WO2024066770A9

WO2024066770A9 - Information acquisition method and apparatus, and storage medium

Info

Publication number: WO2024066770A9
Application number: PCT/CN2023/112918
Authority: WO
Inventors: 牛煜霞; 赵嵩
Original assignee: 中国电信股份有限公司
Priority date: 2022-09-26
Filing date: 2023-08-14
Publication date: 2024-05-02
Also published as: WO2024066770A1; CN117768937A

Abstract

The present disclosure relates to the technical field of communications. Provided are an information acquisition method and apparatus, and a storage medium. The information acquisition method in the present disclosure comprises: acquiring interaction statistical information of a target network entity, wherein the interaction statistical information comprises at least one of the number of requests received by the target network entity and the number of responses of the target network entity; and determining a performance parameter of the target network entity according to the interaction statistical information. By means of the method, the management capability of a network analysis service is improved.

Description

Information acquisition method, device and storage medium

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on the application with CN application number 202211174434.4 and application date September 26, 2022, and claims its priority. The disclosed content of the CN application is hereby introduced as a whole into this application.

Technical Field

The present disclosure relates to the field of communication technology, and in particular to an information acquisition method, device and storage medium.

Background technique

The NWDAF (Network Data Analytics Function) entity is a network element in the 5GC (5G Core), which supports collecting data from NFs (Network Functions), AFs (Application Functions) and OAM (Operation Administration and Maintenance), and provides analysis information to NFs, AFs and OAM.

The services that the NWDAF entity can provide include analysis services, data management services, and ML (Machine Learning) model-related services.

Summary of the invention

One purpose of the present disclosure is to propose a method for obtaining performance parameters of network entities to improve the management capability of network analysis services.

According to one aspect of some embodiments of the present disclosure, a method for obtaining information is proposed, comprising: obtaining interaction statistical information of a target network entity, the interaction statistical information comprising at least one of the number of requests received by the target network entity or the number of responses of the target network entity; and determining performance parameters of the target network entity based on the interaction statistical information.

In some embodiments, the performance parameter includes at least one of a request success ratio, a service success ratio, a request failure ratio, a service failure ratio, and a service type ratio.

In some embodiments, the service type includes at least one of an analysis service, a data management service, or a model-related service.

In some embodiments, the performance parameters include at least one of a request success rate, a service success rate, a request failure rate, a service failure rate, and a service type ratio, wherein the service type includes at least one of an analysis service, a data management service, or a model-related service.

In some embodiments, the number of requests includes a composite number of request receptions; the number of responses includes a composite number of response transmissions; and the performance parameter includes a composite rate of service success.

In some embodiments, the method complies with at least one of the following: the number of requests also includes at least one of the comprehensive number of request acceptances, the comprehensive number of request rejections, the number of request receptions corresponding to the service type, the number of request acceptances corresponding to the service type, or the number of request rejections corresponding to the service type; or the number of responses also includes at least one of the comprehensive number of successful responses, the comprehensive number of error responses, the number of response sendings corresponding to the service type, the number of successful responses corresponding to the service type, or the number of error responses corresponding to the service type.

In some embodiments, the method complies with at least one of the following: the request success ratio includes at least one of the comprehensive request success ratio, the request success ratio of the analysis service, the request success ratio of the data management service, or the request success ratio of the model-related service; the service success ratio includes at least one of the comprehensive service success ratio, the service success ratio of the analysis service, the service success ratio of the data management service, or the service success ratio of the model-related service; the request failure ratio includes at least one of the comprehensive request failure ratio, the request failure ratio of the analysis service, the request failure ratio of the data management service, or the request failure ratio of the model-related service; or the service failure ratio includes at least one of the comprehensive service failure ratio, the service failure ratio of the analysis service request, the service failure ratio of the data management service, or the service failure ratio of the model-related service.

In some embodiments, the method also includes: determining a filtering condition, the filtering condition includes at least one of a network slice identifier or a network analysis identifier; obtaining interaction statistical information of the target network entity includes: obtaining interaction statistical information of the target network entity that meets the filtering condition; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining the performance parameters of the target network entity under the filtering condition based on the interaction statistical information.

In some embodiments, obtaining interaction statistics of the target network entity includes: obtaining at least two types of interaction statistics through a counter; determining the performance parameters of the target network entity according to the interaction statistics includes: obtaining at least one performance parameter according to the relationship between the at least two types of interaction statistics.

In some embodiments, obtaining interaction statistics of the target network entity includes: obtaining a comprehensive number of request receptions and a comprehensive number of request acceptances to the target network entity; determining a performance parameter of the target network entity based on the interaction statistics includes at least one of the following: determining a comprehensive request success ratio based on a ratio of a comprehensive number of request acceptances to a comprehensive number of request receptions; or determining a comprehensive request success ratio based on a ratio of a comprehensive number of request acceptances to a comprehensive number of request receptions, and determining a comprehensive request failure ratio based on the comprehensive request success ratio, wherein the sum of the comprehensive request success ratio and the comprehensive request failure ratio is 1.

In some embodiments, obtaining interaction statistical information of the target network entity includes: obtaining a comprehensive number of request receptions and a comprehensive number of request rejections for the target network entity; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining a comprehensive request failure ratio based on a ratio of a comprehensive number of request rejections to a comprehensive number of request receptions; or determining a comprehensive request failure ratio based on a ratio of a comprehensive number of request rejections to a comprehensive number of request receptions, and determining a comprehensive request success ratio based on the comprehensive request failure ratio, wherein the sum of the comprehensive request success ratio and the comprehensive request failure ratio is 1.

In some embodiments, obtaining the interaction statistical information of the target network entity includes: obtaining the comprehensive number of successful responses of the target network entity, and obtaining the comprehensive number of responses sent or the comprehensive number of requests received to the target network entity; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining the comprehensive service success ratio based on the ratio of the comprehensive number of successful responses to the comprehensive number of responses sent or the comprehensive number of requests received; or determining the comprehensive service success ratio based on the ratio of the comprehensive number of successful responses to the comprehensive number of responses sent or the comprehensive number of requests received, and determining the comprehensive service failure ratio based on the comprehensive service success ratio, wherein the sum of the comprehensive service success ratio and the comprehensive service failure ratio is 1.

In some embodiments, obtaining the interaction statistical information of the target network entity includes: obtaining the comprehensive number of error responses of the target network entity, and obtaining the comprehensive number of responses sent or the comprehensive number of requests received to the target network entity; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining the comprehensive service failure ratio based on the ratio of the comprehensive number of error responses to the comprehensive number of responses sent or the comprehensive number of requests received; or determining the comprehensive service failure ratio based on the ratio of the number of error responses to the comprehensive number of responses sent or the comprehensive number of requests received, and determining the comprehensive service success ratio based on the comprehensive service failure ratio, wherein the sum of the comprehensive service success ratio and the comprehensive service failure ratio is 1.

In some embodiments, obtaining interaction statistics of the target network entity includes: obtaining the number of request receptions of a first type of service of the target network entity and the number of request acceptances of the first type of service; determining the performance parameters of the target network entity based on the interaction statistics includes at least one of the following: determining a request success ratio of the first type of service based on a ratio of the number of request acceptances of the first type of service to the number of request receptions of the first type of service; or determining a request success ratio of the first type of service based on a ratio of the number of request acceptances of the first type of service to the number of request receptions of the first type of service, and determining a request failure ratio of the first type of service based on the request success ratio of the first type of service, wherein the sum of the request success ratio of the first type of service and the request failure ratio of the first type of service is 1, and the first type of service includes an analysis service, a data management service, or a model-related service.

In some embodiments, obtaining interaction statistics of the target network entity includes: obtaining the number of request receptions and the number of request rejections of the first type of service of the target network entity; determining the performance parameters of the target network entity based on the interaction statistics includes at least one of the following: determining the request failure ratio of the first type of service based on the ratio of the number of request rejections of the first type of service to the number of request receptions of the first type of service; or determining the request failure ratio of the first type of service based on the ratio of the number of request rejections of the first type of service to the number of request receptions of the first type of service, and determining the request success ratio of the first type of service based on the request failure ratio of the first type of service, wherein the sum of the request success ratio and the request failure ratio of the first type of service is 1, and the first type of service includes an analysis service, a data management service, or a model-related service.

In some embodiments, obtaining interaction statistical information of the target network entity includes: obtaining the number of successful responses of a second type of service of the target network entity, and obtaining the number of responses sent for the second type of service or the number of requests received for the second type of service of the target network entity; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining the service success ratio of the second type of service based on the ratio of the number of successful responses to the second type of service and the number of responses sent or the number of requests received for the second type of service; or determining the service success ratio of the second type of service based on the number of successful responses to the second type of service and the ratio of the number of responses sent or the number of requests received for the second type of service, and determining the service failure ratio of the second type of service based on the service success ratio of the second type of service, wherein the sum of the service success ratio of the second type of service and the service failure ratio of the second type of service is 1, and the second type of service includes an analysis service, a data management service, or a model-related service.

In some embodiments, obtaining interaction statistical information of the target network entity includes: obtaining the number of error responses of a second type of service of the target network entity, and obtaining the number of responses sent for the second type of service or the number of requests received for the second type of service of the target network entity; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining the service failure ratio of the second type of service based on the ratio of the number of error responses to the second type of service and the number of responses sent or the number of requests received for the second type of service; or determining the service failure ratio of the second type of service based on the number of error responses to the second type of service and the ratio of the number of responses sent or the number of requests received for the second type of service, and determining the service success ratio of the second type of service based on the service failure ratio of the second type of service, wherein the sum of the service success ratio and the service failure ratio of the second type of service is 1, and the second type of service includes analysis services, data management services, or model-related services.

In some embodiments, obtaining interaction statistical information of the target network entity includes: obtaining the comprehensive number of request receptions of the target network entity, and the number of request receptions of a third type of service; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining the proportion of the third type of service based on the ratio of the number of request receptions of the third type of service to the comprehensive number of request receptions, wherein the third type of service includes an analysis service, a data management service, or a model-related service.

In some embodiments, the method further includes: evaluating the performance of the target network entity based on performance parameters, including at least one of the following: determining the operating status of the target network entity based on at least one of a request success ratio, a service success ratio, a request failure ratio, or a service failure ratio; or determining the resource occupancy status of a service of a corresponding service type for the target network entity based on a request ratio of the service type.

In some embodiments, the method further includes at least one of the following: determining at least one of resource configuration rationality, task allocation rationality or fault status of the target network entity based on the operating status of the target network entity; or allocating resources to the target network entity based on the resource occupancy status.

In some embodiments, the method also includes: determining the target service type; obtaining interaction statistical information of the target network entity includes: obtaining interaction statistical information related to the target service type; determining the performance parameters of the target network entity based on the interaction statistical information includes: determining the performance parameters related to the target service type of the target network entity based on the interaction statistical information related to the target service type.

In some embodiments, the method complies with at least one of the following: the number of requests includes the number of at least one of service requests or service subscriptions; or the number of responses includes the number of at least one of service responses or subscription notifications.

In some embodiments, the method further includes: obtaining a performance analysis request, wherein obtaining interaction statistics of the target network entity is performed under the triggering of the performance analysis request; and sending the determined performance parameters to one or more network elements.

In some embodiments, the target network entity includes an entity having a network data analysis function.

According to one aspect of some embodiments of the present disclosure, an information acquisition device is proposed, including: a statistical information acquisition unit, configured to obtain interaction statistical information of a target network entity, the interaction statistical information including at least one of the number of requests received by the target network entity or the number of responses of the target network entity; a performance parameter determination unit, configured to determine the performance parameters of the target network entity based on the interaction statistical information.

In some embodiments, the device also includes: a performance evaluation unit configured to evaluate the performance of the target network based on performance parameters, including at least one of the following: determining the operating status of the target network based on at least one of the request success ratio, service success ratio, request failure ratio or service failure ratio; or determining the resource occupancy status of the target network by the service of the corresponding service type based on the request ratio of the service type.

In some embodiments, the device also includes at least one of the following: a state analysis unit, configured to determine at least one of the rationality of resource configuration, rationality of task allocation or fault status of the target network based on the operating status of the target network; or a resource allocation unit, configured to allocate resources to the target network entity based on the resource occupancy status.

In some embodiments, the device also includes: a type determination unit configured to determine the target service type; a statistical information acquisition unit configured to acquire interaction statistical information related to the target service type; and a performance parameter determination unit configured to determine performance parameters related to the target service type of the target network entity based on the interaction statistical information related to the target service type.

In some embodiments, the device further includes: a receiving unit configured to obtain a performance analysis request and trigger the statistical information acquisition unit to operate according to the performance analysis request; and a sending unit configured to send the determined performance parameters to one or more network elements.

According to one aspect of some embodiments of the present disclosure, an information acquisition device is proposed, including: a memory; and a processor coupled to the memory, wherein the processor is configured to execute any one of the information acquisition methods mentioned above based on instructions stored in the memory.

According to one aspect of some embodiments of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored, and when the instructions are executed by a processor, the steps of any one of the information acquisition methods mentioned above are implemented.

According to one aspect of some embodiments of the present disclosure, a computer program is proposed, for causing a processor to execute any one of the information acquisition methods mentioned above.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described herein are used to provide further understanding of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute improper limitations on the present disclosure.

FIG. 1 is a flow chart of some embodiments of the information acquisition method disclosed herein.

FIG. 2 is a flow chart of other embodiments of the information acquisition method disclosed herein.

FIG3 is a schematic diagram of some embodiments of network elements targeted by the information acquisition method of the present disclosure.

FIG. 4 is a flow chart of some further embodiments of the information acquisition method disclosed herein.

FIG. 5 is a schematic diagram of some embodiments of the information acquisition device disclosed herein.

FIG. 6 is a schematic diagram of some other embodiments of the information acquisition device disclosed in the present invention.

FIG. 7 is a schematic diagram of some further embodiments of the information acquisition device disclosed herein.

Detailed ways

The technical solution of the present disclosure is further described in detail below through the accompanying drawings and embodiments.

The inventors have discovered that when a NWDAF entity in the related art provides services, due to the mismatch between the needs of service consumers and the processing capabilities of the NWDAF entity, service failure or low user experience may occur.

In view of the above problems, the information acquisition method and device disclosed in the present invention enable the performance of the NWDAF entity to be evaluated, thereby providing a data basis for determining whether the NWDAF entity can provide services.

The flowchart of some embodiments of the information acquisition method of the present disclosure is shown in Figure 1. In some embodiments, the information acquisition method of the present disclosure can be executed by the target network entity, or by a service consumer or service producer entity, or by other network entities that have information interaction functions with the target network entity.

In step 130, the interaction statistics information of the target network entity is obtained. In some embodiments, the target network entity includes a network entity with a network data analysis function, such as a NWDAF entity.

In some embodiments, if the information acquisition method is executed by the target network entity itself, the interaction statistical information can be obtained by monitoring its own behavior; if the information acquisition method is executed by a service producer, the interaction statistical information can be obtained by collecting messages sent and received by the target network entity through the service producer, or by monitoring the target network entity; if the information acquisition method is executed by a service consumer or other network entity that has information interaction function with the target network entity, it can be achieved by monitoring the target network entity.

In some embodiments, the interaction statistics include at least one of the number of requests received by the target network entity or the number of responses of the target network entity. In some embodiments, the number of requests may include the number of request receptions, i.e., the number of requests received by the target network entity, and may also include the number of request acceptances, i.e., the number of times the target network entity determines to provide the corresponding service after receiving the request. In some embodiments, the number of responses may include the number of successful responses, i.e., the responses sent when the service is successful; the number of responses may also include the number of error responses, i.e., the responses sent when the service fails.

In some embodiments, the service types provided by the target network entity may include one or more of analysis services, data management services, or model-related services, and the interaction statistics information may be a comprehensive count of the number of various service types, or a sub-type count of the number of times for each service type. In some embodiments, the above-mentioned model-related services are ML model-related services.

In some embodiments, the number of requests may include the number of at least one of service requests or service subscriptions. In some embodiments, the number of responses may include the number of at least one of service responses or subscription notifications.

In some embodiments, CC (Cumulative Counter) can be used to count the number of requests and responses, and the counter performs a "+1" operation on the requests or responses it counts to ensure the accuracy of the interaction statistics. In some embodiments, a counter can be set for each number of times that need to be counted to further ensure the accuracy of the interaction statistics.

In step 140, the performance parameter of the target network entity is determined according to the interaction statistical information. In some embodiments, at least one performance parameter may be obtained according to a relationship, such as a proportional relationship, between at least two types of interaction statistical information.

In some embodiments, the performance parameter may include at least one of a request success rate, a service success rate, a request failure rate, a service failure rate, and a service type ratio. The service type ratio may include at least one of an analysis service ratio, a data management service, or a model-related service ratio.

In some embodiments, the above-mentioned request success ratio, service success ratio, request failure ratio, and service failure ratio may also be ratio values for one or more service types. For example, the request success ratio includes at least one of the request success comprehensive ratio, the request success ratio of the analysis service, the request success ratio of the data management service, or the request success ratio of the model-related service; the service success ratio includes at least one of the service success comprehensive ratio, the service success ratio of the analysis service, the service success ratio of the data management service, or the service success ratio of the model-related service; the request failure ratio includes at least one of the request failure comprehensive ratio, the request failure ratio of the analysis service, the request failure ratio of the data management service, or the request failure ratio of the model-related service; the service failure ratio includes at least one of the service failure comprehensive ratio, the service failure ratio of the analysis service request, the service failure ratio of the data management service, or the service failure ratio of the model-related service.

In some embodiments, when the number of requests includes the comprehensive number of request receptions (the number of request receptions regardless of service type), and the number of responses includes the comprehensive number of response transmissions (the number of response transmissions regardless of service type), the performance parameter may include a comprehensive request success ratio and may also include a comprehensive service success ratio. In some embodiments, the comprehensive service success ratio may be the ratio of the comprehensive response transmission times to the comprehensive request success ratio.

Based on the method in the above embodiment, the performance of the network entity can be evaluated by collecting the number of requests and responses of the network entity, thereby realizing the quantification of the performance of the network entity, providing a data basis for the scheduling of subsequent requests and the allocation of service resources, and improving the management capabilities of the network analysis service.

In some embodiments, as shown in FIG. 1 , the information acquisition method may further include step 150 .

In step 150, the performance of the target network entity is evaluated according to the performance parameter.

In some embodiments, the performance of the target network entity may include the operating state of the target network entity. In some embodiments, the operating state of the target network entity may be determined based on at least one of the request success rate, service success rate, request failure rate, or service failure rate. For example, if the request and service success rate of the target network entity is low and the failure rate is high, the target network entity may be in an abnormal state and is not suitable for continuing to provide services; if the success rate is high and the failure rate is low, it is in a normal operating state and can continue to provide services. In some embodiments, the rationality of the resource configuration of the target network entity may also be determined based on the operating state of the target network entity. For example, when the failure rate exceeds a threshold, the resource configuration for the target network entity may be adjusted; in some embodiments, the rationality of the task allocation of the target network entity may also be determined based on the operating state of the target network entity. For example, when the failure rate of a certain type or several types of services exceeds a threshold, reduce or avoid scheduling this type of service to the target network entity.

In some embodiments, the performance of the target network entity may include a resource occupancy status of the target network entity. In some embodiments, the resource type and amount occupied by each type of service can be preconfigured, and then the resource occupation status of the service of the corresponding service type to the target network entity is determined according to the request ratio of the service type. In some embodiments, resources can be allocated to the target network entity according to the resource occupation status, such as allocating one or more of storage resources, computing resources, etc.

In some embodiments, by evaluating the success or failure of the target type service, the working status or performance of the target network entity providing various types of services can be understood. For example, if the failure rate of the analysis service is relatively high, while the failure rates of other types of services are not high, it means that the target network entity is currently not performing well in providing the analysis service. At this time, the manager needs to find out the problem and solve it to improve the performance of the target network entity in providing the analysis service. Therefore, by evaluating the success or failure of the target type service, the working status of the target network entity in providing various types of services can be understood in a timely manner, providing necessary references for the performance management of the target network entity.

In some embodiments, by evaluating the situation of the target type service request, the workload of the target network entity providing various types of services can be understood. For example, if the ratio of model training service requests is relatively high, while the ratio of other types of service requests is not high, it means that the current main task of the target network entity is model training service, and more computing resources are needed to provide the service. At this time, the manager can adjust the resource allocation plan to improve the performance of the target network entity in providing services. Therefore, by evaluating the situation of the target type service request, the working status of the target network entity when providing various types of services can be understood in a timely manner, providing necessary references for the performance management of the target network entity.

Based on the method in the above embodiment, the performance of the network entity can be evaluated based on its performance parameters, and then the evaluation results can be used to make targeted adjustments to the service request or network entity resources, thereby improving the service level of the target network entity and the success rate of the network service request; it can also reduce unnecessary consumption of the target network entity resources due to attempts with a high failure rate, thereby improving the effective utilization of network entity resources.

In some embodiments, the above-mentioned request times may include, in addition to the comprehensive number of request receptions, at least one of the comprehensive number of request acceptances, the comprehensive number of request rejections, the number of request receptions corresponding to the service type, the number of request acceptances corresponding to the service type, or the number of request rejections corresponding to the service type. In some embodiments, the above-mentioned response times may include, in addition to the comprehensive number of response transmissions, at least one of the comprehensive number of successful responses, the comprehensive number of error responses, the number of response transmissions corresponding to the service type, the number of successful responses corresponding to the service type, or the number of error responses corresponding to the service type.

Based on the method in the above embodiment, more detailed interaction statistical information can be obtained, and then performance parameters of more dimensions can be obtained, thereby improving the performance evaluation capability of the target network entity.

In some embodiments, in the above step 130, a variety of interaction statistical information may be obtained, and then in step 140, performance parameters of multiple dimensions may be obtained, which may be specifically as follows.

[For request success rate and request failure rate]

In some embodiments, without considering the service type corresponding to the request, the request success rate and request failure rate of various service types can be obtained.

In some embodiments, in the above step 130, the comprehensive number of request receptions and the comprehensive number of request acceptances to the target network entity may be obtained, and then in the above step 140, the comprehensive request success ratio is determined according to the ratio of the comprehensive number of request acceptances to the comprehensive number of request receptions, for example:

The overall ratio of successful requests = the overall number of accepted requests/the overall number of received requests.

In some embodiments, in the above step 130, the comprehensive number of request receptions and the comprehensive number of request rejections for the target network entity may be obtained, and then in the above step 140, the comprehensive request failure ratio may be determined according to the ratio of the comprehensive number of request rejections to the comprehensive number of request receptions, for example:

The total request failure rate = the total number of request rejections/the total number of request receptions.

By using such a method, the ratio of requests of the target network entity being accepted or rejected can be obtained, which helps to understand the busy, idle or fault state of the target network entity based on the parameter.

In some embodiments, in the above step 130, one of the comprehensive number of request acceptances and the comprehensive number of request rejections can be selected, and after obtaining one of the comprehensive ratio of request success and the comprehensive ratio of request failures through proportional calculation, the other item is determined based on the relationship between the comprehensive ratio of request success and the comprehensive ratio of request failures. For example, after determining the comprehensive ratio of request failures, the comprehensive ratio of request success is determined according to the comprehensive ratio of request success = 1-comprehensive ratio of request failures; or after determining the comprehensive ratio of request success, the comprehensive ratio of request failures is determined according to the comprehensive ratio of request failure = 1-comprehensive ratio of request success.

Through this method, the relationship between performance parameters can be used to obtain success and failure parameters, reduce the amount of data that needs to be counted, and reduce the data statistics burden of the device.

In some embodiments, for one or more service types, request success ratios and request failure ratios corresponding to the service types may be obtained. The above service types include analysis, data management, or model-related service types.

In some embodiments, in step 130, the number of times the target network entity receives analysis service requests and the number of times the analysis service requests are accepted are obtained; in step 140, the request success ratio of the analysis service is determined based on the ratio of the number of times the analysis service requests are accepted to the number of times the analysis service requests are received, such as:

Analysis service request success rate = number of analysis service request acceptances/number of analysis service request receptions.

In some embodiments, in step 130, the number of requests received for the analysis service and the number of requests rejected for the analysis service of the target network entity are obtained; in step 140, the request failure ratio of the analysis service is determined according to the ratio of the number of requests rejected for the analysis service to the number of requests received for the analysis service, such as:

Analysis service request failure rate = number of analysis service request rejections/number of analysis service request receptions.

Through such a method, the ratio of accepted or rejected requests for analysis services of the target network entity can be obtained, which helps to understand the service acceptance status of the target network entity for the analysis service type based on this parameter.

In some embodiments, in the above step 130, either the number of request rejections for the analysis service or the number of request acceptances for the analysis service can be selectively obtained. After obtaining one of the request failure ratio of the analysis service and the request success ratio of the analysis service through proportional calculation, the other item is determined based on the relationship between the request failure ratio of the analysis service and the request success ratio of the analysis service. For example, after determining the request failure ratio of the analysis service, the request success ratio of the analysis service is determined based on the analysis service request success ratio = 1-the analysis service request failure ratio; or after determining the analysis service request success ratio, the analysis service request failure ratio is determined based on the analysis service request failure ratio = 1-the analysis service request success ratio.

In some embodiments, in step 130, the number of requests received by the target network entity for the data management service and the number of requests accepted by the data management service are obtained; in step 140, the request success ratio of the data management service is determined according to the ratio of the number of requests accepted by the data management service and the number of requests received by the data management service, such as:

Data management service request success rate = number of data management service request acceptance times / number of data management service request reception times.

In some embodiments, in step 130, the number of requests received by the target network entity for the data management service and the number of requests rejected by the data management service are obtained; in step 140, the request failure ratio of the data management service is determined according to the ratio of the number of requests rejected by the data management service to the number of requests received by the data management service, such as:

The request failure rate of the data management service = the number of requests rejected by the data management service / the number of requests received by the data management service.

By using such a method, the ratio of accepted or rejected requests for data management services of the target network entity can be obtained, which helps to understand the service acceptance status of the target network entity for the data management service type based on the parameter.

In some embodiments, in the above step 130, either the number of request rejections for the data management service or the number of request acceptances for the data management service can be selectively obtained. After obtaining one of the request failure ratio of the data management service and the request success ratio of the data management service through proportional calculation, the other item is determined based on the relationship between the request failure ratio of the data management service and the request success ratio of the data management service. For example, after determining the request failure ratio of the data management service, the request success ratio of the data management service is determined according to the request success ratio of the data management service = 1-the request failure ratio of the data management service; or after determining the request success ratio of the data management service, the request failure ratio of the data management service is determined according to the request failure ratio of the data management service = 1-the request success ratio of the data management service.

In some embodiments, in step 130, the number of model-related service request receptions and the number of model-related service request acceptances of the target network entity are obtained; in step 140, the request success ratio of the model-related service is determined according to the ratio of the number of model-related service request acceptances and the number of model-related service request receptions, such as:

Model-related service request success rate = number of model-related service request acceptances/number of model-related service request receptions.

In some embodiments, in step 130, the number of model-related service request receptions and the number of model-related service request rejections of the target network entity are obtained; in step 140, the model-related service request failure ratio is determined based on the ratio of the number of model-related service request rejections to the number of model-related service request receptions, such as:

Model-related service request failure rate = number of model-related service request rejections/number of model-related service request receptions.

By using such a method, the ratio of accepted or rejected requests for model-related services of the target network entity can be obtained, which helps to understand the service acceptance status of the target network entity for the model-related service type based on this parameter.

In some embodiments, in the above step 130, either the number of request rejections for model-related services or the number of request acceptances for model-related services can be selectively obtained. After obtaining one of the request failure rate of the model-related services and the request success rate of the model-related services through proportional calculation, the other item is determined based on the relationship between the request failure rate of the model-related services and the request success rate of the model-related services. For example, after determining the request failure rate of the model-related services, the request success rate of the model-related services is determined according to the request success rate of the model-related services = 1-the request failure rate of the model-related services; or after determining the request success rate of the model-related services, the request failure rate of the model-related services is determined according to the request failure rate of the model-related services = 1-the request success rate of the model-related services.

【For service success rate and service failure rate】

In some embodiments, without considering the service type corresponding to the request, the service success rate and service failure rate of various service types can be obtained.

In some embodiments, in the above step 130, the comprehensive number of successful responses of the target network entity and the comprehensive number of responses sent or the comprehensive number of requests received to the target network entity may be obtained, and then in step 140, the comprehensive service success ratio is determined according to the ratio of the comprehensive number of successful responses to the comprehensive number of responses sent or the comprehensive number of requests received, for example:

Comprehensive service success ratio = Comprehensive number of successful responses / Comprehensive number of responses sent

or

The overall service success rate = the overall number of successful responses/the overall number of requests received.

The specific calculation method can be preset according to system conventions.

In some embodiments, in the above step 130, the comprehensive number of error responses of the target network entity may be obtained, as well as the comprehensive number of responses sent or the comprehensive number of requests received to the target network entity. Then, in step 140, the comprehensive service failure ratio may be determined according to the ratio of the comprehensive number of error responses to the comprehensive number of responses sent or the comprehensive number of requests received, for example:

Service failure ratio = total number of error responses / total number of responses sent

or

The overall service failure rate = the overall number of error responses/the overall number of request receptions.

The specific calculation method can be preset according to system conventions.

By using such a method, the ratio of successful responses or the ratio of incorrect responses to requests of the target network entity can be obtained, thereby facilitating understanding of the request processing status of the target network entity based on the parameter.

In some embodiments, in the above step 130, either the comprehensive number of error responses or the comprehensive number of successful responses of the target network entity can be selected for acquisition. After obtaining one of the comprehensive ratio of request success and the comprehensive ratio of request failure through proportional calculation, the other one is determined based on the relationship between the comprehensive ratio of service failure and the comprehensive ratio of service success. For example, after determining the comprehensive ratio of service failure, the comprehensive ratio of service success is determined according to the comprehensive ratio of service success = 1-comprehensive ratio of service failure; or after determining the comprehensive ratio of service success, the comprehensive ratio of service failure is determined according to the comprehensive ratio of service failure = 1-comprehensive ratio of service success.

In some embodiments, for one or more service types, a service success rate and a service failure rate corresponding to the service type may be obtained. The above service types include analysis, data management or model-related service types.

In some embodiments, in the above step 130, the number of successful responses of the analysis service of the target network entity is obtained, and the number of responses sent to the analysis service or the number of requests received to the analysis service of the target network entity is obtained, and then in step 140, the service success ratio of the analysis service is determined according to the ratio of the number of successful responses to the analysis service and the number of responses sent or the number of requests received to the analysis service, such as:

Analysis service success rate = number of successful responses of the analysis service / number of responses sent by the analysis service

or

The service success rate of the analysis service = the number of successful responses of the analysis service / the number of requests received for the analysis service.

The specific calculation method can be preset according to system conventions.

In some embodiments, in the above step 130, the number of error responses of the analysis service of the target network entity is obtained, and the number of responses sent to the analysis service or the number of requests received to the analysis service of the target network entity is obtained, and then in step 140, the service failure rate of the analysis service is determined according to the ratio of the number of error responses to the number of responses sent to the analysis service or the number of requests received, such as:

Analysis service failure rate = Number of error responses from the analysis service / Number of responses sent from the analysis service

or

The service failure rate of the analysis service = the number of error responses of the analysis service / the number of requests received by the analysis service.

The specific calculation method can be preset according to system conventions.

Through such a method, the ratio of successful execution or failed execution of the analysis service of the target network entity can be obtained, which helps to understand the ability of the target network entity to further provide analysis services based on this parameter.

In some embodiments, in the above step 130, either the comprehensive number of error responses of the analysis service of the target network entity or the comprehensive number of successful responses of the analysis service can be selected and obtained. After obtaining one of the request success rate of the analysis service and the request failure rate of the analysis service by proportional calculation, the other one is determined based on the relationship between the service failure rate of the analysis service and the service success rate of the analysis service. For example, after determining the service failure rate of the analysis service, the service success rate of the analysis service is determined according to the service success rate of the analysis service = 1-the service failure rate of the analysis service; or after determining the service success rate of the analysis service, the service failure rate of the analysis service is determined according to the service failure rate of the analysis service = 1-the service success rate of the analysis service.

In some embodiments, in the above step 130, the number of successful responses of the data management service of the target network entity is obtained, and the number of responses sent by the data management service or the number of requests received for the data management service of the target network entity is obtained, and then in step 140, the service success ratio of the data management service is determined according to the ratio of the number of successful responses of the data management service to the number of responses sent or the number of requests received by the data management service, such as:

Service success rate of data management service = number of successful responses of data management service / number of responses sent by data management service

or

The service success rate of the data management service = the number of successful responses of the data management service/the number of requests received by the data management service.

The specific calculation method can be preset according to system conventions.

In some embodiments, in the above step 130, the number of error responses of the data management service of the target network entity is obtained, and the number of responses sent by the data management service or the number of requests received for the data management service of the target network entity is obtained, and then in step 140, the service failure rate of the data management service is determined according to the ratio of the number of error responses of the data management service to the number of responses sent or the number of requests received by the data management service, such as:

Service failure rate of data management service = number of error responses of data management service / number of responses sent by data management service

or

The service failure rate of the data management service = the number of error responses of the data management service/the number of requests received by the data management service.

The specific calculation method can be preset according to system conventions.

Through such a method, the ratio of successful execution or failed execution of the data management service of the target network entity can be obtained, which helps to understand the ability of the target network entity to further provide data management services based on this parameter.

In some embodiments, in the above step 130, either the comprehensive number of error responses of the data management service of the target network entity or the comprehensive number of successful responses of the data management service can be selected and obtained. After obtaining one of the request success ratio of the data management service and the request failure ratio of the data management service through proportional calculation, the other one is determined based on the relationship between the service failure ratio of the data management service and the service success ratio of the data management service. For example, after determining the service failure ratio of the data management service, the service success ratio of the data management service is determined according to the service success ratio of the data management service = 1-the service failure ratio of the data management service; or after determining the service success ratio of the data management service, the service failure ratio of the data management service is determined according to the service failure ratio of the data management service = 1-the service success ratio of the data management service.

In some embodiments, in the above step 130, the number of successful responses of the model-related service of the target network entity is obtained, as well as the number of responses sent by the model-related service or the number of requests received for the model-related service of the target network entity. Then, in step 140, the service success ratio of the model-related service is determined according to the ratio of the number of successful responses of the model-related service to the number of responses sent or the number of requests received of the model-related service, such as:

Service success rate of model-related services = number of successful responses of model-related services / number of responses sent by model-related services

or

The service success rate of the model-related service = the number of successful responses of the model-related service/the number of requests received by the model-related service.

The specific calculation method can be preset according to system conventions.

In some embodiments, in the above step 130, the number of error responses of the model-related service of the target network entity is obtained, and the number of responses sent by the model-related service or the number of requests received for the model-related service of the target network entity is obtained, and then in step 140, the service failure rate of the model-related service is determined according to the ratio of the number of error responses of the model-related service to the number of responses sent or the number of requests received of the model-related service, such as:

Service failure rate of model-related services = number of error responses from model-related services / number of responses sent from model-related services

or

The service failure rate of the model-related service = the number of error responses of the model-related service / the number of requests received by the model-related service.

The specific calculation method can be preset according to system conventions.

Through such a method, the ratio of successful execution or failed execution of the model-related services of the target network entity can be obtained, which helps to understand the ability of the target network entity to further provide model-related services based on this parameter.

In some embodiments, in the above step 130, either the comprehensive number of error responses of the model-related services and the comprehensive number of successful responses of the model-related services of the target network entity can be selected for acquisition. After obtaining one of the request success rate of the model-related services and the request failure rate of the model-related services through proportional calculation, the other item is determined based on the relationship between the service failure rate of the model-related services and the service success rate of the model-related services. For example, after determining the service failure rate of the model-related services, the service success rate of the model-related services is determined according to the service success rate of the model-related services = 1-the service failure rate of the model-related services; or after determining the service success rate of the model-related services, the service failure rate of the model-related services is determined according to the service failure rate of the model-related services = 1-the service success rate of the model-related services.

【Ratio of service types】

In some embodiments, the request ratio or service ratio of each service among the service types that the target network entity can provide may also be obtained as the corresponding service type ratio.

In some embodiments, if the service type ratio is the ratio of service requests, then in the above step 130, the comprehensive number of request receptions of the target network entity and the number of request receptions of the analysis service may be obtained. In the above step 150, the analysis service type ratio is determined based on the ratio of the number of request receptions of the analysis service to the comprehensive number of request receptions, such as:

Proportion of analysis service types = number of analysis service request receptions/total number of request receptions.

In some embodiments, if the service type ratio is the ratio of requests being served, then in the above step 130, the comprehensive number of request acceptances of the target network entity and the number of request acceptances of the analysis service may be obtained. In the above step 150, the analysis service type ratio is determined based on the ratio of the number of request acceptances of the analysis service to the comprehensive number of request acceptances, such as:

Proportion of analysis service types = number of analysis service request acceptances/total number of request acceptances.

Based on the method in this embodiment, the proportion of the analysis service in the services received or accepted by the target network entity can be obtained, which helps to understand the resource consumption status of the target network entity.

In some embodiments, if the service type ratio is the ratio of service requests, then in the above step 130, the comprehensive number of request receptions of the target network entity and the number of request receptions of the data management service may be obtained. In the above step 150, the data management service type ratio is determined according to the ratio of the number of request receptions of the data management service to the comprehensive number of request receptions, such as:

The proportion of data management service types = the number of requests received for data management services / the total number of requests received.

In some embodiments, if the service type ratio is the ratio of requests being served, then in the above step 130, the comprehensive number of request acceptances of the target network entity and the number of request acceptances of the data management service may be obtained. In the above step 150, the data management service type ratio is determined according to the ratio of the number of request acceptances of the data management service to the comprehensive number of request acceptances, such as:

The proportion of data management service types = the number of requests accepted for data management services / the total number of requests accepted.

Based on the method in this embodiment, the proportion of the data management service in the services received or accepted by the target network entity can be obtained, which helps to understand the resource consumption status of the target network entity.

In some embodiments, if the service type ratio is the ratio of service requests, then in the above step 130, the comprehensive number of request receptions of the target network entity and the number of request receptions of the model-related service may be obtained. In the above step 150, the model-related service type ratio is determined according to the ratio of the number of request receptions of the model-related service to the comprehensive number of request receptions, such as:

The proportion of model-related service types = the number of requests received for model-related services / the total number of requests received.

In some embodiments, if the service type ratio is the ratio of requests served, then in the above step 130, the comprehensive number of request acceptances of the target network entity and the number of request acceptances of the model-related service may be obtained. In the above step 150, the model-related service type ratio is determined according to the ratio of the number of request acceptances of the model-related service to the comprehensive number of request acceptances, such as:

The proportion of model-related service types = the number of requests accepted for model-related services / the total number of requests accepted.

Based on the method in this embodiment, the proportion of model-related services in the services received or accepted by the target network entity can be obtained, which helps to understand the resource consumption status of the target network entity.

In some embodiments, the sum of the service type ratios of various services that the target network entity can provide is 1, so the number of statistics on one type of service can be reduced, such as obtaining the service type ratio of two of the analysis services, data management services, and model-related services, and then calculating the ratio of another service, thereby reducing counting resource consumption.

Through the methods in the above embodiments, multi-dimensional performance parameters can be obtained, which is helpful to provide a rich data basis for subsequent performance evaluation of the target network entity.

In some embodiments, the target service type can be determined in advance, or the performance parameters to be obtained can be determined in advance. The service type corresponding to the interaction statistical information to be obtained is determined based on the performance parameters to be obtained, which is called the target service type. Then, the interaction statistical information is obtained for the target service type, and the performance parameters related to the target service type are determined.

Through such a method, it is possible to reduce the burden of obtaining interactive statistical information on the device and reduce data processing pressure on the basis of obtaining the required performance parameters.

In some embodiments, the name of the measurement of the number of requests received may be in the form of DANS.SerReqReceived, wherein the name of the measurement of the number of requests received for a service type may be DANS.SerReqReceived.ServiceName, where ServiceName is used to distinguish services.

In some embodiments, the name for measuring the number of successful requests may be in the form of DANS.SerReqAccepted, wherein the name for measuring the number of requests received for a service type may be DANS.SerReqAccepted.ServiceName, where ServiceName is used to distinguish services.

In some embodiments, the name for measuring the number of failed requests may be in the form of DANS.SerReqRejected, wherein the name for measuring the number of received requests for a service type may be DANS.SerReqRejected.ServiceName, where ServiceName is used to distinguish services.

In some embodiments, the name for measuring the number of service responses may be in the form of DANS.SerResponseGenerated, where the name for measuring the number of requests received for a service type may be DANS.SerResponseGenerated.ServiceName, e, where ServiceName is used to distinguish services.

The flowcharts of other embodiments of the information acquisition method disclosed in the present invention are shown in FIG2 .

In step 220, a performance analysis request is obtained, and the performance analysis request may include a service consumer entity, or come from a network management device, etc. In some embodiments, the performance analysis request may include a target service type, or a target performance parameter.

In step 230, the interaction statistics of the target network entity are obtained, and the interaction statistics include at least one of the number of requests received by the target network entity or the number of responses of the target network entity. In some embodiments, the operation in step 230 may be the same as the operation in one or more of the above-mentioned steps 130. In some embodiments, if the performance analysis request includes the target service type or the target performance parameter, the interaction statistics related to the target network entity and the target service type and the target performance parameter are obtained; if the performance analysis request does not include the target service type or the target performance parameter, each type of interaction statistics is obtained.

In some embodiments, the interactive statistical information of the target network entity can be continuously counted, and the corresponding data is extracted to calculate the performance parameters when the performance analysis request is obtained, thereby improving the feedback efficiency. In other embodiments, statistics can also be started after the performance analysis request is obtained, and the performance parameters are calculated after a predetermined period of time, thereby reducing the pressure of data statistics.

In step 240, the performance parameters of the target network entity are determined according to the interaction statistical information. In some embodiments, the operation in step 240 may be the same as the operation in one or more of the above-mentioned steps 140. In some embodiments, if the performance analysis request includes the target service type or the target performance parameter, the performance parameter or the target performance parameter of the target network entity related to the target service type is obtained; if the performance analysis request does not include the target service type or the target performance parameter, each interaction statistical information is obtained.

In step 260, the determined performance parameters are sent to one or more network elements. The target network elements of the performance parameters include the network element that sends the performance analysis request, and may also include a service consumer entity, a network management device, and the like.

Through the method in the above embodiment, an operation of acquiring performance parameters can be initiated according to a performance analysis request. This allows other network elements to understand the performance of the target network entity.

In some embodiments, the performance parameters of the target network entity may also include performance parameters related to a slice or analysis identifier. In some embodiments, a filtering condition may be set, the filtering condition including at least one of a network slice identifier or a network analysis identifier.

When the filtering condition is the network slice identifier (S-NSSAI), the interaction statistical information of the target network entity that meets the filtering condition is obtained in the above step 130, and then in the above step 140, the performance parameters of the target network entity under the filtering condition are determined based on the interaction statistical information.

When the filtering condition is the analytical ID, the interaction statistics corresponding to the target Analytic ID are obtained in the above step 130, and then the request ratio, service or request success ratio, service or request failure ratio, etc. of the service corresponding to the target Analytic ID are obtained in the above step 140.

Through such a method, the pertinence of performance parameters can be improved, which is conducive to the subsequent refined scheduling of requests and the refined management of target network entities.

In some embodiments, the target network entity of the present disclosure may be a NWDAF entity. As shown in FIG3 , in the information acquisition system, a performance evaluation service producer 32 and NWDAFs 331 to 33n may be included, where n is a positive integer. The performance evaluation service producer 32 is capable of executing any of the information acquisition methods mentioned above, providing management functions or services of the NWDAF, quantifying the service status of the NWDAF, and evaluating the performance of the NWDAF. Each of the NWDAFs 331 to 33n may be the target network entity mentioned above. In some embodiments, the information acquisition system may also include a performance evaluation service consumer 31, which is capable of sending a performance analysis request and obtaining at least one of the performance parameters or evaluation results fed back by the performance evaluation service producer. Based on the network structure, a flowchart of some further embodiments of the information acquisition method of the present disclosure is shown in FIG4 .

In step 410, according to the service type of the NWDAF service, the NWDAF interaction data of the target type service is measured, including the number of requests received by the NWDAF and the number of responses generated by the NWDAF. The target type service includes at least one of analysis service, data management service and model-related service.

In some embodiments, the request method includes: at least one of request and subscription.

In some embodiments, the response method includes: at least one of response and notification.

In step 420, the performance indicators of NWDAF are quantified according to the service types of NWDAF services and the measurement data of the corresponding NWDAF interactions.

In step 450, the service performance of the NWDAF is evaluated based on the above performance indicators.

Through this method, the service status and service performance of NWDAF that supports multiple service types can be quantified and evaluated. According to the service types of NWDAF services, the measurement data and performance indicators of NWDAF interaction can be determined, the service status and service performance of NWDAF can be evaluated, and the necessary performance indicators can be provided as a reference for the management of NWDAF.

A schematic diagram of some embodiments of the information acquisition device 50 disclosed in the present invention is shown in FIG5 .

The statistical information acquisition unit 503 acquires the interaction statistical information of the target network entity. In some embodiments, the interaction statistical information includes at least one of the number of requests received by the target network entity or the number of responses of the target network entity. In some embodiments, the statistical information acquisition unit 503 can perform any of the methods shown in step 130 or 230 above.

The performance parameter determination unit 504 can determine the performance parameter of the target network entity according to the interaction statistical information. In some embodiments, at least one performance parameter can be obtained according to the relationship between at least two types of interaction statistical information, such as a proportional relationship. In some embodiments, the performance parameter determination unit 504 can perform any of the methods shown in step 140 or 240 above.

Such an information acquisition device can evaluate the performance of network entities by collecting the number of requests and responses related to network entities, thereby quantifying the performance of network entities, providing a data basis for the scheduling of subsequent requests and allocation of service resources, and improving the management capabilities of network analysis services.

In some embodiments, as shown in FIG5 , the information acquisition device further includes a performance evaluation unit 505, which can determine the operating state of the target network entity according to at least one of the request success rate, service success rate, request failure rate or service failure rate. For example, if the request and service success rate of the target network entity is low and the failure rate is high, the target network entity may be in an abnormal state and is not suitable for continuing to provide services; if the success rate is high and the failure rate is low, it is in a normal operating state and can continue to provide services. In some embodiments, the information acquisition device may also include a state analysis unit 507, which can determine the rationality of the resource configuration of the target network entity according to the operating state of the target network entity, for example, when the failure rate exceeds a threshold, the resource configuration for the target network entity can be adjusted; in some embodiments, the state analysis unit 507 can also determine the rationality of the task allocation of the target network entity according to the operating state of the target network entity, for example, when the failure rate of a certain type or several types of services exceeds a threshold, reduce or avoid scheduling this type of service to the target network entity. In some embodiments, the status analysis unit 507 can also determine whether the network entity is faulty based on the operating status of the network entity. For example, if the request and service success rate of the target network entity is low and the failure rate is high, the target network entity may be in an abnormal state and is not suitable for continuing to provide services; if the success rate is high and the failure rate is low, it is in a normal operating state and can continue to provide services.

In some embodiments, the performance evaluation unit 505 can also determine the resource occupation status of the target network by the service of the corresponding service type according to the request ratio of the service type. In some embodiments, the information acquisition device can also include a resource allocation unit 506 capable of allocating resources to the target network entity according to the resource occupation status.

Such a device can evaluate the performance of a network entity based on its performance parameters, and then use the evaluation results to make targeted adjustments to service requests or network entity resources, thereby improving the service level of the target network entity and the success rate of network service requests; it can also reduce unnecessary consumption of target network entity resources due to attempts with a high failure rate, and improve the effective utilization of network entity resources.

In some embodiments, as shown in FIG5 , the information acquisition device may further include a type determination unit 501, which is capable of determining the target service type. In some embodiments, the target service type may be predetermined, or the performance parameters to be obtained may be predetermined. The service type corresponding to the interaction statistical information to be obtained is determined based on the performance parameters to be obtained, which is called the target service type. The statistical information acquisition unit 503 is capable of obtaining interaction statistical information related to the target service type, and the performance parameter determination unit 504 is configured to determine the performance parameters related to the target service type of the target network entity based on the interaction statistical information related to the target service type. Such a device can reduce the burden of obtaining interaction statistical information on the device and reduce data processing pressure on the basis of obtaining the required performance parameters.

In some embodiments, as shown in FIG5 , the information acquisition device may further include a receiving unit 502, which is capable of acquiring a performance analysis request and triggering the statistical information acquisition unit 503 to work according to the performance analysis request. In some embodiments, the performance analysis request may include a target service type or a target performance parameter. A sending unit 508 is capable of sending the determined performance parameter to one or more network elements, and the target network element of the performance parameter includes the network element that sends the performance analysis request, and may also include a service consumer entity, a network management device, etc.

Such a device can initiate an operation to obtain performance parameters according to a performance analysis request, thereby satisfying other network elements to understand the performance of the target network entity.

A schematic diagram of the structure of an embodiment of the information acquisition device disclosed in the present invention is shown in FIG6. The information acquisition device includes a memory 601 and a processor 602. Among them: the memory 601 can be a disk, a flash memory or any other non-volatile storage medium. The memory is used to store the instructions in the corresponding embodiment of the information acquisition method described above. The processor 602 is coupled to the memory 601 and can be implemented as one or more integrated circuits, such as a microprocessor or a microcontroller. The processor 602 is used to execute instructions stored in the memory, which can improve the management capabilities of the network analysis service.

In one embodiment, as shown in FIG. 7 , the information acquisition device 700 includes a memory 701 and a processor 702. The processor 702 is coupled to the memory 701 via a BUS bus 703. The information acquisition device 700 can also be connected to an external storage device 705 via a storage interface 704 to call external data, and can also be connected to a network or another computer system (not shown) via a network interface 706. No further detailed description will be given here.

In this embodiment, the management capability of the network analysis service can be improved by storing data instructions in a memory and processing the instructions through a processor.

In another embodiment, a computer-readable storage medium stores thereon computer program instructions, which, when executed by a processor, implement the steps of the method in the corresponding embodiment of the information acquisition method. It should be understood by those skilled in the art that the embodiments of the present disclosure may be provided as methods, devices, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable non-transient storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

The present disclosure is described with reference to the flowcharts and/or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each process and/or box in the flowchart and/or block diagram and the combination of the processes and/or boxes in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one process or multiple processes in the flowchart and/or one box or multiple boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

So far, the present disclosure has been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solution disclosed here.

The method and apparatus of the present disclosure may be implemented in many ways. For example, the method and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present disclosure may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present disclosure. Therefore, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present disclosure rather than to limit it. Although the present disclosure has been described in detail with reference to the preferred embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present disclosure can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solution of the present disclosure, which should be included in the scope of the technical solution for protection of the present disclosure.

Claims

A method for obtaining information, comprising:

Acquire interaction statistics of a target network entity, where the interaction statistics include at least one of a number of requests received by the target network entity or a number of responses of the target network entity;

A performance parameter of the target network entity is determined according to the interaction statistical information.
The information acquisition method according to claim 1, wherein the performance parameter includes at least one of a request success ratio, a service success ratio, a request failure ratio, a service failure ratio, and a service type ratio.
The information acquisition method according to claim 2, wherein the service type includes at least one of an analysis service, a data management service, or a model-related service.
The information acquisition method according to claim 1, wherein:

The number of requests includes the comprehensive number of request receptions;

The number of responses includes a comprehensive number of responses sent; and

The performance parameters include a comprehensive service success ratio.
The information acquisition method according to claim 1 or 4, wherein the method meets at least one of the following conditions:

The number of requests includes at least one of a comprehensive number of request acceptances, a comprehensive number of request rejections, a number of request receptions corresponding to a service type, a number of request acceptances corresponding to a service type, or a number of request rejections corresponding to a service type; or

The number of responses includes at least one of a comprehensive number of successful responses, a comprehensive number of error responses, a number of response sending times corresponding to a service type, a number of successful responses corresponding to a service type, or a number of error responses corresponding to a service type.
The information acquisition method according to claim 2 or 3, wherein the method meets at least one of the following conditions:

The request success ratio includes at least one of a comprehensive request success ratio, a request success ratio of an analysis service, a request success ratio of a data management service, or a request success ratio of a model-related service;

The service success ratio includes at least one of a comprehensive service success ratio, a service success ratio of an analysis service, a service success ratio of a data management service, or a service success ratio of a model-related service;

The request failure ratio includes at least one of a comprehensive request failure ratio, a request failure ratio of an analysis service, a request failure ratio of a data management service, or a request failure ratio of a model-related service; or

The service failure rate includes at least one of a comprehensive service failure rate, a service failure rate for analysis service requests, a service failure rate for data management services, or a service failure rate for model-related services.
The information acquisition method according to any one of claims 1 to 4, further comprising: determining a filtering condition, wherein the filtering condition comprises at least one of a network slice identifier or a network analysis identifier;

The acquiring the interaction statistics information of the target network entity comprises: acquiring the interaction statistics information of the target network entity that meets the filtering condition;

Determining the performance parameter of the target network entity according to the interaction statistical information includes: determining the performance parameter of the target network entity under the filtering condition according to the interaction statistical information.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring the interaction statistics information of the target network entity comprises: acquiring at least two types of the interaction statistics information through a counter;

The determining the performance parameter of the target network entity according to the interaction statistical information includes: acquiring at least one performance parameter according to a relationship between at least two types of the interaction statistical information.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity comprises: acquiring a comprehensive number of request receptions and a comprehensive number of request acceptances to the target network entity;

The determining the performance parameter of the target network entity according to the interaction statistical information comprises at least one of the following:

Determine the comprehensive request success ratio according to the ratio of the comprehensive number of request acceptances to the comprehensive number of request receptions; or

The comprehensive request success ratio is determined based on the ratio of the comprehensive number of request acceptances to the comprehensive number of request receptions, and the comprehensive request failure ratio is determined based on the comprehensive request success ratio, wherein the sum of the comprehensive request success ratio and the comprehensive request failure ratio is 1.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity comprises: acquiring a comprehensive number of request receptions and a comprehensive number of request rejections to the target network entity;

Determining the performance parameter of the target network entity according to the interaction statistical information includes:

Determine the comprehensive request failure ratio according to the ratio of the comprehensive number of request rejections to the comprehensive number of request receptions; or

The comprehensive request failure ratio is determined based on the ratio of the comprehensive number of request rejections to the comprehensive number of request receptions, and the comprehensive request success ratio is determined based on the comprehensive request failure ratio, wherein the sum of the comprehensive request success ratio and the comprehensive request failure ratio is 1.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity comprises: acquiring the comprehensive number of successful responses of the target network entity, and acquiring the comprehensive number of responses sent or the comprehensive number of requests received to the target network entity;

Determining the performance parameter of the target network entity according to the interaction statistical information includes:

Determine a comprehensive service success ratio according to a ratio of the comprehensive number of successful responses to the comprehensive number of responses sent or the comprehensive number of requests received; or

The comprehensive service success ratio is determined based on the ratio of the comprehensive number of successful responses to the comprehensive number of responses sent or the comprehensive number of requests received, and the comprehensive service failure ratio is determined based on the comprehensive service success ratio, wherein the sum of the comprehensive service success ratio and the comprehensive service failure ratio is 1.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity includes: acquiring the comprehensive number of error responses of the target network entity, and acquiring the comprehensive number of response sending or the comprehensive number of request receiving to the target network entity;

Determining the performance parameter of the target network entity according to the interaction statistical information includes:

Determine a comprehensive service failure ratio according to a ratio of the comprehensive number of error responses to the comprehensive number of responses sent or the comprehensive number of requests received; or

The comprehensive service failure ratio is determined based on the ratio of the number of error responses to the comprehensive number of responses sent or the comprehensive number of requests received, and the comprehensive service success ratio is determined based on the comprehensive service failure ratio, wherein the sum of the comprehensive service success ratio and the comprehensive service failure ratio is 1.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity comprises: acquiring the number of requests for receiving the first type of service and the number of requests for accepting the first type of service of the target network entity;

The determining the performance parameter of the target network entity according to the interaction statistical information comprises at least one of the following:

Determining a request success ratio of the first type of service according to a ratio of the number of requests accepted for the first type of service to the number of requests received for the first type of service; or

Determine the request success ratio of the first type of service based on the ratio of the number of request acceptances of the first type of service to the number of request receptions of the first type of service, and determine the request failure ratio of the first type of service based on the request success ratio of the first type of service, wherein the sum of the request success ratio of the first type of service and the request failure ratio of the first type of service is 1, and the first type of service includes analysis services, data management services or model-related services.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity comprises: acquiring the number of requests received for the first type of service and the number of requests rejected for the first type of service of the target network entity;

The determining the performance parameter of the target network entity according to the interaction statistical information comprises at least one of the following:

Determining a request failure ratio of the first type of service according to a ratio of the number of request rejections of the first type of service to the number of request receptions of the first type of service; or

Determine the request failure ratio of the first type of service based on the ratio of the number of request rejections of the first type of service to the number of request receipts of the first type of service, and determine the request success ratio of the first type of service based on the request failure ratio of the first type of service, wherein the sum of the request success ratio and the request failure ratio of the first type of service is 1, and the first type of service includes analysis services, data management services or model-related services.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity includes: acquiring the number of successful responses of the second type service of the target network entity, and acquiring the number of responses sent for the second type service or the number of requests received for the second type service of the target network entity;

Determining the performance parameter of the target network entity according to the interaction statistical information includes:

Determine a service success ratio of the second type of service according to a ratio of the number of successful responses to the second type of service to the number of responses sent or the number of requests received for the second type of service; or

Determine the service success ratio of the second type service based on the ratio of the number of successful responses of the second type service to the number of responses sent or the number of requests received for the second type service, and determine the service failure ratio of the second type service based on the service success ratio of the second type service, wherein the sum of the service success ratio of the second type service and the service failure ratio of the second type service is 1, and the second type service includes analysis service, data management service or model-related service.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity includes: acquiring the number of error responses of the second type service of the target network entity, and acquiring the number of responses sent for the second type service or the number of requests received for the second type service of the target network entity;

Determining the performance parameter of the target network entity according to the interaction statistical information includes:

determining a service failure ratio of the second type of service according to a ratio of the number of error responses to the second type of service to the number of responses sent or the number of requests received for the second type of service; or

Determine the service failure ratio of the second type of service based on the ratio of the number of error responses of the second type of service to the number of responses sent or the number of requests received of the second type of service, and determine the service success ratio of the second type of service based on the service failure ratio of the second type of service, wherein the sum of the service success ratio and the service failure ratio of the second type of service is 1, and the second type of service includes analysis service, data management service or model-related service.
The information acquisition method according to any one of claims 1 to 4, wherein:

The acquiring of the interaction statistics information of the target network entity comprises: acquiring the comprehensive number of request receptions of the target network entity and the number of request receptions of the third type of service;

The determining of the performance parameters of the target network entity based on the interaction statistical information includes: determining the proportion of the third type of service based on the ratio of the number of request receptions of the third type of service to the comprehensive number of request receptions, wherein the third type of service includes analysis services, data management services or model-related services.
The information acquisition method according to claim 2 or 3, further comprising: evaluating the performance of the target network entity according to the performance parameter, including at least one of the following:

Determining the operating state of the target network entity according to at least one of the request success ratio, the service success ratio, the request failure ratio, or the service failure ratio; or

The resource occupation status of the target network entity by the service of the corresponding service type is determined according to the request ratio of the service type.
The information acquisition method according to claim 18, further comprising at least one of the following:

Determining at least one of resource configuration rationality, task allocation rationality, or fault status of the target network entity according to the operating status of the target network entity; or

Allocate resources to the target network entity according to the resource occupancy status.
The information acquisition method according to any one of claims 1 to 4, further comprising:

Determine the target service type;

The acquiring the interaction statistics information of the target network entity comprises: acquiring the interaction statistics information related to the target service type;

The determining the performance parameter of the target network entity according to the interaction statistical information includes: determining the performance parameter related to the target service type of the target network entity according to the interaction statistical information related to the target service type.
The information acquisition method according to any one of claims 1 to 4, wherein the method meets at least one of the following conditions:

The number of requests includes the number of at least one of service requests or service subscriptions; or

The number of responses includes the number of at least one of a service response or a subscription notification.
The information acquisition method according to any one of claims 1 to 4, further comprising:

Obtaining a performance analysis request, wherein the obtaining of interaction statistics of a target network entity is performed under the triggering of the performance analysis request; and

The determined performance parameters are sent to one or more network elements.
The information acquisition method according to any one of claims 1 to 4, wherein the target network entity includes an entity having a network data analysis function.
An information acquisition device, comprising:

a statistical information acquisition unit, configured to acquire interaction statistical information of a target network entity, the interaction statistical information comprising at least one of a number of requests received by the target network entity or a number of responses of the target network entity;

A performance parameter determination unit is configured to determine the performance parameter of the target network entity according to the interaction statistical information.
The information acquisition device according to claim 24, further comprising: a performance evaluation unit configured to evaluate the performance of the target network entity according to the performance parameter, including at least one of the following:

Determining the operating state of the target network entity according to at least one of the request success ratio, the service success ratio, the request failure ratio, or the service failure ratio; or

The resource occupation status of the target network entity by the service of the corresponding service type is determined according to the request ratio of the service type.
The information acquisition device according to claim 25, further comprising at least one of the following:

a state analysis unit configured to determine at least one of resource configuration rationality, task allocation rationality or fault state of the target network entity according to the operating state of the target network entity; or

A resource allocation unit is configured to allocate resources to the target network entity according to the resource occupancy status.
The information acquisition device according to claim 24, further comprising: a type determination unit configured to determine a target service type;

The statistical information acquisition unit is configured to acquire the interaction statistical information related to the target service type;

The performance parameter determination unit is configured to determine the performance parameter related to the target service type of the target network entity according to the interaction statistical information related to the target service type.
The information acquisition device according to claim 24, further comprising:

a receiving unit configured to obtain a performance analysis request and trigger the statistical information obtaining unit to operate according to the performance analysis request; and

The sending unit is configured to send the determined performance parameter to one or more network elements.
An information acquisition device, comprising:

Memory; and

A processor coupled to the memory, the processor being configured to execute the method according to any one of claims 1 to 23 based on instructions stored in the memory.
A computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of the method described in any one of claims 1 to 23.
A computer program for causing a processor to execute the method according to any one of claims 1 to 23.