5g network health monitoring method, apparatus, device, and medium

Abstract

The present application relates to the technical field of communication, and provides a 5G network health monitoring method, device, equipment and medium, which can construct a 5G network health monitoring model including a 5G private network layer model, a sub-domain layer model and a network element device layer model based on a pre-constructed basic index library, a 5G network health monitoring model framework and an application scenario, and perform health monitoring on the 5G network based on the 5G network health monitoring model, so as to refine, layer, classify and evaluate the network health degree from the whole to the part, layer by layer, which can not only evaluate the global network health degree of the 5G private network, but also evaluate the network health degree of each sub-domain and each device in a more fine-grained manner, and provide comprehensive network health degree real-time evaluation capability for 5G private network operation and maintenance.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication technology, in particular to a 5G network health monitoring method, device, equipment and medium. BACKGROUND

[0002] 5G (5th Generation Mobile Communication Technology) technology will promote the digital and intelligent transformation of production factors in the form of dedicated networks in the fields of factories, energy, mines, power, transportation, hospitals, education, etc., to innovate industry digital application scenarios and evolve information-based businesses, with a significant improvement in communication performance indicators. With the construction of 5G dedicated networks, higher requirements are placed on the operation and maintenance of 5G dedicated networks, and existing network operation and maintenance methods are increasingly difficult to meet the operation and maintenance needs of 5G dedicated networks.

[0003] Currently, the monitoring of 5G dedicated network status mainly has the following problems:

[0004] 1. Lack of intuitive, simple and effective evaluation methods for 5G dedicated network status: there is currently a lack of effective evaluation methods for the overall status of 5G dedicated networks, especially for the overall status of dedicated networks. 5G dedicated networks involve multiple sub-domains, a variety of devices, and numerous influencing factors, making it difficult for operation and maintenance personnel to effectively evaluate the status of dedicated networks using existing network operation and maintenance systems and methods.

[0005] 2. How to evaluate both the overall status of 5G dedicated networks and the local network status, and to combine the overall and local status organically, is a difficult problem faced by 5G dedicated network operation and maintenance, and there is currently still a lack of effective solutions.

[0006] 3. 5G dedicated networks involve different specialties, a variety of devices, and multiple operation and maintenance indicators, making it a significant challenge to build a suitable network status evaluation model. SUMMARY

[0007] In view of the above, it is necessary to provide a 5G network health monitoring method, device, equipment and medium, aiming to solve the problem of monitoring the health status of 5G dedicated networks.

[0008] A 5G network health monitoring method, the 5G network health monitoring method comprising:

[0009] obtaining a pre-constructed basic index library, obtaining a pre-constructed 5G network health monitoring model framework, and obtaining at least one application scenario of a 5G network; wherein the 5G network health monitoring model framework comprises a 5G dedicated network layer model framework, a sub-domain layer model framework, and a network element device layer model framework;

[0010] construct a 5G network health monitoring model according to the basic index library and a 5G network health monitoring model framework in each application scenario; wherein the 5G network health monitoring model comprises a 5G private network layer model, a sub-domain layer model and a network element device layer model;

[0011] in response to a health monitoring instruction of the 5G network in the target application scenario, calling the 5G network health monitoring model in the target application scenario as a target model;

[0012] collecting an index value of each index in the target application scenario;

[0013] generating a health monitoring result according to each index value and the target model;

[0014] identifying a network health degradation index from each index according to the health monitoring result;

[0015] pushing and displaying the health monitoring result and the network health degradation index.

[0016] According to the preferred embodiment of the present application, the 5G network health monitoring model is constructed according to the basic index library and the 5G network health monitoring model framework in each application scenario, which comprises:

[0017] obtaining a basic index corresponding to each application scenario from the basic index library;

[0018] configuring a degradation strategy of the basic index corresponding to each application scenario;

[0019] filling the 5G network health monitoring model framework according to the basic index corresponding to each application scenario and the degradation strategy of the basic index corresponding to each application scenario, to obtain the 5G network health monitoring model.

[0020] According to the preferred embodiment of the present application, the degradation strategy of the basic index corresponding to each application scenario comprises:

[0021] configuring a degradation standard of the basic index corresponding to each application scenario;

[0022] configuring a deduction value corresponding to each degradation standard.

[0023] According to the preferred embodiment of the present application, the health monitoring result is generated according to each index value and the target model, which comprises:

[0024] obtaining the degradation standard and the corresponding deduction value of each index from the target model;

[0025] obtaining an initial score of each index in the target model;

[0026] comparing each index value with a corresponding degradation standard to obtain a comparison result;

[0027] determining at least one target deduction value of each index value from corresponding deduction values of each index according to the comparison result;

[0028] deducting a corresponding target deduction value from an initial score of each index in the target model to obtain a target score of each index;

[0029] integrating the target scores of each index to obtain the health monitoring result.

[0030] According to a preferred embodiment of the present application, when the corresponding target deduction value is deducted from the initial score of each index in the target model, the method further comprises:

[0031] In the deduction process, when the initial score of an index is deducted to a negative number, the target score of the index is determined as 0.

[0032] According to a preferred embodiment of the present application, the identifying the network health degradation index from each index according to the health detection result comprises:

[0033] calculating a sum of the target deduction values corresponding to each index to obtain an actual deduction value of each index;

[0034] sorting each index according to the actual deduction value from high to low;

[0035] obtaining indexes ranked in the front of a preset position as the network health degradation index.

[0036] According to a preferred embodiment of the present application, the method further comprises:

[0037] obtaining a preconfigured position value and determining the position value as a value of the preset position; or

[0038] obtaining a preconfigured deduction threshold value and obtaining a number of indexes whose actual deduction values are greater than or equal to the deduction threshold value as a value of the preset position.

[0039] A 5G network health monitoring device, comprising:

[0040] an obtaining unit, configured to obtain a preconstructed basic index library, obtain a preconstructed 5G network health monitoring model framework, and obtain at least one application scenario of a 5G network; wherein the 5G network health monitoring model framework comprises a 5G private network layer model framework, a sub-domain layer model framework, and a network element device layer model framework;

[0041] a constructing unit configured to construct a 5G network health monitoring model according to the basic index library and the 5G network health monitoring model framework in each application scenario; wherein the 5G network health monitoring model comprises a 5G private network layer model, a sub-domain layer model and a network element device layer model;

[0042] a calling unit configured to call the 5G network health monitoring model in the target application scenario as a target model in response to a health monitoring instruction of the 5G network in the target application scenario;

[0043] a collecting unit configured to collect an index value of each index in the target application scenario;

[0044] a generating unit configured to generate a health monitoring result according to each index value and the target model;

[0045] an identifying unit configured to identify a network health degradation index from each index according to the health monitoring result;

[0046] a pushing and displaying unit configured to push and display the health monitoring result and the network health degradation index.

[0047] A computer device, comprising:

[0048] a memory configured to store at least one instruction; and

[0049] a processor configured to execute the instruction stored in the memory to implement the 5G network health monitoring method.

[0050] A computer readable storage medium, wherein the computer readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in a computer device to implement the 5G network health monitoring method.

[0051] As can be seen from the above technical solutions, the present application can construct a 5G network health monitoring model comprising a 5G private network layer model, a sub-domain layer model and a network element device layer model based on a pre-constructed basic index library, a 5G network health monitoring model framework and an application scenario, and perform health monitoring of the 5G network based on the 5G network health monitoring model, which can refine, layer, classify and evaluate the network health degree from the whole to the local, and can not only evaluate the global network health degree of the 5G private network, but also evaluate the network health degree of each sub-domain and each device in a more fine-grained manner, thereby providing comprehensive network health degree real-time evaluation capability for 5G private network operation and maintenance. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 is a flowchart of a preferred embodiment of the 5G network health monitoring method of the present application.

[0053] Figure 2is a schematic diagram of a 5G network health monitoring model framework of the present application.

[0054] Figure 3 is a schematic diagram of index dimension division of the 5G network health monitoring model framework of the present application.

[0055] Figure 4 is a functional module diagram of a preferred embodiment of the 5G network health monitoring device of the present application.

[0056] Figure 5 is a structural schematic diagram of a computer device of a preferred embodiment of the 5G network health monitoring method of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be described in detail below with reference to the drawings and specific embodiments.

[0058] As shown in Figure 1 is a flowchart of a preferred embodiment of the 5G network health monitoring method of the present application. The order of steps in the flowchart can be changed according to different needs, and some steps can be omitted.

[0059] The 5G network health monitoring method is applied in one or more computer devices, and the computer device is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions, the hardware of which includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0060] The computer device can be any kind of electronic product that can interact with the user, such as personal computers, tablet computers, smart phones, personal digital assistants (PDAs), game consoles, interactive Internet protocol televisions (IPTVs), smart wearable devices, etc.

[0061] The computer device can also include network devices and / or user devices. The network device includes but is not limited to a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of hosts or network servers based on cloud computing.

[0062] The server can be a standalone server, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0063] Among them, artificial intelligence (AI) is to use digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. Theory, method, technology and application system.

[0064] The basic technology of artificial intelligence generally includes technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction system, mechatronics, etc. Artificial intelligence software technology mainly includes computer vision technology, robot technology, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning, etc. Several major directions.

[0065] The network in which the computer device is located includes but is not limited to the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN), etc.

[0066] S10, acquiring a pre-constructed basic index library, acquiring a pre-constructed 5G (5th Generation Mobile Communication Technology) network health monitoring model framework, and acquiring at least one application scenario of the 5G network; wherein the 5G network health monitoring model framework includes a 5G private network layer model framework, a sub-domain layer model framework, and a network element device layer model framework.

[0067] In the embodiment, the basic index library includes alarm data and performance data of core network AMF (Authentication Management Function), SMF (Service Management Function), UPF (User Port Function), and wireless network gNB (the next Generation Node B, i.e. 5G base station), CU (Centralized Unit), and DU (Distributed Unit). The basic index library of each device alarm data includes alarm level, alarm quantity, etc.; the basic index library of performance data includes load dimension (system load, service load, resource load), and main indexes of service dimension. For example, the basic index library (performance data) shown in the following table can be referred to.

[0068]

[0069]

[0070]

[0071] In the embodiment, the 5G network health monitoring model framework is constructed according to the principle of refining from the whole to the part and layer by layer. For example, the following table can be referred to. Figure 2 , which is a schematic diagram of the 5G network health monitoring model framework. The 5G network health monitoring model framework includes a 5G private network layer model framework, a sub-domain layer model framework, and a network element device layer model framework. The sub-domain layer includes a wireless network sub-domain and a core network sub-domain; the network element device layer includes AMF, SMF, UPF, gNB, etc.

[0072] Each layer model can include three dimensions of fault, load, and service. The fault dimension includes alarm level, alarm quantity, etc.; the load dimension includes system load, service load, and resource load; the service dimension of different types of network element devices includes different service categories. For example, the service dimension of AMF includes registration, authentication, paging, and handover service categories. For details, refer to the examples in Figure 3 .

[0073] In this embodiment, the at least one application scenario can include, but is not limited to, enhanced mobile broadband (eMBB), massive machine type communication (mMTC), ultra-reliable low-latency communication (uRLLC), etc. Each type of application scenario corresponds to a different 5G network health monitoring model.

[0074] S11, under each application scenario, a 5G network health monitoring model is constructed according to the basic index library and the 5G network health monitoring model framework; wherein the 5G network health monitoring model includes a 5G private network layer model, a sub-domain layer model, and a network element device layer model.

[0075] In this embodiment, constructing the 5G network health monitoring model under each application scenario according to the basic index library and the 5G network health monitoring model framework includes:

[0076] Obtaining the basic index corresponding to each application scenario from the basic index library;

[0077] Configuring a degradation strategy for the basic index corresponding to each application scenario;

[0078] Filling the 5G network health monitoring model framework according to the basic index corresponding to each application scenario and the degradation strategy of the basic index corresponding to each application scenario, to obtain the 5G network health monitoring model.

[0079] Specifically, configuring the degradation strategy for the basic index corresponding to each application scenario includes:

[0080] Configuring a degradation standard for the basic index corresponding to each application scenario;

[0081] Configuring a deduction value corresponding to each degradation standard.

[0082] Taking the 5G private network layer model as an example, a corresponding index is configured for the 5G private network layer for each type of scenario, and a degradation standard and a deduction value after degradation are set for each index, as shown in the following table, which is an example of an eMBB type private network layer model. Other scenarios can also be configured with corresponding models, which are not described here.

[0083]

[0084] In the constructed model, different degradation strategies are configured for different levels, and the general principle is as follows:

[0085] 1) From the 5G private network layer to the sub-domain layer, and then to the network element device layer, the selection of model parameters follows the principle of from coarse to fine, for example: the 5G private network layer model parameters include the main parameters affecting the private network business, such as delay, uplink / downlink average rate, uplink / downlink PRB occupancy rate, and the failure of key devices affecting the private network, such as base station out-of-service and cell out-of-service; the sub-domain layer and the network element device layer include more and more refined parameters, such as the network element device layer UPF includes the traffic parameters of N3 interface, N6 interface and N9 interface.

[0086] 2) From the 5G private network layer to the sub-domain layer, and then to the network element device layer, the parameter granularity of the model follows the principle of from large to small, for example: the 5G private network layer includes parameters at each sub-domain level and device-level parameters of key devices, and generally does not include more fine-grained parameters, such as cell DU-level parameters; and the network element device layer includes device-level parameters and more fine-grained parameters, such as cell DU-level parameters.

[0087] S12, in response to a health monitoring instruction of a 5G network in a target application scenario, calling a 5G network health monitoring model in the target application scenario as a target model.

[0088] The health monitoring instruction can be triggered by relevant staff, and the present application does not limit it.

[0089] S13, collecting an index value of each index in the target application scenario.

[0090] For example, the AMF system average load value and the AMF authentication request times can be collected.

[0091] S14, generating a health monitoring result according to each index value and the target model.

[0092] In this embodiment, the generation of the health monitoring result according to each index value and the target model includes:

[0093] obtaining the degradation standard and the corresponding deduction value of each index from the target model;

[0094] obtaining the initial score of each index in the target model;

[0095] comparing each index value with the corresponding degradation standard to obtain a comparison result;

[0096] determining at least one target deduction value of each index value from the corresponding deduction value of each index according to the comparison result;

[0097] deducting the corresponding target deduction value on the basis of the initial score of each index in the target model to obtain the target score of each index;

[0098] The target score of each indicator is integrated to obtain the health monitoring result.

[0099] Specifically, when the target deduction value of each indicator is deducted from the initial score of the indicator in the target model, the method further comprises:

[0100] In the deduction process, when the initial score of an indicator is deducted to a negative number, the target score of the indicator is determined as 0.

[0101] For example, when generating the health monitoring result, the following principles can be followed:

[0102] 1) The evaluation score is taken as the health monitoring result, and 100 points are taken as the full score and 0 points are taken as the minimum score;

[0103] 2) The initial score is 100 points;

[0104] 3) When the model indicator deteriorates, a certain score, i.e., the deduction value, is deducted;

[0105] 4) The sum of the deduction values of all indicators can be greater than or less than 100 points, but the final evaluation score cannot be lower than 0 points.

[0106] S15, identifying a network health deterioration indicator from each indicator according to the health detection result.

[0107] In the embodiment, identifying the network health deterioration indicator from each indicator according to the health detection result comprises:

[0108] Calculating the sum of the target deduction values of each indicator to obtain the actual deduction value of each indicator;

[0109] Sorting each indicator according to the actual deduction value from high to low;

[0110] Obtaining indicators ranked in the front of the preset position as the network health deterioration indicator.

[0111] Specifically, the method further comprises:

[0112] Obtaining a pre-configured position value and determining the position value as the value of the preset position; for example, the preset position can be set as a fixed value of 3, 5, etc.

[0113] Or obtaining a pre-configured deduction threshold value, and obtaining the number of indicators whose actual deduction value is greater than or equal to the deduction threshold value as the value of the preset position. For example, a deduction score threshold value can be set to obtain a dynamic preset position value.

[0114] For example, the way of generating the health monitoring result and identifying the network health deterioration indicator can comprise:

[0115] 1) Collect, converge, and calculate the base index library indicators of each device in the private network to generate network element device layer indicator data.

[0116] 2) Converge, calculate, and correlate the network element device layer indicator data to generate sub-domain layer and 5G private network layer indicator data.

[0117] 3) Calculate the 5G private network layer health degree evaluation score based on the hierarchical 5G network health monitoring model and hierarchical indicator data: set the initial score of the 5G private network health degree to 100 points, and perform indicator degradation determination on each indicator according to the model corresponding to the scene (such as eMBB). If the indicator degrades, the corresponding score is deducted; if the evaluation score is less than 0 after deduction, the evaluation score is recorded as 0 points. After traversing all indicators of the 5G private network layer model of the eMBB scene, the score calculation is completed. At the same time, sort the indicators according to the deduction score from high to low to obtain the sorted indicator set.

[0118] 4) Calculate the health degree evaluation score and topN deduction score of each sub-domain and each network element device of the private network, and the processing process is as described in step 3).

[0119] 5) Obtain the topN indicators with deduction scores from the sorted indicator set calculated in 3) to recommend the 5G private network layer network health degree degradation topN indicators. N can be set to a fixed value such as 3 or 5, or can be a dynamic value, such as setting a deduction score threshold to obtain a dynamic N.

[0120] 6) Obtain the network health degree degradation topN indicators of each sub-domain and each network element device of the 5G private network from 4).

[0121] As described above, the network health degree evaluation score calculation and degradation indicator recommendation results of each layer are completed for the 5G private network layer, the sub-domain layer, and the network element device layer.

[0122] Since the network element device layer parameters are more detailed and have smaller granularity than the sub-domain layer parameters, and the sub-domain layer parameters are more detailed and have smaller granularity than the 5G private network layer parameters, the network state of the private network from the whole to the local and which parameters degradation affect it can be explored layer by layer from the 5G private network layer to the sub-domain layer and then to the network element device layer, and used to guide the 5G private network network operation and maintenance work.

[0123] S16, push and display the health monitoring result and the network health degradation indicator.

[0124] For example, the health monitoring result and the network health degradation indicator can be pushed to the triggerer of the health monitoring instruction for network improvement.

[0125] The embodiment constructs a 5G private network health degree hierarchical monitoring model, constructs a hierarchical monitoring basic index library, and implements a hierarchical monitoring model for network health degrees in different scenarios, which is suitable for 5G private network health degree evaluation in different scenarios and has good universality.

[0126] The embodiment intuitively, concisely and effectively gives a network state evaluation result of the 5G private network dimension through the evaluation scores of the 5G private network layer, so that non-professional operation and maintenance personnel can quickly understand and master the overall state of the private network, and professional operation and maintenance personnel can be guided to understand the overall state of the private network; through the evaluation scores of the sub-domain layer and the network element device layer, the local network state of the 5G private network is presented layer by layer and layer by layer, which provides a qualitative and quantitative professional basis for more professional 5G private network operation and maintenance, is suitable for a wide range of people, and has high value for professional and non-professional 5G private network operation and maintenance personnel.

[0127] It can be seen from the above technical solutions that the present application can construct a 5G network health monitoring model including a 5G private network layer model, a sub-domain layer model and a network element device layer model based on a pre-constructed basic index library, a 5G network health monitoring model framework and an application scenario, and perform 5G network health monitoring based on the 5G network health monitoring model, from the whole to the local, layer by layer, layer by layer, and classifying evaluation of network health degree, which can not only evaluate the overall network health degree of the 5G private network, but also evaluate the network health degree of each sub-domain and each device in a more fine-grained manner, and provide comprehensive network health degree real-time evaluation capability for 5G private network operation and maintenance.

[0128] As shown in Figure 4 , it is a functional module diagram of the preferred embodiment of the 5G network health monitoring device. The 5G network health monitoring device 11 includes an acquisition unit 110, a construction unit 111, a calling unit 112, an acquisition unit 113, a generation unit 114, an identification unit 115, a pushing and display unit 116. The module / unit referred to in the present application refers to a series of computer program segments that can be executed by a processor and can complete a fixed function, which is stored in a memory. In the embodiment, the functions of each module / unit will be described in detail in the subsequent embodiments.

[0129] The acquisition unit 110 is configured to acquire a pre-constructed basic index library, acquire a pre-constructed 5G (5th Generation Mobile Communication Technology) network health monitoring model framework, and acquire at least one application scenario of the 5G network; wherein the 5G network health monitoring model framework includes a 5G private network layer model framework, a sub-domain layer model framework and a network element device layer model framework.

[0130] In the embodiment, the basic index library includes alarm data and performance data of core network AMF (Authentication Management Function), SMF (Service Management Function), UPF (User Port Function), and wireless network gNB (the next Generation Node B, i.e. 5G base station), CU (Centralized Unit), and DU (Distributed Unit). The basic index library of each device alarm data includes alarm level, alarm quantity, etc.; the basic index library of performance data includes load dimension (system load, service load, resource load), and main indexes of service dimension. For example, the basic index library (performance data) shown in the following table can be referred to.

[0131]

[0132]

[0133]

[0134] In the embodiment, the 5G network health monitoring model framework is constructed according to the principle of from the whole to the part, layer by layer refinement, for example, the following table can be referred to. Figure 2 , which is a schematic diagram of the 5G network health monitoring model framework. The 5G network health monitoring model framework includes a 5G private network layer model framework, a sub-domain layer model framework, and a network element device layer model framework. The sub-domain layer includes a wireless network sub-domain and a core network sub-domain; the network element device layer includes AMF, SMF, UPF, gNB, etc.

[0135] Each layer model can include three dimensions of fault, load, and service. The fault dimension includes alarm level, alarm quantity, etc.; the load dimension includes system load, service load, and resource load; the service dimension of different types of network element devices includes different service categories, for example, the service dimension of AMF includes registration, authentication, paging, handover, etc. service categories, which can be referred to for details. Figure 3

[0136] ​In the embodiment, the at least one application scenario can include, but is not limited to, enhanced mobile broadband (eMBB), massive machine type communication (mMTC), ultra-reliable low-latency communications (uRLLC), and the like. Each type of application scenario corresponds to a different 5G network health monitoring model.

[0137] The construction unit 111 is configured to construct a 5G network health monitoring model according to the basic index library and a 5G network health monitoring model framework under each application scenario; wherein the 5G network health monitoring model includes a 5G private network layer model, a sub-domain layer model, and a network element device layer model.

[0138] In the embodiment, the construction unit 111 constructs a 5G network health monitoring model according to the basic index library and the 5G network health monitoring model framework under each application scenario, which includes:

[0139] obtaining a basic index corresponding to each application scenario from the basic index library;

[0140] configuring a degradation strategy of the basic index corresponding to each application scenario;

[0141] filling the 5G network health monitoring model framework according to the basic index corresponding to each application scenario and the degradation strategy of the basic index corresponding to each application scenario, to obtain the 5G network health monitoring model.

[0142] Specifically, the configuration of the degradation strategy of the basic index corresponding to each application scenario includes:

[0143] configuring a degradation standard of the basic index corresponding to each application scenario;

[0144] configuring a deduction value corresponding to each degradation standard.

[0145] Taking the 5G private network layer model as an example, a corresponding index is configured for the 5G private network layer for each type of scenario, and a degradation standard and a deduction value after degradation are set for each index, as shown in the following table, which is an example of an eMBB type private network layer model. Other scenarios can also be configured with corresponding models, which are not described here.

[0146]

[0147] In the constructed model, different degradation strategies are configured for different levels, and the general principle is as follows:

[0148] 1) From the 5G private network layer to the sub-domain layer, and then to the network element device layer, the selection of model parameters follows the principle of from coarse to fine, for example: the 5G private network layer model parameters include the main parameters affecting the private network business, such as delay, uplink / downlink average rate, uplink / downlink PRB occupancy rate, and the failure of key devices affecting the private network, such as base station out-of-service and cell out-of-service; the sub-domain layer and the network element device layer include more and more refined parameters, such as the network element device layer UPF includes the traffic parameters of N3 interface, N6 interface and N9 interface.

[0149] 2) From the 5G private network layer to the sub-domain layer, and then to the network element device layer, the parameter granularity of the model follows the principle of from large to small, for example: the 5G private network layer includes parameters at each sub-domain level and device-level parameters of key devices, and generally does not include more fine-grained parameters, such as cell DU-level parameters; and the network element device layer includes device-level parameters and more fine-grained parameters, such as cell DU-level parameters.

[0150] The calling unit 112 is configured to call the 5G network health monitoring model in the target application scenario as a target model in response to a health monitoring instruction for the 5G network in the target application scenario.

[0151] The health monitoring instruction can be triggered by relevant staff, and the present application does not limit it.

[0152] The collection unit 113 is configured to collect an index value of each index in the target application scenario.

[0153] For example, the AMF system average load value and the AMF authentication request times can be collected.

[0154] The generation unit 114 is configured to generate a health monitoring result according to each index value and the target model.

[0155] In the present embodiment, the generation unit 114 generates a health monitoring result according to each index value and the target model, which includes:

[0156] obtaining the degradation standard and the corresponding deduction value of each index from the target model;

[0157] obtaining the initial score of each index in the target model;

[0158] comparing each index value with the corresponding degradation standard to obtain a comparison result;

[0159] determining at least one target deduction value of each index value from the corresponding deduction value of each index according to the comparison result;

[0160] deducting the corresponding target deduction value on the basis of the initial score of each index in the target model to obtain the target score of each index.

[0161] The target score of each indicator is integrated to obtain the health monitoring result.

[0162] Specifically, when the target deduction value corresponding to each indicator is deducted based on the initial score of each indicator in the target model, if the initial score of an indicator is deducted to a negative number during the deduction process, the target score of the indicator is determined as 0.

[0163] For example, when the health monitoring result is generated, the following principles can be followed:

[0164] 1) The evaluation score is taken as the health monitoring result, and 100 points are taken as the full score and 0 points are taken as the lowest score.

[0165] 2) The initial score is 100 points.

[0166] 3) When the model indicator deteriorates, a certain score, i.e., the deduction value, is deducted.

[0167] 4) The sum of the deduction values of all indicators can be greater than or less than 100 points, but the final evaluation score cannot be lower than 0 points.

[0168] The identification unit 115 is configured to identify a network health deterioration indicator from each indicator according to the health monitoring result.

[0169] In this embodiment, the identification unit 115 identifies a network health deterioration indicator from each indicator according to the health monitoring result, which includes:

[0170] The sum of the target deduction values corresponding to each indicator is calculated to obtain the actual deduction value of each indicator.

[0171] Each indicator is sorted according to the actual deduction value from high to low.

[0172] The indicators ranked in the front of the preset position are obtained as the network health deterioration indicators.

[0173] Specifically, a bit number value is obtained in advance, and the bit number value is determined as the value of the preset position; for example, the preset position can be set as a fixed value such as 3 or 5.

[0174] Or a deduction threshold value is obtained in advance, and the number of indicators whose actual deduction value is greater than or equal to the deduction threshold value is obtained as the value of the preset position. For example, the deduction score threshold value can be set to obtain a dynamic preset position value.

[0175] For example, the way of generating the health monitoring result and identifying the network health deterioration indicator can include:

[0176] 1) Collect, aggregate, and calculate the basic index library indicators of each device in the private network to generate network element device layer indicator data.

[0177] 2) Aggregate, calculate, and correlate the network element device layer indicator data to generate sub-domain layer and 5G private network layer indicator data.

[0178] 3) Calculate the 5G private network layer health degree evaluation score based on the hierarchical 5G network health monitoring model and hierarchical indicator data: set the initial score of the 5G private network health degree to 100 points, and perform indicator degradation determination on each indicator according to the model corresponding to the scene (such as eMBB). If the indicator degrades, the corresponding score is deducted; if the evaluation score is less than 0 after deduction, the evaluation score is recorded as 0 points. After traversing all indicators of the 5G private network layer model of the eMBB scene, the score calculation is completed. At the same time, sort the indicators according to the deduction score from high to low to obtain the sorted indicator set.

[0179] 4) Calculate the health degree evaluation score and topN deduction score of each sub-domain and network element device of the private network, and the processing process is as described in step 3).

[0180] 5) Obtain the topN indicators of the 5G private network layer network health degree degradation indicator topN recommendation from the sorted indicator set calculated in 3). N can be set to a fixed value such as 3, 5, or a dynamic value such as a deduction score threshold to obtain a dynamic N.

[0181] 6) Obtain the network health degree degradation indicator topN of each sub-domain and network element device of the 5G private network from 4).

[0182] As described above, the network health degree evaluation score calculation and degradation indicator recommendation results of each layer are completed for the 5G private network layer, sub-domain layer, and network element device layer.

[0183] Since the network element device layer parameters are more detailed and have smaller granularity than the sub-domain layer parameters, and the sub-domain layer parameters are more detailed and have smaller granularity than the 5G private network layer parameters, the network state of the private network from the whole to the local can be explored, and which parameters are degraded and affected can be determined, and used to guide the 5G private network network operation and maintenance work, from the 5G private network layer to the sub-domain layer, and then to the network element device layer.

[0184] The pushing and displaying unit 116 is configured to push and display the health monitoring result and the network health degradation indicator.

[0185] For example, the health monitoring result and the network health degradation indicator can be pushed to the triggerer of the health monitoring instruction for network improvement.

[0186] The embodiment constructs a 5G private network health degree hierarchical monitoring model, constructs a hierarchical monitoring basic index library, and implements a hierarchical monitoring model for network health degrees in different scenarios, is suitable for 5G private network health degree evaluation in different scenarios, and has good universality.

[0187] The embodiment intuitively, concisely and effectively gives a 5G private network dimension network state evaluation result through the 5G private network layer evaluation score, can enable non-professional operation and maintenance personnel to quickly understand and master the overall state of the private network, and can provide guidance for professional operation and maintenance personnel to understand the overall state of the private network; through the evaluation scores of the sub-domain layer and the network element device layer, the local network state of the 5G private network is presented layer by layer and layer by layer, which provides a qualitative and quantitative professional basis for more professional 5G private network operation and maintenance, is suitable for a wide range of people, and has high value for professional and non-professional 5G private network operation and maintenance personnel.

[0188] As can be seen from the above technical solutions, the present application can construct a 5G network health monitoring model including a 5G private network layer model, a sub-domain layer model and a network element device layer model based on a pre-constructed basic index library, a 5G network health monitoring model framework and an application scenario, and perform 5G network health monitoring based on the 5G network health monitoring model, from the whole to the local, layer by layer, layer by layer, and classifies and evaluates the network health degree, which can not only globally evaluate the network health degree of the 5G private network, but also finely evaluate the network health degree of each sub-domain and each device, and provide comprehensive network health degree real-time evaluation capability for 5G private network operation and maintenance.

[0189] As shown in Figure 5 , it is a structural schematic diagram of a computer device of a preferred embodiment of the present application for realizing the 5G network health monitoring method.

[0190] The computer device 1 can include a memory 12, a processor 13 and a bus, and can also include a computer program stored in the memory 12 and executable on the processor 13, such as a 5G network health monitoring program.

[0191] Those skilled in the art can understand that the schematic diagram is only an example of the computer device 1 and does not constitute a limitation on the computer device 1, the computer device 1 can be a bus type structure or a star type structure, and the computer device 1 can also include more or less other hardware or software or different component arrangements, for example, the computer device 1 can also include an input / output device, a network access device, etc.

[0192] It should be noted that the computer device 1 is only an example, and other existing or future electronic products, such as those adaptable to the present application, should also be included within the protection scope of the present application and included by reference.

[0193] The memory 12 includes at least one type of readable storage medium, such as a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the computer device 1, such as a mobile hard disk of the computer device 1. In other embodiments, the memory 12 can also be an external storage device of the computer device 1, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 12 can include both an internal storage unit and an external storage device of the computer device 1. The memory 12 can be used to store application software and various data installed in the computer device 1, such as the code of the 5G network health monitoring program, etc., and can also be used to temporarily store data that has been output or will be output.

[0194] The processor 13 can be composed of an integrated circuit in some embodiments, such as a single packaged integrated circuit or a plurality of packaged integrated circuits with the same or different functions, including one or more combinations of a central processing unit (CPU), a microprocessor, a digital processing chip, a graphics processor, and various control chips, etc. The processor 13 is the control unit of the computer device 1, which connects various components of the computer device 1 through various interfaces and lines, executes programs or modules stored in the memory 12 (such as the 5G network health monitoring program, etc.), and calls data stored in the memory 12 to perform various functions and process data of the computer device 1.

[0195] The processor 13 executes the operating system and various application programs installed in the computer device 1. The processor 13 executes the application programs to implement the steps in each of the above 5G network health monitoring method embodiments, such as Figure 1 the steps shown in the above embodiments.

[0196] The computer program can be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete the present application. The one or more modules / units can be a series of computer-readable instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the computer device 1. For example, the computer program can be divided into an acquisition unit 110, a construction unit 111, a calling unit 112, a collection unit 113, a generation unit 114, an identification unit 115, and a pushing and display unit 116.

[0197] The integrated units in the form of software function modules described above can be stored in a computer-readable storage medium. The software function modules described above are stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a computer device, or a network device, etc.) or a processor to execute part of the 5G network health monitoring method described in various embodiments of the present application.

[0198] The modules / units integrated in the computer device 1, if implemented in the form of software function modules and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiments of the present application can also be instructed by a computer program to complete related hardware devices, and the computer program can be stored in a computer-readable storage medium. When the processor executes the computer program, the steps of each method embodiment described above can be implemented.

[0199] The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, etc.

[0200] Further, the computer-readable storage medium can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function, etc.; and the data storage area can store data created according to the use of the blockchain node, etc.

[0201] The blockchain referred to in the present application is a new application mode of distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm and other computer technologies. Blockchain, in essence, is a decentralized database, which is a series of data blocks associated using cryptographic methods, each data block containing a batch of network transaction information for verifying the validity (anti-fake) of the information and generating the next block. The blockchain can include a blockchain underlying platform, a platform product service layer, and an application service layer, etc.

[0202] The bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one straight line is used in the Figure 5 However, it does not mean that there is only one bus or only one type of bus. The bus is arranged to realize the connection and communication between the memory 12, the at least one processor 13, etc.

[0203] Although not shown, the computer device 1 can also include a power supply (such as a battery) for powering the various components. Preferably, the power supply can be logically connected to the at least one processor 13 through a power management device, so as to realize functions such as charge management, discharge management, and power consumption management through the power management device. The power supply can also include one or more direct current or alternating current power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. Any components. The computer device 1 can also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described here.

[0204] Further, the computer device 1 can also include a network interface, which can optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used to establish a communication connection between the computer device 1 and other computer devices.

[0205] Optionally, the computer device 1 can further include a user interface, which can be a display, an input unit such as a keyboard, and optionally, a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. The display can also be appropriately referred to as a display screen or a display unit, for displaying information processed in the computer device 1 and for displaying a visualized user interface.

[0206] It should be understood that the embodiments are only for illustration and are not limited in the scope of the patent application by the structure.

[0207] Figure 5 Only the computer device 1 with components 12-13 is shown, and those skilled in the art can understand that, Figure 5 The structure shown does not constitute a limitation on the computer device 1, and can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0208] In combination Figure 1 The memory 12 in the computer device 1 stores a plurality of instructions to implement a 5G network health monitoring method, and the processor 13 can execute the plurality of instructions to implement:

[0209] Obtaining a pre-constructed basic index library, obtaining a pre-constructed 5G network health monitoring model framework, and obtaining at least one application scenario of a 5G network; wherein the 5G network health monitoring model framework includes a 5G private network layer model framework, a sub-domain layer model framework, and a network element device layer model framework;

[0210] In each application scenario, a 5G network health monitoring model is constructed according to the basic index library and the 5G network health monitoring model framework; wherein the 5G network health monitoring model includes a 5G private network layer model, a sub-domain layer model, and a network element device layer model;

[0211] In response to a health monitoring instruction for a 5G network in a target application scenario, the 5G network health monitoring model in the target application scenario is called as a target model;

[0212] Collecting an index value of each index in the target application scenario;

[0213] Generating a health monitoring result according to each index value and the target model;

[0214] Identifying a network health degradation index from each index according to the health detection result;

[0215] push and display the health monitoring result and the network health degradation indicator.

[0216] Specifically, the processor 13 can refer to the specific implementation method of the above instructions Figure 1 The description of the related steps in the corresponding embodiments will not be repeated here.

[0217] It should be noted that the data involved in the present case are all legally obtained.

[0218] In several embodiments provided by the present application, it should be understood that the disclosed system, device and method can be implemented by other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there can be another division way in actual implementation.

[0219] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present 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. The present application can also be practiced in a distributed computing environment, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0220] The modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical units, i.e. they can be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment.

[0221] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically independently, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of hardware plus software functional module.

[0222] It will be obvious to a person skilled in the art that the application is not limited to the details of the above-described exemplary embodiments but can be implemented in other embodiments without departing from the scope of the application.

[0223] The embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the above description, all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. No single feature or combination of features should be considered essential unless expressly stated in the claims.

[0224] Moreover, the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural and vice-versa, unless expressly stated otherwise. The use of the term "comprising" in the claims does not exclude other elements or steps than those listed in the claims. The use of the term "comprising" also covers the case where the elements or steps are "consisting of" the elements or steps listed in the claims.

[0225] Finally, it should be noted that the above-mentioned embodiments illustrate rather than limit the application, since the scope of the application is to be determined by the appended claims.

Claims

1. A 5G network health monitoring method, characterized in that, The 5G network health monitoring method comprises: acquiring a pre-constructed basic index library, acquiring a pre-constructed 5G network health monitoring model framework, and acquiring at least one application scenario of a 5G network; wherein the 5G network health monitoring model framework comprises a 5G private network layer model framework, a sub-domain layer model framework, and a network element device layer model framework; under each application scenario, constructing a 5G network health monitoring model according to the basic index library and the 5G network health monitoring model framework; wherein the 5G network health monitoring model comprises a 5G private network layer model, a sub-domain layer model, and a network element device layer model; in response to a health monitoring instruction for a 5G network in a target application scenario, calling the 5G network health monitoring model in the target application scenario as a target model; collecting index values of each index in the target application scenario; generating a health monitoring result according to each index value and the target model; identifying a network health degradation index from each index according to the health monitoring result; pushing and displaying the health monitoring result and the network health degradation index; wherein each layer model comprises three dimensions of fault, load, and service; the fault dimension comprises alarm level and alarm quantity; the load dimension comprises system load, service load, and resource load; and the service dimension of different types of network element devices comprises different service categories.

2. The 5G network health monitoring method of claim 1, wherein, The method of constructing a 5G network health monitoring model according to the basic index library and the 5G network health monitoring model framework under each application scenario comprises: acquiring basic indexes corresponding to each application scenario from the basic index library; configuring a degradation strategy of the basic indexes corresponding to each application scenario; filling the 5G network health monitoring model framework according to the basic indexes corresponding to each application scenario and the degradation strategy of the basic indexes corresponding to each application scenario to obtain the 5G network health monitoring model.

3. The 5G network health monitoring method of claim 2, wherein, The method of configuring a degradation strategy of the basic indexes corresponding to each application scenario comprises: configuring a degradation standard of the basic indexes corresponding to each application scenario; configuring a deduction value corresponding to each degradation standard.

4. The 5G network health monitoring method of claim 3, wherein, The method of generating a health monitoring result according to each index value and the target model comprises: acquiring the degradation standard and the corresponding deduction value of each index from the target model; acquiring an initial score of each index in the target model; comparing each index value with the corresponding degradation standard to obtain a comparison result; determining at least one target deduction value of each index value from the corresponding deduction value of each index according to the comparison result; deducting the corresponding target deduction value on the basis of the initial score of each index in the target model to obtain a target score of each index; integrating the target scores of each index to obtain the health monitoring result.

5. The 5G network health monitoring method of claim 4, wherein, When deducting the corresponding target deduction value on the basis of the initial score of each index in the target model, the method further comprises: during the deduction process, when the initial score of an index is deducted to a negative number, the target score of the index is determined as 0.

6. The 5G network health monitoring method of claim 4, wherein, The method of identifying a network health degradation index from each index according to the health monitoring result comprises: Sum the target deduction values corresponding to each indicator to obtain an actual deduction value of each indicator; Sort each indicator according to the actual deduction value from high to low; Obtain the indicators ranked in the front of the preset position as the network health degradation indicators.

7. The 5G network health monitoring method of claim 6, wherein, The method further comprises: Obtaining a pre-configured position value and determining the position value as the value of the preset position; or Obtaining a pre-configured deduction threshold, and obtaining the number of indicators whose actual deduction values are greater than or equal to the deduction threshold as the value of the preset position. 8.A 5G network health monitoring apparatus, characterized in that, The 5G network health monitoring device comprises: An obtaining unit configured to obtain a pre-configured basic indicator library, a pre-configured 5G network health monitoring model framework, and at least one application scenario of a 5G network; wherein the 5G network health monitoring model framework comprises a 5G private network layer model framework, a sub-domain layer model framework, and a network element device layer model framework; A constructing unit configured to construct a 5G network health monitoring model according to the basic indicator library and the 5G network health monitoring model framework in each application scenario; wherein the 5G network health monitoring model comprises a 5G private network layer model, a sub-domain layer model, and a network element device layer model; A calling unit configured to call the 5G network health monitoring model in a target application scenario as a target model in response to a health monitoring instruction of the 5G network in the target application scenario; An acquiring unit configured to acquire an indicator value of each indicator in the target application scenario; A generating unit configured to generate a health monitoring result according to each indicator value and the target model; An identifying unit configured to identify a network health degradation indicator from each indicator according to the health monitoring result; A pushing and displaying unit configured to push and display the health monitoring result and the network health degradation indicator. Each layer model comprises three dimensions of fault, load, and service; the fault dimension comprises an alarm level and an alarm number; the load dimension comprises system load, service load, and resource load; and the service dimension of different types of network element devices comprises different service categories.

9. A computer device, comprising: The computer device comprises: A memory configured to store at least one instruction; and A processor configured to execute the instruction stored in the memory to implement the 5G network health monitoring method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in a computer device to implement the 5G network health monitoring method according to any one of claims 1 to 7.

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