CN111836291A - Slice resource scheduling method and network element - Google Patents
Slice resource scheduling method and network element Download PDFInfo
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- CN111836291A CN111836291A CN201910313295.0A CN201910313295A CN111836291A CN 111836291 A CN111836291 A CN 111836291A CN 201910313295 A CN201910313295 A CN 201910313295A CN 111836291 A CN111836291 A CN 111836291A
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- H04W72/12—Wireless traffic scheduling
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W72/12—Wireless traffic scheduling
- H04W72/1263—Mapping of traffic onto schedule, e.g. scheduled allocation or multiplexing of flows
Abstract
The invention provides a slice resource scheduling method and a network element, wherein the method comprises the following steps: acquiring analysis data of the slice; analyzing and updating the analysis data to obtain a data analysis result; and sending the data analysis result to a network slice selection function NSSF or a policy control function PCF. The NSSF acquires a data analysis result of the slice from a network analysis logic function NWDAF; and according to the data analysis result, the KPIs and the network performance at the slicing level are adjusted. PCF obtains data analysis result of slice from network analysis logic function NWDAF; and according to the data analysis result, performing strategy configuration adjustment on different slices. The NWDAF of the embodiment of the invention can obtain a data analysis result according to the analysis data of the current network, distribute the data analysis result to the NSSF or PCF, and dynamically adjust the slicing resources by the NSSF or PCF, thereby improving the resource utilization rate and meeting the SLA requirements of more slicing users.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method and a network element for scheduling slice resources.
Background
Fifth generation (5)thGeneration, 5G) Mobile communication System support includes the followingNetwork architecture of a network node (or called network element): a Network analysis logic Function (NWDAF), an Access and mobility management Function (AMF), a Policy Control Function (PCF), a Network Slice Selection Function (NSSF), a Radio Access Network (RAN), and a Network Function (NFs), etc. The NWDAF analyzes and sends the specific network information state of the subscribed user to other related network nodes according to the slice granularity, that is, analyzes and sends the network information state divided by slices with the subscription information to other network elements. In addition, the NWDAF may also send specific network data analysis to other network elements on a per-slice basis. In addition, other network elements can also directly collect the network state analysis information required by each network element from the NWDAF. The PCF may use data obtained from the NWDAF in policy decisions (policies), and the NSSF may perform slice selection according to load level information (load level information) provided by the NWDAF.
When multiple slices appear in a network, a slice user cares about Service-level agreement (SLA) guarantee of the slices, and currently, the SLA of the user is ensured by the following methods, for example: shared RAN using RAN resource scheduling to guarantee SLAs for slices, e.g. transmission time intervals
(Transmission Timing Interval, TTI) does not enforce the allocation of a portion of the frequencies to any slice; the transmission network is shared, and Flex-E interfaces and a tunnel technology are utilized to reduce delay and improve isolation and reliability; user Plane Functions (UPFs) are deployed to the edge using a private Core Network (CN) with dedicated or shared Dual Connectivity (DC) resources to reduce latency. However, the above manners are realized based on network resources and network capabilities, which are limited, and the SLA requirements of more slice users cannot be met.
Disclosure of Invention
The invention provides a slice resource scheduling method and a network element, which solve the problem that the prior art can not meet the SLA requirement of slice users.
The embodiment of the invention provides a slice resource scheduling method, which is applied to a network analysis logic function (NWDAF) and comprises the following steps:
acquiring analysis data of the slice;
analyzing and updating the analysis data to obtain a data analysis result;
and sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
An embodiment of the present invention further provides a network analysis logic function NWDAF network element, including: a processor; a memory coupled to the processor, and a transceiver coupled to the processor; wherein the content of the first and second substances,
the transceiver is configured to: acquiring analysis data of the slice;
the processor is configured to: analyzing and updating the analysis data to obtain a data analysis result;
the transceiver is further configured to: and sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
An embodiment of the present invention further provides a network element, where the network element is a network analysis logic function NWDAF, and the network element includes:
the acquisition module is used for acquiring analysis data of the slice;
the analysis module is used for analyzing and updating the analysis data to obtain a data analysis result;
and the first sending module is used for sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
The embodiment of the invention also provides a slice resource scheduling method, which is applied to a network slice selection function NSSF and comprises the following steps:
acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
and adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
The embodiment of the present invention further provides a network slice selection function NSSF network element, including: a processor; a memory coupled to the processor, and a transceiver coupled to the processor; wherein the content of the first and second substances,
the transceiver is configured to: acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
the processor is configured to: and adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
An embodiment of the present invention further provides a network element, where the network element selects a function NSSF for a network slice, and the method includes:
the first acquisition module is used for acquiring a data analysis result of the slice from a network analysis logic function NWDAF;
and the first adjusting module is used for adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
The embodiment of the invention also provides a slice resource scheduling method, which is applied to a policy control function PCF and comprises the following steps:
acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
and according to the data analysis result, performing strategy configuration adjustment on different slices.
The embodiment of the invention also provides a policy control function PCF network element, comprising: a processor; a memory coupled to the processor, and a transceiver coupled to the processor; wherein the content of the first and second substances,
the transceiver is configured to: receiving a sliced data analysis result from a network analysis logic function (NWDAF) side;
the processor is configured to: and according to the data analysis result, performing strategy configuration adjustment on different slices.
The embodiment of the invention also provides a slice resource scheduling method, which is applied to a policy control function PCF and comprises the following steps:
the second acquisition module is used for acquiring a data analysis result of the slice from a network analysis logic function NWDAF;
and the second adjusting module is used for performing strategy configuration adjustment on different slices according to the data analysis result.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the slice resource scheduling method on the NWDAF side, the NSSF side, or the PCF side.
The technical scheme of the invention has the beneficial effects that: the NWDAF can obtain a data analysis result of the slice resources of the current network according to the analysis data of the current network, distribute the data analysis result to the NSSF or PCF, and dynamically adjust the slice resources by the NSSF or PCF, so that the resource utilization rate is improved, and SLA requirements of more slice users are met.
Drawings
Fig. 1 is a flowchart illustrating a method for scheduling slice resources on an NWDAF side according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a method for scheduling slice resources on the NSSF side according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a method for scheduling slice resources at a PCF side according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for scheduling slice resources according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a network element module on the NWDAF side according to an embodiment of the present invention;
fig. 6 is a schematic diagram illustrating a network element module structure on the NSSF side according to an embodiment of the present invention;
fig. 7 is a schematic diagram illustrating a network element module structure at the PCF side in accordance with an embodiment of the present invention;
fig. 8 shows a block diagram of a network element according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments. In the following description, specific details such as specific configurations and components are provided only to help the full understanding of the embodiments of the present invention. Thus, it will be apparent to those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In addition, the terms "system" and "network" are often used interchangeably herein.
In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.
As shown in fig. 1, an embodiment of the present invention provides a slice resource scheduling method, which is applied to a network analysis logic function NWDAF, and specifically includes the following steps:
step 11: analytical data for the slices are acquired.
The NWDAF is a service interface, and may collect analysis data from the network at regular time, for example, obtain information from NFs, an Operation Administration Maintenance (OAM) entity or an Application Function (AF), and analyze the information offline, and periodically update network performance information. The NSSF may subscribe to the NWDAF for network performance information, or the NWDAF may notify the NSSF of the network performance information.
Wherein step 11 may comprise at least one of:
obtaining first analysis data from network function NFs and/or an operation, administration, and maintenance, OAM; wherein the first analytical data comprises: at least one of Key Performance Indicators (KPIs) and Performance measurement Indicators (Performance measures) of the stored slices. The first analysis data may be from network elements such as NFs, OAM, etc. The first analysis data may include KPIs and performance measurement indicators of currently stored slices at the RAN side and the CN side of the radio access network.
Acquiring second analysis data from the PCF; wherein the second analysis data comprises: slice priority information. That is, the PCF reports slice priority information for different slices of the policy configuration to the NWDAF.
From the NSSF, third analytical data was obtained. Wherein the third analysis data comprises: at least one of slice congestion information, percentage information of user experience values, and service demand information of newly added slices. Wherein, the percentage information of the user experience value refers to what percentage of the user experience value each slice can satisfy. That is, the NSSF simultaneously reports at least one of slice congestion information of a current network slice, percentage of user experience values that each slice can satisfy, and service demand information of a newly added slice to the NWDAF.
Step 12: and analyzing and updating the analysis data to obtain a data analysis result.
Wherein step 12 comprises: and analyzing and updating the analysis data by using the analysis model to obtain a data analysis result. Wherein, the analysis model is trained by performing offline data analysis on the NWDAF.
Accordingly, step 12 is preceded by: and (5) performing off-line data analysis and training an analysis model. That is, the NWDAF performs offline data analysis to train out an analysis model, and then performs online analysis update through the input data.
Specifically, the NWDAF needs to perform Quality of service (Qos) file (profile) conversion to form a Qos profile data model with the user service experience as a target.
Step 13: and sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
When slices are newly added in the network, the NWDAF issues corresponding optimization indexes to PCF and NSSF for reasonable resource scheduling after the NWDAF analyzes according to the network congestion state, the optimization indexes are decomposed into an access network, a transmission network and a core network, the existing slice network resources and indexes of each domain are dynamically adjusted, the SLA of signed users is guaranteed to the maximum extent, and the SLA signing reliability guarantee is provided for potential users.
Wherein, the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information. Specifically, step 13 includes: and the NWDAF issues the data analysis result to the NSSF according to the slice priority information. For example, the QoS profile recommendation for each service of a slice and the slice load information of different slices are issued to the NSSF. Accordingly, the NSSF adjusts according to the current situation, whether to satisfy the SLA of the slice tenant and how many users can be satisfied. It should be noted that, at this time, the NSSF is to partially add users in the slice, test the SLA that can be met, finally take a data to sign with the tenant, and then perform configuration. Furthermore, the data analysis result may further include at least one of the following information: spatial validity conditions such as Tracking Area Identity (TAI); a spatial validity condition (Time validity condition), such as a Time Window (Time Window); NWDAF service identification (transactionid); single Network Slice Selection assistance information (S-NSSAI); a list of S-NSSAIs (a list of S-NSSAIs); maximum number of registered Users (maximum registration Users); an application list (a list of applications), and the like. Wherein, the related information of the reference list may include: an application identifier (application id), a Maximum number of Users of the application (Maximum Users for the application), an average Score of general services (MOS), a user experience satisfaction percentage of the application (how management UE's experience for the application satisfy), and the like.
That is, when a slice is newly added to the network, the NWDAF may perform statistical calculation according to collected KPIs of the slice level (of the slice level) in the current network and performance measurement indexes of the RAN/CN, such as what percentage of user (e.g., slice user/stream QoS) service experience is met, slice priority, uplink/downlink bandwidth/bit rate of each slice of each RAN node, and the like, and then send the statistical result to the NSSF or PCF, which performs reasonable slice resource planning and scheduling.
The foregoing describes a method for scheduling slice resources on the NWDAF side, and the following embodiment of the present invention further describes a method for scheduling slice resources on the NSSF side.
As shown in fig. 2, an embodiment of the present invention provides a method for scheduling slice resources, which is applied to a network slice selection function NSSF, and specifically includes the following steps:
step 21: and acquiring a data analysis result of the slice from a network analysis logic function NWDAF.
And when the data analysis result is that slices are newly added in the network, the NWDAF sends the corresponding optimization indexes to the PCF and the NSSF after analyzing the NWDAF according to the network congestion state. The data analysis results include: quality of service QoS profile recommendations for a slice service and/or slice load information.
Step 22: and adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
The NSSF can adjust the KPIs and the network performance at the slicing level aiming at the RAN and the CN according to the data analysis result. In particular, the NSSF may request or subscribe to network status information directly from the NWDAF through the service interface. The NSSF can determine the quality information of the slicing level and the slicing satisfaction degree of the SLA of the tenant which can be achieved according to the data analysis result of the slicing level given by the NWDAF and the current network strategy.
Wherein, step 21 also includes before: and sending at least one of slice congestion information of different slices, percentage information of user experience values and service requirement information of newly added slices to the NWDAF. Wherein, the percentage information of the user experience value refers to what percentage of the user experience value each slice can satisfy. That is, the NSSF simultaneously reports at least one of slice congestion information of a current network slice, percentage of user experience values that each slice can satisfy, and service demand information of a newly added slice to the NWDAF.
Specifically, an operator can divide the network load degree into different levels through testing, quantize the SLA of the slice tenant into a specific value interval according to the network load degree, that is, a user experience value, and then according to each network index required by each type of input slice, for example: and reporting the coverage condition of the service area cell, the current network load information and the like to the NWDAF for analysis so as to output a corresponding user experience value.
The foregoing describes the slice resource scheduling method at the NWDAF and NSSF sides, and the following embodiment of the present invention further describes the slice resource scheduling method at the PCF side.
As shown in fig. 3, an embodiment of the present invention provides a method for scheduling slice resources, which is applied to specifically include the following steps:
step 31: and acquiring a data analysis result of the slice from a network analysis logic function NWDAF.
And when the data analysis result is that slices are newly added in the network, the NWDAF sends the corresponding optimization indexes to the PCF and the NSSF after analyzing the NWDAF according to the network congestion state. Wherein the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
Step 32: and according to the data analysis result, performing strategy configuration adjustment on different slices.
The PCF performs the adjustment of the policy configuration again according to the slice priority information of each slice according to the data analysis result received from the NWDAF.
Wherein, step 31 also includes before: slice priority information for different slices is sent to the NWDAF. That is, the PCF reports slice priority information for different slices of the policy configuration to the NWDAF.
The slice resource scheduling method according to the embodiment of the present invention is introduced from the NWDAF, NSSF and PCF side, and the following implementation of the present invention will further describe the slice resource scheduling method with reference to the drawings.
As shown in fig. 4, the method for scheduling slice resources is applied to a slice network, which includes but is not limited to: network elements such as NWDAF, NFs/OAM, NSSF and PCF. The method comprises the following steps:
step 41: and acquiring analysis data.
Wherein step 41 comprises:
step 41 a: NFs/OAM sends at least one of KPIs and performance measurement indicators of stored slices at RAN/CN side to NWDAF.
Step 41 b: the NSSF sends at least one of slice congestion information, percentage information of user experience values and service demand information of newly added slices to the NWDAF.
Step 41 c: the PCF sends slice priority information to the NWDAF.
It is noted that the timing sequence between steps 41a, 41b and 41c is not limited by the embodiments of the present invention, and the steps may be executed in parallel or executed in series in any order.
Step 42: and analyzing and updating the acquired analysis data by using the analysis model to obtain a data analysis result.
Step 43 a: the NWDAF sends the data analysis results to the NSSF.
Step 44 a: and the NSSF performs slice-level KPIs and network performance adjustment according to the data analysis result.
Alternatively, after step 42, the method further comprises:
step 43 b: the NWDAF sends the data analysis results to the PCF.
Step 44 b: and the PCF performs strategy configuration adjustment on different slices according to the data analysis result.
In the embodiment of the present invention, the timing sequence between steps 43a and 43b and the timing sequence between step 44a and step 44b are not limited.
In the slice resource scheduling method of the embodiment of the invention, the NWDAF can obtain the data analysis result of the slice resource of the current network according to the analysis data of the current network, distribute the data analysis result to the NSSF or PCF, and dynamically adjust the slice resource by the NSSF or PCF, thereby improving the resource utilization rate and meeting the SLA requirements of more slice users.
The above embodiments are respectively introduced to the slice resource scheduling method of the present invention, and the following embodiments will further describe a network element corresponding thereto with reference to the accompanying drawings.
Specifically, as shown in fig. 5, a network element 500 according to an embodiment of the present invention is a network analysis logic function NWDAF, and includes the following functional modules:
an obtaining module 510 for obtaining analysis data of the slice;
the analysis module 520 is configured to perform analysis and update on the analysis data to obtain a data analysis result;
a first sending module 530, configured to send the data analysis result to the network slice selecting function NSSF or the policy control function PCF.
Wherein the obtaining module 510 comprises at least one of:
a first obtaining sub-module, configured to obtain first analysis data from the network function NFs and/or the operation, administration and maintenance OAM;
the second acquisition submodule is used for acquiring second analysis data from the PCF;
and the third acquisition submodule is used for acquiring third analysis data from the NSSF.
Wherein the first analytical data comprises: storing at least one of key performance indicators, KPIs, and performance measurement indicators for the slice.
Wherein the second analysis data comprises: slice priority information.
Wherein the third analysis data comprises: at least one of slice congestion information, percentage information of user experience values, and service demand information of newly added slices.
Wherein, the network element 500 further includes:
and the training module is used for performing offline data analysis and training an analysis model.
Wherein, the analysis module 520 includes:
and the analysis submodule is used for analyzing and updating the analysis data by using the analysis model to obtain a data analysis result.
Wherein, the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
The network element embodiment on the NWDAF side of the present invention is corresponding to the above method embodiment, and all implementation means in the above method embodiment are applicable to the network element embodiment, and can achieve the same technical effect.
As shown in fig. 6, a network element 600 according to an embodiment of the present invention, which is a network slice selection function NSSF, includes the following functional modules:
a first obtaining module 610, configured to obtain a data analysis result of a slice from a network analysis logic function NWDAF;
and a first adjusting module 620, configured to perform slice-level KPIs and network performance adjustment according to the data analysis result.
Wherein, the network element 600 further includes:
and the second sending module is used for sending slice congestion information of different slices, percentage information of user experience values and service requirement information of newly added slices to the NWDAF.
Wherein, the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
The embodiment of the network element on the NSSF side of the present invention is corresponding to the embodiment of the method, and all implementation means in the embodiment of the method are applicable to the embodiment of the network element, and the same technical effect can be achieved.
As shown in fig. 7, a network element 700 according to an embodiment of the present invention is a policy control function PCF, and includes the following functional modules:
a second obtaining module 710, configured to obtain a data analysis result of the slice from a network analysis logic function NWDAF;
and a second adjusting module 720, configured to perform policy configuration adjustment on different slices according to the data analysis result.
Wherein the network element 700 further comprises:
and a third sending module, configured to send slice priority information of different slices to the NWDAF.
Wherein, the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
The embodiment of the PCF-side network element of the present invention corresponds to the embodiment of the above-mentioned method, and all the implementation means in the above-mentioned method embodiment are applicable to the embodiment of the network element, and can achieve the same technical effect.
In the embodiment of the invention, the NWDAF can obtain the data analysis result of the slice resource of the current network according to the analysis data of the current network, distribute the data analysis result to the NSSF or PCF, and dynamically adjust the slice resource by the NSSF or PCF, thereby improving the resource utilization rate and meeting the SLA requirements of more slice users.
In order to better achieve the above object, as shown in fig. 8, a fourth embodiment of the present invention further provides a network element, which includes: a processor 800; a memory 820 connected to the processor 800 through a bus interface, and a transceiver 810 connected to the processor 800 through a bus interface; the memory 820 is used for storing programs and data used by the processor in performing operations; transmitting data information or pilot frequency through the transceiver 810, and receiving an uplink control channel through the transceiver 810; when the processor 800 calls and executes the programs and data stored in the memory 820, the following functions are implemented:
the network element is a network analysis logic function NWDAF network element, and the transceiver 810 is configured to: acquiring analysis data of the slice;
the processor 800 is configured to: analyzing and updating the analysis data to obtain a data analysis result;
the transceiver 810 is further configured to: and sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
Wherein the transceiver 810 is specifically configured for at least one of:
obtaining first analysis data from network function NFs and/or an operation, administration, and maintenance, OAM;
acquiring second analysis data from the PCF;
from the NSSF, third analytical data was obtained.
Wherein the first analytical data comprises: storing at least one of key performance indicators, KPIs, and performance measurement indicators for the slice.
Wherein the second analysis data comprises: slice priority information.
Wherein the third analysis data comprises: at least one of slice congestion information, percentage information of user experience values, and service demand information of newly added slices.
Wherein the processor 800 is further configured to: and (5) performing off-line data analysis and training an analysis model.
Wherein, the processor 800 is specifically configured to: and analyzing and updating the analysis data by using the analysis model to obtain a data analysis result.
The network element is a network slice selection function NSSF network element, and the transceiver 810 is configured to: acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
the processor 800 is configured to: and adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
Wherein the transceiver 810 is further configured to: and sending slice congestion information of different slices, percentage information of user experience values and service requirement information of newly added slices to the NWDAF.
Wherein, the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
The network element is a policy control function PCF network element, and the transceiver 810 is configured to: acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
the processor 800 is configured to: and according to the data analysis result, performing strategy configuration adjustment on different slices.
Wherein the transceiver 810 is further configured to: slice priority information for different slices is sent to the NWDAF.
Wherein, the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
Where in fig. 8, the bus architecture may include any number of interconnected buses and bridges, with various circuits being linked together, particularly one or more processors represented by processor 800 and memory represented by memory 820. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface. The transceiver 810 may be a number of elements including a transmitter and a transceiver providing a means for communicating with various other apparatus over a transmission medium. The processor 800 is responsible for managing the bus architecture and general processing, and the memory 820 may store data used by the processor 800 in performing operations.
Those skilled in the art will appreciate that all or part of the steps for implementing the above embodiments may be performed by hardware, or may be instructed to be performed by associated hardware by a computer program that includes instructions for performing some or all of the steps of the above methods; and the computer program may be stored in a readable storage medium, which may be any form of storage medium.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the foregoing embodiment of the slice resource scheduling method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
Furthermore, it is to be noted that in the device and method of the invention, it is obvious that the individual components or steps can be decomposed and/or recombined. These decompositions and/or recombinations are to be regarded as equivalents of the present invention. Also, the steps of performing the series of processes described above may naturally be performed chronologically in the order described, but need not necessarily be performed chronologically, and some steps may be performed in parallel or independently of each other. It will be understood by those skilled in the art that all or any of the steps or elements of the method and apparatus of the present invention may be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or any combination thereof, which can be implemented by those skilled in the art using their basic programming skills after reading the description of the present invention.
Thus, the objects of the invention may also be achieved by running a program or a set of programs on any computing device. The computing device may be a general purpose device as is well known. The object of the invention is thus also achieved solely by providing a program product comprising program code for implementing the method or the apparatus. That is, such a program product also constitutes the present invention, and a storage medium storing such a program product also constitutes the present invention. It is to be understood that the storage medium may be any known storage medium or any storage medium developed in the future. It is further noted that in the apparatus and method of the present invention, it is apparent that each component or step can be decomposed and/or recombined. These decompositions and/or recombinations are to be regarded as equivalents of the present invention. Also, the steps of executing the series of processes described above may naturally be executed chronologically in the order described, but need not necessarily be executed chronologically. Some steps may be performed in parallel or independently of each other.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (26)
1. A slice resource scheduling method is applied to a network analysis logic function (NWDAF), and is characterized by comprising the following steps:
acquiring analysis data of the slice;
analyzing and updating the analysis data to obtain a data analysis result;
and sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
2. The slice resource scheduling method of claim 1, wherein the step of obtaining analysis data of the slice comprises at least one of:
obtaining first analysis data from network function NFs and/or an operation, administration, and maintenance, OAM;
acquiring second analysis data from the PCF;
from the NSSF, third analytical data is obtained.
3. The method for scheduling slice resources according to claim 2, wherein the first analysis data comprises: storing at least one of key performance indicators, KPIs, and performance measurement indicators for the slice.
4. The method for scheduling slice resources according to claim 2, wherein the second analysis data comprises: slice priority information.
5. The method of claim 2, wherein the third analysis data comprises: at least one of slice congestion information, percentage information of user experience values, and service demand information of newly added slices.
6. The slice resource scheduling method according to claim 1, wherein the step of analyzing and updating the analysis data to obtain a data analysis result further comprises:
and (5) performing off-line data analysis and training an analysis model.
7. The slice resource scheduling method of claim 6, wherein the step of analyzing and updating the analysis data to obtain a data analysis result comprises:
and analyzing and updating the analysis data by using the analysis model to obtain a data analysis result.
8. The method for scheduling slice resources according to claim 1, wherein the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
9. A network analysis logic function, NWDAF, network element, comprising: a processor; a memory coupled to the processor, and a transceiver coupled to the processor; wherein the content of the first and second substances,
the transceiver is configured to: acquiring analysis data of the slice;
the processor is configured to: analyzing and updating the analysis data to obtain a data analysis result;
the transceiver is further configured to: and sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
10. The network analysis logic function, NWDAF, network element of claim 9, wherein the transceiver is specifically configured to at least one of:
obtaining first analysis data from network function NFs and/or an operation, administration, and maintenance, OAM;
acquiring second analysis data from the PCF;
from the NSSF, third analytical data is obtained.
11. The network analysis logic function, NWDAF, network element of claim 9, wherein the processor is further configured to:
and (5) performing off-line data analysis and training an analysis model.
12. The network analysis logic function, NWDAF, network element of claim 11, wherein the processor is specifically configured to:
and analyzing and updating the analysis data by using the analysis model to obtain a data analysis result.
13. A network element, the network element being a network analysis logic function, NWDAF, comprising:
the acquisition module is used for acquiring analysis data of the slice;
the analysis module is used for analyzing and updating the analysis data to obtain a data analysis result;
and the first sending module is used for sending the data analysis result to a network slice selection function NSSF or a policy control function PCF.
14. A slice resource scheduling method is applied to a network slice selection function NSSF, and is characterized by comprising the following steps:
acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
and adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
15. The slice resource scheduling method of claim 14, wherein the step of obtaining the data analysis result of the slice from a network analysis logic function NWDAF further comprises, before the step of:
and sending at least one of slice congestion information of different slices, percentage information of user experience values and service requirement information of newly added slices to the NWDAF.
16. The method of claim 14, wherein the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
17. A network slice selection function, NSSF, network element, comprising: a processor; a memory coupled to the processor, and a transceiver coupled to the processor; wherein the content of the first and second substances,
the transceiver is configured to: acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
the processor is configured to: and adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
18. The network slice selection function, NSSF, network element of claim 17, wherein the transceiver is further configured to:
and sending slice congestion information of different slices, percentage information of user experience values and service requirement information of newly added slices to the NWDAF.
19. A network element, the network element being a network slice selection function, NSSF, comprising:
the first acquisition module is used for acquiring a data analysis result of the slice from a network analysis logic function NWDAF;
and the first adjusting module is used for adjusting the KPIs and the network performance at the slicing level according to the data analysis result.
20. A slice resource scheduling method is applied to a policy control function PCF, and is characterized by comprising the following steps:
acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
and according to the data analysis result, performing strategy configuration adjustment on different slices.
21. The slice resource scheduling method of claim 20, wherein the step of obtaining the data analysis result of the slice from a network analysis logic function NWDAF further comprises, before the step of:
transmitting slice priority information for different slices to the NWDAF.
22. The method for scheduling slicing resources of claim 20, wherein the data analysis result comprises: quality of service QoS profile recommendations for a slice service and/or slice load information.
23. A policy control function, PCF, network element, comprising: a processor; a memory coupled to the processor, and a transceiver coupled to the processor; wherein the content of the first and second substances,
the transceiver is configured to: acquiring a data analysis result of the slice from a network analysis logic function (NWDAF);
the processor is configured to: and according to the data analysis result, performing strategy configuration adjustment on different slices.
24. The policy control function PCF network element of claim 23 wherein said transceiver is further configured to:
transmitting slice priority information for different slices to the NWDAF.
25. A slice resource scheduling method is applied to a policy control function PCF, and is characterized by comprising the following steps:
the second acquisition module is used for acquiring a data analysis result of the slice from a network analysis logic function NWDAF;
and the second adjusting module is used for performing strategy configuration adjustment on different slices according to the data analysis result.
26. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for slice resource scheduling according to any one of claims 1 to 8, 14 to 16, 20 to 22.
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