CN116847412A - Slice load evaluation method, device, management data analysis function network element and medium - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
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- H04W28/0925—Management thereof using policies
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
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Abstract
The application provides a slice load assessment method, a slice load assessment device, a management data analysis function network element and a management data analysis function medium, and relates to the technical field of communication. The method comprises the following steps: according to load assessment requirements for a preset network slice, a slice data acquisition request is sent to an NWDAF network element, so that the NWDAF network element respectively acquires data of the preset network slice in a plurality of load influence factors from a plurality of NF network elements; receiving a slice data acquisition response returned by the NWDAF network element, wherein the slice data acquisition response comprises the following steps: data for a plurality of load influencing factors; carrying out load evaluation on a preset network slice according to data of a plurality of load influence factors to generate a load evaluation result; and sending load evaluation results to the NF network elements so that the NF network elements adjust the load of the preset network slice according to the load evaluation results. The application can realize accurate evaluation of the load of the network slice.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a slice load evaluation method, a slice load evaluation device, a network element with a management data analysis function, and a medium.
Background
The network slice belongs to a network resource allocation mechanism, and can enable a communication service operator to dynamically allocate network resources so as to furthest improve the client value.
By dynamically controlling end-to-end network slicing, the provided services can expand or contract to control the use of network resources according to traffic demands, and the selection and management of network slicing become a major concern.
In the prior art, the selection priority of the network slice is generally determined according to the analysis of the number of users and the number of resource bearers on the network slice, but because the factors are not specific enough, the analysis result is not accurate enough, and therefore, effective management of the network slice cannot be realized.
Disclosure of Invention
The application aims to provide a slice load evaluation method, a slice load evaluation device, a management data analysis function network element and a management data analysis function medium for realizing accurate evaluation of the load of a network slice.
In order to achieve the above purpose, the technical scheme adopted by the embodiment of the application is as follows:
in a first aspect, an embodiment of the present application provides a slice load assessment method, applied to an MDAF network element with a management data analysis function, where the method includes:
According to load assessment requirements for a preset network slice, a slice data acquisition request is sent to a network data analysis function NWDAF network element, so that the NWDAF network element respectively acquires data of the preset network slice in a plurality of load influence factors from a plurality of network function NF network elements;
receiving a slice data acquisition response returned by the NWDAF network element, wherein the slice data acquisition response comprises: data of the plurality of load influencing factors;
carrying out load evaluation on the preset network slice according to the data of the load influence factors to generate a load evaluation result;
and sending the load evaluation results to the NF network elements so that the NF network elements adjust the load of the preset network slice according to the load evaluation results.
Optionally, the performing load evaluation on the preset network slice according to the data of the plurality of load influencing factors, and generating a load evaluation result includes:
determining target load influence factors of the preset network slice according to the data of the load influence factors;
and generating the load evaluation result according to the target load influence factors.
Optionally, the determining, according to the data of the plurality of load influencing factors, a target load influencing factor of the preset network slice includes:
Calculating the accumulated load contribution rate of the plurality of load influencing factors according to the data of the plurality of load influencing factors;
and determining target load influence factors of the preset network slice according to the accumulated load contribution rate.
Optionally, the calculating the cumulative load contribution rate of the plurality of load influencing factors according to the data of the plurality of load influencing factors includes:
calculating a correlation coefficient matrix among the plurality of load influence factors according to the data of the plurality of load influence factors;
calculating characteristic values of the load influence factors according to the correlation coefficient matrix;
and calculating the accumulated load contribution rate of the plurality of load influence factors according to the characteristic values of the plurality of load influence factors.
Optionally, the sending the load evaluation result to the multiple NF network elements, so that the multiple NF network elements adjust the load of the preset network slice according to the load evaluation result, including:
determining a target NF network element corresponding to the target load influence factor from the NF network elements according to the target load influence factor;
and sending the load evaluation result to the target NF network element, so that the target NF network element adjusts the load of the preset network slice according to the load evaluation result.
Optionally, the load evaluation result is used to make the target NF network element limit the preset network slice to bear the service corresponding to the target load influencing factor; or alternatively, the process may be performed,
and the load evaluation result is used for enabling the target NF network element to switch the service corresponding to the target load influence factor to other network slices.
Optionally, the load influencing factors are multiple kinds of throughput of a user plane function UPF network element, number of protocol data unit sessions of a session management function SMF network element, number of terminal devices managed by an access and mobility management function AMF network element, size of a data packet transmitted by the UPF network element, throughput of terminal devices managed by a base station, and number of terminal devices managed by the base station.
In a second aspect, an embodiment of the present application further provides a slice load assessment apparatus, applied to an MDAF network element for management data analysis function, where the apparatus includes:
a request sending module, configured to send a slice data acquisition request to a network data analysis function NWDAF network element according to a load assessment requirement for a preset network slice, so that the NWDAF network element respectively collects data of the preset network slice at a plurality of load influencing factors from a plurality of network function NF network elements;
A response receiving module, configured to receive a slice data acquisition response returned by the NWDAF network element, where the slice data acquisition response includes: data of the plurality of load influencing factors;
the load evaluation module is used for carrying out load evaluation on the preset network slice according to the data of the load influence factors to generate a load evaluation result;
and the result sending module is used for sending the load evaluation results to the NF network elements so that the NF network elements can adjust the load of the preset network slice according to the load evaluation results.
Optionally, the load evaluation module includes:
a target factor determining unit, configured to determine a target load influence factor of the preset network slice according to the data of the plurality of load influence factors;
and the evaluation result generating unit is used for generating the load evaluation result according to the target load influence factor.
Optionally, the target factor determining unit includes:
a cumulative contribution rate calculation subunit, configured to calculate a cumulative load contribution rate of the plurality of load influencing factors according to data of the plurality of load influencing factors;
and the target factor determining subunit is used for determining a target load influence factor of the preset network slice according to the accumulated load contribution rate.
Optionally, the cumulative contribution rate calculating subunit includes:
a correlation coefficient calculation unit configured to calculate a correlation coefficient matrix between the plurality of load influencing factors according to the data of the plurality of load influencing factors;
a characteristic value calculating unit, configured to calculate characteristic values of the plurality of load influencing factors according to the correlation coefficient matrix;
and the accumulated contribution rate calculating subunit is used for calculating the accumulated load contribution rates of the load influence factors according to the characteristic values of the load influence factors.
Optionally, the result sending module includes:
a target network element determining unit, configured to determine, according to the target load influencing factor, a target NF network element corresponding to the target load influencing factor from the multiple NF network elements;
and the result sending unit is used for sending the load evaluation result to the target NF network element so that the target NF network element adjusts the load of the preset network slice according to the load evaluation result.
Optionally, the load evaluation result is used to make the target NF network element limit the preset network slice to bear the service corresponding to the target load influencing factor; or the load evaluation result is used for enabling the target NF network element to switch the service corresponding to the target load influence factor to other network slices.
Optionally, the load influencing factors are multiple kinds of throughput of a user plane function UPF network element, number of protocol data unit sessions of a session management function SMF network element, number of terminal devices managed by an access and mobility management function AMF network element, size of a data packet transmitted by the UPF network element, throughput of terminal devices managed by a base station, and number of terminal devices managed by the base station.
In a third aspect, an embodiment of the present application further provides a network element for managing data analysis, including:
a transceiver, a processor, and a storage medium;
the transceiver is used for receiving and transmitting data;
the storage medium stores program instructions executable by the processor;
the processor is configured to invoke the program instructions stored in the storage medium to perform the steps of the slice load assessment method according to any of the first aspects.
In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor performs the steps of the slice load assessment method according to any one of the first aspects.
The beneficial effects of the application are as follows:
The application provides a slice load assessment method, a slice load assessment device, a management data analysis function network element and a management data analysis medium, wherein the data of a plurality of load influence factors corresponding to a plurality of NF network elements are obtained so as to calculate a load assessment result according to the data of the plurality of load influence factors, and network business borne on each NF network element is brought into the load influence factors of a network slice, so that fine-grained analysis on the load of the network slice is realized, and the accuracy of the load analysis result is improved; and adjusting network services carried on each NF network element according to the load evaluation result, and adjusting the load state of the network slice on each NF network element to ensure that the communication efficiency of the network slice keeps the optimal communication efficiency and improve the use experience of users.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram of a network architecture according to an embodiment of the present application;
fig. 2 is a flowchart of a slice load evaluation method according to an embodiment of the present application;
fig. 3 is a second flow chart of a slice load evaluation method according to an embodiment of the present application;
fig. 4 is a flowchart illustrating a slice load evaluation method according to an embodiment of the present application;
fig. 5 is a flow chart diagram of a slice load evaluation method according to an embodiment of the present application;
fig. 6 is a flowchart of a slice load evaluation method according to an embodiment of the present application;
fig. 7 is an interactive schematic diagram of a slice load evaluation method according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a slice load assessment device according to an embodiment of the present application;
fig. 9 is a schematic diagram of a network element with management data analysis function according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application.
Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Furthermore, the terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the features of the embodiments of the present application may be combined with each other without conflict.
Before introducing the service subscription method provided by the embodiment of the application, an application scene is described.
Referring to fig. 1, a network architecture diagram provided in an embodiment of the present application, as shown in fig. 1, the network architecture may specifically include:
1. Terminal Equipment (UE): a user equipment, terminal, access terminal, subscriber unit, subscriber station, mobile station, remote terminal, mobile device, user terminal, wireless communication device, user agent, or user device may also be referred to.
2. Access Network (AN): the network access function is provided for authorized users in a specific area, and transmission tunnels with different qualities can be used according to the level of the users, the requirements of services and the like. An access network implementing access network functions based on wireless communication technology may be referred to as a radio access network (Radio Access Network, RAN). The radio access network can manage radio resources, provide access services for the terminal, and further complete forwarding of control signals and user data between the terminal and the core network, and generally provide the radio access network through the base station.
3. Access and mobility management function (access and mobility management function, AMF) network elements: the method is mainly used for mobility management, access management and the like, and can be used for realizing other functions besides session management in the functions of a mobility management entity (mobility management entity, MME), such as legal interception, access authorization (or authentication) and the like.
4. Session management function (Session Management Function, SMF) network element: the method is mainly used for session management, internet protocol (Internet Protocol, IP) address allocation and management of the UE, terminal nodes of a selective manageable user plane function, policy control or charging function interface, downlink data notification and the like.
5. User plane function (User Plane Function, UPF) network element: i.e. a data plane gateway. Quality of service (quality of service, qoS) handling, etc. for packet routing and forwarding, or user plane data. User data may be accessed to a Data Network (DN) through the network element.
6. Network data analysis function (Network Data Analytics Function, NWDAF) network element: the network analysis service may be provided according to request data of the network service.
7. A management data analysis function (Management Data Analytics Function, MDAF) network element: providing the ability to process and analyze data related to network and service events and conditions, including performance measurements, KPIs, trace/MDT/RLF/RCEF reports, qoE reports, alarms, configuration data, network analysis data, and service experience data from AFs, etc., to provide analysis output, i.e., statistics or predictions, root cause analysis issues, and possibly advice to enable necessary actions for network and service operation. The management data analysis output is provided by an MDAS (management data analysis service) producer to a corresponding user requesting analysis. The MDA function of the MDAF network element is adopted to carry out management data analysis and is used as a key pusher for automation and intellectualization, and the MDA function has the basic capability of mobile network and service management and arrangement.
8. A network slice selection function (Network Slice Selection Function, NSSF) network element for managing network slice related information.
It should be understood that the network architecture applied to the embodiments of the present application is merely an exemplary network architecture described from the perspective of a conventional point-to-point architecture and a service architecture, and the network architecture to which the embodiments of the present application are applicable is not limited thereto, and any network architecture capable of implementing the functions of the respective network elements described above is applicable to the embodiments of the present application. It should be understood that the foregoing network elements may communicate through a preset interface, which is not described herein. It should also be understood that the AMF network element, the SMF network element, the UPF network element, the NWDAF network element, the MDAF network element, and the NSSF network element may be understood as network elements for implementing different functions in a core network, where the core network elements may be independent devices, or may be integrated in the same device to implement different functions, which is not limited in this disclosure.
Referring to fig. 2, a first flowchart of a slice load evaluation method according to an embodiment of the present application is shown in fig. 2, where the method may include:
s10: and sending a slice data acquisition request to the NWDAF network element according to load evaluation requirements for the preset network slice, so that the NWDAF network element respectively acquires data of the preset network slice in a plurality of load influence factors from a plurality of network function NF network elements.
In this embodiment, a preset Network Slice (Network Slice) is a virtual core Network obtained by dividing Network resources of a core Network, and one Network Slice forms a virtual core Network to provide mobile Network access service for a group of terminal devices.
In the process of presetting a network slice to provide access service for terminal equipment, the terminal equipment can perform data transmission through the preset network slice and a data network element, and in the data transmission process, the use of the network slice cannot exceed the service flow carried by the network slice, otherwise, the communication efficiency of the network slice is reduced, and the use experience of a user is affected.
In order to ensure that the network slice provides the best communication efficiency, the load carried by the network slice needs to be evaluated, in this case, the MDAF network element determines whether a preset network slice has a load evaluation requirement, where the load evaluation requirement may be determined according to a load evaluation instruction sent by an operator or an external server to the MDAF network element, where the load evaluation instruction is used to instruct the MDAF network element to perform load evaluation on the preset network slice.
After the MDAF network element receives a load evaluation instruction aiming at a preset network slice, determining that load evaluation is required to be carried out on the preset network slice, and starting a slice load evaluation program; after the slice load evaluation program is started, in order to acquire data related to load evaluation, the MDAF network element sends a slice data acquisition request to the NWDAF network element, where the slice data acquisition request includes: the method comprises the steps of presetting a slice identifier of a network slice, a request data identifier and a received data notification identifier, wherein the request data identifier is used for indicating data related to slice load.
After the NWDAF network element receives the slice data acquisition request, starting a data acquisition program, and sending a data acquisition request to a plurality of NF network elements which are data providers of a plurality of data corresponding to the request data identification according to the request data identification, wherein the NF network elements respectively send data of respective load influencing factors to the NWDAF network element based on the data acquisition request, and the load influencing factors are used for indicating network services which are borne by the NF network element and influence the load of a preset network slice.
In one possible implementation, the load influencing factors are a plurality of throughput of the UPF network element, number of protocol data unit sessions of the SMF network element, number of terminal devices managed by the AMF network element, size of data packets transmitted by the UPF network element, throughput of terminal devices managed by the base station, and number of terminal devices managed by the base station.
In this embodiment, the virtual core network formed by the preset network slice includes each network element in the network architecture described in fig. 1, and the NF network element includes: UPF network elements, SMF network elements, AMF network elements or base stations.
The UPF network element is used as a user plane function network element and is used for transmitting user data provided by the terminal equipment to the data network or transmitting external data of the data network to the terminal equipment, and presetting the throughput X of the UPF network element in the virtual core network corresponding to the network slice 1 And the data quantity is transmitted to the data network and the terminal equipment by the UPF network element.
Presetting protocol data units of SMF network elements in a virtual core network corresponding to network slicesSpeech data X 2 The number of PDU sessions established for the virtual core network corresponding to the preset network slice.
Presetting the number X of terminal equipment managed by AMF network elements in virtual core network corresponding to network slices 3 For the number of terminal devices accessing the virtual core network.
Presetting data packet size X transmitted by UPF network element in virtual core network corresponding to network slice 4 Comprising the following steps: the data packet size sent by the terminal equipment to the data network through the UPF network element and the data packet size sent by the data network to the terminal equipment through the UPF network element. In some embodiments, the size of the data packet transmitted by the UPF network element may be the size of the largest data packet in the data packet sent by the terminal device to the data network through the UPF network element and the data packet sent by the data network to the terminal device through the UPF network element.
Presetting terminal equipment throughput X managed by base station gNB in virtual core network corresponding to network slice 5 The base station gNB may be configured to throughput the amount of data for the terminal device.
Presetting number X of terminal equipment managed by base station gNB in virtual core network corresponding to network slice 6 The number of terminal devices accessing to the virtual core network through the base station gNB may be the number of terminal devices accessing to the virtual core network through a New Radio (NR) cell corresponding to the base station.
S20: receiving a slice data acquisition response returned by the NWDAF network element, wherein the slice data acquisition response comprises the following steps: data for a plurality of load influencing factors.
In this embodiment, after the NWDAF network element receives the data of the load influencing factors returned by each NF network element, a slice data acquisition response is sent to the MDAF network element, where the slice data acquisition response carries the data of the load influencing factors of multiple NF network elements.
S30: and carrying out load evaluation on the preset network slice according to the data of the load influence factors, and generating a load evaluation result.
In this embodiment, a preset load evaluation calculation method is adopted to calculate data of a plurality of load influence factors, so as to obtain a load evaluation result, where the load evaluation result is used to indicate a current load state of a preset network slice.
In some embodiments, the load assessment calculation method may be: the weighting algorithm or the weighted average algorithm determines the weight of each load influence factor according to the influence degree of each load influence factor on the preset network slice, and calculates the load evaluation result according to the weight of each load influence factor and the data of each load influence factor.
S40: and sending load evaluation results to the NF network elements so that the NF network elements adjust the load of the preset network slice according to the load evaluation results.
In this embodiment, the MDAF network element sends the load evaluation result to the NF network elements, and the NF network elements determine the current load status of the preset network slice according to the load evaluation result, and determine whether to adjust the network services carried by the respective NF network elements so as to reduce the load of the preset network slice.
In some embodiments, if the load evaluation result indicates that the current load state is an overload state, each NF network element determines to limit the network service carried by the NF network element in a preset time period, so as to ensure the efficiency of processing the network service carried currently by the preset network slice; if the load evaluation result indicates that the current load state is a low load state or a normal load state, each NF network element does not need to reduce the network service carried.
Furthermore, in order to ensure the accuracy of the load evaluation result, the NWDAF network element may collect a plurality of groups of data of the plurality of load influencing factors in a preset time period, and the MDAF calculates the data of the plurality of load influencing factors by using a load evaluation calculation method according to the plurality of groups of data of the plurality of load influencing factors, so as to obtain the load evaluation result.
According to the slice load evaluation method provided by the embodiment, the data of the load influence factors corresponding to the NF network elements are obtained, so that the load evaluation result is calculated according to the data of the load influence factors, the network service borne on each NF network element is brought into the load influence factor of the network slice, fine-grained analysis on the load of the network slice is realized, and the accuracy of the load analysis result is improved; and adjusting network services carried on each NF network element according to the load evaluation result, and adjusting the load state of the network slice on each NF network element to ensure that the communication efficiency of the network slice keeps the optimal communication efficiency and improve the use experience of users.
One possible implementation of generating the load assessment result from the data of the plurality of load influencing factors is described below in connection with the embodiments.
Referring to fig. 3, a second flow chart of the slice load evaluation method provided by the embodiment of the present application, as shown in fig. 3, the step of performing load evaluation on a preset network slice according to data of a plurality of load influencing factors in S30, and generating a load evaluation result may include:
s301: and determining target load influence factors of the preset network slice according to the data of the load influence factors.
S302: and generating a load evaluation result according to the target load influence factors.
In this embodiment, the MDAF network element calculates, according to data of a plurality of load influencing factors, an influence weight of each load influencing factor on a preset network slice, determines a target load influencing factor from the plurality of load influencing factors according to the influence weight of the plurality of load influencing factors on the preset network slice, and generates a load evaluation result according to the target load influencing factor. The target load influence factor is at least one load influence factor with the largest influence weight in the plurality of load influence factors.
In some embodiments, a load influence factor with an influence weight greater than a preset influence weight threshold may be determined from the plurality of load influence factors as the target load influence factor according to the influence weights of the plurality of load influence factors on the preset network slice and the preset influence weight threshold.
One possible implementation of determining the target load influencing factor from the data of the plurality of load influencing factors is described below in connection with the embodiments.
Referring to fig. 4, a third flow chart of the slice load evaluation method according to the embodiment of the present application, as shown in fig. 4, the step of determining, according to data of a plurality of load influencing factors, a target load influencing factor of a preset network slice in S301 may include:
S311: and calculating the accumulated load contribution rate of the plurality of load influence factors according to the data of the plurality of load influence factors.
In this embodiment, the MDAF network element calculates, according to data of a plurality of load influencing factors, an influence weight of each load influencing factor on a preset network slice, takes the influence weight of each load influencing factor as a load contribution rate of each load influencing factor, sequentially accumulates the load contribution rates of each load influencing factor according to a preset order, and obtains an accumulated load contribution rate every time one load contribution rate is accumulated.
In some embodiments, the load contribution rates of the load influencing factors may be sorted in order from large to small, and the load contribution rates of the load influencing factors are sequentially accumulated in order from large to small, and one accumulated load contribution rate is obtained after accumulating one load contribution rate.
For example, load influencing factor X 1 ～X 6 The load contribution ratios of (a) are respectively S 1 ～S 6 Suppose S 1 >S 2 >S 3 >S 4 >S 5 >S 6 The first cumulative load contribution rate is S 1 The second cumulative load contribution rate is S 1 +S 2 The third cumulative load contribution rate is S 1 +S 2 +S 3 The fourth cumulative load contribution rate is S 1 +S 2 +S 3 +S 4 The fifth cumulative load contribution rate is S 1 +S 2 +S 3 +S 4 +S 5 The sixth cumulative load contribution rate is S 1 +S 2 +S 3 +S 4 +S 5 +S 6 。
S321: and determining target load influence factors of the preset network slice according to the accumulated load contribution rate.
In this embodiment, it is determined from a plurality of cumulative load contribution rates that the cumulative load contribution rate is greater than or equal to a preset contribution rate threshold and the smallest cumulative load contribution rate is a target cumulative load contribution rate, and it is determined that load influence factors corresponding to each load contribution rate in the target cumulative load contribution rate are target load influence factors.
For example, if the fourth cumulative load contribution rate, the fifth cumulative load contribution rate, and the sixth load cumulative contribution are all greater than the preset contribution rate threshold, determining the fourth cumulative load contribution rate of the fourth cumulative load contribution rate, the fifth cumulative load contribution rate, and the sixth load cumulative contribution as the target cumulative load contribution rate, according to the load contribution rate S in the fourth cumulative load contribution rate 1 、S 2 、S 3 And S is 4 Corresponding load influencing factor X 1 、X 2 、X 3 And X 4 Is a target load influencing factor.
One possible implementation of calculating the cumulative load contribution from the data of the plurality of load influencing factors is described below with reference to the embodiments.
Referring to fig. 5, a flowchart of a slice load evaluation method according to an embodiment of the present application is shown in fig. 5, where the step S311 of calculating the cumulative load contribution rate of a plurality of load influencing factors according to the data of the plurality of load influencing factors may include:
S311a: and calculating a correlation coefficient matrix among the plurality of load influence factors according to the data of the plurality of load influence factors.
In this embodiment, for any two load influencing factors, a preset correlation coefficient calculation method is adopted, and according to data of any two load influencing factors, a correlation coefficient between any two load influencing factors is calculated, so as to form a correlation coefficient matrix between a plurality of load influencing factors. For example, the preset correlation coefficient calculation method may be a Pearson (Pearson) correlation coefficient calculation method.
In some embodiments, please refer to table 1, a load influencing factor data table provided for an embodiment of the present application, as shown in table 1, includes a plurality of groups of data of a plurality of load influencing factors collected in a preset time period, a plurality of groups of data of a plurality of load influencing factors
TABLE 1 load influencing factor data table
By load influencing factor X 1 And X 2 The calculation formula for calculating the correlation coefficient according to the data of the plurality of groups of load influence factors can be:
referring to table 2, a correlation coefficient list provided in an embodiment of the present application is shown in table 2, in which a correlation coefficient matrix between a plurality of load influencing factors
Table 2 correlation coefficient list
S311b: and calculating characteristic values of a plurality of load influence factors according to the correlation coefficient matrix.
In this embodiment, a homogeneous linear equation set is constructed according to the correlation coefficient matrix a', and the homogeneous linear equation set is solved to obtain the characteristic values a of a plurality of load influence factors 1 ～A 6 。
Specifically, a homogeneous system of linear equationsE is an identity matrix, and the homogeneous linear equation set is solved to obtain characteristic values A of a plurality of load influence factors 1 ～A 6 。
S311c: and calculating the accumulated load contribution rate of the plurality of load influence factors according to the characteristic values of the plurality of load influence factors.
In this embodiment, according to the characteristic values of the load influencing factors, the load contribution rate S of the load influencing factors is calculated 1 ～S 6 . Specifically, the variance percentage of each load influencing factor may be calculated according to the sum of the characteristic value of each load influencing factor and the characteristic values of the plurality of load influencing factors, and the variance percentage is taken as the load contribution rate.
Illustratively, a first cumulative load contribution rateSecond cumulative load contribution->Third cumulative load contribution->Fourth cumulative load contribution->Fifth cumulative load contribution->Sixth cumulative load contribution rate
For the Kth cumulative load contribution rate, where the cumulative load contribution rate is greater than or equal to the preset contribution rate threshold and is the smallest, the first K load influencing factors are determined to be the target load influencing factors, and the load condition of the preset network slice can be well evaluated.
Based on the above embodiment of determining the target load influencing factor, a possible implementation manner of sending the load evaluation result to the NF network element is described below in conjunction with the embodiment.
Referring to fig. 6, a fifth flowchart of a slice load evaluation method according to an embodiment of the present application, as shown in fig. 6, the step of sending a load evaluation result to a plurality of NF network elements in S40, so that the plurality of NF network elements adjust the load of a preset network slice according to the load evaluation result may include:
s41: and determining a target NF network element corresponding to the target load influence factor from the NF network elements according to the target load influence factor.
S42: and sending a load evaluation result to the target NF network element, so that the target NF network element adjusts the load of the preset network slice according to the load evaluation result.
In this embodiment, after determining a target load influence factor with the maximum load influence weight on a preset network slice from multiple load influence factors, the MDAF network element determines that an NF network element corresponding to the target load influence factor is a target NF network element, sends a load evaluation result to the target NF network element, and adjusts network services corresponding to the target load influence factor after the target NF network element receives the load evaluation result. The method for adjusting the network service corresponding to the target load influencing factor by the target NF network element may be: the target NF network element limits network service borne by the NF network element within a preset time period so as to reduce the influence of a target load influence factor on the bearing pressure of the load of the preset network slice, and reduces the load of the preset network slice within the preset time period.
In some embodiments, the load evaluation result is used to make the target NF network element limit the service corresponding to the preset network slice load-bearing target load influencing factor; or the load evaluation result is used for enabling the target NF network element to switch the service corresponding to the target load influence factor to other network slices.
In this embodiment, the load evaluation result includes an impact weight of a target load impact factor on a preset network slice, and the target NF network element determines to shunt network traffic corresponding to the target load impact factor carried by the target NF network element or switch the network slice according to the impact weight of the target load impact factor.
Specifically, if the influence weight of the target load influence factor is smaller than or equal to the preset influence weight threshold, the target NF network element limits the execution of the network service corresponding to the target load influence factor by the preset network slice within the preset time period; if the influence weight of the target load influence factor is greater than the preset influence weight threshold, the target NF network element is selected to switch to other network slices so as to adopt the other network slices to bear network services corresponding to the target load influence factor.
The network slice switching method of the target NF network element may be: the target NF network element sends a slice selection request to the NSSF network element so that the NSSF network element selects a new network slice for the target NF network element, and the NSSF network element sends a slice identification of the new network slice to the target NF network element so that the target NF network element carries network services corresponding to the target load influencing factors through the new network slice.
According to the slice load evaluation method provided by the embodiment, the specific positioning of the influence factors influencing the network slice load is realized by determining the target load influence factors from the plurality of load influence factors, and the reason for influencing the network slice load is solved pertinently by sending the load evaluation result to the target NF network element corresponding to the target load influence factors so that the target NF network element selects to shunt the network service corresponding to the loaded target load influence factors; the network slice is selected to be switched only under the condition that the network service corresponding to the target load influence factor cannot be limited, so that the problems of network resource waste and efficiency reduction caused by directly switching the network slice are avoided, network resources can be saved, and the efficiency is improved.
Based on the slice load evaluation method, an interactive flow for performing slice load evaluation between each network element is described below.
Referring to fig. 7, an interactive schematic diagram of a slice load assessment method according to an embodiment of the present application is shown in fig. 7, where the process may include:
step 1: and the MDAF network element receives the load evaluation instruction and starts a slice load evaluation program.
Step 2: the MDAF network element sends a slice data acquisition request to the NWDAF network element.
Step 3: the NWDAF network element starts a data acquisition procedure and sends data acquisition requests to the NF network elements.
Step 4: and after the NWDAF network element receives the data of the load influence factors returned by each NF network element, the NWDAF network element sends a slice data acquisition response to the MDAF network element.
Step 5: and the NWDAF network element performs slice load assessment according to the data of the load influence factors.
Step 6: and sending the load evaluation result to the AMF network element.
It should be noted that, step 6 is merely taken as an example of an AMF network element, and it is known from the foregoing that the target NF network element includes, but is not limited to, the AMF network element.
Step 7: the AMF network element sends a slice selection request to the NSSF network element requesting the NSSF network element to provide a new network slice.
Step 8: the NSSF network element sends a slice selection response to the AMF network element, so that the SMF network element switches the loaded network service to a new network slice for execution.
It should be noted that, the above steps 7 and 8 are optional implementation steps, and when the AMF network element determines, according to the load evaluation result, that the slice load cannot be reduced by limiting the network service executed on the preset network slice, the step 7 and the step 8 are selected to perform the slice switching.
On the basis of the method embodiment, the embodiment of the application also provides a slice load assessment device which is applied to the MDAF network element. Referring to fig. 8, a schematic structural diagram of a slice load assessment apparatus according to an embodiment of the present application, as shown in fig. 8, the apparatus may include:
A request sending module 10, configured to send a slice data acquisition request to a network data analysis function NWDAF network element according to a load assessment requirement for a preset network slice, so that the NWDAF network element respectively collects data of the preset network slice at a plurality of load influencing factors from a plurality of network function NF network elements;
the response receiving module 20 is configured to receive a slice data acquisition response returned by the NWDAF network element, where the slice data acquisition response includes: data for a plurality of load influencing factors;
the load evaluation module 30 is configured to perform load evaluation on a preset network slice according to data of a plurality of load influencing factors, and generate a load evaluation result;
the result sending module 40 is configured to send load evaluation results to the NF network elements, so that the NF network elements adjust the load of the preset network slice according to the load evaluation results.
Optionally, the load assessment module 30 includes:
the target factor determining unit is used for determining target load influence factors of a preset network slice according to the data of the load influence factors;
and the evaluation result generating unit is used for generating a load evaluation result according to the target load influence factors.
Optionally, the target factor determining unit includes:
A cumulative contribution rate calculation subunit, configured to calculate a cumulative load contribution rate of the plurality of load influencing factors according to data of the plurality of load influencing factors;
and the target factor determining subunit is used for determining target load influence factors of the preset network slice according to the accumulated load contribution rate.
Optionally, the cumulative contribution rate calculation subunit includes:
a correlation coefficient calculation unit for calculating a correlation coefficient matrix between the plurality of load influencing factors according to the data of the plurality of load influencing factors;
the characteristic value calculation unit is used for calculating characteristic values of a plurality of load influence factors according to the correlation coefficient matrix;
and the accumulated contribution rate calculating subunit is used for calculating the accumulated load contribution rates of the load influence factors according to the characteristic values of the load influence factors.
Optionally, the result sending module 40 includes:
a target network element determining unit, configured to determine, according to a target load influencing factor, a target NF network element corresponding to the target load influencing factor from a plurality of NF network elements;
and the result sending unit is used for sending the load evaluation result to the target NF network element so that the target NF network element adjusts the load of the preset network slice according to the load evaluation result.
Optionally, the load evaluation result is used for enabling the target NF network element to limit the service corresponding to the load influencing factor of the preset network slice load; or the load evaluation result is used for enabling the target NF network element to switch the service corresponding to the target load influence factor to other network slices.
Optionally, the load influencing factors are multiple kinds of throughput of a user plane function UPF network element, a protocol data unit session number of a session management function SMF network element, a terminal equipment number managed by an access and mobility management function AMF network element, a data packet size transmitted by the UPF network element, throughput of terminal equipment managed by a base station, and a terminal equipment number managed by the base station.
The foregoing apparatus is used for executing the method provided in the foregoing embodiment, and its implementation principle and technical effects are similar, and are not described herein again.
The above modules may be one or more integrated circuits configured to implement the above methods, for example: one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASICs), or one or more microprocessors, or one or more field programmable gate arrays (Field Programmable Gate Array, abbreviated as FPGAs), etc. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Referring to fig. 9, a schematic diagram of a management data analysis function network element according to an embodiment of the present application is shown in fig. 9, where the management data analysis function network element 100 includes: a transceiver 110, a processor 120, and a storage medium 130; the transceiver 110 is used for receiving and transmitting data; the storage medium 130 stores program instructions executable by the processor 120; the processor 120 is operative to invoke program instructions stored in the storage medium 130 to perform the method embodiments described above. The specific implementation manner and the technical effect are similar, and are not repeated here.
Optionally, the present application also provides a program product, such as a computer readable storage medium, comprising a program for performing the above-described method embodiments when being executed by a processor. The specific implementation manner and the technical effect are similar, and are not repeated here.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units.
The integrated units implemented in the form of software functional units described above may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (english: processor) to perform some of the steps of the methods according to the embodiments of the invention. And the aforementioned storage medium includes: u disk, mobile hard disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.
The foregoing is merely illustrative of embodiments of the present invention, and the present invention is not limited thereto, and any changes or substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and the present invention is intended to be covered by the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. A slice load assessment method, applied to an MDAF network element for management data analysis function, the method comprising:
according to load assessment requirements for a preset network slice, a slice data acquisition request is sent to a network data analysis function NWDAF network element, so that the NWDAF network element respectively acquires data of the preset network slice in a plurality of load influence factors from a plurality of network function NF network elements;
receiving a slice data acquisition response returned by the NWDAF network element, wherein the slice data acquisition response comprises: data of the plurality of load influencing factors;
carrying out load evaluation on the preset network slice according to the data of the load influence factors to generate a load evaluation result;
and sending the load evaluation results to the NF network elements so that the NF network elements adjust the load of the preset network slice according to the load evaluation results.
2. The method of claim 1, wherein the performing load assessment on the preset network slice according to the data of the plurality of load influencing factors, and generating a load assessment result, includes:
determining target load influence factors of the preset network slice according to the data of the load influence factors;
and generating the load evaluation result according to the target load influence factors.
3. The method of claim 2, wherein determining the target load influencing factor for the preset network slice based on the data of the plurality of load influencing factors comprises:
calculating the accumulated load contribution rate of the plurality of load influencing factors according to the data of the plurality of load influencing factors;
and determining target load influence factors of the preset network slice according to the accumulated load contribution rate.
4. The method of claim 3, wherein the calculating the cumulative load contribution of the plurality of load influencing factors from the data of the plurality of load influencing factors comprises:
calculating a correlation coefficient matrix among the plurality of load influence factors according to the data of the plurality of load influence factors;
Calculating characteristic values of the load influence factors according to the correlation coefficient matrix;
and calculating the accumulated load contribution rate of the plurality of load influence factors according to the characteristic values of the plurality of load influence factors.
5. The method of claim 2, wherein the sending the load assessment result to the plurality of NF network elements to cause the plurality of NF network elements to adjust the load of the preset network slice according to the load assessment result comprises:
determining a target NF network element corresponding to the target load influence factor from the NF network elements according to the target load influence factor;
and sending the load evaluation result to the target NF network element, so that the target NF network element adjusts the load of the preset network slice according to the load evaluation result.
6. The method of claim 5, wherein the load evaluation result is used to cause the target NF network element to limit the preset network slice to carry the service corresponding to the target load influencing factor; or alternatively, the process may be performed,
and the load evaluation result is used for enabling the target NF network element to switch the service corresponding to the target load influence factor to other network slices.
7. The method according to any of claims 1-6, wherein the load influencing factor is a plurality of user plane function, UPF, network element throughput, number of protocol data unit sessions of session management, SMF, network element, number of terminal devices managed by an AMF, access and mobility management, network element, size of data packets transmitted by the UPF, base station managed terminal device throughput, number of terminal devices managed by the base station.
8. A slice load assessment apparatus for use in managing data analysis function MDAF network elements, the apparatus comprising:
a request sending module, configured to send a slice data acquisition request to a network data analysis function NWDAF network element according to a load assessment requirement for a preset network slice, so that the NWDAF network element respectively collects data of the preset network slice at a plurality of load influencing factors from a plurality of network function NF network elements;
a response receiving module, configured to receive a slice data acquisition response returned by the NWDAF network element, where the slice data acquisition response includes: data of the plurality of load influencing factors;
the load evaluation module is used for carrying out load evaluation on the preset network slice according to the data of the load influence factors to generate a load evaluation result;
And the result sending module is used for sending the load evaluation results to the NF network elements so that the NF network elements can adjust the load of the preset network slice according to the load evaluation results.
9. A management data analysis function network element, comprising:
a transceiver, a processor, and a storage medium;
the transceiver is used for receiving and transmitting data;
the storage medium stores program instructions executable by the processor;
the processor is configured to invoke the program instructions stored in the storage medium to perform the steps of the slice load assessment method according to any one of claims 1-7.
10. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the slice load assessment method according to any one of claims 1 to 7.
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