes in the same region are determined by clustering the geographical position of each edge node, and the edge node having a geographical position obviously different from other edge nodes is excluded, so that the candidate edge nodes are obtained.

[0068] In one of the embodiments, the real-time health data of each edge node in the network physical logical topology graph is obtained, and if the real-time health data represents that the edge node is in an abnormal running state, the node is excluded from the network physical logical topology graph to generate a dynamic resource topology network.

[0069] In step 204, the historical load data and the predicted load data of each edge node are obtained.

[0070] In step 206, the target edge node is determined according to the priority of the to-be-deployed application, the historical load data and the predicted load data of each edge node.

[0071] The target edge node is used to deploy the to-be-deployed application.

[0072] In one embodiment, historical load data of each edge node in a preset time period is obtained; the historical load data is input into a node load prediction model, and load data of each edge node in a target time period output by the node load prediction model is obtained; and a target edge node is determined according to a priority of an application to be deployed, the load data of each edge node in the target time period, and real-time health data of the edge node.

[0073] The load prediction model is a pre-set model for predicting the load of the edge node in a certain time period. Optionally, the load prediction model can be an LSTM-ARIMA hybrid prediction model.

[0074] In one embodiment, historical load data in a preset time period is obtained, and the load prediction can be implemented by using the historical load data.

[0075] Optionally, the preset time period can be customized, and no limitation is made in this regard. For example, the preset time period can be 21 hours of historical load data.

[0076] In one embodiment, the target time period can be customized as needed. For example, the target time period is 1 hour of future load data.

[0077] In one embodiment, after the historical load data and the target time period are obtained, the target time period and the historical load data are input into the load prediction model, and the load data of the target time period output by the load prediction data is received.

[0078] In one optional embodiment, the target edge node is determined according to the priority of the application to be deployed, the load data of the edge node in the target time period, and the real-time health data of the edge node.

[0079] For example, the edge node whose load data in the target time period is less, whose real-time health data indicates that the edge node is in a good running state, and which meets the priority requirement of the application to be deployed is selected as the target edge node.

[0080] In one embodiment, the edge node can be filtered by using the priority of the application to be deployed to obtain a first candidate edge node, the first candidate edge node is further filtered by using the load data in the target time period to obtain a second candidate edge node, and further, the edge node with the best real-time health data in the second candidate edge node is selected as the target edge node.

[0081] In one of the embodiments, the target time period load data can also be used to screen the edge node to obtain a first candidate edge node, and the priority of the application to be deployed is further used to screen the first candidate edge node to obtain a second candidate edge node, and then the edge node with the best real-time health data in the second candidate edge node is selected as the target edge node.

[0082] In one of the embodiments, the server pre-trains the network agent, and the system including the server and the edge node is identified as a Markov decision process as a whole, and the network agent is used to determine the target edge node according to the real-time running state data of the edge node and the priority of the application to be deployed. It can be understood that the Markov decision process can be to select a node to deploy a task according to the current resource topology and task queue of the system, and the reward is the quantitative value of the execution efficiency of the task after deployment, such as low delay and high throughput.

[0083] In one of the embodiments, the multiple application services to be deployed can also be regarded as multiple participants, and the computing and network resources of the edge node are regarded as shared resources to be allocated. An utility function is defined for each participant, and the utility of the utility function is positively correlated with the amount of resources obtained and the business priority of the participant. A resource allocation scheme that can maximize the overall utility of all participants and is relatively fair is calculated by using an algorithm for finding a Nash equilibrium point, and a specific deployment strategy for each application service is generated according to the resource allocation scheme.

[0084] Step 208, issuing a deployment instruction to the target edge node.

[0085] The deployment instruction is used to instruct the target edge node to deploy the application to be deployed.

[0086] In one of the embodiments, after the server determines the target edge node, the server sends a deployment instruction to the target edge node, so that the target edge node arranges the application to be deployed according to the deployment instruction after receiving the deployment instruction.

[0087] In one of the embodiments, after the target edge node is determined, it can also be verified whether the target edge node is safe to arrange the application to be deployed. If it is safe, the deployment instruction is further issued to the target edge node. If it is not safe, the deployment instruction is not issued to the target edge node.

[0088] In one of the exemplary embodiments, a security verification instruction is sent to the target edge node, an application running security verification report sent by the target edge node is received, and the application running security verification report is verified by using a preset security verification standard. When the application running security verification report is verified, the step of issuing the deployment instruction to the target edge node is continued.

[0089] The security verification instruction is used to instruct the target edge node to perform security verification.

[0090] In one embodiment, upon receiving the security verification instruction, the target edge node verifies whether the communication connection with the server is secure, and when the communication connection is verified to be secure, the target edge node proceeds to the next security verification step, such as generating an application running security verification report.

[0091] In one embodiment, upon receiving the security verification instruction, the target edge node generates an application running security verification report.

[0092] In one embodiment, the application running security verification report is generated by a security running verification system of the target edge node.

[0093] In an optional embodiment, the security running verification system can obtain the running parameters of the current software, and according to the running parameters, generate a security verification report that is verified and signed by the security running verification system. The server and the edge node verify whether the deployment instruction is executed by the trusted execution environment signature, thereby improving the security of data processing.

[0094] Optionally, tamper-proof log record deployment credentials can also be used to preserve the security verification process,

[0095] In one embodiment, the security running verification system can be a measurement system for a basic input / output system (BIOS), an operating system kernel, or a critical library file.

[0096] In one embodiment, after the target edge node generates the application running security verification report, the target edge node sends the application running security verification report to the server, and the server performs further security verification based on the application running security verification report.

[0097] For example, the server obtains the running parameters in the application running security verification report, and verifies and matches the running parameters with a preset security verification standard. When the running parameters do not match the preset security verification standard, it is considered that the verification is not passed, and the server no longer sends a deployment instruction to the target edge node. When the running parameters match the preset security verification standard, the server continues to send a deployment instruction to the target edge node. Optionally, the preset security verification standard can be a golden image baseline.

[0098] In one example embodiment, a security attribute of the application to be deployed is acquired; when the security attribute indicates that the application to be deployed needs to be kept secret, a legality verification pass report of the application is generated, and the legality verification pass report is sent to the target edge node; verification pass feedback information sent by the target edge node is received, and the step of sending a deployment instruction to the target edge node is continued; the verification pass feedback information is feedback information generated by the target edge node after verifying that the legality verification pass report of the application is passed.

[0099] The security attribute is used to determine whether the application to be deployed needs to be kept secret. For example, the application to be deployed is designed as a trade secret, and the security attribute of the application to be deployed is secret.

[0100] In one example embodiment, after the application to be deployed is acquired, the security attribute corresponding to the application to be deployed is identified, and when the security attribute indicates that the application to be deployed needs to be kept secret, a legality verification pass report of the application is generated. For example, the legality verification pass report of the application can be, for example, “the deployment package source is legal and passes the security scan”.

[0101] In one embodiment, the legality verification pass report can be pre-generated, and can be in the form of a module, so that when it is determined that the security attribute of the application to be deployed indicates that it needs to be kept secret, the pre-generated module structure is called to obtain the legality verification pass report of the application.

[0102] In one embodiment, after the server acquires the legality verification pass report, the legality verification pass report is sent to the target edge node, and the target edge node verifies the validity of the legality verification pass report after receiving the legality verification pass report. After the validity of the legality verification pass report is verified, the corresponding application to be deployed is deployed.

[0103] In one embodiment, the network connection state of the target edge node is monitored in real time; when it is determined according to the network connection state that the target edge node has a network interruption event, a backup target node is acquired; and the task of the target edge node is transferred to the backup node.

[0104] The network connection state is used to determine whether the edge node is in a networked state. Optionally, the network connection state includes but is not limited to a networked state and a network interruption state.

[0105] In one embodiment, the server can monitor the network connection state of the target edge node in real time, and determine whether the target edge node needs to be changed to a backup node according to the network connection state.

[0106] In one of the embodiments, the server monitors the network connection state of the target edge node in real time. If the network connection state of the target edge node is a network disconnection state, it indicates that the target edge node has a network disconnection event, and the target edge node cannot continue to be used at present. At this time, a backup node can be obtained, and the backup node is used to deploy the to-be-deployed application.

[0107] In one of the embodiments, the backup node is selected in the same way as the target edge node, and details are not repeated here.

[0108] In the above application remote arrangement method, the priority of the to-be-deployed application, the historical load data and the predicted load data of each edge node are used to determine the target edge node, and the to-be-deployed application is deployed on the target edge node. Through the above steps, different priorities of the to-be-deployed application can be distinguished. The to-be-deployed application with high priority can be deployed on the edge node to improve the timeliness of data transmission. The to-be-deployed application with low priority can be deployed on the cloud. On the basis of ensuring the timeliness of data transmission, the congestion in the data transmission process caused by deploying all applications on the edge node is reduced, and the timeliness of data transmission is improved.

[0109] Based on the same inventive concept, the embodiments of the present application also provide an application remote arrangement device for implementing the above-mentioned application remote arrangement method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method. Therefore, the specific limitations in one or more application remote arrangement device embodiments provided below can refer to the limitations of the application remote arrangement method described above, and details are not repeated here.

[0110] In one exemplary embodiment, as shown in Figure 3 An application remote arrangement device 300 is provided, which includes a first data acquisition module 302, a second data acquisition module 304, a target node determination module 306, and an instruction issuing module 308, wherein:

[0111] The first data acquisition module 302 is configured to acquire a dynamic resource topology network and a priority of a to-be-deployed application.

[0112] The second data acquisition module 304 is configured to acquire historical load data and predicted load data of each edge node.

[0113] The target node determination module 306 is configured to determine a target edge node according to the priority of the to-be-deployed application, the historical load data and the predicted load data of each edge node. The target edge node is used to deploy the to-be-deployed application.

[0114] The instruction issuing module 308 is configured to issue a deployment instruction to the target edge node. The deployment instruction is used to instruct the target edge node to deploy the to-be-deployed application.

[0115] In one embodiment, the application remote arrangement device further comprises a dynamic resource topology network generation module, configured to obtain real-time running state data of the edge nodes before obtaining the dynamic resource topology network, input the real-time running state data into a node health assessment model, and obtain real-time health data of the edge nodes output by the node health assessment model; obtain communication relationships between the edge nodes and geographical positions of the edge nodes, and construct a network physical logical topology graph according to the communication relationships between the edge nodes and the geographical positions of the edge nodes; and generate the dynamic resource topology network according to the real-time health data of the edge nodes and the network physical logical topology graph.

[0116] In one of the embodiments, the target node determination module is further configured to obtain historical load data of the edge nodes in a preset time period; input the historical load data into a node load prediction model, and obtain load data of the edge nodes in a target time period output by the node load prediction model; and determine the target edge node according to the priority of the application to be deployed, the load data of the edge nodes in the target time period, and the real-time health data of the edge nodes.

[0117] In an optional embodiment, the application remote arrangement device further comprises a security verification module, configured to, after determining the target edge node according to the priority of the application to be deployed, the historical load data of the edge nodes, and the predicted load data, send a security verification instruction to the target edge node; receive an application running security verification report sent by the target edge node, and verify the application running security report by using a preset security verification standard; and when the application running security verification report is verified, continue to execute the step of issuing a deployment instruction to the target edge node.

[0118] In an optional embodiment, the security verification module is further configured to, after determining the target edge node according to the priority of the application to be deployed, the historical load data of the edge nodes, and the predicted load data, obtain a security attribute of the application to be deployed; when the security attribute represents that the application to be deployed needs to be kept secret, generate an application legality verification pass report, and send the legality verification pass report to the target edge node; receive verification pass feedback information sent by the target edge node, and continue to execute the step of sending a deployment instruction to the target edge node; and the verification pass feedback information is feedback information generated by the target edge node after verifying that the application legality verification pass report is passed.

[0119] In an optional embodiment, the application remote arrangement device further comprises a handover module, configured to, after issuing a deployment instruction to the target edge node, monitor a network connection state of the target edge node in real time; when it is determined according to the network connection state that a network interruption event occurs in the target edge node, obtain a backup target node; and hand over a task of the target edge node to the backup node.

[0120] The various modules in the application remote arrangement device can be implemented by software, hardware and combinations thereof, in whole or in part. The various modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to the various modules.

[0121] In an exemplary embodiment, a computer device, which can be a server, is provided, and an internal structure diagram of the computer device can be as shown in Figure 4 The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured 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 operating system and the computer program in the non-volatile storage medium to run. The database of the computer device is configured to store data. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with terminals outside through network connection. The computer program is executed by the processor to implement an application remote arrangement method.

[0122] Those skilled in the art can understand that Figure 4 The structure shown in the above description is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0123] In an exemplary embodiment, a computer device is provided, including a memory and a processor, and the memory stores a computer program. The processor executes the computer program to implement the steps in each method embodiment.

[0124] In an embodiment, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program is executed by the processor to implement the steps in each method embodiment.

[0125] In an embodiment, a computer program product is provided, and the computer program product includes a computer program. The computer program is executed by the processor to implement the steps in each method embodiment.

[0126] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0127] It can be understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program. 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 above-mentioned embodiments of each method. In the embodiments provided in the present application, any reference to memory, database or other medium can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, 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 but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., without being limited thereto.

[0128] Any technical features in the above embodiments can be combined, and for the sake of brevity, not all possible combinations are described above, however, any combination of these technical features is deemed to be within the scope of the present application.

[0129] The above embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the patent scope of the present application. It should be pointed out that, for ordinary skilled persons in the art, several modifications 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 should be subject to the appended claims.

Claims

1. A method for applying a remotely arranged method, characterized by, The method comprises: acquiring a dynamic resource topology network and a priority of an application to be deployed; the dynamic resource topology network comprises at least one edge node; acquiring historical load data and predicted load data of each edge node; determining a target edge node according to the priority of the application to be deployed, the historical load data and the predicted load data of each edge node; the target edge node is used for deploying the application to be deployed; issuing a deployment instruction to the target edge node, the deployment instruction being used for instructing the target edge node to deploy the application to be deployed.

2. The method of claim 1, wherein, Before the acquiring the dynamic resource topology network, the method further comprises: acquiring real-time running state data of the edge node, inputting the real-time running state data into a node health assessment model, and acquiring real-time health data of the edge node output by the node health assessment model; acquiring a communication relationship between each edge node and a geographical position of each edge node, and constructing a network physical logical topology graph according to the communication relationship between each edge node and the geographical position of each edge node; generating the dynamic resource topology network according to the real-time health data of the edge node and the network physical logical topology graph.

3. The method of claim 2, wherein, The determining the target edge node according to the priority of the application to be deployed, the historical load data and the predicted load data of each edge node comprises: acquiring historical load data of each edge node in a preset time period; inputting the historical load data into a node load prediction model, and acquiring load data of each edge node in a target time period output by the node load prediction model; determining a target edge node according to the priority of the application to be deployed, the load data of each edge node in the target time period and the real-time health data of the edge node.

4. The method of claim 1, wherein, After the determining the target edge node according to the priority of the application to be deployed, the historical load data and the predicted load data of each edge node, the method further comprises: sending a security verification instruction to the target edge node; receiving an application running security verification report sent by the target edge node, and verifying the application running security report by using a preset security verification standard; when the application running security verification report is verified, continuing to perform the step of issuing the deployment instruction to the target edge node.

5. The method of claim 1, wherein, After the determining the target edge node according to the priority of the application to be deployed, the historical load data and the predicted load data of each edge node, the method further comprises: acquiring a security attribute of the application to be deployed; when the security attribute represents that the application to be deployed needs to be kept secret, generating an application legality verification pass report, and sending the legality verification pass report to the target edge node; receiving verification pass feedback information sent by the target edge node, and continuing to perform the step of sending the deployment instruction to the target edge node; the verification pass feedback information is feedback information generated by the target edge node after verifying that the application legality verification pass report is passed.

6. The method of claim 1, wherein, After the issuing the deployment instruction to the target edge node, the method comprises: monitoring a network connection state of the target edge node in real time; when determining that the target edge node has a network interruption event according to the network connection state, obtaining a backup target node; migrating tasks of the target edge node to the backup node.

7. A remote placement device application, characterized by, The device comprises: a first data obtaining module, configured to obtain a dynamic resource topology network and a priority of an application to be deployed; the dynamic resource topology network comprises at least one edge node; a second data obtaining module, configured to obtain historical load data and predicted load data of each edge node; a target node determining module, configured to determine a target edge node according to the priority of the application to be deployed, the historical load data and the predicted load data of each edge node; the target edge node is used to deploy the application to be deployed; an instruction issuing module, configured to issue a deployment instruction to the target edge node; the deployment instruction is used to instruct the target edge node to deploy the application to be deployed. 8.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-7. The processor executes the computer program to implement the steps of the method in any one of claims 1 to 6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

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