Network data model generation method and electronic equipment

Abstract

The invention discloses a network data model generation method and electronic equipment. The method comprises the following steps: determining network communication demand information; performing information identification processing on the network communication demand information, and determining a demand category corresponding to the network communication demand information; according to the demand category, determining a modeling parameter of target data corresponding to the demand category in the network communication demand information; determining a sub-network data model corresponding to the target data according to the modeling parameters; and determining a target network data model corresponding to the network communication demand according to the sub-network data model. Therefore, the electronic equipment can automatically generate the network data model corresponding to the network communication demand according to the network communication demand information, and the efficiency of constructing the network data model is improved. Moreover, the network data model does not need to be constructed manually, so that errors caused by manual construction are avoided, and the accuracy of the constructed network data model is improved.

Description

Technical Field

[0001] This application relates to the technical field of model construction, and particularly relates to a method for generating a network data model and an electronic device. Background Art

[0002] With the rapid development of intelligent technologies (such as the intelligent cockpit of vehicles, intelligent driving, Over-the-Air Technology (OTA), etc.), there are more and more functions based on network (such as Ethernet) communication. In the process of using the network for communication, it is necessary to construct a network data model, and use a simulation tool to perform simulation tests on the constructed network data model to evaluate the network bandwidth usage and communication latency, etc. Then, according to the evaluated network bandwidth usage and communication latency, the network architecture design scheme is adjusted to meet the network communication requirements of each functional party.

[0003] In the prior art, in the process of constructing a network data model, first, network designers need to manually check the network communication requirements. After the manual check passes, the network data model is manually constructed according to the network communication requirements. However, with the development of technology, there are more and more network communication requirements. The method of manually constructing a network data model according to network communication requirements by humans has low efficiency, and when manually constructing a network data model, there are often some human errors.

[0004] In summary, the existing method for constructing a network data model has problems of low construction efficiency and affecting the accuracy of the network data model due to human errors. Summary of the Invention

[0005] This application provides a method for generating a network data model and an electronic device, which can solve the problems of low construction efficiency and affecting the accuracy of the network data model in the existing method for constructing a network data model. That is, it can automatically generate a network data model corresponding to network communication requirements, improve the efficiency of generating the network data model, and improve the accuracy of the network data model.

[0006] To solve the above technical problems, in a first aspect, an embodiment of this application provides a method for generating a network data model, which is applied to an electronic device. The method includes: determining network communication requirement information; performing information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information; according to the requirement category, determining the modeling parameters of the target data corresponding to the network communication requirement information; according to the modeling parameters, determining the sub-network data model corresponding to the target data; and according to the sub-network data model, determining the target network data model corresponding to the network communication requirement.

[0007] In the implementation manner of this application, during the process of generating (i.e., constructing) a network data model, after the electronic device determines the network communication requirement information, it can perform information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information. Then, according to the requirement category, the modeling parameters of the target data corresponding to the network communication requirement information are determined, and then the sub-network data model corresponding to the target data can be determined according to the modeling parameters. Finally, according to each sub-network data model, the target network data model corresponding to the network communication requirement can be determined. Thus, the electronic device can automatically generate the network data model corresponding to the network communication requirement according to the network communication requirement information, improving the efficiency of constructing the network data model. Moreover, there is no need to manually construct the network data model, avoiding the errors caused by manual construction, and thus improving the accuracy of the constructed network data model.

[0008] Furthermore, inputting the network data model into a simulation tool for simulation testing can obtain more accurate information such as network bandwidth usage and communication latency, facilitating engineers to accurately adjust the network architecture design plan according to the network bandwidth usage information and communication latency and other information to meet the network communication requirements of each functional party.

[0009] In a possible implementation of the above first aspect, performing information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information includes: performing information recognition processing on the network communication requirement information to determine the keyword information corresponding to the network communication requirement information; and determining the requirement category corresponding to the network communication requirement information according to the keyword information.

[0010] In the implementation manner of this application, first, information recognition processing is performed on the network communication requirement information to determine the keyword information corresponding to the network communication requirement information from it. Through the keyword information, the requirement category corresponding to the network communication requirement information can be determined more accurately, improving the accuracy of the constructed network data model.

[0011] In a possible implementation of the above first aspect, performing information recognition processing on the network communication requirement information includes: extracting the keyword fields of the network communication requirement information, performing legality check processing on the keyword fields to determine the first check result; in the case where the first check result meets the corresponding legality requirements, performing information recognition processing on the network communication requirement information; or performing regular expression verification processing on the network communication requirement information to determine the first verification result; in the case where the first verification result meets the corresponding legality requirements, performing information recognition processing on the network communication requirement information.

[0012] In the implementation manner of the present application, when performing information recognition processing on network communication requirement information, by extracting the key fields of the network communication requirement information, performing a legality check on the key fields to determine the first verification result, or performing a regular verification on the network communication requirement information to determine the first verification result. When the first verification result meets the legality requirements, perform information recognition processing on the network communication requirement information, so as to ensure both the accuracy and legality of the network communication requirement information before performing information recognition processing, and the accuracy and legality of the next step of information recognition processing on the network communication requirement information.

[0013] In a possible implementation of the first aspect above, when obtaining multiple requirement categories and determining multiple sub-network data models, according to the sub-network data models, determining the target network data model corresponding to the network communication requirement includes: obtaining the node information of both sides of the data stream interaction corresponding to each sub-network data model; determining the network topology structure corresponding to each sub-network data model according to the node information; determining the transmission path information of the data stream corresponding to each sub-network data model in the network topology according to the network topology structure and the breadth-first algorithm; determining the target network data model corresponding to the network communication requirement according to each sub-network data model, the network topology structure corresponding to each sub-network data model, and the transmission path information corresponding to each sub-network data model.

[0014] In the implementation manner of the present application, through the above method, automatically constructing the target network data model according to each sub-network data model, the transmission path information corresponding to each sub-network data model, and the network topology structure corresponding to each sub-network data model not only increases the accuracy of the constructed target network data model, but also improves the efficiency of model generation.

[0015] In a possible implementation of the first aspect above, when the target data is the first type of data, the modeling parameters include the first modeling parameter and the second modeling parameter. According to the modeling parameters, determining the sub-network data model corresponding to the target data includes: determining the sub-network data model corresponding to the target data according to the first modeling parameter and the second modeling parameter; when the target data is the second type of data, the modeling parameters include the third modeling parameter. According to the modeling parameters, determining the sub-network data model corresponding to the target data includes: determining the sub-network data model corresponding to the target data according to the third modeling parameter.

[0016] In the implementation manner of the present application, when the target data is the first type of data, a sub-network data model corresponding to the target data is constructed according to the first modeling parameter and the second modeling parameter; when the target data is the second type of data, a sub-network data model corresponding to the target data is constructed according to the third modeling parameter. Thus, by determining that the target data is the first type of data or the second type of data, different modeling parameters are determined, and sub-network data models corresponding to different types of target data are respectively constructed according to different modeling parameters, improving the accuracy of the sub-network data model corresponding to the target data.

[0017] In a possible implementation of the above first aspect, when the first type of data is IP-based extensible service-oriented middleware data, the first modeling parameter includes the corresponding service name, service interface name, service interface type, service interface data length, service interface data sending mode, service publisher, service subscriber, transport layer protocol type, and the second modeling parameter includes the priority of the virtual local area network where the service interface data is located; determining the sub-network data model corresponding to the target data according to the first modeling parameter and the second modeling parameter includes: generating service instance information and the publishing and subscribing relationship of the service according to the service name, service interface name, service interface type, service interface data length, service interface data sending mode, service publisher, service subscriber, and transport layer protocol type; generating a first network data frame according to the priority of the virtual local area network where the service interface data is located, the sending party and receiving party information of the service data; and determining the sub-network data communication model corresponding to the IP-based extensible service-oriented middleware data according to the service instance information, the publishing and subscribing relationship of the service, and the first network data frame.

[0018] In the implementation manner of the present application, when the first type of data is IP-based extensible service-oriented middleware data, service instance information and the publishing and subscribing relationship of the service are generated according to the first modeling parameter corresponding to the IP-based extensible service-oriented middleware data, a first network data frame is generated according to the second modeling parameter corresponding to the IP-based extensible service-oriented middleware data, and then a sub-network data communication model corresponding to the IP-based extensible service-oriented middleware data is constructed according to the service instance information, the publishing and subscribing relationship of the service, and the first network data frame, improving the accuracy of the sub-network data model corresponding to the IP-based extensible service-oriented middleware data.

[0019] In a possible implementation of the above first aspect, when the first type of data is Hypertext Transfer Protocol (HTTP) data, the first modeling parameters include the corresponding first data stream name, data length, data sender, data receiver, and protocol stack-related parameters of the data corresponding Transmission Control Protocol (TCP); the second modeling parameters include the first data stream name, data sender, data receiver, and the priority of the virtual local area network (VLAN) where the HTTP data is located; according to the first modeling parameters and the second modeling parameters, determining the sub-network data model corresponding to the target data, including: generating a communication mode in which the HTTP is transmitted based on the TCP according to the first data stream name, data length, data sender, data receiver, and protocol stack-related parameters of the data corresponding TCP; generating a second network data frame according to the first data stream name, data sender, data receiver, and the priority of the VLAN where the HTTP data is located; determining the sub-network data model corresponding to the HTTP data according to the communication mode and the second network data frame.

[0020] In the implementation manner of the present application, when the first type of data is HTTP data, a communication mode in which the HTTP is transmitted based on the TCP is generated according to the first modeling parameters corresponding to the above HTTP data, a second network data frame is generated according to the second modeling parameters corresponding to the above HTTP data, and then the sub-network data model corresponding to the HTTP data is constructed according to the communication mode and the second network data frame, improving the accuracy of the sub-network data model corresponding to the HTTP data.

[0021] In a possible implementation of the above first aspect, when the second type of data is audio data, the third modeling parameters include the corresponding second data stream name, sampling rate, bit depth, number of channels, and the priority of the VLAN where the audio data is located; according to the third modeling parameters, determining the sub-network data model corresponding to the target data, including: determining the first burst period of the audio data, the first number of network frames sent in each first burst period, and the first length of each network frame according to the sampling rate, bit depth, and number of channels; determining the priority information of the VLAN corresponding to the audio data according to the priority of the VLAN where the audio data is located; determining the sub-network data model corresponding to the audio data according to the first burst period, the first number, the first length, and the priority information of the VLAN corresponding to the audio data.

[0022] In the implementation manner of the present application, when the second type of data is audio data, according to the third modeling parameters corresponding to the above audio data, the first burst period, the first quantity, the first length, and the priority information of the virtual local area network corresponding to the audio data are respectively determined, and then according to the first burst period, the first quantity, the first length, and the priority information of the virtual local area network corresponding to the audio data, a sub-network data model corresponding to the audio data is constructed, improving the accuracy of constructing the sub-network data model corresponding to the audio data.

[0023] In a possible implementation of the first aspect above, when the second type of data is video data, the third modeling parameters include the corresponding third data stream name, the number of horizontal pixel points, the number of vertical pixel points, the frame rate, the bit depth, the compression rate, and the priority of the virtual local area network where the video data is located; determining the sub-network data model corresponding to the target data according to the third modeling parameters includes: determining the second burst period of the video data, the second quantity of network frames sent in each second burst period, and the second length of each network frame according to the number of horizontal pixel points, the number of vertical pixel points, the frame rate, the bit depth, and the compression rate; determining the priority information of the virtual local area network corresponding to the video data according to the priority of the virtual local area network where the video data is located; and determining the sub-network data model corresponding to the video data according to the second burst period, the second quantity, the second length, and the priority information of the virtual local area network corresponding to the video data.

[0024] In the implementation manner of the present application, when the second type of data is audio data, according to the third modeling parameters corresponding to the above video data, the second burst period, the second quantity, the second length, and the priority information of the virtual local area network corresponding to the video data are respectively determined, and then according to the second burst period, the second quantity, the second length, and the priority information of the virtual local area network corresponding to the video data, a sub-network data model corresponding to the video data is constructed, improving the accuracy of constructing the sub-network data model corresponding to the video data.

[0025] In a possible implementation of the first aspect above, when the second type of data is network topology data, the third modeling parameters include electronic control unit node information, control information, and the connection relationship between the electronic control unit nodes and the controls; determining the sub-network data model corresponding to the target data according to the third modeling parameters includes: determining the network topology structure according to the electronic control unit node information, the control information, and the connection relationship between the electronic control unit nodes and the controls; and determining the sub-network data model corresponding to the network topology data according to the network topology structure.

[0026] In the implementation manner of the present application, when the second type of data is network topology data, the network topology structure is determined according to the third modeling parameters corresponding to the network topology data, and then a sub-network data model corresponding to the network topology data is constructed according to the network topology structure, improving the accuracy of constructing the sub-network data model corresponding to the network topology data.

[0027] In a possible implementation of the above first aspect, determining the network communication requirement information includes: obtaining a plurality of initial network communication requirement information, each piece of initial network communication requirement information being from a different network communication requirement provider; and performing screening and integration processing on the initial network communication requirement information to obtain the network communication requirement information.

[0028] In a possible implementation of the above first aspect, the method further includes: storing the target network data model in a first format.

[0029] In a second aspect, an embodiment of the present application provides a network data model generation device, including: a first processing module for determining network communication requirement information; a second processing module for performing information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information; a third processing module for determining the modeling parameters of the target data corresponding to the requirement category according to the requirement category; a fourth processing module for determining the sub-network data model corresponding to the target data according to the modeling parameters; and a fifth processing module for determining the target network data model corresponding to the network communication requirement according to the sub-network data model.

[0030] In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory so that the electronic device implements the network data model generation method provided in the above first aspect and / or any possible implementation manner of the first aspect.

[0031] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, the computer program includes program instructions, and the program instructions are run by an electronic device to implement the network data model generation method provided in the above first aspect and / or any possible implementation manner of the first aspect.

[0032] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer programs / instructions, and when the computer programs / instructions are executed by a processor, the network data model generation method provided in the above first aspect and / or any possible implementation manner of the first aspect is implemented.

[0033] For the relevant beneficial effects of the above second aspect to fifth aspect, reference may be made to the relevant descriptions in the above first aspect, and details are not described herein again.

[0034] Advantages of the present application:

[0035] The network data model generation method provided by this application, during the process of generating (i.e., constructing) a network data model, after an electronic device determines the network communication requirement information, it can perform information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information. Then, according to the requirement category, it determines the modeling parameters of the target data corresponding to the network communication requirement information in the network communication requirement information, and then can determine the sub-network data model corresponding to the target data according to the modeling parameters. Finally, according to each sub-network data model, it can determine the target network data model corresponding to the network communication requirement. Thus, the electronic device can automatically generate the network data model corresponding to the network communication requirement according to the network communication requirement information, improving the efficiency of constructing the network data model. Moreover, there is no need to manually construct the network data model, avoiding errors caused by manual construction, and thus improving the accuracy of the constructed network data model.

[0036] Furthermore, inputting the network data model into a simulation tool for simulation testing can obtain more accurate information such as network bandwidth usage and communication latency, facilitating engineers to accurately adjust the network architecture design plan according to the network bandwidth usage information and communication latency and other information to meet the network communication requirements of each functional party. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] To more clearly illustrate the technical solutions of this application, the drawings used in the description of the embodiments will be briefly introduced below.

[0038] Figure 1 FIG. [FIG number] is a schematic flowchart of a network data model generation method according to some embodiments of this application;

[0039] Figure 2 FIG. [FIG number] is a schematic flowchart of a process for determining a requirement category according to some embodiments of this application;

[0040] Figure 3 FIG. [FIG number] is a schematic flowchart of a process for determining a sub-network data model according to some embodiments of this application;

[0041] Figure 4 FIG. [FIG number] is a schematic flowchart of another process for determining a sub-network data model according to some embodiments of this application;

[0042] Figure 5 FIG. [FIG number] is a schematic flowchart of another process for determining a sub-network data model according to some embodiments of this application;

[0043] Figure 6 FIG. [FIG number] is a schematic flowchart of another process for determining a sub-network data model according to some embodiments of this application;

[0044] Please note that the "FIG number" in the translation of , , , , , should be replaced with the actual figure number in the original text. Since the original text doesn't provide specific figure numbers, they are left as placeholders here.Figure 7 According to some embodiments of the present application, it shows a schematic flowchart of another method for determining a sub-network data model;

[0045] Figure 8 According to some embodiments of the present application, it shows a schematic flowchart of a method for determining a target network data model corresponding to network communication requirements according to a sub-network data model;

[0046] Figure 9 According to some embodiments of the present application, it shows a schematic flowchart of another method for generating a network data model;

[0047] Figure 10 According to some embodiments of the present application, it shows a schematic structural diagram of a network data model generation device;

[0048] Figure 11 According to some embodiments of the present application, it shows a schematic structural diagram of an electronic device. Specific Embodiments

[0049] Next, the technical solutions of the present application will be further described in detail with reference to the accompanying drawings.

[0050] As mentioned above, the existing methods for constructing a network data model have problems such as low construction efficiency and inaccurate network data models affected by human errors.

[0051] Based on this, the present application provides a method for generating a network data model, which can automatically generate a network data model corresponding to network communication requirements, improving the efficiency of network data model generation and the accuracy of the network data model.

[0052] Next, with reference to the accompanying drawings, the implementation process and advantages of the method for generating a network data model provided by the present application will be described in detail.

[0053] In one implementation of the present application, as Figure 1 shown, the method for generating a network data model provided by the present application is applied to an electronic device (such as a computer, a computer cluster, etc.), and the specific network type can be, for example, an Ethernet, a CAN network, a wireless network, etc. The method includes the following steps:

[0054] S100: Determine network communication requirement information.

[0055] Among them, the network communication requirement information represents the network communication design requirement information. By obtaining the network communication requirement information and using it as the basis for automatically constructing a network simulation data model (as an example of the target network data model), the consistency between the finally determined simulation network data model and the preset communication network design requirements can be ensured. The network communication requirement information can be collected by network designers from functional system engineers, or obtained by other means.

[0056] In an implementation manner of this application, determining the network communication requirement information includes: obtaining a plurality of initial network communication requirement information, where each initial network communication requirement information comes from different network communication requirement providers; performing screening and integration processing on the initial network communication requirement information to obtain the network communication requirement information.

[0057] That is, the network communication requirement providers can be engineers of each functional system. The initial network communication requirement information provided by the engineers of each functional system is summarized, screened, and integrated to determine the network communication requirement information.

[0058] S200: Perform information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information.

[0059] The network communication requirement information generally corresponds to multiple types of data, and the network communication requirements corresponding to each type of attribute are generally different. Therefore, by performing information recognition processing on the network communication requirement information, the determined requirement category corresponding to the network communication requirement information is usually not limited to one requirement category, and may include one or more than one requirement category. By performing information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information, the accuracy and comprehensiveness of the next processing and the final simulation model construction can be ensured.

[0060] S300: According to the requirement category, determine the modeling parameters of the target data corresponding to the network communication requirement information.

[0061] The modeling parameters of the target data corresponding to different requirement categories are generally different. According to the requirement category, determining the modeling parameters of at least one target data in the network communication requirement information can ensure the accuracy of the sub-network data model constructed subsequently according to the modeling parameters corresponding to different requirement categories.

[0062] S400: According to the modeling parameters, determine the sub-network data model corresponding to the target data.

[0063] The modeling parameters of the target data corresponding to different demand categories are different. Therefore, the sub-network data models corresponding to the obtained target data are also different. Determining the sub-network data model corresponding to the target data according to the modeling parameters corresponding to at least one demand category can ensure the accuracy of the sub-network data model corresponding to the target data.

[0064] S500: Determine the target network data model corresponding to the network communication demand according to the sub-network data model.

[0065] According to the sub-network data model, automatically generate or construct the target network data model corresponding to the network communication demand, without the need for manual construction of the network data communication model (i.e., the network data model), avoiding errors caused by manual construction, and thus increasing the accuracy of the target network data model. Moreover, the final target network data model is obtained from the sub-network data models corresponding to all demand categories corresponding to the network communication demand information, and the target network data model can comprehensively reflect the data requirements corresponding to the network communication demand information.

[0066] In the network data model generation method provided by this application, during the process of generating (i.e., constructing) the network data model, after the electronic device determines the network communication demand information, it can perform information recognition processing on the network communication demand information to determine the demand category corresponding to the network communication demand information. Then, according to the demand category, determine the modeling parameters of the target data corresponding to the network communication demand information that match the demand category, and then, according to the modeling parameters, the sub-network data model corresponding to the target data can be determined. Finally, according to each sub-network data model, the target network data model corresponding to the network communication demand can be determined. Thus, the electronic device can automatically generate the network data model corresponding to the network communication demand according to the network communication demand information, improving the efficiency of network data model construction. Moreover, there is no need for manual construction of the network data model, avoiding errors caused by humans, and thus improving the accuracy of the constructed network data model.

[0067] Furthermore, inputting the network data model into a simulation tool for simulation testing can obtain more accurate information such as network bandwidth usage and communication latency, facilitating engineers to accurately adjust the network architecture design plan according to the network bandwidth usage information and communication latency and other information to meet the network communication requirements of each functional party.

[0068] In one implementation manner of this application, as Figure 2 shown, performing information recognition processing on the network communication demand information to determine the demand category corresponding to the network communication demand information includes the following steps:

[0069] S210: Perform information recognition processing on the network communication demand information to determine the keyword information corresponding to the network communication demand information.

[0070] In one implementation of the present application, information recognition processing of network communication requirement information includes: extracting key fields of the network communication requirement information, performing legality check processing on the key fields to determine a first check result, and performing information recognition processing on the network communication requirement information when the first check result meets the corresponding legality requirements.

[0071] Alternatively, perform regular expression verification processing on the network communication requirement information to determine a first verification result, and perform information recognition processing on the network communication requirement information when the first verification result meets the corresponding legality requirements.

[0072] The legality requirements corresponding to the first check result and the legality requirements corresponding to the first verification result may be the same or different.

[0073] If the legality check or regular expression verification is passed, it indicates that the network communication requirement information is legal, and then the legal network communication requirement information is recognized; if it is illegal, an illegal prompt is generated, and the illegal field data in the illegal network communication requirement information can also be marked to form an error report, and the error report is fed back to the system designer for the system designer to modify and adjust the network communication requirement information.

[0074] S220: Determine the requirement category corresponding to the network communication requirement information according to the keyword information.

[0075] Through the extracted keyword information, the requirement category corresponding to the network communication requirement information can be accurately determined.

[0076] In one implementation of the present application, the target data includes first-type data and second-type data, and when the target data is first-type data, the modeling parameters include first modeling parameters and second modeling parameters. According to the modeling parameters, determining the sub-network data model corresponding to the target data includes: determining the sub-network data model corresponding to the target data according to the first modeling parameters and the second modeling parameters; when the target data is second-type data, the modeling parameters include third modeling parameters. According to the modeling parameters, determining the sub-network data model corresponding to the target data includes: determining the sub-network data model corresponding to the target data according to the third modeling parameters.

[0077] In one implementation of the present application, such as Figure 3As shown, when the first type of data is Scalable service-Oriented MiddlewarE over IP (SOME / IP) data, the first modeling parameters include the corresponding service name, service interface name, service interface type (such as Event, Field, and Method), service interface data length, service interface data sending mode (such as Cyclic, On Change Event, and RPC Method), service publisher, service subscriber, and transport layer protocol type. The second modeling parameter includes the priority of the virtual local area network (VLAN) where the service interface data is located. According to the first modeling parameter and the second modeling parameter, determining the sub-network data model corresponding to the target data includes the following steps:

[0078] S410: Generate service instance information and the publish-subscribe relationship of the service according to the service name, service interface name, service interface type, service interface data length, service interface data sending mode, service publisher, service subscriber, and transport layer protocol type.

[0079] S420: Generate a first network data frame according to the priority of the virtual local area network where the service interface data is located, and the sender and receiver information of the service data.

[0080] S430: Determine the sub-network data communication model corresponding to the Scalable service-Oriented MiddlewarE over IP data according to the service instance information, the publish-subscribe relationship of the service, and the first network data frame.

[0081] Specifically, when the first type of data is Scalable service-Oriented MiddlewarE over IP data, the first modeling parameters include the corresponding service name, service interface name, service interface type, service interface data length, service interface data sending mode, service publisher, service subscriber, and transport layer protocol type, and the second modeling parameter includes the priority of the virtual local area network where the service interface data is located. And in the process of constructing the sub-network data model, first generate service instance information and the publish-subscribe relationship of the service according to the service name, service interface name, service interface type, service interface data length, service interface data sending mode, service publisher, service subscriber, and transport layer protocol type, then construct a two-layer first network data frame according to the priority of the virtual local area network where the service interface data is located, and the sender and receiver information of the service data, and finally establish a mapping relationship between the service instance information, the publish-subscribe relationship of the service, and the two-layer first network data frame, thereby completing the establishment of the sub-network data communication model (i.e., the sub-network data model) corresponding to the Scalable service-Oriented MiddlewarE over IP data.

[0082] In an implementation manner of the present application, as Figure 4 shown, when the first type of data is Hypertext Transfer Protocol (HTTP) data, the first modeling parameters include the corresponding first data name, data length, data sender, data receiver, and protocol stack related parameters of the data corresponding transmission control protocol (such as the data sending period of the sender, the amount of data sent by the sender per period, the period for the receiver to read data through the socket, the size of the receive buffer of the receiver's socket, the on / off state of the Nagle algorithm, the minimum RTO time, the on / off state of the congestion control algorithm), and the second modeling parameters include the first data stream name, data sender, data receiver, and the priority of the virtual local area network where the Hypertext Transfer Protocol data is located. According to the first modeling parameters and the second modeling parameters, to determine the sub-network data model corresponding to the target data, the following steps are included:

[0083] S410’: Generate a communication mode in which the Hypertext Transfer Protocol is transmitted based on the Transmission Control Protocol according to the first data stream name, data length, data sender, data receiver, and protocol stack related parameters of the data corresponding transmission control protocol.

[0084] S420’: Generate a second network data frame according to the first data stream name, data sender, data receiver, and the priority of the virtual local area network where the Hypertext Transfer Protocol data is located.

[0085] S430’: Determine the sub-network data model corresponding to the Hypertext Transfer Protocol data according to the communication mode and the second network data frame.

[0086] Specifically, when the first type of data is Hypertext Transfer Protocol data, the first modeling parameters include the name of the corresponding first data, data length, data sender, data receiver, and protocol stack related parameters of the data corresponding transmission control protocol, and the second modeling parameters include the first data stream name, data sender, data receiver, and the priority of the virtual local area network where the Hypertext Transfer Protocol data is located. And in the process of constructing the sub-network data model, first generate a communication mode in which the Hypertext Transfer Protocol is transmitted based on the Transmission Control Protocol according to the first data stream name, data length, data sender, data receiver, and protocol stack related parameters of the data corresponding transmission control protocol, then construct a two-layer second network data frame according to the first data stream name, data sender, data receiver, and the priority of the virtual local area network where the Hypertext Transfer Protocol data is located, and finally establish a mapping relationship between the communication mode in which the Hypertext Transfer Protocol is transmitted based on the Transmission Control Protocol and the two-layer second network data frame, thereby completing the establishment of the sub-network data model corresponding to the Hypertext Transfer Protocol data.

[0087] In an implementation of the present application, as Figure 5 shown, when the second type of data is audio data (i.e., Audio data), the third modeling parameter includes the corresponding second data stream name, sampling rate, bit depth, number of channels, and the priority of the virtual local area network where the audio data is located; according to the third modeling parameter, determining the sub-network data model corresponding to the target data includes the following steps:

[0088] S410”: Determine the first burst period of the audio data, the first number of network frames sent in each first burst period, and the first length of each network frame according to the sampling rate, bit depth, and number of channels.

[0089] S420”: Determine the priority information of the virtual local area network corresponding to the audio data according to the priority of the virtual local area network where the audio data is located.

[0090] S430”: Determine the sub-network data model corresponding to the audio data according to the first burst period, the first number, the first length, and the priority information of the virtual local area network corresponding to the audio data.

[0091] Specifically, when the second type of data is audio data, the third modeling parameter includes the corresponding second data stream name, sampling rate, bit depth, number of channels, and the priority of the virtual local area network where the audio data is located. And in the process of constructing the sub-network data model, first determine the first burst period of the audio data, the first number of network frames sent in each burst period, and the first length of each network frame according to the sampling rate, bit depth, and number of channels, then determine the priority information of the virtual local area network corresponding to the audio data according to the priority of the virtual local area network where the audio data is located, and finally complete the establishment of the sub-network data model corresponding to the audio data according to the first burst period, the first number, the first length, and the priority information of the virtual local area network corresponding to the audio data.

[0092] In an implementation of the present application, as Figure 6 shown, when the second type of data is video data (i.e., Video data), the third modeling parameter includes the corresponding third data stream name, number of horizontal pixels, number of vertical pixels, frame rate, bit depth, compression rate, and the priority of the virtual local area network where the video data is located; according to the third modeling parameter, determining the sub-network data model corresponding to the target data includes the following steps:

[0093] S401: Determine the second burst period of the video data, the second number of network frames sent in each second burst period, and the second length of each network frame according to the number of horizontal pixels, number of vertical pixels, frame rate, bit depth, and compression rate.

[0094] S402: Determine the priority information of the virtual local area network corresponding to the video data according to the priority of the virtual local area network where the video data is located.

[0095] S403: Determine the sub-network data model corresponding to the video data according to the second burst period, the second quantity, the second length, and the priority information of the virtual local area network corresponding to the video data.

[0096] Specifically, when the second type of data is video data, the third modeling parameters include the corresponding third data stream name, the number of horizontal pixels, the number of vertical pixels, the frame rate, the bit depth, the compression rate, and the priority of the virtual local area network where the video data is located. And in the process of constructing the sub-network data model, first, according to the number of horizontal pixels, the number of vertical pixels, the frame rate, the bit depth, and the compression rate, determine the second burst period of the video data, the second quantity of network frames sent in each second burst period, and the second length of each network frame. Then, determine the priority information of the virtual local area network corresponding to the video data according to the priority of the virtual local area network where the video data is located. Finally, according to the second burst period, the second quantity, the second length, and the priority information of the virtual local area network corresponding to the video data, complete the establishment of the sub-network data model corresponding to the video data.

[0097] In an implementation manner of the present application, as Figure 7 shown, when the second type of data is network topology data, the third modeling parameters include the electrical control unit (ECU) node information, the switch / gateway information, and the connection relationship between the electrical control unit node and the switch / gateway. According to the third modeling parameters, determining the sub-network data model corresponding to the target data includes the following steps:

[0098] S401': Determine the network topology according to the electrical control unit node information, the switch / gateway information, and the connection relationship between the electrical control unit node and the switch / gateway.

[0099] S402': Determine the sub-network data model corresponding to the network topology data according to the network topology.

[0100] Specifically, when the second type of data is network topology data, the third modeling parameters include the electrical control unit node information, the switch / gateway information, and the connection relationship between the electrical control unit node and the switch / gateway. And in the process of constructing the sub-network data model, first, according to the electrical control unit node information, the switch / gateway information, and the connection relationship between the electrical control unit node and the switch / gateway, determine the network topology. Then, according to the network topology, complete the establishment of the sub-network data model corresponding to the network topology data.

[0101] In the above-mentioned optional methods for establishing sub-network data models of multiple types, the target data is divided into first-type data and second-type data. For the first-type data and the second-type data, sub-network data models corresponding to the target data are established according to different modeling parameters. In this way, according to the differences in the target data, sub-network data models corresponding to different target data are established, which improves the accuracy and comprehensiveness of constructing the sub-network data models corresponding to the target data.

[0102] It should be noted that the above construction of the sub-network data model in this application is only an illustrative example for a part of the data corresponding to the network, such as SOME / IP data, HTTP data, Audio data, Video data, and network topology data, etc. In actual network communication requirements, the data categories corresponding to the network communication requirement information are far more than these, and no further description will be given here one by one.

[0103] In one implementation manner of this application, as Figure 8 shown, when multiple requirement categories are obtained and multiple sub-network data models are determined, according to the sub-network data models, determining the target network data model corresponding to the network communication requirement includes the following steps:

[0104] S510: Obtain the node information of both sides of the data flow interaction corresponding to each sub-network data model;

[0105] S520: Determine the network topology structure corresponding to each sub-network data model according to the node information;

[0106] S530: Determine the transmission path information of the data flow corresponding to each sub-network data model in the network topology according to the network topology structure and the breadth-first algorithm;

[0107] S540: Determine the target network data model corresponding to the network communication requirement according to each sub-network data model, the network topology structure corresponding to each sub-network data model, and the transmission path information corresponding to each sub-network data model.

[0108] When multiple requirement categories are obtained and multiple sub-network data models are determined, first obtain the node information of both sides of the data flow interaction corresponding to each sub-network data model, determine the network topology structure corresponding to each sub-network data model according to the node information, then determine the transmission path information of the data flow corresponding to each sub-network data model in the network topology according to the network topology structure and the breadth-first algorithm, and finally merge each sub-network data model, the transmission path information corresponding to each sub-network data model, and the network topology structure corresponding to each sub-network data model to obtain the target network data model corresponding to the network communication requirement.

[0109] In one implementation of the present application, for the network data model generation method described above, the target network data model is stored in a first format.

[0110] Optionally, after obtaining the target network data model corresponding to the network communication requirements, the target network data model corresponding to the network communication requirements is saved in a corresponding file in a specific format.

[0111] In one implementation of the present application, taking the corresponding network as in-vehicle Ethernet as an example, the network data model generation method provided by the present application is described. As Figure 9 shown, the method includes the following steps:

[0112] S01: Import in-vehicle Ethernet communication requirement information (as an example of network communication requirement information).

[0113] S02: Identify the in-vehicle Ethernet communication requirement information to determine the requirement category.

[0114] S03: According to the requirement category, extract the modeling parameters of SOME / IP data, HTTP data, Audio data, Video data, and network topology data (as an example of target data) in the communication requirement information.

[0115] S04: According to the extracted modeling parameters, complete the automated construction of SOME / IP data model, HTTP data model, Audio data model, Video data model, and network topology data model (as an example of sub-network data model).

[0116] S05: Integrate various simulation data models to obtain an in-vehicle Ethernet communication simulation data model (as an example of the target data network model) and export it.

[0117] The network data model generation method provided by the present application is applied to the field of in-vehicle Ethernet communication, and can also be called an automated construction method for in-vehicle Ethernet simulation data model. It can realize automatic inspection of the compliance of Ethernet communication requirement content, automatic identification and classification of requirements, and automatic construction and export of in-vehicle Ethernet communication simulation data model, which can greatly improve the simulation efficiency and save a large amount of manpower and time costs.

[0118] The network data model generation method provided by the present application can effectively shorten the construction cycle of the simulation data model and effectively improve the construction efficiency of the network data model.

[0119] Please refer to Figure 10 , Figure 10The following shows a network data model generation device provided by an implementation manner of the present application, including: a first processing module, configured to determine network communication requirement information; a second processing module, configured to perform information recognition processing on the network communication requirement information to determine a requirement category corresponding to the network communication requirement information; a third processing module, configured to determine modeling parameters of target data corresponding to the requirement category in the network communication requirement information according to the requirement category; a fourth processing module, configured to determine a sub-network data model corresponding to the target data according to the modeling parameters; and a fifth processing module, configured to determine a target network data model corresponding to the network communication requirement according to the sub-network data model.

[0120] For the specific operation content that each processing module can perform, refer to the above Figure 1 corresponding network data model generation method. Moreover, according to the specific operation steps of the above network data model generation method, the network data model generation device may include more or fewer processing modules for processing the content in the above network data model generation method.

[0121] Please refer to Figure 11 , Figure 11 The following shows a structural block diagram of an electronic device provided by an implementation manner of the present application. The electronic device may include one or more processors 1002, a system control logic 1008 connected to at least one of the processors 1002, a system memory 1004 connected to the system control logic 1008, a non-volatile memory (NVM) 1006 connected to the system control logic 1008, and a network interface 1010 connected to the system control logic 1008.

[0122] The processor 1002 may include one or more single-core or multi-core processors. The processor 1002 may include any combination of a general-purpose processor and a dedicated processor (e.g., a graphics processor, an application processor, a baseband processor, etc.). In the implementation manner herein, the processor 1002 may be configured to execute the foregoing network data model generation method.

[0123] In some implementation manners, the system control logic 1008 may include any suitable interface controller to provide any suitable interface to at least one of the processors 1002 and / or any suitable device or component communicating with the system control logic 1008.

[0124] In some implementations, the system control logic 1008 may include one or more memory controllers to provide an interface to the system memory 1004. The system memory 1004 may be used to load and store data and / or instructions. In some implementations, the system memory 1004 of the electronic device may include any suitable volatile memory, such as a suitable Dynamic Random Access Memory (DRAM).

[0125] The NVM / memory 1006 may include one or more tangible, non-transitory computer-readable media for storing data and / or instructions. In some implementations, the NVM / memory 1006 may include any suitable non-volatile memory such as flash memory and / or any suitable non-volatile storage device, such as at least one of a Hard Disk Drive (HDD), a Compact Disc (CD) drive, and a Digital Versatile Disc (DVD) drive.

[0126] The NVM / memory 1006 may include a portion of the storage resources installed on the device of the electronic device, or it may be accessible by the device but not necessarily part of the device. For example, the NVM / memory 1006 may be accessed via the network interface 1010 over a network.

[0127] Specifically, the system memory 1004 and the NVM / memory 1006 may respectively include: a temporary copy and a permanent copy of the instructions 1020. The instructions 1020 may include: instructions that, when executed by at least one of the processors 1002, cause the electronic device to implement the foregoing network data model generation method. In some implementations, the instructions 1020, hardware, firmware, and / or its software components may alternatively be disposed in the system control logic 1008, the network interface 1010, and / or the processor 1002.

[0128] The network interface 1010 may include a transceiver for providing a radio interface for the electronic device to communicate with any other suitable device (such as a front-end module, an antenna, etc.) over one or more networks. In some implementations, the network interface 1010 may be integrated with other components of the electronic device. For example, the network interface 1010 may be integrated with at least one of the processor 1002, the system memory 1004, the NVM / memory 1006, and a firmware device (not shown) having instructions, and when at least one of the processors 1002 executes the instructions, the electronic device implements the foregoing network data model generation method.

[0129] The network interface 1010 may further include any suitable hardware and / or firmware to provide a multiple-input multiple-output radio interface. For example, the network interface 1010 may be a network adapter, a wireless network adapter, a telephone modem, and / or a wireless modem.

[0130] In one implementation, at least one of the processors 1002 may be packaged with the logic of one or more controllers for the system control logic 1008 to form a System In a Package (SiP). In one implementation, at least one of the processors 1002 may be integrated with the logic of one or more controllers for the system control logic 1008 on the same die to form a System on Chip (SoC).

[0131] The electronic device may further include: an input / output (I / O) device 1012. The I / O device 1012 may include a user interface that enables a user to interact with the electronic device; the design of the peripheral component interface enables peripheral components to also interact with the electronic device. In some implementations, the electronic device further includes sensors for determining at least one of environmental conditions and location information related to the electronic device.

[0132] In some implementations, the user interface may include, but is not limited to, a display (e.g., a liquid crystal display, a touch screen display, etc.), a speaker, a microphone, one or more cameras (e.g., a still image camera and / or a video camera), a flashlight (e.g., a light-emitting diode flash), and a keyboard.

[0133] In some implementations, the peripheral component interface may include, but is not limited to, a non-volatile memory port, an audio jack, and a power interface.

[0134] In some implementations, the sensors may include, but are not limited to, a gyroscope sensor, an accelerometer, a proximity sensor, an ambient light sensor, and a positioning unit. The positioning unit may also be part of the network interface 1010 or interact with the network interface 1010 to communicate with components of a positioning network (e.g., Global Positioning System (GPS) satellites).

[0135] It can be understood that the structure illustrated in the implementation of the present invention does not constitute a specific limitation on the electronic device. In other implementations of the present application, the electronic device may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0136] Program code can be applied to input instructions to perform the various functions described herein and generate output information. The output information can be applied to one or more output devices in a known manner. For purposes of the implementations of this application, a processing system includes any system having a processor such as, for example, a Digital Signal Processor (DSP), a microcontroller, an Application Specific Integrated Circuit (ASIC), or a microprocessor.

[0137] The program code can be implemented in a high-level procedural or object-oriented programming language so as to communicate with the processing system. When needed, the program code can also be implemented in assembly language or machine language. In fact, the mechanisms described herein are not limited to the scope of any particular programming language. In any case, the language can be a compiled language or an interpreted language.

[0138] One or more aspects of at least one implementation can be realized by representative instructions stored on a computer-readable storage medium, the instructions representing various logic in a processor, the instructions causing the machine, when read by the machine, to fabricate the logic for performing the techniques described herein. These representations, referred to as “IP cores,” can be stored on a tangible computer-readable storage medium and provided to multiple customers or production facilities to be loaded into a manufacturing machine that actually fabricates the logic or processor.

[0139] It should be noted that in the drawings, some structural or method features may be shown in a particular arrangement and / or order. However, it should be understood that such a particular arrangement and / or ordering may not be required. Rather, in some implementations, these features may be arranged in a manner and / or order different from that shown in the illustrative drawings. Additionally, the inclusion of a structural or method feature in a particular figure does not imply that such a feature is required in all implementations, and in some implementations, these features may not be included or may be combined with other features.

[0140] It should be noted that the terms “first,” “second,” etc. are used only for descriptive distinction and should not be construed as indicating or implying relative importance.

[0141] It should be noted that in the drawings, some structural or method features may be shown in a particular arrangement and / or order. However, it should be understood that such a particular arrangement and / or ordering may not be required. Rather, in some embodiments, these features may be arranged in a manner and / or order different from that shown in the illustrative drawings. Additionally, the inclusion of a structural or method feature in a particular figure does not imply that such a feature is required in all embodiments, and in some embodiments, these features may not be included or may be combined with other features.

[0142] Although the present application has been illustrated and described by reference to certain preferred embodiments thereof, those of ordinary skill in the art should understand that the above is a further detailed description of the present application in conjunction with specific embodiments, and it cannot be determined that the specific implementation of the present application is limited only to these descriptions. Those skilled in the art can make various changes in form and detail, including making several simple deductions or substitutions, without departing from the spirit and scope of the present application.

Claims

1. A method for generating a network data model, characterized in that, applied to an electronic device, the method includes: Determine network communication requirement information; Perform information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information; According to the requirement category, determine the modeling parameters of the target data corresponding to the network communication requirement information; According to the modeling parameters, determine the sub-network data model corresponding to the target data; According to the sub-network data model, determine the target network data model corresponding to the network communication requirement.

2. The network data model generation method according to claim 1, characterized in that, Performing information recognition processing on the network communication requirement information to determine the requirement category corresponding to the network communication requirement information includes: Performing information recognition processing on the network communication requirement information to determine the keyword information corresponding to the network communication requirement information; Determine the requirement category corresponding to the network communication requirement information according to the keyword information.

3. The network data model generation method according to claim 2, characterized in that, Performing information recognition processing on the network communication requirement information includes: Extract the keyword fields of the network communication requirement information, perform legality check processing on the keyword fields, and determine the first check result; In the case where the first check result meets the corresponding legality requirements, perform information recognition processing on the network communication requirement information; or Perform regular verification processing on the network communication requirement information to determine the first verification result; In the case where the first verification result meets the corresponding legality requirements, perform information recognition processing on the network communication requirement information.

4. The network data model generation method according to any one of claims 1-3, characterized in that, In the case of obtaining multiple said requirement categories and determining multiple said sub-network data models, according to the sub-network data models, determining the target network data model corresponding to the network communication requirement includes: Obtain the node information of both sides of the data stream interaction corresponding to each sub-network data model; Determine the network topology structure corresponding to each sub-network data model according to the node information; According to the network topology structure and the breadth-first algorithm, determine the transmission path information of the data stream corresponding to each sub-network data model in the network topology; According to each sub-network data model, the network topology structure corresponding to each sub-network data model, and the transmission path information corresponding to each sub-network data model, determine the target network data model corresponding to the network communication requirement.

5. The network data model generation method according to any one of claims 1-4, characterized in that, In the case where the target data is the first type of data, the modeling parameters include the first modeling parameter and the second modeling parameter. According to the modeling parameters, determining the sub-network data model corresponding to the target data includes: Determine the sub-network data model corresponding to the target data according to the first modeling parameter and the second modeling parameter; When the target data is of the second type, the modeling parameters include third modeling parameters. Determining the sub-network data model corresponding to the target data according to the modeling parameters includes: Determining the sub-network data model corresponding to the target data according to the third modeling parameters.

6. The method for generating a network data model according to claim 5, wherein, When the first type of data is IP-based extensible service-oriented middleware data, the first modeling parameters include the corresponding service name, service interface name, service interface type, service interface data length, service interface data sending mode, service publisher, service subscriber, and transport layer protocol type, and the second modeling parameters include the priority of the virtual local area network where the service interface data is located; Determining the sub-network data model corresponding to the target data according to the first modeling parameters and the second modeling parameters includes: Generating service instance information and the publication and subscription relationship of the service according to the service name, the service interface name, the service interface type, the service interface data length, the service interface data sending mode, the service publisher, the service subscriber, and the transport layer protocol type; Generating a first network data frame according to the priority of the virtual local area network where the service interface data is located, and the sender and receiver information of the service data; Determining the sub-network data model corresponding to the IP-based extensible service-oriented middleware data according to the service instance information, the publication and subscription relationship of the service, and the first network data frame.

7. The method for generating a network data model according to claim 5 or 6, wherein, When the first type of data is hypertext transfer protocol data, the first modeling parameters include the corresponding first data stream name, data length, data sender, data receiver, and protocol stack related parameters of the data corresponding transport control protocol, and the second modeling parameters include the first data stream name, the data sender, the data receiver, and the priority of the virtual local area network where the hypertext transfer protocol data is located; Determining the sub-network data model corresponding to the target data according to the first modeling parameters and the second modeling parameters includes: Generating a communication mode for the hypertext transfer protocol based on the transport control protocol according to the first data stream name, the data length, the data sender, the data receiver, and the protocol stack related parameters of the data corresponding transport control protocol; Generating a second network data frame according to the first data stream name, the data sender, the data receiver, and the priority of the virtual local area network where the hypertext transfer protocol data is located; Determining the sub-network data model corresponding to the hypertext transfer protocol data according to the communication mode and the second network data frame.

8. The method for generating a network data model according to any one of claims 5-7, wherein, In the case where the second type of data is audio data, the third modeling parameter includes the corresponding second data stream name, sampling rate, bit depth, number of channels, and priority of the virtual local area network where the audio data is located; Determining the sub-network data model corresponding to the target data according to the third modeling parameter includes: Determining a first burst period of the audio data, a first number of network frames sent in each of the first burst periods, and a first length of each of the network frames according to the sampling rate, the bit depth, and the number of channels; Determining priority information of the virtual local area network corresponding to the audio data according to the priority of the virtual local area network where the audio data is located; Determining the sub-network data model corresponding to the audio data according to the first burst period, the first number, the first length, and the priority information of the virtual local area network corresponding to the audio data.

9. The method for generating a network data model according to any one of claims 5-8, characterized in that, In the case where the second type of data is video data, the third modeling parameter includes the corresponding third data stream name, number of horizontal pixel points, number of vertical pixel points, frame rate, bit depth, compression rate, and priority of the virtual local area network where the video data is located; Determining the sub-network data model corresponding to the target data according to the third modeling parameter includes: Determining a second burst period of the video data, a second number of network frames sent in each of the second burst periods, and a second length of each of the network frames according to the number of horizontal pixel points, the number of vertical pixel points, the frame rate, the bit depth, and the compression rate; Determining priority information of the virtual local area network corresponding to the video data according to the priority of the virtual local area network where the video data is located; Determining the sub-network data model corresponding to the video data according to the second burst period, the second number, the second length, and the priority information of the virtual local area network corresponding to the video data.

10. The method for generating a network data model according to any one of claims 5-9, characterized in that, In the case where the second type of data is network topology data, the third modeling parameter includes electronic control unit node information, control information, and connection relationship between the electronic control unit node and the control; Determining the sub-network data model corresponding to the target data according to the third modeling parameter includes: Determining a network topology structure according to the electronic control unit node information, the control information, and the connection relationship between the electronic control unit node and the control; Determining the sub-network data model corresponding to the network topology data according to the network topology structure.

11. The method for generating a network data model according to any one of claims 1-10, characterized in that, Determining network communication requirement information includes: Obtaining a plurality of initial network communication requirement information, and each of the initial network communication requirement information is from different network communication requirement providers; Performing screening and integration processing on the initial network communication requirement information to obtain the network communication requirement information.

12. The method for generating a network data model according to any one of claims 1-11, characterized in that, The method further includes: Storing the target network data model in a first format.

13. An electronic device characterized in that it includes a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, so that the electronic device implements the network data model generation method according to any one of claims 1-12.

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