A 5G core network API-based instruction processing method and related device

Abstract

The application discloses a 5G core network API-based instruction processing method and related equipment, which can be applied to the technical field of 5G networks. After all configuration instructions encapsulated in the API of the 5G core network are acquired, an instruction association graph is constructed according to all the configuration instructions, and all the configuration instructions are clustered to obtain a plurality of first instruction sets. When an abnormal instruction in a current service opening process is acquired, a first instruction set to which the abnormal instruction belongs is determined as a second instruction set from all the first instruction sets, a rollback range of the abnormal instruction is determined according to the positional relationship of the abnormal instruction in the second instruction set, and a rollback operation is performed on the abnormal instruction according to the rollback range, so that the rollback time can be effectively reduced, the service opening configuration time is further reduced, and the service opening configuration efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of 5G network technology, and in particular to an instruction processing method and related equipment based on 5G core network API. Background Technology

[0002] In related technologies, the 5GC core network controller provides open API capabilities for orchestration systems to call. By calling these APIs, commands are issued to network elements to activate services. Typically, an API encapsulates multiple configuration commands. If a configuration command fails to be issued during the command issuance process, exception handling is required. Specifically, a rollback operation is performed on successfully issued commands to undo the previously successfully executed parts, restoring network devices and user data to their stable state before activation, thereby avoiding "partial activation" or "data inconsistency" faults. However, since successfully issued commands can include countless items, the existing rollback method requires a considerable amount of time, increasing service activation configuration time and reducing service activation efficiency.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] The main objective of this application is to propose an instruction processing method and related equipment based on the 5G core network API, which can effectively reduce rollback time, thereby reducing service activation and configuration time and improving service activation and configuration efficiency.

[0005] To achieve the above objectives, one aspect of this application proposes an instruction processing method based on a 5G core network API, the method comprising the following steps: Retrieve all configuration commands encapsulated in the 5G core network API; Construct an instruction association graph based on all the aforementioned configuration instructions; Cluster all the configuration instructions to obtain several first instruction sets; Retrieve any abnormal commands during the current service activation process; The first instruction set to which the abnormal instruction belongs is determined from all the first instruction sets and designated as the second instruction set; The rollback range of the abnormal instruction is determined based on its positional relationship within the second instruction set. The abnormal instruction is rolled back according to the rollback range.

[0006] In some embodiments, constructing the instruction association graph based on all the configuration instructions includes: Analyze the dependencies between all the configuration directives described; The instruction association graph is constructed based on the dependencies.

[0007] In some embodiments, after obtaining the instruction association graph, the method further includes the following steps: Calculate the overall correlation factor among all the configuration instructions.

[0008] In some embodiments, calculating the comprehensive correlation factor among all the configuration instructions includes: The first association factor is determined based on the dependencies between the configuration instructions; The second association factor is determined based on the temporal order of the configuration instructions; A third correlation factor is determined based on the resource utilization relationship between the configuration instructions; A fourth association factor is determined based on the semantic similarity between the configuration instructions; Based on the current business scenario information, the first correlation factor, the second correlation factor, the third correlation factor, and the fourth correlation factor are weighted and calculated to obtain the comprehensive correlation factor.

[0009] In some embodiments, clustering all the configuration instructions to obtain several first instruction sets includes: Based on the configuration function of the configuration instructions, all the configuration instructions in the instruction association diagram are clustered to obtain several first instruction sets.

[0010] In some embodiments, determining the first instruction set to which the abnormal instruction belongs among all the first instruction sets as the second instruction set includes: Calculate the matching degree between the abnormal instruction and all configuration instructions in all the first instruction sets; The second instruction set is determined from all the first instruction sets based on the matching degree.

[0011] In some embodiments, determining the rollback range of the abnormal instruction based on its positional relationship within the second instruction set includes: The configuration instruction corresponding to the abnormal instruction is determined from the second instruction set as the instruction to be processed. When the positional relationship of the instruction to be processed in the second instruction set is independent, the second instruction set is determined as the rollback range of the abnormal instruction; When the positional relationship of the instruction to be processed in the second instruction set is not independent, the comprehensive correlation factor between the instruction to be processed and the configuration instructions in the remaining first instruction set is obtained as the correlation factor to be processed; based on the correlation factor to be processed, a third instruction set associated with the instruction to be processed is determined from the remaining first instruction set; the second instruction set and the third instruction set are used as the rollback range of the abnormal instruction.

[0012] To achieve the above objectives, another aspect of this application proposes an instruction processing apparatus based on a 5G core network API, the apparatus comprising: The first module is used to obtain all configuration instructions encapsulated in the API of the 5G core network; The second module is used to construct an instruction association graph based on all the configuration instructions; The third module is used to cluster all the configuration instructions to obtain several first instruction sets; The fourth module is used to obtain abnormal instructions during the current service activation process; The fifth module is used to determine, among all the first instruction sets, the first instruction set to which the abnormal instruction belongs as the second instruction set; The sixth module is used to determine the rollback range of the abnormal instruction based on its positional relationship within the second instruction set. The seventh module is used to perform a rollback operation on the abnormal instruction according to the rollback range.

[0013] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides an instruction processing method and related equipment based on the 5G core network API. This solution obtains all configuration instructions encapsulated in the 5G core network API, constructs an instruction association graph based on all configuration instructions, and clusters all configuration instructions to obtain several first instruction sets. Then, when an abnormal instruction is obtained in the current service activation process, the first instruction set to which the abnormal instruction belongs is determined as a second instruction set from all the first instruction sets. The rollback range of the abnormal instruction is determined according to the positional relationship of the abnormal instruction in the second instruction set, and the abnormal instruction is rolled back according to the rollback range. This can effectively reduce the rollback time, thereby reducing the service activation configuration time and improving the service activation configuration efficiency. Attached Figure Description

[0017] Figure 1 This is a flowchart of an instruction processing method based on a 5G core network API provided in an embodiment of this application; Figure 2 This is a flowchart illustrating the construction of an instruction association graph based on all configuration instructions, provided in an embodiment of this application. Figure 3 This is a flowchart illustrating the calculation of the comprehensive correlation factor among all configuration instructions, provided in an embodiment of this application. Figure 4 This is a flowchart provided in an embodiment of the present application for determining the rollback range of an abnormal instruction based on its positional relationship in the second instruction set; Figure 5 This is a schematic diagram of the configuration instructions provided in the embodiments of this application; Figure 6 This is a schematic diagram of the instruction association diagram and clustering results provided in the embodiments of this application; Figure 7 This is a schematic diagram of the structure of an instruction processing device based on a 5G core network API provided in an embodiment of this application; Figure 8 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0020] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] Before providing a detailed description of the embodiments of this application, some of the nouns and terms used in the embodiments of this application will be explained first. The nouns and terms used in the embodiments of this application shall be interpreted as follows: The 5GC (5G Core Network) is the core of a 5G mobile network. The 5GC establishes reliable and secure network connections for end users and provides access to their services. The core domain handles various essential functions in the mobile network, such as connectivity and mobility management, authentication and authorization, user data management, and policy management. The 5G core network functions are entirely software-based and designed to be cloud-native, meaning they are independent of the underlying cloud infrastructure, enabling greater deployment agility and flexibility.

[0023] An API (Application Programming Interface) is a set of definitions, programs, and protocols that enable communication between computer software.

[0024] An instruction is a command that instructs a computer to perform a certain operation. This application specifically refers to network element instructions, which complete network element configuration and service activation by issuing relevant instructions to the network element.

[0025] The orchestration system can call multiple APIs based on the 5G core network controller to send service configuration instructions to network elements and complete the service activation.

[0026] VLAN is a technology that logically divides a physical local area network (LAN) into multiple independent broadcast domains. Even if devices are connected to the same switch, they cannot communicate directly after being divided by VLANs, unless they are connected through a router or a Layer 3 switch.

[0027] An IP address is a unique logical identifier assigned to each device in a network, used to locate devices at the network layer and to route and forward data packets. The difference between an IP address and a VLAN is that VLANs operate at the data link layer (Layer 2), while IP addresses operate at the network layer (Layer 3). Typically, one VLAN corresponds to one independent IP subnet, and cross-VLAN communication must be routed via IP through a Layer 3 device (such as a router or Layer 3 switch).

[0028] DNN is a key concept in the 5G core network (5GC) used to identify a specific data network (such as the Internet, enterprise private networks, or IMS multimedia networks). It is similar to APN (Access Point Name) in 4G, but with more flexible functionality.

[0029] In related technologies, the 5GC core network controller provides open API capabilities for orchestration systems to call. By calling these APIs, commands are issued to network elements to activate services. Typically, an API encapsulates multiple configuration commands. If a configuration command fails to be issued during the command issuance process, exception handling is required. Specifically, a rollback operation is performed on successfully issued commands to undo the previously successfully executed parts, restoring network devices and user data to their stable state before activation, thereby avoiding "partial activation" or "data inconsistency" faults. However, since successfully issued commands can include countless items, the existing rollback method requires a considerable amount of time, increasing service activation configuration time and reducing service activation efficiency.

[0030] In view of this, this application provides an instruction processing method and related equipment based on 5G core network API, which can effectively reduce rollback time, thereby reducing service activation and configuration time and improving service activation and configuration efficiency.

[0031] This application provides an instruction processing method based on a 5G core network API, relating to the field of 5G network technology. This instruction processing method based on a 5G core network API can be applied to a terminal, a server, or software running on a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited thereto; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application implementing an instruction processing method based on a 5G core network API, but is not limited to the above forms.

[0032] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0033] The embodiments of this application will be described in detail below with reference to the accompanying drawings: Figure 1 This is an optional flowchart of an instruction processing method based on a 5G core network API provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S110 to S170: Step S110: Obtain all configuration instructions encapsulated in the API of the 5G core network; Step S120: Construct an instruction association diagram based on all configuration instructions; Step S130: Cluster all configuration instructions to obtain several sets of first instructions; Step S140: Obtain abnormal instructions during the current service activation process; Step S150: Determine the first instruction set to which the abnormal instruction belongs from all the first instruction sets as the second instruction set; Step S160: Determine the rollback range of the abnormal instructions based on their positional relationship in the second instruction set; Step S170: Roll back the abnormal command according to the rollback range.

[0034] It is understood that this embodiment can provide an interactive module so that users can interact with the business system through the interactive module and can input configuration commands encapsulated in API and product manuals from equipment manufacturers in the interactive module.

[0035] It is understandable that this embodiment constructs an instruction association graph of all configuration instructions after obtaining all configuration instructions from the API. For example... Figure 2 As shown, the construction process of the instruction association graph in this embodiment includes, but is not limited to, the following steps: Step S210: Analyze the dependencies between all configuration instructions; Step S220: Construct an instruction association graph based on the dependency relationship.

[0036] Specifically, to facilitate the identification of all configuration instructions, this embodiment can number the configuration instruction steps sequentially. For example, all configuration instruction steps are numbered starting from 1 and increasing sequentially. For instance, the numbers 1, 2, 3, ..., n correspond to the first configuration instruction, the second configuration instruction, the third configuration instruction, ..., the nth configuration instruction, respectively.

[0037] Specifically, after numbering all configuration instructions, this embodiment treats the configuration instructions as entities and determines the directed connections between entities by analyzing the dependencies between them. For example, taking a configuration instruction format of "action + object + parameter", when configuration instruction 1 is an object and this object is referenced as a parameter by configuration instruction 2, the dependency between configuration instruction 1 and configuration instruction 2 is clear: the execution of configuration instruction 2 depends on configuration instruction 1. Therefore, the directed connection between configuration instruction 1 and configuration instruction 2 in the instruction association graph is: configuration instruction 1 → configuration instruction 2. This embodiment, by analyzing the dependencies between all configuration instructions, can determine the directed connections between all configuration instructions, thereby obtaining the instruction association graph.

[0038] It is understandable that, after obtaining the instruction association graph, this embodiment will also calculate the comprehensive association factor among all configuration instructions. For example... Figure 3As shown, the process of calculating the comprehensive correlation factor among all configuration instructions in this embodiment includes, but is not limited to, the following steps: Step S310: Determine the first association factor based on the dependencies between configuration instructions; Step S320: Determine the second association factor according to the timing sequence of the configuration instructions; Step S330: Determine the third association factor based on the resource utilization relationship between configuration instructions; Step S340: Determine the fourth association factor based on the semantic similarity between root configuration instructions; Step S350: Based on the current business scenario information, perform weighted calculations on the first correlation factor, the second correlation factor, the third correlation factor, and the fourth correlation factor to obtain the comprehensive correlation factor.

[0039] The calculation process for the first correlation factor is as follows: when the output parameter of one configuration instruction is the input parameter of another configuration instruction, there is a strong correlation between the two configuration instructions. For any configuration instruction x and configuration instruction y, the corresponding first correlation factor L1_{xy} = (the number of dependencies between the output parameter of configuration instruction x and the input parameter of configuration instruction y) / (the union of all parameters in configuration instruction x and all parameters in configuration instruction y).

[0040] The calculation process for the second correlation factor is as follows: If two configuration instructions appear in a fixed order in the historical execution log, then these two configuration instructions are strongly correlated. For any configuration instruction x and configuration instruction y, the number of times they appear in the same service activation process is N_{xy}, and the number of times configuration instruction x is executed before configuration instruction y is N_{x\rightarrow y}. The corresponding second correlation factor L2_{xy} = N_{x\rightarrow y} / N_{xy}.

[0041] For the third association factor: if any two configuration instructions operate on the same resource (e.g., the same port, the same user data) and cannot be executed concurrently, then the third association factor L3_{xy} can be assigned a value of 1; otherwise, the third association factor L3_{xy} can be assigned a value of 0.

[0042] For the fourth association factor: In this embodiment, natural language processing or domain knowledge graph analysis can be used to analyze the semantic similarity between configuration instructions as the fourth association factor L4_{xy}.

[0043] In this embodiment, after obtaining the first, second, third, and fourth correlation factors, the weight coefficients (w1, w2, w3, and w4) of each correlation factor can be set based on the current business scenario information. For example, if the business scenario information determines that the current business is sensitive to time series, the weight coefficient w2 corresponding to the second correlation factor can be set to its maximum value. Where w1 + w2 + w3 + w4 = 1. Specifically, after setting the values ​​of all weight coefficients, the comprehensive correlation factor L in this embodiment is w1. L1_{xy}+ w2 L2_{xy}+ w3 L3_{xy}+ w4 L4_{xy}. This embodiment calculates a comprehensive correlation factor between any two configuration instructions, thereby characterizing the correlation strength between the two instructions. If L=0, it indicates that the two configuration instructions are completely independent.

[0044] It is understood that, after obtaining the instruction association diagram, this embodiment further clusters all configuration instructions in the diagram according to their configuration functions to obtain several first instruction sets. For example, if the configuration functions of configuration instructions 1, 2, and 3 are all used to isolate business systems, then configuration instructions 1, 2, and 3 are grouped into the same instruction set; if the configuration functions of configuration instructions 4, 5, 6, and 7 are all used for addressing, then configuration instructions 4, 5, 6, and 7 are grouped into the same instruction set. This embodiment, by grouping all configuration instructions, provides a selectable range for subsequent rollback operations.

[0045] Understandably, upon obtaining an abnormal instruction during the current service activation process, the second instruction set can be determined from all first instruction sets by calculating the matching degree between the abnormal instruction and all configuration instructions in all first instruction sets. For example, if the matching degree between the abnormal instruction and configuration instruction 1 in first instruction set A is 99%, and the matching degree between the abnormal instruction and configuration instruction 2 in first instruction set B is 20%, then the abnormal instruction can be determined to be a configuration instruction in first instruction set A. Therefore, first instruction set A is taken as the second instruction set to which the abnormal instruction belongs.

[0046] It is understood that, after determining the second instruction set to which the abnormal instruction belongs, this embodiment can determine the rollback range of the abnormal instruction based on its positional relationship within the second instruction set. Specifically, as shown... Figure 4 As shown, the process of determining the rollback range includes, but is not limited to, the following steps: Step S410: Determine the configuration instruction corresponding to the abnormal instruction from the second instruction set as the instruction to be processed; Step S420: Determine the positional relationship of the instruction to be processed in the second instruction set. If it is an independent position, proceed to step S430; if it is a non-independent position, proceed to steps S440 to S460. Step S430: Determine the rollback range of the second instruction set as abnormal instructions; Step S440: Obtain the comprehensive correlation factor between the instruction to be processed and the configuration instructions in the remaining first instruction set as the correlation factor to be processed; Step S450: Determine the third instruction set associated with the instruction to be processed from the remaining first instruction set based on the association factor to be processed; Step S460: Use the second instruction set and the third instruction set as the rollback range for abnormal instructions.

[0047] Specifically, if the position of the instruction to be processed in the second instruction set is independent, it indicates that the instruction to be processed is not related to the configuration instructions in the remaining first instruction set. Therefore, only the configuration instructions in the second instruction set need to be rolled back, and the second instruction set is taken as the rollback scope for the abnormal instruction. If the position of the instruction to be processed in the second instruction set is not independent, it indicates that the instruction to be processed is related to some configuration instructions in the remaining first instruction set. Therefore, the third instruction set associated with the instruction to be processed can be determined from all the remaining first instruction sets based on the comprehensive association factor corresponding to the instruction to be processed, and the second and third instruction sets are taken as the rollback scope for the abnormal instruction.

[0048] Specifically, if multiple sets of third instructions are obtained through filtering, this embodiment can set a factor threshold Lo to further filter the sets of third instructions. For example, when the factor threshold Lo = 0.5, only when the comprehensive correlation factor corresponding to the instruction to be processed is greater than 0.5 will the corresponding third instruction set be retained. The retained sets of third instructions and second instructions will be used as the rollback range for abnormal instructions, thereby further narrowing the scope of the rollback operation and improving the efficiency of the rollback operation.

[0049] It is understandable that, after determining the rollback range, this embodiment performs rollback operations on abnormal instructions within the rollback range to automatically undo the previously successfully executed instructions, restore the network device and user data to the stable state before activation, thereby avoiding "partial activation" or "data inconsistency" failures.

[0050] by Figure 5 Taking the script diagram of the configuration instructions shown as an example, the complete implementation process of the method in this application embodiment will be described: Step 1: Obtain all configuration instructions in the script corresponding to the configuration instructions; Step 2: Construct the instruction association graph; from Figure 5 It can be seen that the API encapsulates 8 configuration directives, with corresponding directive numbers 1, 2, 3...8; a dependency analysis is performed on these 8 configuration directives: In instruction 1, the DNN entity APNDNN is referenced in the parameters of instruction 2; therefore, instruction 1 -> instruction 2 (instruction 2 depends on instruction 1). The DNN entity APNDNN in instruction 1 and the address pool entity IPPOOLNAME in instruction 3 are referenced in the parameters of instruction 5. Therefore, instruction 1 -> instruction 5 (instruction 5 depends on instruction 1), and instruction 3 -> instruction 5 (instruction 5 depends on instruction 3). The address pool entity IPPOOLNAME in instruction 2 is referenced in the parameters of instruction 3, therefore instruction 3 -> instruction 4 (instruction 4 depends on instruction 3); The filter entity FILTERNAME from instruction 5 is referenced in the parameters of instruction 6, therefore instruction 6 -> instruction 7 (instruction 7 depends on instruction 6); The leave filter entity RULENAME of instruction 8 is referenced in the parameters of instruction 8, therefore instruction 8 -> instruction 9 (instruction 9 depends on instruction 8).

[0051] Based on the dependencies obtained from the above analysis, a corresponding instruction association graph can be constructed.

[0052] Step 3: Calculate the overall correlation factor L among all configuration instructions; Step 4: Cluster all configuration instructions in the instruction association diagram according to their configuration functions to obtain several first instruction sets; like Figure 5 It can be seen that the configuration functions of the configuration commands correspond to service isolation (VLAN), addressing (IP), and session management (DNN) functions, respectively. Therefore, configuration commands 1 and 2, both configuring DNN, can be clustered into one category and labeled as command set 1. Commands 3, 4, and 5, both configuring address pools and address ranges, are all IP-related configurations and can be clustered into one category and labeled as command set 2. Commands 6 and 7, both configuring flow filters, can be clustered into one category and labeled as command set 3. Commands 8 and 9, both configuring rules, can be clustered into one category and labeled as command set 4. After completing the clustering of configuration commands, this embodiment can obtain the following... Figure 6 The relationship between the instruction association diagram and the clustering results is shown.

[0053] Step 5: Obtain any abnormal commands during the current service activation process; Step Six: When an abnormal instruction is independent within a clustered instruction set, it indicates that the abnormal instruction is unrelated to configuration instructions in other clustered instruction sets. Therefore, this clustered instruction set is determined as the rollback scope for the abnormal instruction. For example, in... Figure 6 If the abnormal instruction is configuration instruction 4, then only instruction 3 needs to be rolled back in this instruction set.

[0054] Step 7: When an abnormal instruction is not independent within a clustered instruction set, it indicates that the abnormal instruction is associated with configuration instructions in other clustered instruction sets. This embodiment can define a factor threshold Lo, and the clustered instruction sets corresponding to those with a comprehensive correlation factor L greater than the factor threshold Lo will form the rollback range. For example, using... Figure 6 For example, if the association factor L between aggregation instruction set 1 and aggregation instruction set 2 is 0.9, and the set factor threshold Lo is 0.5, L is greater than Lo. When configuration instruction 5 is abnormal, configuration instruction 5 is in aggregation instruction set 2. Therefore, aggregation instruction set 1 and aggregation instruction set 2 need to be combined to form the rollback range of abnormal instruction 5.

[0055] by Figure 6 For example, based on the positional relationship of the abnormal instructions, this embodiment can dynamically decide to minimize the rollback range of the abnormal instructions: (1) When there is an error in configuration instruction 1, since configuration instruction 1 is the first instruction, there is no need to roll back.

[0056] (2) When configuration instruction 2 is abnormal, the minimum rollback range is configuration instruction 1 in aggregate instruction set 1.

[0057] (3) No rollback is required when there is an exception in configuration instruction 3. (4) When configuration instruction 4 is abnormal, the minimum rollback range is to roll back configuration instruction 3.

[0058] (5) When configuration instruction 5 is abnormal, the minimum rollback range is configuration instruction 1, configuration instruction 2, configuration instruction 3 and configuration instruction 4 in aggregate instruction set 1 and aggregate instruction set 12.

[0059] (6) No rollback is required if there is an exception in configuration instruction 6.

[0060] (7) When configuration instruction 7 is abnormal, the minimum rollback range is configuration instruction 6 in aggregate instruction set 3.

[0061] (8) No rollback is required if there is an exception in configuration instruction 8.

[0062] (9) When configuration instruction 9 is abnormal, the minimum rollback range is the rollback configuration instruction 8 in the aggregate instruction set 4.

[0063] As can be seen from the above, the method of this application embodiment constructs an instruction association graph and uses graph theory to represent the association and sequential relationship between configuration instructions. It clusters multiple instructions and establishes the association and independence between instruction sets. Thus, based on the location of the abnormal instruction, the instruction association relationship, and the instruction set clustering results, it comprehensively decides to minimize the scope of rollback instructions, thereby improving the efficiency of service activation and configuration.

[0064] Please see Figure 7 This application also provides an instruction processing device based on a 5G core network API, the device comprising: The first module is used to obtain all configuration instructions encapsulated in the API of the 5G core network; The second module is used to construct an instruction association graph based on all configuration instructions; The third module is used to cluster all configuration instructions to obtain several sets of first instructions. The fourth module is used to obtain abnormal instructions during the current service activation process; The fifth module is used to determine, among all the first instruction sets, the first instruction set to which the abnormal instruction belongs as the second instruction set; The sixth module is used to determine the rollback range of the abnormal instruction based on its positional relationship within the second instruction set. The seventh module is used to perform rollback operations on abnormal instructions based on the rollback range.

[0065] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0066] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0067] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0068] Please see Figure 8 , Figure 8 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 810 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 820 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 820 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 820 and is called and executed by the processor 810 using the methods described in the embodiments of this application. The input / output interface 830 is used to implement information input and output; The communication interface 840 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 850 transmits information between various components of the device (e.g., processor 810, memory 820, input / output interface 830, and communication interface 840); The processor 810, memory 820, input / output interface 830 and communication interface 840 are connected to each other within the device via bus 850.

[0069] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0070] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0071] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0072] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0073] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0074] This application provides an instruction processing method and related equipment based on a 5G core network API. After acquiring all configuration instructions encapsulated in the 5G core network API, an instruction association graph is constructed based on all configuration instructions, and the instructions are clustered to obtain several first instruction sets. Then, when an abnormal instruction is acquired during the current service activation process, the first instruction set to which the abnormal instruction belongs is determined from all the first instruction sets as a second instruction set. The rollback range of the abnormal instruction is determined based on its positional relationship within the second instruction set, and the abnormal instruction is rolled back according to the rollback range. This effectively reduces rollback time, thereby reducing service activation configuration time and improving service activation configuration efficiency.

[0075] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0076] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0077] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0078] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0079] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0080] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0081] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0082] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0084] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0085] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for instruction processing based on 5G core network API, characterized in that, The method includes the following steps: Retrieve all configuration commands encapsulated in the 5G core network API; Construct an instruction association graph based on all the aforementioned configuration instructions; Cluster all the configuration instructions to obtain several first instruction sets; Retrieve any abnormal commands during the current service activation process; The first instruction set to which the abnormal instruction belongs is determined from all the first instruction sets and designated as the second instruction set; The rollback range of the abnormal instruction is determined based on its positional relationship within the second instruction set. The abnormal instruction is rolled back according to the rollback range.

2. The method according to claim 1, characterized in that, The step of constructing an instruction association graph based on all the configuration instructions includes: Analyze the dependencies between all the configuration directives described; The instruction association graph is constructed based on the dependencies.

3. The method according to claim 2, characterized in that, After obtaining the instruction association graph, the method further includes the following steps: Calculate the overall correlation factor among all the configuration instructions.

4. The method according to claim 3, characterized in that, The calculation of the comprehensive correlation factor among all the configuration instructions includes: The first association factor is determined based on the dependencies between the configuration instructions; The second association factor is determined based on the temporal order of the configuration instructions; A third correlation factor is determined based on the resource utilization relationship between the configuration instructions; A fourth association factor is determined based on the semantic similarity between the configuration instructions; Based on the current business scenario information, the first correlation factor, the second correlation factor, the third correlation factor, and the fourth correlation factor are weighted and calculated to obtain the comprehensive correlation factor.

5. The method according to claim 2, characterized in that, The clustering of all the configuration instructions yields several first instruction sets, including: Based on the configuration function of the configuration instructions, all the configuration instructions in the instruction association diagram are clustered to obtain several first instruction sets.

6. The method according to claim 1, characterized in that, The step of determining the first instruction set to which the abnormal instruction belongs from all the first instruction sets as the second instruction set includes: Calculate the matching degree between the abnormal instruction and all configuration instructions in all the first instruction sets; The second instruction set is determined from all the first instruction sets based on the matching degree.

7. The method according to claim 1, characterized in that, Determining the rollback range of the abnormal instruction based on its positional relationship within the second instruction set includes: The configuration instruction corresponding to the abnormal instruction is determined from the second instruction set as the instruction to be processed. When the positional relationship of the instruction to be processed in the second instruction set is independent, the second instruction set is determined as the rollback range of the abnormal instruction; When the positional relationship of the instruction to be processed in the second instruction set is not independent, the comprehensive correlation factor between the instruction to be processed and the configuration instructions in the remaining first instruction set is obtained as the correlation factor to be processed; based on the correlation factor to be processed, a third instruction set associated with the instruction to be processed is determined from the remaining first instruction set; the second instruction set and the third instruction set are used as the rollback range of the abnormal instruction.

8. An instruction processing device based on a 5G core network API, characterized in that, The device includes: The first module is used to obtain all configuration instructions encapsulated in the API of the 5G core network; The second module is used to construct an instruction association graph based on all the configuration instructions; The third module is used to cluster all the configuration instructions to obtain several first instruction sets; The fourth module is used to obtain abnormal instructions during the current service activation process; The fifth module is used to determine, among all the first instruction sets, the first instruction set to which the abnormal instruction belongs as the second instruction set; The sixth module is used to determine the rollback range of the abnormal instruction based on its positional relationship within the second instruction set. The seventh module is used to perform a rollback operation on the abnormal instruction according to the rollback range.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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