Service priority determination method, apparatus, and network data analytics function network element

Abstract

The application provides a service priority determination method and device and a network data analysis function network element, and relates to the technical field of communication. The method comprises the following steps: receiving an analysis request sent by a preset network function (NF) network element, wherein the analysis request comprises an analysis identifier of a service priority and a terminal device list to be analyzed; monitoring the service quality and the device state of each terminal device in the terminal device list according to the analysis identifier and the terminal device list, and obtaining the service quality monitoring index and the state information of each terminal device; and determining the priority level of each terminal device according to the service quality monitoring index and the state information of each terminal device, so that the management device executes a service adjustment strategy corresponding to the priority level on each terminal device according to the priority level. The application can determine the priority level of the terminal device, thereby dynamically adjusting the service strategy of the terminal device.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to a service priority determination method, device and network data analysis function network element. BACKGROUND

[0002] With the development of artificial intelligence technology, the application field of intelligent terminal equipment is becoming wider and wider, which promotes the transformation and upgrading of various industries.

[0003] Different business scenarios applied by intelligent terminal equipment have different requirements for network bandwidth, delay and other indicators to ensure smooth task execution. When an intelligent terminal equipment can perform tasks of different business scenarios, the management device needs to specify the application service type of the intelligent terminal equipment to meet the network requirements of the intelligent terminal equipment through the static configuration of the intelligent terminal equipment.

[0004] However, when the intelligent terminal equipment can dynamically change the service type, the static configuration may not adapt to the situation after the service type changes, causing the intelligent terminal equipment to fail to normally execute tasks. If the static configuration is constantly changed to adapt to different service types, it will cause waste of human resources. SUMMARY

[0005] The present application aims to overcome the deficiencies in the prior art and provide a service priority determination method, device and network data analysis function network element to determine the priority level of terminal equipment and dynamically adjust the service strategy of the terminal equipment.

[0006] To achieve the above-mentioned purpose, the technical solutions adopted by the embodiments of the present application are as follows:

[0007] In a first aspect, the embodiments of the present application provide a service priority determination method applied to a network data analysis function NWDAF network element, and the method comprises:

[0008] receiving an analysis request sent by a preset network function NF network element, wherein the analysis request comprises an analysis identifier of service priority and a list of terminal equipment to be analyzed;

[0009] monitoring the service quality and device state of each terminal equipment in the list of terminal equipment according to the analysis identifier and the list of terminal equipment, to obtain the service quality monitoring indicators and state information of the each terminal equipment;

[0010] determining the priority level of each terminal equipment according to the service quality monitoring indicators and state information of each terminal equipment, so that the management device executes the service adjustment strategy corresponding to the priority level of each terminal equipment according to the priority level.

[0011] Optionally, the service quality monitoring indicators include: multiple service quality monitoring sub-data of the first dimension; the status information includes: multiple status sub-data of the second dimension; and the step of determining the priority level of each terminal device based on the service quality monitoring indicators and status information of each terminal device includes:

[0012] Based on the multiple service quality monitoring sub-data of the first dimension and the multiple status sub-data of the second dimension, the service evaluation parameters of each terminal device are determined;

[0013] The priority level is determined based on the service evaluation parameters.

[0014] Optionally, determining the service evaluation parameters for each terminal device based on the plurality of first-dimensional service quality monitoring sub-data and the plurality of second-dimensional status sub-data includes:

[0015] Calculate the first weight of the service quality monitoring indicator and the second weight of the status information;

[0016] Calculate the multiple third weights corresponding to the multiple first dimensions, and the multiple fourth weights corresponding to the multiple second dimensions;

[0017] Based on the first weight and the plurality of third weights, the service quality monitoring sub-data of the plurality of first dimensions are weighted and calculated to obtain the first weighting parameter;

[0018] Based on the second weight and the plurality of fourth weights, the state sub-data of the plurality of second dimensions are weighted and calculated to obtain the second weighting parameter;

[0019] The service evaluation parameters are calculated based on the first weighted parameter and the second weighted parameter.

[0020] Optionally, calculating the first weight of the service quality monitoring indicator and the second weight of the status information includes:

[0021] Obtain a first comparison matrix between the service quality monitoring indicators and the status information, wherein the first comparison matrix includes: a relative importance parameter between the service quality monitoring indicators and the status information;

[0022] The first weight and the second weight are calculated based on the first comparison matrix.

[0023] Optionally, calculating the multiple third weights corresponding to the multiple first dimensions includes:

[0024] Obtain a second comparison matrix among the plurality of first dimensions, the second comparison matrix including: relative importance parameters between every two first dimensions;

[0025] The plurality of third weights are calculated based on the second comparison matrix.

[0026] Optionally, calculating the plurality of third weights based on the second comparison matrix includes:

[0027] Calculate the first largest eigenvalue of the second comparison matrix;

[0028] Based on the first maximum eigenvalue, a first consistency index is calculated. The first consistency index is used to indicate whether the relative importance parameter between each pair of first dimensions is correct.

[0029] If the first consistency index meets the preset consistency condition, the plurality of third weights are calculated according to the second comparison matrix.

[0030] Optionally, calculating the multiple fourth weights corresponding to the multiple second dimensions includes:

[0031] Obtain a third comparison matrix among the plurality of second dimensions, the third comparison matrix including: the relative importance parameter between every two second dimensions;

[0032] The plurality of fourth weights are calculated based on the third comparison matrix.

[0033] Optionally, before calculating the plurality of fourth weights based on the third comparison matrix, the method further includes:

[0034] Calculate the second largest eigenvalue of the third comparison matrix;

[0035] Based on the second maximum eigenvalue, a second consistency index is calculated, which is used to indicate whether the relative importance parameter between each pair of second dimensions is correct.

[0036] If the second consistency index meets the preset consistency condition, the plurality of fourth weights are calculated according to the third comparison matrix.

[0037] Secondly, embodiments of this application also provide a service priority determination device, applied to a network element with network data analysis function (NWDAF), the device comprising:

[0038] The request receiving module is used to receive analysis requests sent by preset network function (NF) network elements. The analysis request includes: an analysis identifier of service priority and a list of terminal devices to be analyzed.

[0039] The data monitoring module is used to monitor the service quality and device status of each terminal device in the terminal device list based on the analysis identifier and the terminal device list, and to obtain the service quality monitoring indicators and status information of each terminal device.

[0040] The priority calculation module is used to determine the priority level of each terminal device based on the service quality monitoring indicators and status information of each terminal device, so that the management device can execute the service adjustment strategy corresponding to the priority level of each terminal device.

[0041] Optionally, the service quality monitoring indicators include: multiple service quality monitoring sub-data of the first dimension; the status information includes: multiple status sub-data of the second dimension; and the level calculation module includes:

[0042] The evaluation parameter calculation unit is used to determine the service evaluation parameters of each terminal device based on the multiple first-dimensional service quality monitoring sub-data and the multiple second-dimensional status sub-data.

[0043] The priority determination unit is used to determine the priority level based on the service evaluation parameters.

[0044] Optionally, the evaluation parameter calculation unit is specifically used to calculate the first weight of the service quality monitoring indicator and the second weight of the status information; calculate the multiple third weights corresponding to the multiple first dimensions and the multiple fourth weights corresponding to the multiple second dimensions; perform weighted calculation on the service quality monitoring sub-data of the multiple first dimensions according to the first weight and the multiple third weights to obtain a first weighted parameter; perform weighted calculation on the status sub-data of the multiple second dimensions according to the second weight and the multiple fourth weights to obtain a second weighted parameter; and calculate the service evaluation parameter according to the first weighted parameter and the second weighted parameter.

[0045] Optionally, the evaluation parameter calculation unit is specifically used to obtain a first comparison matrix between the service quality monitoring index and the status information, wherein the first comparison matrix includes: relative importance parameters between the service quality monitoring index and the status information; and to calculate the first weight and the second weight based on the first comparison matrix.

[0046] Optionally, the evaluation parameter calculation unit is specifically used to obtain a second comparison matrix between the plurality of first dimensions, the second comparison matrix including: relative importance parameters between every two first dimensions; and to calculate the plurality of third weights based on the second comparison matrix.

[0047] Optionally, the evaluation parameter calculation unit is specifically used to calculate the first maximum eigenvalue of the second comparison matrix; calculate the first consistency index based on the first maximum eigenvalue, the first consistency index being used to indicate whether the relative importance parameters between each pair of first dimensions are correct; if the first consistency index meets the preset consistency conditions, calculate the plurality of third weights based on the second comparison matrix.

[0048] Optionally, the evaluation parameter calculation unit is specifically used to obtain a third comparison matrix among the plurality of second dimensions, the third comparison matrix including: relative importance parameters between every two second dimensions; and to calculate the plurality of fourth weights based on the third comparison matrix.

[0049] Optionally, the evaluation parameter calculation unit is specifically used to calculate the second maximum eigenvalue of the third comparison matrix; calculate the second consistency index based on the second maximum eigenvalue, the second consistency index being used to indicate whether the relative importance parameter between each pair of second dimensions is correct; if the second consistency index meets the preset consistency condition, calculate the plurality of fourth weights based on the third comparison matrix.

[0050] Thirdly, embodiments of this application also provide a network element with network data analysis functionality, including:

[0051] Transceiver, processor, and storage media;

[0052] The transceiver is used to receive and send data;

[0053] The storage medium stores program instructions executable by the processor;

[0054] The processor is used to invoke the program instructions stored in the storage medium to execute the steps of the service priority determination method as described in any of the third aspects.

[0055] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the service priority determination method as described in any of the first aspects.

[0056] The beneficial effects of this application are:

[0057] This application provides a service priority determination method, apparatus, and network data analysis function network element. By monitoring the service quality and device status of terminal devices, and analyzing the priority level of terminal devices based on the service quality monitoring indicators and status information, the service strategy of terminal devices can be adjusted according to the priority level. This enables flexible policy adjustment for terminal devices that can flexibly adjust their services to meet network resource needs, avoid service execution problems caused by insufficient network resources, or resource waste caused by excessive network resources. It achieves intelligent adjustment of service strategies for terminal devices without manual configuration, saving human resources. Attached Figure Description

[0058] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A network architecture diagram provided for embodiments of this application;

[0060] Figure 2 Flowchart of the service priority determination method provided in the embodiments of this application Figure 1 ;

[0061] Figure 3 An interactive diagram illustrating the service priority determination method provided in this application embodiment;

[0062] Figure 4 Flowchart of the service priority determination method provided in the embodiments of this application Figure 2 ;

[0063] Figure 5 Flowchart of the service priority determination method provided in the embodiments of this application Figure 3 ;

[0064] Figure 6 A schematic diagram of the hierarchical model provided in the embodiments of this application;

[0065] Figure 7 Flowchart of the service priority determination method provided in the embodiments of this application Figure 4 ;

[0066] Figure 8 Flowchart of the service priority determination method provided in the embodiments of this application Figure 5 ;

[0067] Figure 9 Flowchart of the service priority determination method provided in the embodiments of this application Figure 6 ;

[0068] Figure 10 Flowchart of the service priority determination method provided in the embodiments of this application Figure 7 ;

[0069] Figure 11 Flowchart of the service priority determination method provided in the embodiments of this application Figure 8 ;

[0070] Figure 12 A schematic diagram of the service priority determination device provided in the embodiments of this application;

[0071] Figure 13 A schematic diagram of the network data analysis function network element provided in the embodiments of this application. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0073] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0074] Furthermore, the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Additionally, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0075] It should be noted that, where there is no conflict, the features in the embodiments of this application can be combined with each other.

[0076] Before introducing the service priority determination method provided in the embodiments of this application, its application scenarios will be explained first.

[0077] Please refer to Figure 1 Here is a network architecture diagram provided in the embodiments of this application, such as... Figure 1 As shown, the network architecture may specifically include:

[0078] 1. Unmanned Aerial Vehicle (UAV): The terminal equipment (User Equipment, UE) targeted in this application is mainly unmanned aerial vehicles.

[0079] 2. Access Network (AN): Provides network access functionality to authorized users in a specific area and can use transmission tunnels of different qualities based on user level and service requirements. An access network that implements access network functions based on wireless communication technology can be called a Radio Access Network (RAN). The RAN manages radio resources, provides access services to terminals, and facilitates the forwarding of control signals and user data between terminals and the core network. It is typically provided through base stations.

[0080] 3. Session Management Function (SMF) network element: mainly used for session management, UE Internet Protocol (IP) address allocation and management, selection of manageable user plane functions, policy control, or terminal points of charging function interfaces, and downlink data notification, etc.

[0081] 4. Policy Control Function (PCF) network element: A unified policy framework used to guide network behavior, providing policy rule information to control plane functional network elements (such as AMF network element, SMF network element, etc.).

[0082] 5. User Plane Function (UPF) network element: also known as a data plane gateway. It can be used for packet routing and forwarding, or for quality of service (QoS) processing of user plane data. User data can access the data network (DN) through this network element.

[0083] 6. Network Data Analytics Function (NWDAF): This network element can provide network analysis services based on network service request data.

[0084] 7. Uncrewed Aerial Systems Network Function (UAS-NF) network element: used for control and management equipment to communicate with the UAV through the core network.

[0085] 8. Unmanned Aerial Vehicle (UAS) Traffic Management (UTM) and Unmanned Aerial Vehicle (UAS) Service Supplier (USS): Used to manage unmanned aerial vehicles (UAVs).

[0086] It should be understood that the aforementioned network elements can communicate with each other through preset interfaces, which will not be elaborated further here. It should also be understood that SMF network elements, PCF network elements, UPF network elements, NWDAF network elements, and UAS-NF network elements can be understood as network elements in the core network used to implement different functions. These core network elements can be independent devices or integrated into the same device to implement different functions. This application does not limit this.

[0087] Based on the above network architecture, this application provides a method for determining the service priority of NWDAF network elements in the above network architecture.

[0088] Please refer to Figure 2 The following is a flowchart illustrating the service priority determination method provided in the embodiments of this application. Figure 1 ,like Figure 2 As shown, the method may include:

[0089] S10: Receive the analysis request sent by the NF network element. The analysis request includes: the analysis identifier of service priority and the list of terminal devices to be analyzed.

[0090] In this embodiment, the terminal device is a drone, the NF network element is a UAS-NF network element, and after receiving the event reporting request sent by the management device UTM / USS, the UAS-NF network element authorizes the event reporting request of UTM / USS and sends an analysis request to the NWDAF network element.

[0091] The event report request may include at least: an event identifier and a list of UAVs to be analyzed. The event identifier is used to indicate the event for obtaining a service priority level status report of a UAV. The UAV list includes the device identifier of at least one UAV. The analysis request may include at least: an analysis identifier and a list of UAVs to be analyzed. The analysis identifier can be determined based on the event identifier in the event report request and is used to indicate the analysis of the service priority of the UAVs.

[0092] In some embodiments, the event reporting request further includes: reporting conditions, wherein the reporting conditions are used to instruct the UAS-NF network element to send a service priority level status report to the UTM / USS, wherein if the reporting conditions are periodic reporting, the event reporting request further includes: the reporting time interval, wherein the UAS-NF network element periodically sends the service priority level status report to the UTM / USS according to the time interval; if the reporting conditions are change-based reporting, the UAS-NF network element sends the service priority level status report to the UTM / USS when it determines that the priority level of the UAV has changed.

[0093] If the event reporting request includes a reporting time interval, the analysis request will also include an analysis time interval. The reporting time interval and the analysis time interval are the same, instructing the NWDAF network element to periodically perform priority analysis on the UAVs in the UAV list to be analyzed. If the event reporting request does not include a reporting time interval, the analysis time interval in the analysis request will be the default time interval, such as 10 seconds.

[0094] S20: Based on the analysis identifier and the list of terminal devices, monitor the service quality and device status of each terminal device in the list of terminal devices to obtain the service quality monitoring indicators and status information of each terminal device.

[0095] In this embodiment, the parameters affecting the UAV's execution of tasks in the service scenario include: the UAV's quality of service (QoS) and the UAV's device status. The UAV's QoS is jointly monitored by the base station where the UAV is located and the UPF network element and reported to the MWDAF network element, while the UAV's device status is reported by the UAV to the NWDAF network element.

[0096] In some embodiments, after receiving an analysis request, the NWDAF network element initiates a monitoring request to the PCF network element. The monitoring request message may include at least: QoS, a list of UAVs and the PDU sessions corresponding to each UAV, and device status notifications for the UAVs. The device status notifications for the UAVs are used to indicate the acquisition of UAV status information. Furthermore, the monitoring request may also include: a monitoring time interval, which is the same as the analysis time interval and the reporting time interval.

[0097] The PCF network element generates a monitoring policy based on the monitoring request and sends it to the SMF network element. The monitoring policy may include at least: QoS, UAV list and PDU sessions corresponding to each UAV, and device status notification of the UAV. Furthermore, it may also include: the monitoring time interval.

[0098] The SMF network element generates monitoring rules according to the monitoring strategy and sends them to the RAN and UPF network elements respectively. It also forwards the UAV's device status notification and time interval information to the UAV through the RAN. Specifically, the RAN monitors the service quality of the UAV during the uplink process based on the PDU session corresponding to the UAV and sends the service quality monitoring indicators of the UAV during the uplink process to the NWDAF network element. The UPF monitors the service quality of the UAV during the downlink process based on the PDU session corresponding to the UAV and sends the service quality monitoring indicators of the UAV during the downlink process to the NWDAF network element. The UAV also sends its own status information to the NWDAF network element.

[0099] S30: Based on the service quality monitoring indicators and status information of each terminal device, determine the priority level of each terminal device so that the management device can execute the service adjustment strategy corresponding to the priority level of each terminal device.

[0100] In this embodiment, the MWDAF network element analyzes the priority level of each UAV based on the service quality monitoring indicators and status information of each UAV, determines the priority level of each UAV, and sends the priority level of each UAV to the UAS-NF network element. The UAS-NF network element, based on the reporting conditions in the event reporting request, sends the priority level of each UAV to the UTM / USS in the form of a service priority level status report when it determines that the reporting conditions are met.

[0101] After receiving the service priority level status report, the UTM / USS executes the service adjustment policy corresponding to the priority level of each UAV.

[0102] In some embodiments, the service adjustment policy is used to instruct, when network resources are limited, to control the highest priority UAVs to execute their corresponding tasks, control the remaining UAVs to suspend task execution, and control the remaining UAVs to execute previously suspended tasks after the tasks of the highest priority UAVs have been completed.

[0103] In other embodiments, the service adjustment policy is used to instruct the 5GS to request a new QoS policy for the UAV when the priority level of the UAV changes, so as to allocate new network resources that match the priority level to the UAV, ensuring that the UAV with a high priority level has enough network resources to perform the corresponding tasks, and avoiding the waste of network resources caused by the UAV with a low priority level temporarily using too many network resources.

[0104] Please refer to Figure 3 This is an interactive schematic diagram of the service priority determination method provided in the embodiments of this application, such as... Figure 3 As shown, the process may include:

[0105] 1. After UAV is registered, certified and authorized by 5GS, it establishes a PDU session with UTM / USS.

[0106] 2. The UTM / USS sends tasks to the UAV and responds.

[0107] 3. The UTM / USS initiates an event report request to the UAS-NF network element.

[0108] 4. The UAS-NF network element authorizes the UTM / USS request and initiates an analysis request to the NWDAF network element.

[0109] 5. The NWDAF network element initiates a monitoring request to the PCF network element.

[0110] 6. The PCF network element generates monitoring strategies and distributes them to the SMF network element.

[0111] 7. The SMF network element generates monitoring rules according to the monitoring strategy and sends them to the RAN and UPF network elements respectively. It also forwards the UAV's device status notification and time interval information to the UAV through the RAN.

[0112] 8. SMF network element responds to PCF network element.

[0113] 9. PCF network element responds to NWDAF network element.

[0114] 10. NWDAF network element responds to UAS-NF network element.

[0115] 11. UAS-NF network element response to UTM / USS.

[0116] 12. RAN and UPF network elements monitor the QoS of UAV and report QoS monitoring indicators, while UAV reports status information.

[0117] 13. The NWDAF network element performs statistical analysis based on the reported QoS monitoring indicators and UAV status information, and obtains priority analysis results.

[0118] 14. The NWDAF network element sends the analysis results to the UAS-NF network element.

[0119] 15. The UAS-NF network element reports the analysis results to the UTM / USS.

[0120] 16. UTM / USS executes the service adjustment strategy corresponding to the priority level based on the priority analysis results.

[0121] The service priority determination method provided in the above embodiments monitors the service quality and device status of terminal devices, analyzes the priority level of terminal devices based on the service quality monitoring indicators and status information of the terminal devices, and adjusts the service strategy of terminal devices according to the priority level of the terminal devices. This enables flexible policy adjustment for terminal devices that can flexibly adjust their services to meet the needs of network resources, avoids service execution problems of terminal devices due to insufficient network resources, or resource waste due to excessive network resources, and realizes intelligent adjustment of service strategies of terminal devices without manual configuration, thus saving human resources.

[0122] In some embodiments, the service quality monitoring metrics include: multiple service quality monitoring sub-data of a first dimension, and the status information includes: multiple status sub-data of a second dimension.

[0123] The following describes a possible implementation of determining priority levels based on service quality monitoring indicators and status information, with reference to an embodiment.

[0124] Please refer to Figure 4 The following is a flowchart illustrating the service priority determination method provided in the embodiments of this application. Figure 2 ,like Figure 4 As shown, the process of determining the priority level of each terminal device based on the service quality monitoring indicators and status information of each terminal device in S30 above may include:

[0125] S301: Determine the service evaluation parameters for each terminal device based on multiple service quality monitoring sub-data from the first dimension and multiple status sub-data from the second dimension.

[0126] In this embodiment, multiple service quality monitoring sub-data of the first dimension and multiple status sub-data of the second dimension are weighted and calculated to determine the service evaluation parameters for each terminal device.

[0127] In some embodiments, the service evaluation parameters for each terminal device are determined by calculating the weights of multiple first dimensions and multiple second dimensions, and performing weighted calculations on multiple service quality monitoring sub-data and multiple status sub-data.

[0128] S302: Determine the priority level based on service evaluation parameters.

[0129] In this embodiment, the service evaluation parameters are divided into intervals according to preset service evaluation parameters, and the interval to which the service evaluation parameters belong is determined to obtain the priority level. The priority level is used to indicate the level at which the UAV performs the current task.

[0130] Exemplarily, taking the three levels of low, medium, and high as examples, the service evaluation parameter interval [a, b] is the low-priority level, the service evaluation parameter interval (b, c] is the medium-priority level, and the service evaluation parameter interval (c, d] is the high-priority level, where a < b < c < d. Of course, this priority level interval is only an exemplary interval and not the only limited interval. Specifically, the divided interval can be determined according to actual needs, and this embodiment does not limit this.

[0131] The service priority determination method provided by the above embodiment calculates the service evaluation parameters of the terminal device based on the service quality monitoring sub-data of multiple first dimensions and the status sub-data of multiple second dimensions, making the result of the calculated service evaluation parameters more accurate. Thus, the priority equivalence determined according to the service evaluation parameters can be more accurate, ensuring that the service adjustment strategy executed for the terminal device is more accurate and achieving the optimal use of network resources.

[0132] The following describes a possible implementation manner of calculating the service evaluation parameters of the above terminal device in conjunction with an embodiment.

[0133] Please refer to Figure 5 , which is the flowchart of the service priority determination method provided by the embodiment of the present application Figure 3 , as Figure 5 shown, the process of determining the service evaluation parameters of each terminal device according to the service quality monitoring sub-data of multiple first dimensions and the status sub-data of multiple second dimensions in S301 above may include:

[0134] S311: Calculate the first weight of the service quality monitoring index and the second weight of the status information.

[0135] In this embodiment, please refer to Figure 6 , which is the schematic diagram of the hierarchical model provided by the embodiment of the present application. As Figure 6 shown, the hierarchical model of the UAV consists of a three-layer structure. Among them, the factor in the first-layer structure is the service evaluation parameter (A), the factors in the second-layer structure are the service quality monitoring index (B1) and the status information (B2) that constitute the service evaluation parameter, and the factors in the third-layer structure include: multiple first-dimensional service quality monitoring sub-data (Ci, i = 1 to n) that constitute the service quality monitoring index, and multiple second-dimensional status sub-data (Ci, i = n + 1 to m) that constitute the status information.

[0136] Among them, the first weight w1 of the service quality monitoring index and the second weight w2 of the status information can be determined according to the influence degrees of the service quality and the status of the UAV on the UAV's task execution.

[0137] S312: Calculate multiple third weights corresponding to multiple first dimensions, and multiple fourth weights corresponding to multiple second dimensions.

[0138] In this embodiment, multiple third weights w corresponding to the multiple first dimensions are determined based on the importance of the service quality monitoring sub-data of the multiple first dimensions to the service quality monitoring indicators. Ci (i = i = 1 to n), based on the importance of multiple second-dimensional state sub-data to the state information, determine multiple fourth weights w for multiple second-dimensional dimensions. Ci (i = n+1 ~ m).

[0139] For example, such as Figure 6 As shown, the multiple first dimensions may include: latency dimension (C1), bandwidth dimension (C2), jitter dimension (C3), and reliability dimension (C4). The multiple second dimensions may include: task type dimension (C5), task time limit dimension (C6), task distance dimension (C7), flight time dimension (C8), and remaining power dimension (C9). Among them, task type is used to indicate the type of task performed by the UAV, task time limit is used to indicate the time limit required for the task performed by the UAV, task distance is used to indicate the flight distance of the task performed by the UAV, flight time is used to indicate the time required for the UAV to perform the task, and remaining power is used to indicate the remaining available power of the UAV.

[0140] S313: Based on the first weight and multiple third weights, perform weighted calculations on multiple service quality monitoring sub-data of the first dimension to obtain the first weighted parameter.

[0141] In this embodiment, based on multiple third weights w Ci (i = i = 1 ~ n) After weighted summation of multiple service quality monitoring sub-data xi of the first dimension, the weighted summation result is then weighted according to the first weight w1 to obtain the first weighting parameter.

[0142] S314: Based on the two weights and multiple fourth weights, perform weighted calculations on the state sub-data of multiple second dimensions to obtain the second weighted parameters.

[0143] In this embodiment, based on multiple fourth weights w Ci (i = n + 1 ~ m) After weighted summation of multiple state sub-data of the second dimension, the weighted summation result is further weighted according to the second weight w2 to obtain the second weighting parameter.

[0144] S315: Calculate the service evaluation parameters based on the first weighted parameter and the second weighted parameter.

[0145] In this embodiment, the service evaluation parameters are obtained based on the sum of the first weighted parameter and the second weighted parameter.

[0146] For example, the formula for calculating service evaluation parameters can be expressed as:

[0147]

[0148] The service priority determination method provided in the above embodiments calculates a first weight of service quality monitoring indicators and a second weight of status information, as well as multiple third weights of multiple first dimensions and multiple fourth weights corresponding to multiple second dimensions. It then determines service evaluation parameters by weighting multiple service quality monitoring sub-data based on the first weight and multiple third weights, and by weighting multiple status sub-data based on the second weight and multiple fourth weights. This makes the priority equivalence determined based on the service evaluation parameters more accurate, ensuring that the service adjustment strategy executed for terminal devices is more accurate, and achieving optimal use of network resources.

[0149] The following describes a possible implementation of the above calculation of the first weight and the second weight, with reference to an embodiment.

[0150] Please refer to Figure 7 The following is a flowchart illustrating the service priority determination method provided in the embodiments of this application. Figure 4 ,like Figure 7 As shown, the process of calculating the first weight of the service quality monitoring indicator and the second weight of the status information in S311 above may include:

[0151] S3111: Obtain the first comparison matrix of service quality monitoring indicators and status information. The first comparison matrix includes the relative importance parameters between service quality monitoring indicators and status information.

[0152] In this embodiment, a first comparison matrix is ​​constructed based on the importance of service quality monitoring indicators and status information relative to the priority of the tasks performed by the UAV. The first comparison matrix includes: a relative parameter of the importance of service quality monitoring indicators relative to status information, and a relative parameter of the importance of status information relative to service quality monitoring indicators, which are reciprocals of each other.

[0153] For example, the first comparison matrix can be represented as: Let 1, 3, 5, 7, and 9 represent the relative importance parameters between pairs of indicators. For b... ij This indicates the degree of importance of indicator i compared to indicator j, with 1 representing equal importance, 3 representing slightly important, 5 representing significantly important, 7 representing strongly important, and 9 representing extremely important. For example, b 12 =3 indicates that, compared to indicator 2, indicator 1 is slightly more important, and b 21 =1 / 3, that is, b ij=1 / b ji In addition, 2, 4, 6, and 8 represent the median values ​​of the pairwise importance values ​​mentioned above. For example, the importance value of 2 is between that of 1 and 3.

[0154] S3112: Calculate the first weight and the second weight based on the first comparison matrix.

[0155] In this embodiment, the weight vector is calculated on the first comparison matrix to obtain the first weight and the second weight. The specific calculation method can be: arithmetic mean method, geometric mean method or eigenvalue method, etc.

[0156] In some embodiments, the specific calculation method can be as follows: First, for each column in the first comparison matrix, the column is summed, and then the value of the column is divided by the sum of the column to obtain the ratio of each value in the column to the total sum of the column; Second, for the values ​​calculated above, the average value of each row is calculated, that is, for each row, the values ​​of the row are summed and then divided by the number to obtain the corresponding weight.

[0157] For example, for the first comparison matrix First, calculate the sum of the first column as 1 + b. 21 The sum of the second column is b. 21 +1, divide the value in each column by the sum of that column, and get Then, the values ​​in each row are summed and divided by the number of rows to obtain the average value. The average value of each row corresponds to a weight, and the weight vector is W. B =[w1,w2] T Where w1 is the first weight and w2 is the second weight.

[0158] The following describes a possible implementation of the above-described calculation of multiple third weights in conjunction with an example.

[0159] Please refer to Figure 8 The following is a flowchart illustrating the service priority determination method provided in the embodiments of this application. Figure 5 ,like Figure 8 As shown, the process of calculating multiple third weights corresponding to multiple first dimensions in S312 above may include:

[0160] S3121: Obtain the second comparison matrix between multiple first dimensions.

[0161] In this embodiment, a second comparison matrix is ​​constructed based on the degree of importance of each first dimension relative to the service quality monitoring indicators. The second comparison matrix includes the relative importance parameters between each pair of first dimensions.

[0162] For example, the second comparison matrix can be represented as:

[0163] S3122: Calculate multiple third weights based on the second comparison matrix.

[0164] In this embodiment, a weight vector is calculated on the second comparison matrix to obtain multiple third weights. The calculation method can refer to S3112 above, and will not be repeated here. The multiple third weights are W. CB1 =(w C1 ,w C2 ,w C3 ,w C4 ) T .

[0165] Please refer to some possible implementation methods. Figure 9 The following is a flowchart illustrating the service priority determination method provided in the embodiments of this application. Figure 6 ,like Figure 9 As shown, the process of calculating multiple third weights based on the second comparison matrix in S3122 above may include:

[0166] S3122a: Calculate the first largest eigenvalue of the second comparison matrix.

[0167] In this embodiment, the characteristic polynomial λE-C is constructed based on the second comparison matrix. Bi =0, solve for the characteristic polynomial, and obtain the first largest eigenvalue λ of the second comparison matrix. max .

[0168] S3122b: Calculate the first consistency index based on the first maximum eigenvalue. The first consistency index is used to indicate whether the relative importance parameters between any two first dimensions are correct.

[0169] In this embodiment, a first consistency index is calculated based on the first maximum eigenvalue to determine whether the relative importance parameters between every two first dimensions in the constructed second comparison matrix are correct. The first consistency index can be calculated as follows: Where n is the number of multiple first dimensions, and RI is the average random consistency index, which can be determined by looking up a table.

[0170] S3122c: If the first consistency index meets the preset consistency conditions, calculate multiple third weights based on the second comparison matrix.

[0171] In this embodiment, it is determined whether the first consistency index meets the preset consistency condition. If the first consistency index meets the preset consistency condition, it is determined that the second comparison matrix passes the consistency check. The relative importance parameters between each pair of first dimensions in the second comparison matrix are correct. Multiple third weights can be calculated for the second comparison matrix using the steps of S3122 described above.

[0172] If the first consistency index does not meet the preset consistency conditions, it is determined that the second comparison matrix has failed the consistency check. The relative importance parameters between every two first dimensions in the second comparison matrix are incorrect, and the relative importance parameters in the second comparison matrix need to be adjusted.

[0173] The preset consistency condition can be, for example, CR < 0.1.

[0174] Please refer to Figure 10 The following is a flowchart illustrating the service priority determination method provided in the embodiments of this application. Figure 7 ,like Figure 10 As shown, the process of calculating multiple fourth weights corresponding to multiple second dimensions in S312 above may include:

[0175] S3123: Obtain the third comparison matrix between multiple second dimensions.

[0176] S3124: Calculate multiple fourth weights based on the third comparison matrix.

[0177] In this embodiment, a third comparison matrix is ​​constructed based on the degree of importance of each second dimension relative to the state information. The third comparison matrix includes the relative importance parameters between each pair of second dimensions.

[0178] For example, the third comparison matrix can be represented as:

[0179] The weight vector of the third comparison matrix is ​​calculated to obtain multiple fourth weights. The calculation method can be referred to S3112 above, and will not be repeated here. The multiple fourth weights are W. CB2 =(w C5 ,w C6 ,w C7 ,w C8 w C9 ) T .

[0180] Please refer to some possible implementation methods. Figure 11 The following is a flowchart illustrating the service priority determination method provided in the embodiments of this application. Figure 8 ,like Figure 11 As shown, the process of calculating multiple fourth weights based on the third comparison matrix in S3124 above may include:

[0181] S3124a: Calculate the second largest eigenvalue of the third comparison matrix.

[0182] S3124b: Calculate the second consistency index based on the second largest eigenvalue. The second consistency index is used to indicate whether the relative importance parameters between each pair of second dimensions are correct.

[0183] S3124c: If the second consistency index meets the preset consistency conditions, calculate multiple fourth weights based on the third comparison matrix.

[0184] In this embodiment, the process of determining whether the third comparison matrix satisfies the preset consistency condition can refer to the steps S3122a-S3122c above, and will not be repeated here.

[0185] In addition to the above method embodiments, this application also provides a service priority determination device applied to an NWDAF network element. Please refer to... Figure 12 The above is a schematic diagram of the service priority determination device provided in the embodiments of this application. Figure 12 As shown, the device may include:

[0186] The request receiving module 10 is used to receive analysis requests sent by preset network function NF network elements. The analysis request includes: analysis identifier of service priority and list of terminal devices to be analyzed.

[0187] The data monitoring module 20 is used to monitor the service quality and device status of each terminal device in the terminal device list based on the analysis identifier and the terminal device list, and to obtain the service quality monitoring indicators and status information of each terminal device.

[0188] The priority calculation module 30 is used to determine the priority level of each terminal device based on the service quality monitoring indicators and status information of each terminal device, so that the management device can execute the service adjustment strategy corresponding to the priority level of each terminal device.

[0189] Optionally, service quality monitoring indicators include: multiple first-dimensional service quality monitoring sub-data; status information includes: multiple second-dimensional status sub-data; and the rating calculation module 30 includes:

[0190] The evaluation parameter calculation unit is used to determine the service evaluation parameters of each terminal device based on multiple first-dimensional service quality monitoring sub-data and multiple second-dimensional status sub-data.

[0191] The priority determination unit is used to determine the priority level based on service evaluation parameters.

[0192] Optionally, the evaluation parameter calculation unit is specifically used to calculate the first weight of the service quality monitoring indicators and the second weight of the status information; calculate multiple third weights corresponding to multiple first dimensions and multiple fourth weights corresponding to multiple second dimensions; perform weighted calculation on the service quality monitoring sub-data of multiple first dimensions according to the first weight and multiple third weights to obtain the first weighted parameter; perform weighted calculation on the status sub-data of multiple second dimensions according to the second weight and multiple fourth weights to obtain the second weighted parameter; and calculate the service evaluation parameter according to the first weighted parameter and the second weighted parameter.

[0193] Optionally, the evaluation parameter calculation unit is specifically used to obtain a first comparison matrix between service quality monitoring indicators and status information. The first comparison matrix includes: relative importance parameters between service quality monitoring indicators and status information; and to calculate a first weight and a second weight based on the first comparison matrix.

[0194] Optionally, the evaluation parameter calculation unit is specifically used to obtain a second comparison matrix between multiple first dimensions, the second comparison matrix including: the relative importance parameters between every two first dimensions; and to calculate multiple third weights based on the second comparison matrix.

[0195] Optionally, the evaluation parameter calculation unit is specifically used to calculate the first maximum eigenvalue of the second comparison matrix; calculate the first consistency index based on the first maximum eigenvalue, the first consistency index being used to indicate whether the relative importance parameters between each pair of first dimensions are correct; if the first consistency index meets the preset consistency conditions, calculate multiple third weights based on the second comparison matrix.

[0196] Optionally, the evaluation parameter calculation unit is specifically used to obtain a third comparison matrix between multiple second dimensions, the third comparison matrix including: the relative importance parameters between every two second dimensions; and to calculate multiple fourth weights based on the third comparison matrix.

[0197] Optionally, the evaluation parameter calculation unit is specifically used to calculate the second largest eigenvalue of the third comparison matrix; based on the second largest eigenvalue, calculate the second consistency index, which is used to indicate whether the relative importance parameters between each pair of second dimensions are correct; if the second consistency index meets the preset consistency conditions, calculate multiple fourth weights based on the third comparison matrix.

[0198] The above-described device is used to execute the method provided in the foregoing embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

[0199] These modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more microprocessors, or one or more Field Programmable Gate Arrays (FPGAs). Alternatively, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together as a system-on-a-chip (SOC).

[0200] Please refer to Figure 13 This is a schematic diagram of the network data analysis function network element provided in the embodiments of this application, such as... Figure 13 As shown, the network data analysis function network element 100 may include: a transceiver 101, a processor 102, and a storage medium 103; the transceiver 101 is used to receive and send data; the storage medium 103 stores program instructions executable by the processor 102; the processor 102 is used to call the program instructions stored in the storage medium 103 to execute the above method embodiment. The specific implementation method and technical effect are similar, and will not be described in detail here.

[0201] Optionally, the present invention also provides a computer-readable storage medium storing a computer program, which is executed by a processor to perform the above-described method embodiments.

[0202] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0203] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0204] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0205] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0206] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for determining service priority, characterized in that, The method, applied to the NWDAF network element for network data analysis, includes: Receive analysis requests sent by preset network function (NF) network elements, wherein the analysis requests include: analysis identifier of service priority and list of terminal devices to be analyzed; Based on the analysis identifier and the terminal device list, the service quality and device status of each terminal device in the terminal device list are monitored to obtain the service quality monitoring indicators and status information of each terminal device. Based on the service quality monitoring indicators and status information of each terminal device, the priority level of each terminal device is determined so that the management device can execute the service adjustment strategy corresponding to the priority level of each terminal device. The service quality monitoring indicators include multiple service quality monitoring sub-data of the first dimension, and the status information includes multiple status sub-data of the second dimension. The step of determining the priority level of each terminal device based on the service quality monitoring indicators and status information of each terminal device includes: Calculate the first weight of the service quality monitoring indicator and the second weight of the status information; Calculate the multiple third weights corresponding to the multiple first dimensions, and the multiple fourth weights corresponding to the multiple second dimensions; Based on the first weight and the plurality of third weights, the service quality monitoring sub-data of the plurality of first dimensions are weighted and calculated to obtain the first weighting parameter; Based on the second weight and the plurality of fourth weights, the state sub-data of the plurality of second dimensions are weighted and calculated to obtain the second weighting parameter; The service evaluation parameters for each terminal device are determined based on the first weighting parameter and the second weighting parameter. The priority level is determined based on the service evaluation parameters.

2. The method as described in claim 1, characterized in that, The calculation of the first weight of the service quality monitoring indicator and the second weight of the status information includes: Obtain a first comparison matrix between the service quality monitoring indicators and the status information, wherein the first comparison matrix includes: a relative importance parameter between the service quality monitoring indicators and the status information; The first weight and the second weight are calculated based on the first comparison matrix.

3. The method as described in claim 1, characterized in that, The calculation of the multiple third weights corresponding to the multiple first dimensions includes: Obtain a second comparison matrix among the plurality of first dimensions, the second comparison matrix including: relative importance parameters between every two first dimensions; The plurality of third weights are calculated based on the second comparison matrix.

4. The method as described in claim 3, characterized in that, The step of calculating the plurality of third weights based on the second comparison matrix includes: Calculate the first largest eigenvalue of the second comparison matrix; Based on the first maximum eigenvalue, a first consistency index is calculated. The first consistency index is used to indicate whether the relative importance parameter between each pair of first dimensions is correct. If the first consistency index meets the preset consistency condition, the plurality of third weights are calculated according to the second comparison matrix.

5. The method as described in claim 1, characterized in that, The calculation of multiple fourth weights corresponding to multiple second dimensions includes: Obtain a third comparison matrix among the plurality of second dimensions, the third comparison matrix including: the relative importance parameter between every two second dimensions; The plurality of fourth weights are calculated based on the third comparison matrix.

6. The method as described in claim 5, characterized in that, The calculation of the plurality of fourth weights based on the third comparison matrix includes: Calculate the second largest eigenvalue of the third comparison matrix; Based on the second maximum eigenvalue, a second consistency index is calculated, which is used to indicate whether the relative importance parameter between each pair of second dimensions is correct. If the second consistency index meets the preset consistency condition, the plurality of fourth weights are calculated according to the third comparison matrix.

7. A service priority determination device, characterized in that, The device, applied to the NWDAF network element for network data analysis, includes: The request receiving module is used to receive analysis requests sent by preset network function (NF) network elements. The analysis request includes: an analysis identifier of service priority and a list of terminal devices to be analyzed. The data monitoring module is used to monitor the service quality and device status of each terminal device in the terminal device list based on the analysis identifier and the terminal device list, and to obtain the service quality monitoring indicators and status information of each terminal device. The priority calculation module is used to determine the priority level of each terminal device based on the service quality monitoring indicators and status information of each terminal device, so that the management device can execute the service adjustment strategy corresponding to the priority level of each terminal device according to the priority level. The service quality monitoring indicators include: multiple service quality monitoring sub-data of the first dimension; the status information includes: multiple status sub-data of the second dimension; the level calculation module includes: The evaluation parameter calculation unit is used to calculate the first weight of the service quality monitoring indicator and the second weight of the status information; calculate the third weights corresponding to the multiple first dimensions and the fourth weights corresponding to the multiple second dimensions; perform weighted calculation on the service quality monitoring sub-data of the multiple first dimensions according to the first weight and the multiple third weights to obtain a first weighting parameter; perform weighted calculation on the status sub-data of the multiple second dimensions according to the second weight and the multiple fourth weights to obtain a second weighting parameter; and determine the service evaluation parameters of each terminal device according to the first weighting parameter and the second weighting parameter. The priority determination unit is used to determine the priority level based on the service evaluation parameters.

8. A network element with network data analysis function, characterized in that, include: Transceiver, processor, and storage media; The transceiver is used to receive and send data; The storage medium stores program instructions executable by the processor; The processor is used to invoke the program instructions stored in the storage medium to execute the steps of the service priority determination method as described in any one of claims 1-6.

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