Performance detection method and device, service system and storage medium

Abstract

The invention provides a performance detection method and device, a service system and a storage medium, and relates to the technical field of communication. The performance detection method disclosed by the invention comprises the following steps: acquiring a performance detection request; obtaining performance detection information of the target network entity, wherein the performance detection information comprises at least one of data collection performance or data processing performance of the target network entity; and feeding back the performance detection information to the source end node of the performance detection request.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a performance detection method, device, service system and storage medium. Background Art

[0002] 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.

[0003] The amount of storage and computing resources of NWDAF depends on the operator's configuration. The rationality of the configuration will affect the performance of NWDAF in providing data analysis services. Summary of the invention

[0004] One purpose of the present disclosure is to propose a solution for monitoring the performance of a network entity, which helps to improve the efficiency and rationality of resource allocation of the network entity.

[0005] According to one aspect of some embodiments of the present disclosure, a performance detection method is proposed, including: obtaining a performance detection request; obtaining performance detection information of a target network entity, the performance detection information including at least one of data collection performance or data processing performance of the target network entity; and feeding back the performance detection information to a source node of the performance detection request.

[0006] In some embodiments, the data collection performance includes at least one of data load or signaling load.

[0007] In some embodiments, obtaining performance detection information of the target network entity includes: obtaining the signaling load of the target network entity, including: measuring the number of times the target network entity sends at least one of a data collection request or subscription within a predetermined first time length, as a first number; measuring the number of times the target network entity receives at least one of a data collection response or notification within a predetermined first time length, as a second number; and obtaining the sum of the first number and the second number, as the signaling load.

[0008] In some embodiments, obtaining performance detection information of the target network entity includes: obtaining data load of the target network entity, including: measuring at least one item of first data packets of responses or notifications related to data collection received by the target network entity within a predetermined second time length as a third number; when the target network entity receives at least one item of first data packets of responses or notifications related to data collection within the predetermined second time length, counting the size of the first data packet; and determining the data load based on the third number and the size of the first data packet.

[0009] In some embodiments, obtaining performance detection information of the target network entity includes: obtaining data processing performance of the target network entity, including: determining at least one of the second data packets of received responses or notifications processed by the target network entity within a predetermined third time length as a fourth number; when the target network entity processes at least one of the second data packets of responses or notifications related to data collection within the predetermined third time length, counting the size of the second data packets; determining the data processing amount based on the fourth number and the size of the second data packet; determining the data processing performance based on the data processing amount and the predetermined third time length.

[0010] In some embodiments, the data collection performance also includes the data collection rate; obtaining the performance detection information of the target network entity includes: determining the data collection rate based on at least one of the signaling load and the time length of the statistical signaling load, or the time length of the data load and the statistical data load.

[0011] In some embodiments, the method further includes: adjusting resource configuration of the target network entity according to the performance detection information.

[0012] In some embodiments, adjusting the resource configuration of the target network entity according to the performance detection information includes at least one of the following: when the signaling load is greater than or equal to a predetermined signaling load threshold, determining to adjust the storage resource configuration of the target network entity; when the data load is greater than or equal to a predetermined data load threshold, determining to adjust the storage resource configuration of the target network entity; when the data processing rate is greater than or equal to a predetermined processing rate threshold, determining to adjust the computing resource configuration of the target network entity; or when the data collection rate is greater than the data processing performance and the difference is greater than a predetermined difference threshold, determining to adjust at least one of the storage resource configuration or the computing resource configuration of the target network entity.

[0013] In some embodiments, feeding back the performance detection information to the source node of the performance detection request includes at least one of the following: feeding back at least one of signaling load, data load, data collection rate or data processing rate to the source node of the performance detection request.

[0014] In some embodiments, obtaining the performance detection request includes: obtaining the performance detection request through at least one of information subscription or information request.

[0015] In some embodiments, feeding back the performance detection information to the source node of the performance detection request includes: feeding back the performance detection information to the source node of the performance detection request by at least one of notification or response.

[0016] In some embodiments, the target network entity comprises a NWDAF entity.

[0017] According to one aspect of some embodiments of the present disclosure, a performance detection device is proposed, including: a request acquisition unit, configured to obtain a performance detection request; an information acquisition unit, configured to obtain performance detection information of a target network entity, the performance detection information including at least one of the data collection performance of the target network entity or the data processing performance of the target network entity; an information feedback unit, configured to feed back the performance detection information to a source node of the performance detection request.

[0018] In some embodiments, the apparatus further includes: a configuration adjustment unit configured to adjust resource configuration of the target network entity according to the performance detection information.

[0019] According to one aspect of some embodiments of the present disclosure, a performance detection device is proposed, including: a memory; and a processor coupled to the memory, wherein the processor is configured to execute any one of the above performance detection methods based on instructions stored in the memory.

[0020] According to one aspect of some embodiments of the present disclosure, a non-transitory 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 performance detection methods described above are implemented.

[0021] According to one aspect of some embodiments of the present disclosure, a service system is proposed, comprising: a consumer entity, configured to send a performance detection request to a performance detection device, and receive performance detection information fed back by the performance detection device; a performance detection device, configured to execute any one of the performance detection methods described above; and one or more NWDAF entities, configured to accept detection by the performance detection device. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide a 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 an improper limitation on the present disclosure. In the drawings:

[0023] Figure 1 The following is a flow chart of some embodiments of the performance detection method disclosed in the present invention.

[0024] Figure 2 Flowcharts of other embodiments of the performance detection method disclosed in the present invention.

[0025] Figures 3A-3C Schematic diagram of some embodiments of information interaction in the performance detection method disclosed in the present invention.

[0026] Figure 4 Schematic diagrams of some embodiments of the performance detection device disclosed in the present invention.

[0027] Figure 5 Schematic diagrams of other embodiments of the performance detection device disclosed in the present invention.

[0028] Figure 6 Schematic diagrams of some further embodiments of the performance detection device disclosed in the present invention.

[0029] Figure 7 Schematic diagrams of some embodiments of the service system disclosed herein. DETAILED DESCRIPTION

[0030] The technical solution of the present disclosure is further described in detail below through the accompanying drawings and embodiments.

[0031] The inventors found that if each data source sends too much data and signaling to NWDAF, NWDAF may not be able to store and process the data in time, resulting in data loss. The more data loss there is, the greater the impact on NWDAF's data collection performance and data analysis performance.

[0032] In the related technology, NWDAF can take some measures to reduce data load and signaling load to reduce the impact of limited storage resources on data collection performance, such as prioritizing requests from analysis consumers, reducing the scope of data collection (such as duration), modifying the sampling rate, and other measures to reduce the amount of collected data and signaling load. However, the inventors found that this cannot fundamentally solve the problem of unreasonable configuration of storage resources and computing resources.

[0033] In view of the above problems, the present disclosure proposes a performance detection method, device, service system and storage medium to monitor network entities such as NWDAF, so as to provide necessary reference for operators to optimize the storage resource and computing resource configuration of network entities.

[0034] The flowcharts of some embodiments of the performance detection method disclosed in the present invention are as follows: Figure 1 In some embodiments, the performance detection method may be executed by an executor node of a performance detection event of a target network entity, and the executor node is signal-connected with one or more target network entities.

[0035] In step S11, a performance detection request is obtained. In some embodiments, the source node of the performance detection request is a node that has a detection demand for the target network entity, which can be called a consumer node of the performance detection event, such as an operator's network management node, or a node with authority to detect the target network entity. In some embodiments, the target network entity is a NWDAF entity. In some embodiments, the consumer node can send a performance detection request to the executor node by at least one of information subscription or information request.

[0036] In step S12, performance detection information of the target network entity is obtained, and the performance detection information includes at least one of data collection performance or data processing performance of the target network entity. In some embodiments, the data collection performance of the target network entity can be quantified and measured by the data load or signaling load when performing data collection. The data load can be used to evaluate the throughput when the target network entity performs the data collection service, and the signaling load can be used to evaluate the signaling interaction frequency when the target network entity performs the data collection service. The data collection performance includes at least one of the data load or the signaling load.

[0037] In some embodiments, the performance detection information of the target network entity may be obtained by at least one of requiring the target network entity to actively report its own performance detection information, detecting the interface of the target network entity, monitoring the processor of the target network entity, etc.

[0038] In step S13, the performance detection information is fed back to the source node of the performance detection request.

[0039] In some embodiments, all or part of the types of performance detection information obtained can be fed back to the source node according to the type of performance detection information targeted in the performance detection request of the source node or the type of performance detection information currently detected. In some embodiments, at least one of the signaling load, data load, data collection rate, or data processing rate is fed back to the source node of the performance detection request.

[0040] Based on the method in the embodiment shown above, the data collection and processing performance of the target network entity can be quantified, the data collection and processing performance of the target network entity can be determined in a timely manner, the status monitoring capability of the target network entity is improved, and a reference is provided for the storage resource and computing resource configuration of the network entity, thereby helping to improve the efficiency and rationality of the resource configuration of the network entity.

[0041] In some embodiments, Figure 1 As shown, the performance detection method also includes step S14.

[0042] In step S14, the resource configuration of the target network entity is adjusted according to the performance detection information.

[0043] In some embodiments, taking the NWDAF node as an example, it is evaluated whether the observed signaling load measurement value is greater than or equal to the preconfigured signaling load threshold, and based on the evaluation result, it is determined whether to update the storage resource configuration of the NWDAF; it is evaluated whether the observed data processing rate measurement value is less than the preconfigured data processing rate threshold, and based on the evaluation result, it is determined whether to update the computing resource configuration of the NWDAF; it is evaluated whether the observed data processing rate measurement value is less than the preconfigured data processing rate threshold, and based on the evaluation result, it is determined whether to update the computing resource configuration of the NWDAF; it is evaluated whether the observed data collection rate is much greater than the data processing rate (for example, the difference between the data collection rate and the data processing rate is greater than the predetermined difference threshold). If the data collection rate is much greater than the data processing rate, there may be an unreasonable configuration of computing resources or storage resources, and it is necessary to update the storage resources or computing resource configuration of the NWDAF based on the evaluation result.

[0044] In some embodiments, the executor node of the performance detection event can generate a resource configuration policy and send it to the consumer node of the performance detection event; in some embodiments, the executor node of the performance detection event sends the generated resource configuration policy to the network management node or relevant personnel of the operator, so that the resource configuration of the target network entity can be adjusted in time. This method has low requirements on the data processing capability of the executor node and is conducive to the operator's global adjustment.

[0045] In some embodiments, the executor node of the performance detection event generates a resource configuration policy and can automatically adjust the resource configuration of the target network entity, thereby improving the timeliness of the resource configuration of the target network entity and reducing the burden on the network management node and signaling transmission.

[0046] Based on the method in the embodiment shown above, the resource configuration of the target network entity can be adjusted in time based on the performance detection information, thereby improving the rationality of the resource configuration of the target network entity and the adaptability to changes in network status, and improving the intelligence level of network nodes.

[0047] Flow charts of other embodiments of the performance detection method disclosed in the present invention are as follows: Figure 2 shown.

[0048] In step 211, a performance detection request is obtained. In some embodiments, the performance detection request may be a detection request for data collection performance of the target network entity, in some embodiments, a detection request for the signaling load of the target network entity, or a detection request for the data load of the target network entity. In some embodiments, the detection request may be a detection request for the data processing volume of the target network entity. By using such a method, corresponding detection can be performed as needed, reducing the detection burden and improving the pertinence.

[0049] In some embodiments, the performance detection request may be a detection request for the data collection performance and data processing volume of the target network entity, thereby performing a comprehensive detection of signaling load, data load and data processing, thereby improving the comprehensiveness of performance detection.

[0050] In some embodiments, the flowchart of the "subscribe-notify" service and the "request-response" service between NFs is as follows: Figure 3A , 3B As shown, the service user (NF_A) can subscribe to or request services from the service provider (NF_B) based on the "subscribe-notify" service and the "request-response" service.

[0051] In some embodiments, NF_A is NWDAF, and NWDAF can subscribe to or request services, such as data collection, from the service provider (NF_B) based on the subscription-notification services in 311 and 312, and the request-response services in 321 and 322.

[0052] In some embodiments, the architecture of NWDAF collecting data from other 5GC NFs is as follows Figure 3C As shown, NWDAF can collect data from any other 5GC NF through the Nnf interface.

[0053] In some embodiments, according to the performance detection request, at least one of the following steps 2211 to 2213, steps 2221 to 2223, and steps 2231 to 2234 is executed.

[0054] In steps 2211 to 2213, the signaling load of the target network entity is obtained.

[0055] In step 2211, the number of at least one of a data collection request or a subscription sent by the target network entity within a predetermined first time length is measured as a first number.

[0056] In some embodiments, taking NWDAF as the target network entity as an example, the number of data collection requests sent by NWDAF to other data sources within a period of time is measured: when NWDAF triggers a request / subscription related to data collection, the value of the cumulative counter (CC) related to the number of data collection requests / subscriptions triggered by NWDAF is incremented by 1; the value of the CC is the measured value of the number of data collection requests / subscriptions triggered by NWDAF, as the first number.

[0057] In step 2212, the number of at least one of the data collection responses or notifications received by the target network entity within the predetermined first time length is measured as a second number.

[0058] In some embodiments, the number of data collection responses received by NWDAF from other data sources within a period of time is measured: when NWDAF receives a response / notification related to data collection, the value of a cumulative counter (CC) related to the number of data collection responses / notifications received by NWDAF is incremented by 1; the value of the CC is the measured value of the number of data collection responses / notifications received by NWDAF, which is used as the second number.

[0059] In step 2213, the sum of the first number and the second number, that is, the sum of the measured value of the number of data collection requests / subscriptions triggered by the target network entity within a period of time and the measured value of the number of data collection responses / notifications received by the target network entity, is calculated as the signaling load.

[0060] In some embodiments, step 231 may be further performed to feed back the signaling load to the source node. In some embodiments, the signaling load may be divided by the predetermined first time length to determine the signaling load amount per unit time, and the signaling load amount may be fed back to the source node. In this way, a longer predetermined first time length may be set, and then the deviation caused by accidental events may be averaged to improve the accuracy of signaling load statistics.

[0061] In steps 2221 to 2223, the data load of the target network entity is obtained.

[0062] In step 2221, at least one item of response or notification data packets related to data collection received by the target network entity within a predetermined second time length is measured as a third number.

[0063] In some embodiments, taking NWDAF as the target network entity, the number of data packets received by NWDAF from other data sources within a period of time is measured: when NWDAF receives a response / notification data packet related to data collection, the value of the cumulative counter (CC) related to the number of data packets received by NWDAF is incremented by 1; the value of the CC is the measured value of the number of data packets received by NWDAF, which is used as the third number.

[0064] In step 2222, when the target network entity receives at least one of the response or notification data packets related to data collection within the predetermined second time length, the size of the first data packet is counted.

[0065] In some embodiments, the size of data packets received by NWDAF from other data sources within a period of time is measured: when NWDAF receives a response / notification data packet related to data collection, the size of the data packet is measured in bits or bytes; each time 1 bit or 1 byte is collected, the value of the related cumulative counter (CC) is incremented by 1; the value of the CC is the measured value of the size of the data packet received by NWDAF.

[0066] In step 2223, the data load is determined based on the third number and the size of the data packet.

[0067] In some embodiments, the measured values ​​of the sizes of data packets that meet the third number may be accumulated according to the third number to determine the data load, thereby ensuring the accuracy of the data load statistics.

[0068] In some embodiments, when the sizes of the data packets are the same or have small differences, step 2222 may be performed only for one data packet, and the data load may be determined by multiplying the third divisor by the measured value of the data packet size, thereby reducing the amount of computation required for data monitoring and processing.

[0069] In some embodiments, step 231 may be further performed to feed back the data load to the source node. In some embodiments, the data load may be divided by the predetermined second time length to determine the data load amount per unit time, and the data load amount may be fed back to the source node. In this way, a longer predetermined second time length may be set, and then the deviation caused by accidental events may be avoided by taking an average, thereby improving the accuracy of data load statistics.

[0070] In some embodiments, the predetermined first time length is equal to the predetermined second time length. The processing results of step 2213 and step 2223 are combined, such as adding the two together as the data collection amount, and step 231 is performed to improve the comprehensiveness of the data collection performance measurement. In some embodiments, after obtaining the data collection amount, the data collection rate can be determined by dividing it by the predetermined first time length, thereby avoiding deviations caused by accidental events and improving the accuracy of data collection performance statistics.

[0071] In steps 2231 to 2224, the data processing performance of the target network entity is obtained.

[0072] In step 2231, at least one of the received response or notification data packets processed by the target network entity within a predetermined third time length is determined as a fourth number.

[0073] In some embodiments, taking NWDAF as the target network entity, the number of data packets processed by NWDAF within a period of time is measured: when NWDAF processes the received response / notification data packets, the value of the cumulative counter (CC) related to the number of data packets processed by NWDAF is incremented by 1; the value of the CC is the measured value of the number of data packets processed by NWDAF, which is taken as the fourth time.

[0074] In step 2232, when the target network entity processes at least one of the data packets of the response or notification related to the data collection within a predetermined third time length, the size of the data packet is counted.

[0075] In some embodiments, the size of the data packets processed by NWDAF within a period of time is measured: when NWDAF processes the received response / notification data packets, the size of the data packets is measured in bits or bytes, and the value of the related cumulative counter (CC) is incremented by 1 each time 1 bit or 1 byte is processed; the value of the CC is the measured value of the size of the data packets processed by NWDAF.

[0076] In step 2233, the data processing amount is determined according to the fourth number and the size of the data packet. In some embodiments, the data processing amount can be used as the data processing performance to perform subsequent step 231. In some embodiments, step 2234 can also be continued.

[0077] In some embodiments, the measured values ​​of the sizes of the data packets that meet the fourth number of times may be accumulated according to the fourth number of times to determine the data load, thereby ensuring the accuracy of the data processing amount statistics. In some embodiments, when the sizes of the data packets are the same or have little difference, step 2232 may be performed only for one data packet, and then the data processing amount may be determined by multiplying the fourth number of times by the measured value of the data packet size, thereby reducing the amount of data monitoring and processing operations.

[0078] In step 2234, the data processing performance is determined according to the data processing amount and the predetermined third time length. In some embodiments, the data processing amount can be divided by the predetermined third time length, and the data processing amount per unit time can be used as the data processing performance, thereby avoiding deviations caused by accidental events and improving the accuracy of data processing performance statistics. Further, step 231 is executed.

[0079] In step 231, the performance detection information obtained in the previous step is fed back to the source node of the performance detection request.

[0080] In some embodiments, it may also be determined whether to adjust the resource configuration of the target network entity based on the performance detection result.

[0081] Based on the method in the embodiment shown above, the signaling load, data load, data processing and collection rate can be used as reference quantities to measure the operating burden of the target network entity, and then measure whether the current resource configuration of the target network entity matches the operating burden, thereby ensuring the reliability and accuracy of the operating burden measurement, thereby improving the rationality of the storage and computing resource configuration of the target network entity, and is conducive to improving the service capability of the target network entity on the basis of saving resources.

[0082] In some embodiments, resource configuration of the target network entity may also be adjusted according to the performance detection information.

[0083] In some embodiments, the signaling load is compared with a predetermined signaling load threshold, and when the signaling load is greater than or equal to the predetermined signaling load threshold, it is determined to adjust the storage resource configuration of the target network entity. In some embodiments, the adjustment method may be to determine the storage resource increase amount of the target network entity according to a predetermined granularity or according to a predetermined correspondence between the signaling load and the storage resource increment, and to increase the storage resource for the target network entity.

[0084] In some embodiments, the data load is compared with a predetermined data load threshold. When the data load is greater than or equal to the predetermined data load threshold, it is determined to adjust the storage resource configuration of the target network entity. In some embodiments, the adjustment method can be to determine the storage resource increase amount of the target network entity according to a predetermined granularity or according to a predetermined correspondence between the data load and the storage resource increment, and increase the storage resource for the target network entity.

[0085] In some embodiments, the data processing rate is compared with a predetermined processing rate. When the data processing rate is greater than or equal to a predetermined processing rate threshold, it is determined to adjust the computing resource configuration of the target network entity. In some embodiments, the adjustment method may be to determine the increase in computing resources of the target network entity according to a predetermined granularity or according to a correspondence between a predetermined data processing rate greater than and a computing resource increment, and to increase computing resources for the target network entity.

[0086] In some embodiments, the data collection rate is compared with the data processing performance (wherein the data processing performance here refers to the amount of data processed per unit time), and when the data collection rate is greater than the data processing performance, and the difference is greater than a predetermined difference threshold, it is determined to adjust at least one of the storage resource configuration and the computing resource configuration of the target network entity. In some embodiments, computing resources are increased to improve data processing performance; in some embodiments, storage resources are increased to improve data caching capabilities to provide sufficient time for data processing.

[0087] Based on the methods in the various embodiments shown above, it is possible to determine from multiple perspectives whether storage resources and computing resources need to be adjusted, and determine the adjustment method based on performance detection information, thereby improving the adaptive adjustment capability of resource configuration and ensuring the service capability of network entities.

[0088] Schematic diagrams of some embodiments of the performance detection device disclosed in the present invention are as follows Figure 4 shown.

[0089] The request acquisition unit 401 can acquire a performance detection request. In some embodiments, the source node of the performance detection request is a node that has a detection demand for the target network entity, which can be called a consumer node of the performance detection event, such as a network management node of an operator, or a node with authority to detect the target network entity. In some embodiments, the target network entity is a NWDAF entity. In some embodiments, the request acquisition unit 401 can acquire the performance detection request by receiving at least one of a subscription or an information request.

[0090] The information acquisition unit 402 can acquire performance detection information of the target network entity, and the performance detection information includes at least one of data collection performance or data processing performance of the target network entity. In some embodiments, the data collection performance of the target network entity can be quantified and measured by performing data load or signaling load when data collection is performed, and the data collection performance includes at least one of data load or signaling load.

[0091] In some embodiments, the information acquisition unit 402 may execute the above Figure 2 At least one performance detection operation among steps 2211-2213, steps 2221-2223, and steps 2231-2234 of the illustrated embodiment.

[0092] The information feedback unit 403 feeds back the performance detection information to the source node of the performance detection request. In some embodiments, all or part of the types of performance detection information obtained can be fed back to the source node according to the category of the performance detection information targeted in the performance detection request of the source node or the category of the currently detected performance detection information. In some embodiments, at least one of the signaling load, data load, data collection rate or data processing rate is fed back to the source node of the performance detection request.

[0093] Such a device can timely determine the data collection and processing performance of the target network entity, improve the status monitoring capability of the target network entity, and provide a reference for the storage resource and computing resource configuration of the network entity, thereby helping to improve the efficiency and rationality of the resource configuration of the network entity.

[0094] In some embodiments, Figure 4 As shown, the performance detection device also includes a configuration adjustment unit 404, which can adjust the resource configuration of the target network entity according to the performance detection information. In some embodiments, taking the NWDAF node as an example, it is evaluated whether the observed signaling load measurement value is greater than or equal to the pre-configured signaling load threshold, and whether to update the storage resource configuration of the NWDAF is determined based on the evaluation result; it is evaluated whether the observed data processing rate measurement value is less than the pre-configured data processing rate threshold, and whether to update the computing resource configuration of the NWDAF is determined based on the evaluation result; it is evaluated whether the observed data processing rate measurement value is less than the pre-configured data processing rate threshold, and whether to update the computing resource configuration of the NWDAF is determined based on the evaluation result; it is evaluated whether the observed data collection rate is much greater than the data processing rate (for example, the difference between the data collection rate and the data processing rate is greater than the predetermined difference threshold). If the data collection rate is much greater than the data processing rate, there may be a situation where the computing resources or storage resources are not configured reasonably, and the storage resources or computing resource configuration of the NWDAF needs to be updated based on the evaluation result.

[0095] Such a device can make timely adjustments to the resource configuration of the target network entity based on the performance detection information, thereby improving the rationality of the resource configuration of the target network entity and the adaptability to changes in network status, and improving the intelligence level of network nodes.

[0096] The structural schematic diagram of an embodiment of the performance detection device disclosed in the present invention is as follows Figure 5 As shown. The performance detection device includes a memory 501 and a processor 502. Wherein: the memory 501 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 performance detection method above. The processor 502 is coupled to the memory 501 and can be implemented as one or more integrated circuits, such as a microprocessor or a microcontroller. The processor 502 is used to execute the instructions stored in the memory, which can improve the status monitoring capability of the target network entity, provide a reference for the storage resource and computing resource configuration of the network entity, thereby helping to improve the efficiency and rationality of the resource configuration of the network entity.

[0097] In one embodiment, it is also possible to Figure 6 As shown, the performance detection device 600 includes a memory 601 and a processor 602. The processor 602 is coupled to the memory 601 via a BUS 603. The performance detection device 600 can also be connected to an external storage device 605 via a storage interface 604 to call external data, and can also be connected to a network or another computer system (not shown) via a network interface 606. No further detailed description will be given here.

[0098] In this embodiment, by storing data instructions in a memory and then processing the instructions through a processor, the state monitoring capability of the target network entity can be improved, and a reference can be provided for the configuration of storage resources and computing resources of the network entity, thereby helping to improve the efficiency and rationality of the resource configuration of the network entity.

[0099] 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 performance detection 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.

[0100] Schematic diagrams of some embodiments of the service system disclosed in the present invention are as follows Figure 7 shown.

[0101] The consumer entity 71 of the performance detection event can send a performance detection request to the performance detection device and receive performance detection information fed back by the performance detection device. In some embodiments, the consumer entity 71 is a node that has a detection demand for the target network entity, such as a network management node of an operator, or a node with authority to detect the target network entity.

[0102] The performance detection device 72, as a provider entity of the performance detection events, may be any of the performance detection devices mentioned above, and may execute any of the performance detection methods mentioned above.

[0103] The service system also includes at least one NWDAF node 731-73n, where n is a positive integer. The NWDAF node supports collecting data from NFs, AFs and OAM, and provides analysis information to NFs, AFs and OAM, and can be detected by a performance detection device.

[0104] In such a service system, the data collection and processing performance of the target network entity can be determined in a timely manner, the status monitoring capability of the target network entity can be improved, a reference can be provided for the storage resource and computing resource configuration of the network entity, and the efficiency and rationality of the resource configuration of the network entity can be improved.

[0105] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks 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 generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0106] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0107] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0108] 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.

[0109] 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.

[0110] It should be noted that the terms "first", "second", etc. in the specification, claims, and drawings of the present disclosure are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0111] 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

1. A performance detection method, comprising: Get performance test request; Acquire performance detection information of the target network entity, where the performance detection information includes at least one of data collection performance or data processing performance of the target network entity; The performance detection information is fed back to the source node of the performance detection request.

2. The method according to claim 1, wherein: The data collection performance includes at least one of data load or signaling load.

3. The method according to claim 1 or 2, wherein: The obtaining of the performance detection information of the target network entity includes: obtaining the signaling load of the target network entity, including: measuring the number of at least one of a data collection request or a subscription sent by the target network entity within a predetermined first time length as a first number; measuring the number of at least one of the data collection responses or notifications received by the target network entity within a predetermined first time length as a second number; and The sum of the first number of times and the second number of times is obtained as the signaling load.

4. The method according to claim 1 or 2, wherein: The obtaining of the performance detection information of the target network entity includes: obtaining the data load of the target network entity, including: measuring at least one item in the first data packets of the response or notification related to the data collection received by the target network entity within the predetermined second time length as a third number; When the target network entity receives at least one of the first data packets of response or notification related to data collection within the predetermined second time length, counting the size of the first data packet; and The data load is determined according to the third datagram and the size of the first data packet.

5. The method according to claim 1 or 2, wherein: The obtaining of the performance detection information of the target network entity includes: obtaining the data processing performance of the target network entity, including: determining at least one of the received second data packets of the response or notification processed by the target network entity within a predetermined third time length as a fourth number; When the target network entity processes at least one of the second data packets of response or notification related to data collection within the predetermined third time length, counting the size of the second data packet; determining a data processing amount according to the fourth number and a size of the second data packet; The data processing performance is determined according to the data processing amount and the predetermined third time length.

6. The method according to claim 2, wherein: The data collection performance also includes data collection rate; The obtaining of the performance detection information of the target network entity includes: The data collection rate is determined according to at least one of the signaling load and a time length for collecting statistics on the signaling load, or the data load and a time length for collecting statistics on the data load.

7. The method according to claim 1 or 2, further comprising: The resource configuration of the target network entity is adjusted according to the performance detection information.

8. The method according to claim 7, wherein: The adjusting the resource configuration of the target network entity according to the performance detection information includes at least one of the following: When the signaling load is greater than or equal to a predetermined signaling load threshold, determining to adjust the storage resource configuration of the target network entity; When the data load is greater than or equal to a predetermined data load threshold, determining to adjust the storage resource configuration of the target network entity; When the data processing rate is greater than or equal to a predetermined processing rate threshold, determining to adjust the computing resource configuration of the target network entity; or When the data collection rate is greater than the data processing performance and the difference is greater than a predetermined difference threshold, it is determined to adjust at least one of the storage resource configuration or the computing resource configuration of the target network entity.

9. The method according to claim 1, wherein: The step of feeding back the performance detection information to the source node of the performance detection request includes: At least one of the signaling load, the data load, the data collection rate or the data processing rate is fed back to the source end node of the performance detection request.

10. The method according to claim 1, wherein: The request for obtaining performance detection includes: The performance detection request is obtained by at least one of information subscription and information request.

11. The method according to claim 1, wherein: The step of feeding back the performance detection information to the source node of the performance detection request includes: The performance detection information is fed back to the source node of the performance detection request through at least one of notification and response.

12. The method according to any one of claims 1 to 11, wherein: The target network entity includes a network data analysis function NWDAF entity.

13. A performance detection device, comprising: A request acquisition unit, configured to acquire a performance detection request; an information acquisition unit, configured to acquire performance detection information of a target network entity, wherein the performance detection information includes at least one of a data collection performance of the target network entity or a data processing performance of the target network entity; The information feedback unit is configured to feed back the performance detection information to the source node of the performance detection request.

14. The apparatus according to claim 13, further comprising: A configuration adjustment unit is configured to adjust the resource configuration of the target network entity according to the performance detection information.

15. A performance detection device, comprising: Memory; as well as A processor coupled to the memory, the processor being configured to execute the method according to any one of claims 1 to 12 based on instructions stored in the memory.

16. A non-transitory computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of the method according to any one of claims 1 to 12.

17. A service system comprising: The consumer entity is configured to send a performance detection request to the performance detection device and receive performance detection information fed back by the performance detection device; A performance detection device configured to perform the method according to any one of claims 1 to 12; and One or more network data analysis function NWDAF entities are configured to accept detection by the performance detection device.

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