Network element adaptation method and device, storage medium, and electronic device

Abstract

The present disclosure belongs to the field of communication technology, and relates to a network element adaptation method and device, a storage medium, and an electronic device. The method includes: obtaining user business requirements, and extracting and processing user business requirements to obtain business critical data; determining the corresponding service requirement level according to the business critical data, and building a multi-network element optimization model according to the service requirement level; associating the carried network element group according to the multi-network element optimization model, and determining the target network element combination according to the network element group and the business critical data. The present disclosure can realize the flexible allocation of network resources for different business critical data, and can also avoid the problems of complex network element management logic and unbalanced network resource allocation. It can also comprehensively manage central network elements, edge network elements, and customer-exclusive network elements, and solve the problem of network resource management and allocation difficulties caused by the differentiated SLA network requirements of different services in the 5G 2B industry.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a network element adaptation method and device, a computer-readable storage medium, and an electronic device. Background Art

[0002] With the implementation and development of 5G (5th Generation Mobile Communication Technology) networks, the role of 5G in enabling applications in various industries is becoming increasingly apparent, and the differentiated requirements for SLA (Service Level Agreement) are becoming increasingly prominent. Different performance indicators also require different network resource environments. However, as operator network coverage becomes increasingly extensive, more and more network element devices are deployed, including central network elements, edge network elements, and even customer-exclusive network elements.

[0003] The implementation in the relevant technology is mainly the network resources in the terminal adjacent area. This method not only solves the problem of limiting the use of side chain communication by terminal devices based on application granularity, but also takes into account the problem that the technical standards for network element maintenance, management and development in the existing technology are relatively complex and the development cycle is relatively time-consuming, and realizes the centralized, efficient and convenient management of network elements. However, this technology cannot accurately and flexibly match the optimal network resources for customer services when customer business needs arise, which will not only cause waste and uneven use of network resources, but also greatly increase the workload.

[0004] In view of this, there is an urgent need in the art to develop a new network element adaptation method and device.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0006] The purpose of the present disclosure is to provide a network element adaptation method, a network element adaptation device, a computer-readable storage medium and an electronic device, thereby at least to a certain extent overcoming the technical problems of uneven network resource allocation and heavy workload caused by the limitations of related technologies.

[0007] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0008] According to a first aspect of an embodiment of the present invention, a network element adaptation method is provided, the method comprising:

[0009] Obtaining user business requirements, and extracting and processing the user business requirements to obtain business-critical data;

[0010] Determine a corresponding service requirement level according to the business key data, and construct a multi-network element optimization model according to the service requirement level;

[0011] The network element group to be carried is associated according to the multi-network element optimization model, and the target network element combination is determined according to the network element group and the business key data.

[0012] In an exemplary embodiment of the present invention, the business-critical data includes: network demand parameters and business indicator characteristics, the network demand parameters include: bandwidth, latency, guarantee category, guarantee area and guarantee level, and the business indicator characteristics include: bandwidth, latency and business isolation requirements.

[0013] In an exemplary embodiment of the present invention, the extracting and processing the user service requirements to obtain service-critical data includes:

[0014] Extracting the network requirement parameters from the user service requirements;

[0015] The indicator features of the user's business needs are extracted to obtain business indicator features.

[0016] In an exemplary embodiment of the present invention, determining the corresponding service requirement level according to the business key data includes:

[0017] Acquire a mapping relationship between the business key data and the service requirement level;

[0018] Based on the mapping relationship, a corresponding service requirement level is determined according to the business key data.

[0019] In an exemplary embodiment of the present invention, the step of constructing a multi-network element optimization model according to the service demand level includes:

[0020] Associating the carried network element resources according to the service requirement level;

[0021] A multi-network element optimization model is constructed according to the service demand level and the network element resources, wherein the multi-network element optimization model includes a plurality of network elements.

[0022] In an exemplary embodiment of the present invention, the network element resources associated with the bearer according to the service requirement level include:

[0023] Receiving a resource verification request to verify the network element resources and obtain a verification result;

[0024] When the checking result is that the network element resources are available, the network element resources are associated with the bearer according to the service requirement level.

[0025] In an exemplary embodiment of the present invention, after determining the target network element combination according to the network element group and the service-critical data, the method further includes:

[0026] The service configuration related to the user service demand is issued to the target network element combination.

[0027] According to a second aspect of an embodiment of the present invention, a network element adaptation device is provided, including:

[0028] A data extraction module is configured to obtain user business requirements and extract and process the user business requirements to obtain business-critical data;

[0029] A model building module, configured to determine a corresponding service requirement level according to the business key data, and to build a multi-network element optimization model according to the service requirement level;

[0030] The network element adaptation module is configured to associate the carried network element group according to the multi-network element optimization model, and determine the target network element combination according to the network element group and the business key data.

[0031] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a processor and a memory; wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the network element adaptation method in any of the above exemplary embodiments is implemented.

[0032] According to a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the network element adaptation method in any of the above exemplary embodiments is implemented.

[0033] It can be seen from the above technical solutions that the network element adaptation method, network element adaptation device, computer storage medium and electronic device in the exemplary embodiments of the present disclosure have at least the following advantages and positive effects:

[0034] In the method and device provided by the exemplary embodiment of the present disclosure, the service demand level corresponding to the business key data of different user business needs is analyzed to select the optimal target network element combination. Not only can the flexible allocation of network resources be achieved for different business key data, but also the problems of complex network element management logic and unbalanced network resource allocation can be avoided, and the central network element, edge network element and customer-exclusive network element can be comprehensively managed, solving the problem of network resource management and allocation difficulties caused by the differentiated SLA network requirements of different services in the 5G 2B industry.

[0035] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0037] Figure 1 A schematic diagram schematically illustrates a flow chart of a network element adaptation method in an exemplary embodiment of the present disclosure;

[0038] Figure 2 A schematic diagram schematically illustrates a flow chart of a method for extracting and processing user business requirements in an exemplary embodiment of the present disclosure;

[0039] Figure 3 A flowchart schematically illustrating a method for determining a service requirement level in an exemplary embodiment of the present disclosure;

[0040] Figure 4 A schematic diagram schematically illustrates a flow chart of a method for constructing a multi-network element optimization model in an exemplary embodiment of the present disclosure;

[0041] Figure 5 A schematic diagram schematically illustrates a flow chart of a method for associating network element resources in an exemplary embodiment of the present disclosure;

[0042] Figure 6 A schematic diagram schematically shows the structure of a service networking model in an application scenario in an exemplary embodiment of the present disclosure;

[0043] Figure 7 A schematic diagram schematically illustrates a flow chart of a network element adaptation method in an application scenario in an exemplary embodiment of the present disclosure;

[0044] Figure 8 A schematic diagram showing the structure of a network element adaptation device in an exemplary embodiment of the present disclosure is shown;

[0045] Fig. 9 The present invention schematically illustrates an electronic device for implementing a network element adaptation method in an exemplary embodiment of the present disclosure;

[0046] Fig.10 The present invention schematically illustrates a computer-readable storage medium for implementing a network element adaptation method in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0047] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the example embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0048] The terms "a", "an", "the" and "said" are used in this specification to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express an open-ended inclusion and mean that additional elements / components / etc. may exist in addition to the listed elements / components / etc.; the terms "first" and "second" etc. are used only as labels and are not intended to limit the quantity of their objects.

[0049] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and their repeated descriptions will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities.

[0050] In view of the problems existing in the related technologies, the present disclosure proposes a network element adaptation method. Figure 1 A flow chart of a network element adaptation method is shown, such as Figure 1 As shown, the network element adaptation method includes at least the following steps:

[0051] Step S110: Obtain user business requirements, and extract and process the user business requirements to obtain business-critical data.

[0052] Step S120: Determine the corresponding service requirement level according to the business key data, and build a multi-network element optimization model according to the service requirement level.

[0053] Step S130: associate the carried network element group according to the multi-network element optimization model, and determine the target network element combination according to the network element group and the business key data.

[0054] In the exemplary embodiment of the present disclosure, the service demand level corresponding to the business key data of different user business needs is analyzed to select the optimal target network element combination. Not only can the flexible allocation of network resources be achieved for different business key data, but also the problems of complex network element management logic and unbalanced network resource allocation can be avoided, and the central network element, edge network element and customer-exclusive network element can be comprehensively managed, solving the problem of network resource management and allocation difficulties caused by the differentiated SLA network requirements of different services in the 5G 2B (B2B, enterprise-oriented) industry.

[0055] The following describes in detail the various steps of the network element adaptation method.

[0056] In step S110, the user's business requirements are acquired, and the user's business requirements are extracted to obtain business-critical data.

[0057] In an exemplary embodiment of the present disclosure, a user may input a business requirement as the user business requirement.

[0058] Furthermore, user business requirements can be extracted and processed to obtain business-critical data.

[0059] In an optional embodiment, the business-critical data include: network demand parameters and business indicator characteristics, network demand parameters include: bandwidth, latency, guarantee category, guarantee area and guarantee level, business indicator characteristics include: bandwidth, latency and business isolation requirements.

[0060] In an alternative embodiment, Figure 2 A flow chart of a method for extracting and processing user business requirements is shown, such as Figure 2 As shown, the method may at least include the following steps: In step S210, network demand parameters are extracted from user service requirements.

[0061] After the user inputs the user's service requirements, the service classification data module may store the user's service requirements and extract network requirement parameters of the service requirements.

[0062] The network demand parameters may include bandwidth, latency, guarantee category, guarantee area and guarantee level, and may also include other parameters according to actual conditions, which are not specifically limited in this exemplary embodiment.

[0063] In step S220, the indicator features of the user's business requirements are extracted to obtain business indicator features.

[0064] After the user inputs the user's business requirements, the business indicator feature analysis module extracts business indicator features for the user's business requirements to extract business indicator features such as network bandwidth, latency and business isolation of the user's business requirements.

[0065] In this exemplary embodiment, network demand parameters and service indicator characteristics can be obtained by extracting and processing user service requirements, providing two aspects of data basis and theoretical support for network element adaptation.

[0066] In step S120, the corresponding service requirement level is determined according to the business key data, and a multi-network element optimization model is constructed according to the service requirement level.

[0067] In an exemplary embodiment of the present disclosure, after the business-critical data is extracted, the service requirement level corresponding to the business-critical data can be determined according to the business-critical data.

[0068] In an alternative embodiment, Figure 3 A flow chart showing a method for determining a service requirement level is shown. Figure 3 As shown, the method may at least include the following steps: In step S310, a mapping relationship between business-critical data and service requirement levels is obtained.

[0069] The mapping relationship can be a relationship in which the service requirement level corresponds to both the network requirement parameters and the business indicator characteristics, or a relationship in which the service requirement level corresponds to the network requirement parameters, or a relationship in which the service requirement level corresponds to the business indicator characteristics. This exemplary embodiment does not make any special limitations on this.

[0070] In step S320, based on the mapping relationship, the corresponding service requirement level is determined according to the business key data.

[0071] After obtaining the mapping relationship between business key data and service requirement levels, the business key data can be queried through the business classification data module, and the business key data can be analyzed to evaluate the differentiated service requirement levels of the business SLA.

[0072] In this exemplary embodiment, the service requirement level is determined by business key data and corresponding mapping relationships, which provides a solution to the problem of uneven or difficult network resource management distribution caused by network requirements of different services.

[0073] Furthermore, a corresponding multi-network element optimization model may be constructed according to the service demand level.

[0074] In an alternative embodiment, Figure 4 A schematic diagram of a process for constructing a multi-network element optimization model is shown. Figure 4 As shown, the method may at least include the following steps: In step S410, the network element resources of the bearer are associated according to the service requirement level.

[0075] In an alternative embodiment, Figure 5A schematic diagram of a process for associating network element resources is shown, such as Figure 5 As shown, the method may at least include the following steps: In step S510, a resource verification request is received to verify the network element resources to obtain a verification result.

[0076] When a user wants to query the resource verification module for network element resources through the service order system, a resource verification request can be sent to the resource verification module to verify whether the network element resources of the service-related 5G network are available.

[0077] Among them, network element resources may include wireless network resources, bearer network resources, core network resources and slice resources, etc., and may also include other resources according to actual conditions. This exemplary embodiment does not make any special limitations on this.

[0078] In step S520, when the checking result is that the network element resources are available, the network element resources of the bearer are associated according to the service requirement level.

[0079] Only when the resource checking module's checking result indicates that all checked network element resources are available, can the network element resources to be carried be associated according to the service requirement level.

[0080] In this exemplary embodiment, the resource verification request can determine whether the network element resources are available and whether they can be associated, which ensures the feasibility of associating network element resources, is a prerequisite for network element adaptation, and further ensures the accuracy of network element adaptation.

[0081] In step S420, a multi-network element optimization model is constructed according to the service demand level and the network element resources, and the multi-network element optimization model includes multiple network elements.

[0082] Through the network element adaptation multi-objective optimization module, a multi-network element optimization model can be built according to the service demand level and network element resources.

[0083] Specifically, a multi-network element optimization model is constructed by using the service demand level and network element resources of the business indicator feature analysis module. The multi-network element optimization model may include multiple network elements, such as network element A, network element B, and network element C.

[0084] In step S130, the network element groups of the bearers are associated according to the multi-network element optimization model, and the target network element combination is determined according to the network element groups and the key service data.

[0085] In an exemplary embodiment of the present disclosure, after a multi-network element optimization model is constructed, a network element group carried by the multi-network element optimization model can be associated.

[0086] It is worth noting that the network element group may cover multi-domain network elements of the wireless network, the bearer network and the core network.

[0087] Furthermore, the genetic algorithm is used to analyze the network element group and the business key data to obtain a target network element combination that meets the business requirements. In this case, the business indicator characteristics may be analyzed, and the target network element combination is the optimal adaptive network element combination.

[0088] After the target network element combination is determined, further processing can be performed through the orchestration control module.

[0089] In an optional embodiment, a service configuration related to the user's service demand is delivered to the target network element combination.

[0090] The orchestration control module issues relevant service configurations to the selected target network element combination, wherein the service configurations may include DNN (Data Network Name), DNN routing, and interconnection address configurations.

[0091] The network element adaptation method in the embodiment of the present disclosure is described in detail below in conjunction with an application scenario.

[0092] Figure 6 The schematic diagram of the structure of the business networking model in the application scenario is shown as follows: Figure 6 As shown, the service networking model may include customer sites, gNB (NR Node B, NR node), bearer network, core network and customer network.

[0093] The service networking model introduces important modules such as service classification data module, service indicator feature analysis module, and network element adaptation multi-objective optimization module. Through the interaction between multiple modules, the service indicator feature analysis is performed on the SLA differentiation requirements of customer services. Furthermore, by constructing a service classification target optimization model and genetic algorithm, the optimal adaptation network element is selected for the service.

[0094] Among them, the business classification data module can store order input business requirements and corresponding network attributes, provide data resource proofreading for business analysis, and analyze the order input business orders to match their corresponding network attributes and store and record them in this module. Specifically, it can include network attributes such as local / cross-domain business, network bandwidth, latency, and business isolation requirements.

[0095] The business indicator feature analysis module extracts business indicator features for order input services to extract business indicator features such as network bandwidth, latency, and business isolation requirements. Furthermore, by querying and analyzing the business classification data module, the differentiated demand level of the business SLA is evaluated and associated with the network element resources it carries.

[0096] The network element adaptation multi-objective optimization module can analyze the relevant data of the module according to the business indicator characteristics and build a multi-network element target optimization model. Then, by analyzing the business indicator characteristics and network element conditions, the optimal adaptation network element that meets the business needs is obtained.

[0097] Figure 7 A schematic diagram of the process of network element adaptation method in an application scenario is shown, such as Figure 7 As shown, in step S701, business requirements are entered.

[0098] Users can enter business requirements as user business requirements.

[0099] In step S702, service network requirements are extracted.

[0100] After the user inputs the user's service requirements, the service classification data module may store the user's service requirements and extract network requirement parameters of the service requirements.

[0101] The network demand parameters may include bandwidth, latency, guarantee category, guarantee area and guarantee level, and may also include other parameters according to actual conditions, which are not specifically limited in this exemplary embodiment.

[0102] In step S703, the service requests resource verification (whether service-related 5GC (5G Core) network element resources are available).

[0103] When a user wants to query the resource verification module for network element resources through the service order system, a resource verification request can be sent to the resource verification module to verify whether the network element resources of the service-related 5G network are available.

[0104] Among them, network element resources may include wireless network resources, bearer network resources, core network resources and slice resources, etc., and may also include other resources according to actual conditions. This exemplary embodiment does not make any special limitations on this.

[0105] In step S704, the resource verification result is fed back.

[0106] Among them, the verification result of the resource verification module may be that all the verified network element resources are available.

[0107] In step S705, business indicator features are extracted.

[0108] After the user inputs the user's business requirements, the business indicator feature analysis module extracts business indicator features for the user's business requirements to extract business indicator features such as network bandwidth, latency and business isolation.

[0109] In step S706, the service classification data module is queried and analyzed, and network element resource information associated with the service is output.

[0110] Obtain the mapping relationship between business-critical data and service requirement levels.

[0111] The mapping relationship can be a relationship in which the service requirement level corresponds to both the network requirement parameters and the business indicator characteristics, or a relationship in which the service requirement level corresponds to the network requirement parameters, or a relationship in which the service requirement level corresponds to the business indicator characteristics. This exemplary embodiment does not make any special limitations on this.

[0112] Based on the mapping relationship, the corresponding service requirement level is determined according to the business key data.

[0113] After obtaining the mapping relationship between the business key data and the service requirement level, the business key data of the business classification data module can be queried and the business key data can be analyzed and evaluated to obtain the differentiated service requirement level of the business SLA.

[0114] Furthermore, the network element resources carried are associated according to the service demand level.

[0115] In step S707, a service classification multi-objective optimization model is constructed to obtain multiple groups of target network element models.

[0116] Through the network element adaptation multi-objective optimization module, a multi-network element optimization model can be built according to the service demand level and network element resources.

[0117] Specifically, a multi-network element optimization model is constructed by using the service demand level and network element resources of the business indicator feature analysis module. The multi-network element optimization model may include multiple network elements, such as network element A, network element B, and network element C.

[0118] In step S708, business characteristic analysis data is obtained.

[0119] After the multi-network element optimization model is constructed, the network element group carried by the multi-network element optimization model can be associated.

[0120] It is worth noting that the network element group may cover multi-domain network elements of the wireless network, the bearer network and the core network.

[0121] In step S709, the optimal service adaptation network element combination is obtained through genetic algorithm analysis.

[0122] The genetic algorithm is used to analyze the network element group and the business key data to obtain a target network element combination that meets the business requirements. The business indicator characteristics can be analyzed at this time, and the target network element combination is the optimal adaptive network element combination.

[0123] In step S710, a network element configuration instruction is issued.

[0124] The orchestration control module sends relevant service configurations to the selected target network element combination, where the service configurations may include DNN, DNN routing, and interconnection address configurations.

[0125] The network element adaptation method may be applicable to the 5G 2B field.

[0126] Specifically, for example, in the SLA differentiated network assurance scenario of different services in 5G 2B application services, it effectively solves the problems of inflexible 5G network resource allocation and waste of network resources caused by various SLA differentiated business requirements as 5G industry applications become more and more extensive.

[0127] Flexible allocation of network resources for integrated management center network elements, edge network elements, and customer-exclusive network elements will further enhance customers' application experience and facilitate the further promotion and development of 5G services.

[0128] In scenarios where customized network assurance is required for 5G 2B application services, network resources with different SLAs can be flexibly matched to different services, effectively improving the use value and benefits of the operator's network and facilitating the deployment and planning of network resources.

[0129] The network element adaptation method in this application scenario analyzes the corresponding service demand levels for the business key data of different user business needs to select the optimal target network element combination. It can not only realize the flexible allocation of network resources for different business key data, effectively improve the use value and benefits of the operator's network, but also avoid the problems of complex network element management logic and unbalanced network resource allocation. It can also comprehensively manage central network elements, edge network elements and customer-exclusive network elements, solving the problem of network resource management and allocation difficulties caused by the differentiated SLA network requirements of different services in the 5G 2B industry.

[0130] Figure 8 A schematic diagram of the structure of a network element adaptation device is shown, such as Figure 8 As shown, the network element adaptation device 800 may include: a data extraction module 810, a model construction module 820 and a network element adaptation module 830. Among them:

[0131] The data extraction module 810 is configured to obtain user business requirements and extract and process the user business requirements to obtain business-critical data;

[0132] A model building module 820 is configured to determine a corresponding service requirement level according to the business key data, and build a multi-network element optimization model according to the service requirement level;

[0133] The network element adaptation module 830 is configured to associate the carried network element group according to the multi-network element optimization model, and determine the target network element combination according to the network element group and the business key data.

[0134] In an exemplary embodiment of the present invention, the business-critical data includes: network demand parameters and business indicator characteristics, the network demand parameters include: bandwidth, latency, guarantee category, guarantee area and guarantee level, and the business indicator characteristics include: bandwidth, latency and business isolation requirements.

[0135] In an exemplary embodiment of the present invention, the extracting and processing the user service requirements to obtain service-critical data includes:

[0136] Extracting the network requirement parameters from the user service requirements;

[0137] The indicator features of the user's business needs are extracted to obtain business indicator features.

[0138] In an exemplary embodiment of the present invention, determining the corresponding service requirement level according to the business key data includes:

[0139] Acquire a mapping relationship between the business key data and the service requirement level;

[0140] Based on the mapping relationship, a corresponding service requirement level is determined according to the business key data.

[0141] In an exemplary embodiment of the present invention, the step of constructing a multi-network element optimization model according to the service demand level includes:

[0142] Associating the carried network element resources according to the service requirement level;

[0143] A multi-network element optimization model is constructed according to the service demand level and the network element resources, wherein the multi-network element optimization model includes a plurality of network elements.

[0144] In an exemplary embodiment of the present invention, the network element resources associated with the bearer according to the service requirement level include:

[0145] Receiving a resource verification request to verify the network element resources and obtain a verification result;

[0146] When the checking result is that the network element resources are available, the network element resources are associated with the bearer according to the service requirement level.

[0147] In an exemplary embodiment of the present invention, after determining the target network element combination according to the network element group and the service-critical data, the method further includes:

[0148] The service configuration related to the user service demand is issued to the target network element combination.

[0149] The specific details of the above-mentioned network element adaptation device 800 have been described in detail in the corresponding network element adaptation method, so they will not be repeated here.

[0150] It should be noted that although several modules or units of the network element adaptation device 800 are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0151] In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0152] Refer to the following Fig. 9 An electronic device 900 according to such an embodiment of the present invention will be described. Fig. 9 The electronic device 900 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0153] like Fig. 9 As shown, the electronic device 900 is in the form of a general computing device. The components of the electronic device 900 may include, but are not limited to: the at least one processing unit 910, the at least one storage unit 920, a bus 930 connecting different system components (including the storage unit 920 and the processing unit 910), and a display unit 940.

[0154] The storage unit stores program codes, which can be executed by the processing unit 910, so that the processing unit 910 executes the steps according to various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0155] The storage unit 920 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 921 and / or a cache memory unit 922 , and may further include a read-only memory unit (ROM) 923 .

[0156] The storage unit 920 may also include a program / utility 924 having a set (at least one) of program modules 925, such program modules 925 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0157] Bus 930 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0158] The electronic device 900 may also communicate with one or more external devices 1100 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 900, and / or may communicate with any device that enables the electronic device 900 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 950. Furthermore, the electronic device 900 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 960. As shown, the network adapter 960 communicates with other modules of the electronic device 900 via a bus 930. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0159] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiment of the present disclosure.

[0160] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible embodiments, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to perform the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present specification.

[0161] refer to Fig.10As shown, a program product 1000 for implementing the above method according to an embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0162] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0163] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0164] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0165] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0166] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. A network element adaptation method, characterized in that: The method comprises: Obtaining user business requirements, and extracting and processing the user business requirements to obtain business-critical data; Determine a corresponding service requirement level according to the business key data, and construct a multi-network element optimization model according to the service requirement level; Associating the carried network element group according to the multi-network element optimization model, and determining the target network element combination according to the network element group and the business key data; Wherein, constructing a multi-network element optimization model according to the service demand level includes: Associating the carried network element resources according to the service demand level; Constructing a multi-network element optimization model according to the service demand level and the network element resources, wherein the multi-network element optimization model includes a plurality of network elements; The network element resources associated with the bearer according to the service requirement level include: Receiving a resource verification request to verify the network element resources and obtain a verification result; When the checking result is that the network element resources are available, the network element resources are associated with the bearer according to the service requirement level.

2. The network element adaptation method according to claim 1, characterized in that: The business key data includes: network demand parameters and business indicator characteristics. The network demand parameters include: bandwidth, latency, guarantee category, guarantee area and guarantee level. The business indicator characteristics include: bandwidth, latency and business isolation requirements.

3. The network element adaptation method according to claim 2, characterized in that: The extracting and processing the user's business requirements to obtain business-critical data includes: Extracting the network requirement parameters from the user service requirements; The indicator features of the user's business needs are extracted to obtain business indicator features.

4. The network element adaptation method according to claim 1, characterized in that: Determining the corresponding service requirement level according to the business key data includes: Acquire a mapping relationship between the business key data and the service requirement level; Based on the mapping relationship, a corresponding service requirement level is determined according to the business key data.

5. The network element adaptation method according to claim 1, characterized in that: After determining the target network element combination according to the network element group and the business key data, the method further includes: The service configuration related to the user service demand is issued to the target network element combination.

6. A network element adaptation device, characterized in that: include: A data extraction module is configured to obtain user business requirements and extract and process the user business requirements to obtain business-critical data; A model building module, configured to determine a corresponding service requirement level according to the business key data, and to build a multi-network element optimization model according to the service requirement level; A network element adaptation module, configured to associate a carried network element group according to the multi-network element optimization model, and determine a target network element combination according to the network element group and the business key data; Wherein, constructing a multi-network element optimization model according to the service demand level includes: Associating the carried network element resources according to the service demand level; Constructing a multi-network element optimization model according to the service demand level and the network element resources, wherein the multi-network element optimization model includes a plurality of network elements; The network element resources associated with the bearer according to the service requirement level include: Receiving a resource verification request to verify the network element resources and obtain a verification result; When the checking result is that the network element resources are available, the network element resources are associated with the bearer according to the service requirement level.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the network element adaptation method described in any one of claims 1 to 5 is implemented.

8. An electronic device, characterized in that: include: processor; A memory, configured to store executable instructions of the processor; The processor is configured to execute the network element adaptation method described in any one of claims 1-5 by executing the executable instructions.

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