CN108632848B

CN108632848B - Network slice self-optimization coordination method and device

Info

Publication number: CN108632848B
Application number: CN201710166834.3A
Authority: CN
Inventors: 孙文琦; 杨水根; 陆伟
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2017-03-20
Filing date: 2017-03-20
Publication date: 2021-03-30
Anticipated expiration: 2037-03-20
Also published as: CN108632848A

Abstract

The patent application provides a network slice self-optimization coordination method and device. The method comprises the following steps: the network slice self-optimization coordination function sends a self-optimization coordination message to the network slice subnet self-optimization function, and the self-optimization coordination message is used for coordinating the self-optimization of the self-optimization functions of a plurality of network slice subnets in the network slice subnets; and the network slice self-optimization coordination function receives a self-optimization coordination solution result sent by the network slice subnet self-optimization function.

Description

Network slice self-optimization coordination method and device

Technical Field

The present invention relates to the field of wireless communications, and in particular, to a method and an apparatus for network slice self-optimization coordination in a wireless communication system.

Background

With the rapid development of wireless communication technology, the fifth Generation (5th Generation, abbreviated as 5G) wireless communication technology has been the hot spot in the industry. The 5G will support diverse application requirements including access capability supporting higher rate experience and larger bandwidth, lower latency and highly reliable information interaction, and access and management of larger-scale and low-cost machine type communication devices, etc. In addition, 5G can support various vertical industry application scenes such as vehicle networking, emergency communication, industrial internet and the like. In the face of the performance requirements and application scenarios of 5G, the 5G network needs to be closer to the specific requirements of users, and the customization capability needs to be further improved.

To this end, 5G introduces the important concept of network slicing. A network slice is a combination of a plurality of network functions and corresponding resources that implement a communication service. The 5G network is composed of various network slices that satisfy different connection capabilities, one network slice being a logical network that satisfies the communication service requirements of one class or one use case. Fig. 1 shows a 5G network scenario after introducing a network slicing concept, which includes Communication of three cases, namely Critical Machine Type Communication (referred to as Critical MTC), Massive Machine Type Communication (referred to as Massive MTC), and Mobile broadband (referred to as MBB). As shown in fig. 1, a 3GPP operator network may include a critical machine type communication network slice, a large scale machine type communication network slice, and a mobile broadband network slice, where each network slice serves different use cases of communication services.

A unified network platform, which supports communication services with different functions and quality of service requirements using dynamic, secure network slices, is one of the basic capabilities of a 5G network. The logical network formed by a network slice is realized by the network slice instance, namely, a network slice is formed by instantiating each network function and corresponding resource of the network slice. In order to ensure that the network slice can normally operate, the 5G network needs to optimize the network slice in real time according to the conditions of the network (such as performance state and service requirement). The network slice self-optimization technology is a technology for realizing automatic monitoring, management and optimization of network slice performance by a network. Specifically, the network slice can automatically change the configuration while continuously providing the service, thereby adapting to dynamically changing flow, topology, network resources, traffic states, and the like. The network slice self-optimization enables the system of the network slice to be automatically optimized, thereby avoiding the influence on the service as much as possible, reducing the manual participation as much as possible and reducing the operation and maintenance cost of an operator on the network slice management.

The basic implementation mode of the self-optimization technology is that the self-optimization function runs a self-optimization algorithm according to the condition of the network, and then the parameters in the network are configured according to the result of the self-optimization algorithm, so that the purpose of performance optimization is achieved. Due to the existence of a plurality of different self-optimization functions in the network, the optimization purposes, the optimization criteria and the optimization objects of the different self-optimization functions may be different, which may cause conflicts when the different self-optimization functions execute the results of their respective optimization algorithms. How to coordinate a plurality of optimization functions for self-optimization and ensure that no self-optimization conflict is generated, no proper solution is available at present.

Disclosure of Invention

The embodiment of the application provides a self-optimization coordination method and device for network slices, so that coordination is provided for various optimization functions of the network slices, and conflict is avoided in self-optimization of the network slices.

In a first aspect, an embodiment of the present application provides a network slice self-optimization coordination method, where a network slice self-optimization coordination function sends a self-optimization coordination message to a network slice subnet self-optimization function, where the self-optimization coordination message is used to coordinate self-optimization of multiple network slice subnets in a network slice subnet self-optimization function; and the network slice self-optimization coordination function receives a self-optimization coordination solution result sent by the network slice subnet self-optimization function.

In one possible implementation, the self-optimization coordination message includes a self-optimization coordination configuration message and/or a self-optimization coordination solution message; the self-optimization coordination configuration message is used for indicating the self-optimization function of the network slice subnet to report a self-optimization algorithm result to the network slice self-optimization coordination function before the self-optimization is executed; the self-optimization coordination solution message is used for instructing the self-optimization function of the network slice subnet to execute self-optimization coordination solution.

In a possible implementation manner, before the network slice self-optimization coordination function sends the self-optimization coordination message, the method further includes: and the network slice self-optimization coordination function obtains a self-optimization coordination strategy and determines the self-optimization function and parameters needing to be coordinated.

In a possible implementation manner, before the network slice self-optimization coordination function sends the self-optimization coordination solution message, the method further includes: and the network slice self-optimization coordination function decides self-optimization coordination according to the self-optimization coordination strategy.

Therefore, according to the network slice self-optimization coordination method provided by the embodiment of the application, when a network slice subnet instance is shared by a plurality of network slice instances, self-optimization coordination solution can be realized when the network slice subnet instance self-optimization caused by optimization strategies of different network slice instances generates conflict; self-optimizing coordination resolution may also be achieved when multiple network slice subnet instances within one network slice instance self-optimize to create conflicts.

In a second aspect, an embodiment of the present application provides a network slice self-optimization coordination method, where the method includes: the network slice subnet self-optimization function receives a self-optimization coordination message sent by the network slice self-optimization coordination function; the network slice subnet self-optimization function carries out self-optimization coordination processing according to the self-optimization coordination message; and the network slice subnet self-optimization function sends a self-optimization coordination processing result to the network slice self-optimization coordination function.

In one possible implementation, the self-optimization coordination process includes running a self-optimization algorithm and/or executing a self-optimization coordination solution.

In a possible implementation manner, the network slice subnet self-optimization function runs a self-optimization algorithm after receiving the self-optimization coordination configuration message, and reports a result of the self-optimization algorithm to the network slice self-optimization coordination function.

In a possible implementation manner, the network slice subnet self-optimization function executes a self-optimization coordination solution after receiving the self-optimization coordination solution message, and reports a result of the self-optimization coordination solution to the network slice self-optimization coordination function.

In a third aspect, an embodiment of the present application provides a network slice self-optimization coordination method, where a network slice self-optimization coordination function sends a self-optimization coordination policy to a network slice subnet self-optimization coordination function; and the network slice self-optimization coordination function receives a self-optimization coordination solution result sent by the network slice subnet self-optimization coordination function.

In one possible implementation, the self-optimizing coordination policy includes at least one of: self-optimizing priority among NSIs; self-optimizing an NSI, wherein the priorities of different self-optimizing functions and self-optimizing parameters are different; the need to detect parameters that create collisions, such as NSSI capacity; different parameters such as self-optimized mobility support and self-optimized latency, etc. may result in collisions.

In a possible implementation manner, before the network slice self-optimization coordination function sends the self-optimization coordination policy, the method further includes: the network slice self-optimization coordination function obtains a self-optimization coordination strategy.

Therefore, according to the network slice self-optimization coordination method provided by the embodiment of the application, self-optimization coordination resolution can be achieved when self-optimization functions of multiple network slice subnets with different optimization purposes in one network slice subnet in one network slice instance generate conflicts.

In a fourth aspect, an embodiment of the present application provides a network slice self-optimization coordination method, where a network slice subnet self-optimization coordination function receives a self-optimization coordination policy sent by the network slice self-optimization coordination function; the network slice subnet self-optimization coordination function carries out self-optimization coordination according to a self-optimization coordination strategy; and the network slice subnet self-optimization coordination function sends a self-optimization coordination solution result to the network slice self-optimization coordination function.

In a fifth aspect, a communication device is provided for performing the method of the first to third aspects or any possible implementation manner of the first to third aspects, and in particular, the communication device may include means for performing the method of the first to third aspects or any possible implementation manner of the first to third aspects.

In a sixth aspect, there is provided a communication apparatus comprising a memory for storing a computer program and a processor for invoking and running the computer program from the memory so that a communication device performs the method of the first to third aspects or any possible implementation manner of the first to third aspects.

In a seventh aspect, a computer program product is provided, the computer program product comprising: computer program code which, when run by a communication unit, a processing unit or a transceiver, a processor of a communication device (e.g. a network device or a network management device), causes the communication device to perform the method of the first to third aspect or any of the possible implementations of the first to third aspects.

In an eighth aspect, a computer-readable storage medium is provided, which stores a program that causes a user equipment to execute the method of the first to third aspects or any possible implementation manner of the first to third aspects.

These and other aspects of the invention will be apparent from and elucidated with reference to the embodiment(s) described hereinafter.

Drawings

The drawings that accompany the detailed description can be briefly described as follows:

fig. 1 is a 5G network scenario provided in an embodiment of the present application;

fig. 2 is a schematic diagram of a possible network slice management architecture provided in an embodiment of the present application;

FIG. 3 is a schematic diagram of a possible network slice self-optimization coordination architecture provided by an embodiment of the present application;

FIG. 4 is a schematic diagram of a possible network slice self-optimization coordination process provided by an embodiment of the present application;

FIG. 5 is a schematic diagram of another possible network slice self-optimization coordination architecture provided in an embodiment of the present application;

FIG. 6 is a schematic diagram of another possible network slice self-optimization coordination architecture provided by an embodiment of the present application;

FIG. 7 is a schematic diagram of another possible network slice self-optimization coordination flow provided by an embodiment of the present application;

fig. 8 is a schematic structural diagram of a network slice self-optimization coordination function provided in an embodiment of the present application;

fig. 9 is another structural diagram of a network slice self-optimization coordination function provided in an embodiment of the present application;

fig. 10 is a schematic structural diagram of a network slice subnet self-optimization coordination function provided in an embodiment of the present application;

fig. 11 is another schematic structural diagram of a network slice subnet self-optimization coordination function provided in an embodiment of the present application;

fig. 12 is a schematic structural diagram of a self-optimization function of a network slice subnet provided in an embodiment of the present application;

fig. 13 is another schematic structural diagram of a network slice subnet self-optimization function provided in an embodiment of the present application.

Detailed Description

The embodiments of the present application will be described below with reference to the drawings.

In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for the purpose of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not shown in detail to avoid obscuring the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or 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.

The terms "system" and "network" are often used interchangeably herein. The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.

As a key feature of 5G, a 5G network may be divided into multiple network slices. One Network Slice (NS) corresponds to one logical Network, and the logical Network is used to meet the communication service requirement of one use case. A Network Slice is composed of one or more Network Functions (NF), and is implemented by a Network Slice Instance (NSI), that is, a Network Slice is formed by instantiating each Network Function of the Network Slice and corresponding resources and configurations. A network slice may contain at least one network slice instance, and a network slice instance may also contain multiple network slice subnet instances, each of which is an integral part of a network slice instance. Different network slice instances and/or network slice subnet instances may have different configurations of network functions and/or resources. The self-optimization of the network slice comprises self-optimization of network slice examples and/or network slice subnet examples, and the self-optimization of different network slice examples and/or network slice subnet examples can cause conflict, so that the self-optimization performance is greatly reduced, how to coordinate the self-optimization of different network slice examples and/or network slice subnet examples is realized, and the application of a self-optimization technology in network slice management is guaranteed.

To facilitate understanding, some terms appearing herein are introduced.

Network Slice (NS): different logical networks are customized according to different service requirements on the basis of physical or virtual network infrastructure. The network slice can be a complete end-to-end network comprising a terminal, an access network, a transmission network, a core network and an application server, can provide telecommunication service and has certain network capacity; the network slice may also be any combination of the above terminals, access networks, transport networks, core networks and application servers, e.g. a network slice only contains access networks and core networks. A network slice may have one or more of the following characteristics: the access network may or may not be sliced. The access network may be shared by multiple network slices. The characteristics of different NS and the network functions that make up the NS may be different.

Network Function (NF): the network function can be realized by special hardware, software running on the special hardware, or virtual function on general hardware platform. From an implementation point of view, network functions can be divided into physical network functions and virtual network functions. From a usage perspective, NFs can be classified as proprietary NFs and shared NFs. When one NF only belongs to one network slice instance or network slice subnet instance, the NF is an exclusive NF; when an NF belongs to multiple network slice instances or network slice subnet instances, the NF is a shared NF.

Network Slice Instance (Network Slice Instance; NSI for short): a truly operating logical network can meet certain network characteristics or service requirements. One network slice instance may provide one or more services. The network slice instance can be created by a network management system, and one network management system can create a plurality of network slice instances and manage the network slice instances simultaneously, including performance monitoring, fault management and the like in the operation process of the network slice instances. When multiple network slice instances coexist, portions of the network resources and network functions may be shared between the network slice instances. The network slice instance may or may not be created from a network slice template. A complete network slice instance is capable of providing a complete end-to-end network service, and what constitutes the network slice instance may be a sub-network slice instance (network slice sub-network instance) and/or a network function. The network functions may include physical network functions and/or virtual network functions. Hereinafter, a physical network function and/or a virtual network function are collectively referred to as a network function.

Network Slice Subnet Instance (NSSI): the NSSI may be a collection of network functions of the same equipment provider in the NSI, or may be a collection of network functions divided by domains, such as a network slice instance of a core network, a network slice instance of an access network, or a collection composed by other manners. The NSSI may be shared by multiple NSIs. An NSI may comprise a plurality of NSSIs, each NSSI comprising at least one network function and/or one or more other NSSIs embedded within the NSSI; an NSI may comprise at least one NSSI and/or at least one network function; an NSI may also include only at least one NF.

Fig. 2 shows a schematic diagram of a possible network slice management architecture. As shown in fig. 2, the Network Slice Management Function may include a Service Management Function (SvMF), a Network Slice Management Function (NSMF), and a Network Slice Subnet Management Function (NSSMF). The SvMF is mainly responsible for converting telecommunication service requirements of an operator and/or a third party customer into requirements for the NS, sending the requirements for the NS to the NSMF, receiving subscription requirements of the operator and/or the third party customer for NS management data (such as performance data, fault repair data, and the like), and acquiring the management data of the NS from the NSMF. The NSMF is mainly responsible for receiving NS requirements sent by the SvMF, managing the life cycle, performance, faults and the like of the NSI, arranging the composition of the NSI, decomposing the requirements of the NSI into the requirements of each NSSI, sending NSSI management requests to each NSSMF and the like. NSSMF receives the needs for NSSI from NSMF, manages the life cycle, performance, failure, etc. of NSSI, orchestrates the composition of NSSI, etc.

Fig. 3 shows a schematic diagram of a possible network slice self-optimization coordination architecture. A Network Slice Self-Optimization Coordination Function (NS _ SO _ COF) is located in the NSMF, and is responsible for coordinating Network Slice Self-Optimization in the Network, specifically, coordinating a plurality of Self-Optimization functions in at least one Network Slice instance, and/or coordinating at least one Self-Optimization Function shared by a plurality of Network Slice instances. The function of the NS _ SO _ COF includes at least one of: receiving a self-optimization coordination policy of the network slice from the operator or SvMF, such as priority between NSI, priority between self-optimization functions; calculating self-optimization coordination strategies applied to the self-optimization coordination strategies according to the obtained self-optimization coordination strategies and all self-optimization function information, for example, which self-optimization functions need to be coordinated, which optimization parameters need to be coordinated, and the like; interacting with the self-optimization function, notifying the self-optimization function which is possibly conflicted, and enabling the self-optimization function to execute a self-optimization result and report an optimization algorithm result to an NS _ SO _ COF before modifying NSSI configuration; and performing self-optimization coordination, informing a self-optimization function, and judging whether an optimization result can be executed or not. The Network Slice Subnet Optimization Function (NSS _ SO _ F) is located in the NSSMF and is responsible for Self-optimizing the NSSI. For example, different NSS _ SO _ fs may have different self-optimization purposes, such as capacity self-optimized NSS _ SO _ F for increasing the capacity of the network slice subnet, load self-optimized NSS _ SO _ F for improving the load of the network slice subnet, and SO on. Different NSS _ SO _ F may also have the same self-optimization purpose but different optimization strategies, e.g. a first capacity self-optimization NSS _ SO _ F is to optimize the capacity of a corresponding first NSSI according to the optimization strategy of the first NSI, a second capacity self-optimization NSS _ SO _ F is to optimize the capacity of a corresponding second NSSI according to the optimization strategy of the second NSI, etc. The scenario corresponding to the network slice self-optimization coordination architecture illustrated in fig. 3 is a scenario in which one NSI is shared by multiple NSIs. As shown in fig. 3, the NSSMF includes a first NSS _ SO _ F (hereinafter, simply referred to as "NSS _ SO _ F1") and a second NSS _ SO _ F (hereinafter, simply referred to as "NSS _ SO _ F2"). Wherein the NSSI managed by the NSSMF is a NSSI shared by a plurality of NSIs, and NSS _ SO _ F1 is a first NSI sharing the NSSI for optimizing the function of the NSSI; NSS _ SO _ F2 is a second NSI that shares the NSSI for optimizing the function of the NSSI. Illustratively, the NSSI is shared by a first NSI and a second NSI, and the optimization strategy of the NSSI by the first NSI is different from that of the second NSI, SO that the optimization of the NSSI by the NSS _ SO _ F1 and the optimization of the NSSI by the NSS _ SO _ F2 may conflict, for example, the modification requirements of the NSS _ SO _ F1 on the configuration parameters of the NSSI from the optimization and the modification requirements of the NSS _ SO _ F2 on the configuration parameters of the NSSI from the optimization are different, which causes the configuration of the NSSI to conflict after the respective self-optimization is performed. In this case, NS _ CO _ COF is responsible for coordinating the optimization of NSs _ SO _ F1 and NSs _ SO _ F2, avoiding possible collisions. It should be understood that fig. 3 schematically depicts two NSS _ SO _ F included in NSSMF; in an actual network, one NSSMF may include at least one NSS _ SO _ F; different NSS _ SO _ F may be a self-optimization function belonging to one NSI, or may be a self-optimization function belonging to different NSIs, which is not limited in this embodiment of the present application. Similarly, fig. 3 schematically depicts the association of NSMF with one NSSMF; in an actual network, an NSMF may be associated with at least one NSSMF; different NSSMFs may be management functions belonging to one NSI, or may be management functions belonging to different NSIs, which is not limited in this embodiment of the present application.

With reference to fig. 3, fig. 4 shows a schematic diagram of a possible network slice self-optimization coordination flow provided by the embodiment of the present application. The process illustrated in fig. 4 may be applied to the coordination of a network slice self-optimization function for an NSI shared by multiple NSIs, comprising the steps of:

401. and the NS _ SO _ COF acquires a network slice self-optimization coordination strategy.

Optionally, the NS _ SO _ COF receives the network slice self-optimization coordination policy from the operator, which may be received from the operator operation and maintenance personnel, or a management module such as SvMF, or other management module. The network slice self-optimization coordination strategy comprises at least one of the following: self-optimizing priority among NSIs; self-optimizing an NSI, wherein the priorities of different self-optimizing functions and self-optimizing parameters are different; the need to detect parameters that create collisions, such as NSSI capacity; different parameters such as self-optimized mobility support and self-optimized latency, etc. may result in collisions.

402. The NS _ SO _ COF determines the NSs _ CO _ F and optimization parameters that need to be coordinated.

The NS _ SO _ COF, upon receiving the conflict resolution policy from the operator, determines the self-optimization function and related parameters that may generate a conflict, for example, determines that the NSs _ SO _ F1 performs self-optimization and that the NSs _ SO _ F2 performs self-optimization.

403. The NS _ SO _ COF sends a self-optimization coordination configuration message to the NSs _ SO _ F.

The self-optimization coordination configuration message is used for indicating NSS _ SO _ F to report the result of the self-optimization algorithm before self-optimization is executed. That is, after the NSS _ SO _ F is instructed to run the self-optimization algorithm according to the self-optimized NSSI condition, the result of the self-optimization algorithm is not executed, but the result of the self-optimization algorithm is reported to the NS _ SO _ COF.

In this step, the NS _ SO _ COF may send self-optimization coordination configuration information to the NSs _ CO _ F of at least one NSSI of the plurality of NSIs it manages.

404. NSS _ SO _ F runs the liberalization algorithm.

Where the multiple NSS _ SO _ F's that received the self-optimizing coordination configuration message at step 403 run the liberalization algorithm according to the conditions of their self-optimized NSSI. Specifically, the NSSI self-optimized by NSS _ SO _ F runs a liberalization algorithm for optimizing a specific performance of NSS _ SO _ F when the NSS _ SO _ F self-optimization condition is reached. For example, when the capacity of the NSSI decreases to a preset threshold, the network slice subnet capacity self-optimization function of the NSSI is triggered to operate the capacity self-optimization algorithm.

405. And the NSS _ SO _ F reports the self-optimization algorithm result to the NS _ SO _ COF.

406. And the NS _ SO _ COF decides self-optimization coordination according to the self-optimization coordination strategy.

In this step, the NS _ SO _ COF determines the self-optimization algorithm results reported by the NSs _ SO _ fs, and makes a decision of self-optimization coordination when the optimization results of the NSs _ SO _ fs conflict. For example, if the self-optimization result of NSS _ SO _ F1 conflicts with the self-optimization result of NSS _ SO _ F2, and the self-optimization priority of NSS _ CO _ F1 is higher than that of NSS _ SO _ F2 in the self-optimization coordination strategy, the self-optimization coordination decision of NS _ SO _ COF may be to give priority to self-optimization of NSS _ SO _ F1 and not to self-optimization of NSS _ SO _ F2. Or the self-optimization coordination decision of the NS _ SO _ COF can select a self-optimization result which can be accepted by both NSS _ SO _ F1 and NSS _ SO _ F2, and realize the compromise of the self-optimization results of the two. Illustratively, NSS _ SO _ F1 indicates that the NSSI capacity is expanded to 120% of the current capacity, and the upper limit of the capacity is greater than 150% of the current capacity, NSS _ SO _ F2 indicates that the NSSI capacity is expanded to 200% of the current capacity, and NS _ SO _ COF may select a compromise result, such as expanding the NSSI capacity to 150% of the current capacity.

407. The NS _ SO _ COF sends a self-optimization coordination solution message to the NSs _ SO _ F instructing the NSs _ SO _ F to perform self-optimization coordination solution.

In this step, the NS _ SO _ COF sends the self-optimized coordinated solution decided in step 406 to the NSs _ SO _ F, SO that the NSs _ SO _ F performs the self-optimized coordinated solution. Illustratively, if the self-optimization result of NSS _ SO _ F1 and the self-optimization result of NSS _ SO _ F2 conflict and the self-optimization priority of NSS _ SO _ F1 is higher than the self-optimization priority of NSS _ SO _ F2, in this step, NS _ SO _ COF may instruct NSS _ SO _ F1 to perform its self-optimization algorithm result, instructing NSS _ SO _ F2 not to perform its self-optimization algorithm result. For another example, the self-optimization algorithm result of NSS _ SO _ F1 is to expand NSSI capacity to 120% of current capacity with the upper capacity limit being greater than 150% of current capacity, and the self-optimization algorithm result of NSS _ SO _ F2 is to expand NSSI capacity to 200% of current capacity, then in this step NS _ SO _ COF may instruct both NSS _ SO _ F1 and NSS _ SO _ F2 to adjust execution of the respective self-optimization algorithms such that NSSI capacity is expanded to 150% of current capacity.

408. NSS _ SO _ F performs self-optimizing reconciliation.

In this step, NSS _ SO _ F performs self-optimizing reconciliation according to the indication in the received self-optimizing reconciliation message. Specifically, the execution of the self-optimization coordination solution may include a result of executing the self-optimization algorithm, may further include a result of not executing the self-optimization algorithm, and may further include a result of adjusting the execution of the self-optimization algorithm. For example, if the self-optimization result of NSS _ SO _ F1 and the self-optimization result of NSS _ SO _ F2 conflict and the self-optimization priority of NSS _ SO _ F1 is higher than that of NSS _ SO _ F2, NSS _ SO _ F1 may execute its self-optimization algorithm result according to the indication of NSS _ SO _ COF and NSS _ SO _ F2 may not execute its self-optimization algorithm result according to the indication of NSS _ SO _ COF. For another example, the self-optimization algorithm of NSS _ SO _ F1 results in expansion of the NSSI capacity to 120% of the current capacity, and the capacity cap is greater than 150% of the current capacity, and the self-optimization algorithm of NSS _ SO _ F2 results in expansion of the NSSI capacity to 200% of the current capacity, then in this step, NSS _ SO _ F1 and NSS _ SO _ F2 may adjust the execution of the respective self-optimization algorithms according to the NSS _ SO _ COF indication, such that the NSSI capacity is expanded to 150% of the current capacity.

409. And the NSS _ SO _ F reports a self-optimization coordination solution result to the NS _ SO _ COF.

In this step, NSS _ SO _ F reports the execution result to NS _ SO _ COF after performing self-optimization reconciliation. Optionally, if the NSS _ SO _ F does not execute its self-optimization algorithm result in step 408, the NSS _ SO _ F may not report to the NS _ SO _ COF in this step.

Optionally, after receiving the self-optimization coordination solution result reported by the NSS _ SO _ F, the NS _ SO _ COF may report the self-optimization coordination solution result to the operator.

Through the steps, the embodiment of the application can realize self-optimization coordination and solution when NSSI is shared by a plurality of NSIs and NSSI self-optimization caused by optimization strategies of different NSIs conflicts.

Fig. 5 shows another possible network slice self-optimization coordination architecture diagram, which corresponds to a scenario of network slice self-optimization coordination among NSSIs within one NSI. In this scenario, multiple NSSIs within an NSI have their own network slice self-optimization function, and the results from multiple NSS _ SO _ fs located on different NSSMFs for optimizing different NSSIs may affect each other, resulting in repeated optimization, such as repeated configuration of NSSI parameters. As shown in fig. 5, the first NSSMF of the first NSSI (referred to herein simply as "NSSMF 1") includes a first NSS _ SO _ F (referred to herein simply as "NSS _ SO _ F1"); the second NSSMF of the second NSSI (referred to herein as "NSSMF 2" for short) includes a second NSS _ SO _ F (referred to herein as "NSS _ SO _ F2" for short). Wherein NSSMF1 manages a first NSSI and NSSMF2 manages a second NSSI; NSS _ SO _ F1 is the function that the NSI uses to self-optimize the first NSSI; NSS _ SO _ F2 is the function that this NSI uses to self-optimize the second NSSI.

The network slice self-optimization coordination flow of the network slice self-optimization coordination framework shown in fig. 5 is similar to the flow diagram described in fig. 4, and is not described herein again. The main difference between the flow for this scenario and the flow of fig. 4 is that: in a scenario of network slice self-optimization coordination between NSSIs within an NSI, NSS _ SO _ F1 is located in NSSMF1 that manages a first NSSI, NSS _ SO _ F2 is located in NSSMF2 that manages a second NSSI, and the self-optimization policy obtained by NS _ SO _ COF is a self-optimization coordination policy between NSSIs under the NSI. Specific self-optimization coordination strategy in addition to the examples in the flow step of fig. 4, the self-optimization coordination strategy for different NSSIs may also include a self-optimization coordination strategy for different NSSIs, for example, when different NSS _ SO _ F self-optimization results may conflict and priorities of the NSS _ SO _ F are different, the optimization strategy of NS _ SO _ COF may instruct the NSS _ SO _ F to execute respective self-optimization algorithm results according to a priority order. Illustratively, NSS _ SO _ F1 has a higher priority than NSS _ SO _ F2, NSS _ SO _ COF may instruct NSS _ SO _ F1 to perform its self-optimization algorithm result to self-optimize the first NSSI first, and after NSS _ SO _ F1 completes the self-optimization of the first NSSI, NSS _ SO _ F2 then operates the self-optimization algorithm on the second NSSI and performs the self-optimization of the second NSSI.

Through the steps, the embodiment of the application can realize self-optimization coordination resolution when self-optimization of multiple NSSIs in one NSI generates conflict.

Fig. 6 shows a schematic diagram of yet another possible network slice self-optimization coordination architecture. This corresponds to a scenario of network slice self-optimization coordination between NSS _ SO _ F in one NSSI within one NSI. In this scenario, NSS _ SO _ F with different self-optimization objectives are located on one NSSMF, self-optimizing one NSSI within one NSI. Due to different optimization objectives of different NSS _ SO _ fs, different NSS _ SO _ fs may conflict with the optimization results. In addition, since different NSS _ SO _ F self-optimize the same NSSI, NSS _ SO _ F self-optimization coordination solution can be completed in the SSMF of one NSSI. As shown in fig. 6, the NSMF of the NSI includes NS _ SO _ COF; the NSSMF of the NSSI includes an NSS _ SO _ COF, wherein the NS _ SO _ COF is used to pass the self-optimization coordination policy to the NSS _ SO _ COF, and the NSS _ SO _ COF indicates that the self-optimization coordination solution of different NSS _ SO _ fs in its corresponding NSSI is completed.

With reference to fig. 6, fig. 7 is a schematic diagram illustrating another possible network slice self-optimization coordination flow provided by the embodiment of the present application. The process described in fig. 7 may be applied to coordinate self-optimization functions for multiple network slices in an NSSI within an NSI, and includes the following steps:

701. the NS _ SO _ COF obtains the self-optimizing conflict coordination strategy.

702. The NS _ SO _ COF sends a self-optimizing coordination policy to the NSs _ SO _ COF.

It should be understood that there are different self-optimizing coordination strategies for different NSSIs, NS _ SO _ COF. In this step, the NS _ SO _ COF sends to each of the NSs _ SO _ COFs of the at least one NSs _ SO _ COF an auto-optimization coordination policy associated with the NSs _ SO _ COF.

703. And the NSS _ SO _ COF performs self-optimization coordination according to a self-optimization coordination strategy.

In this step, NSS _ SO _ COF interacts with multiple NSS _ SO _ fs in NSSMF to which the NSS _ SO _ COF belongs, and network slice self-optimization coordination processing is realized. Specifically, the interaction between the NSS _ SO _ COF and the NSS _ SO _ fs in the NSSMF may refer to steps 402 to 409 in the foregoing embodiment, which is not repeated herein.

704. And the NSS _ SO _ COF reports a self-optimization coordination solution result to the NS _ SO _ COF.

In this step, the NSS _ SO _ COF reports the execution result to the NS _ SO _ COF after performing the self-optimization reconciliation.

Optionally, after receiving the self-optimization coordination solution result reported by the NSS _ SO _ COF, the NS _ SO _ COF may report the self-optimization coordination solution result to the operator.

Through the steps, the embodiment of the application can realize self-optimization coordination and solution when multiple NSS _ CO _ F self-optimizations with different optimization purposes in one NSSI in one NSI generate conflicts.

It should be understood that the names of the respective step execution entities involved in the above-described method embodiments of the present application are exemplary, and other names may be used in an actual network. For example, an entity having a network slice self-optimization coordination function may be referred to as a network slice self-optimization coordination function, a self-optimization coordinator, and the like, which is not limited in this embodiment of the present application. Similarly, the message names of the information interaction between the execution entities of the steps in the above method embodiments of the present application are also exemplary, and other message names may also be used in an actual network. For example, a message with configuration self-optimization coordination may be referred to as a self-optimization coordination configuration message, a self-optimization coordination indication message, and the like, which is not limited in this embodiment of the present application.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present patent application.

The present application further provides embodiments of apparatus for performing the steps and methods of the above-described method embodiments. It is noted that the device embodiments may be used in conjunction with the above-described methods, or may be used alone.

Fig. 8 is a schematic structural diagram of an NS _ SO _ COF according to an embodiment of the present disclosure. As shown in fig. 8, the NS _ SO _ COF 800 includes a processor 801, a memory 802, and a communication interface 803. The processor 801 is connected to the memory 802 and the communication interface 803, for example, the processor 801 may be connected to the memory 802 and the communication interface 803 through a bus. The NS _ SO _ COF in the embodiment of the present application may be located in the NSMF, may exist independently of the NSMF, or may be the NSMF.

The processor 801 is configured to support the NS _ SO _ COF to perform the corresponding functions in the above method. The Processor 801 may be a Central Processing Unit (CPU), a Network Processor (NP), a hardware chip, or any combination thereof. The hardware chip may be an Application-Specific Integrated Circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA), a General Array Logic (GAL), or any combination thereof.

The memory 802 is used for storing signaling and data that the NS _ SO _ COF needs to send and receiving signaling and data from the NSs _ SO _ COF and/or the NSs _ SO _ F, and the like. The Memory 802 may include a Volatile Memory (Volatile Memory), such as a Random-Access Memory (RAM); the Memory 802 may also include a Non-Volatile Memory (Non-Volatile Memory), such as a Read-Only Memory (ROM), a Flash Memory (Flash Memory), a Hard Disk Drive (Hard Disk Drive, HDD) or a Solid-State Drive (SSD); the memory 802 may also comprise a combination of the above-described types of memory.

The communication interface 803 is used for the NS _ SO _ COF to communicate with the NSs _ SO _ COF and/or the NSs _ SO _ F, and to transceive signaling and data involved in the above methods with the NSs _ SO _ COF and/or the NSs _ SO _ F.

The processor 801 may perform the following operations:

performing, by the communication interface 803, at least one of: sending a self-optimization coordination configuration message, receiving a self-optimization algorithm result, sending a self-optimization coordination solution message, receiving a self-optimization coordination solution result, and sending a self-optimization coordination strategy. Optionally, the processor 801 determines a self-optimization function and parameters that need to be coordinated, and the processor 801 receives a self-optimization coordination policy from an operator or SvMF through the communication interface 803, and sends a self-optimization coordination solution result to the operator. Please refer to the steps executed by the NS _ SO _ COF in the methods of fig. 3 to fig. 7.

Fig. 9 is a schematic structural diagram of another NS _ SO _ COF provided in the embodiment of the present application. As shown in fig. 9, the NS _ SO _ COF 900 includes a receiving module 901, a processing module 902, and a transmitting module 903. The NS _ SO _ COF in the embodiment of the present application may be located in the NSMF, may exist independently of the NSMF, or may be the NSMF.

The receiving module 901 is configured to receive a self-optimization algorithm result and a self-optimization coordination solution result sent by the NSS _ SO _ F, and receive a self-optimization coordination solution result sent by the NSS _ SO _ COF. Optionally, the receiving module 901 is configured to receive a self-optimization coordination policy sent by an operator or SvMF.

A processing module 902 for performing at least one of: sending a self-optimization coordination configuration message, receiving a self-optimization algorithm result, sending a self-optimization coordination solution message, receiving a self-optimization coordination solution result, and sending a self-optimization coordination strategy. Optionally, the processing module 902 determines a self-optimization function and parameters that need to be coordinated; the processing module 902 receives the self-optimization coordination policy from the operator or SvMF, and sends a self-optimization coordination solution result to the operator. Please refer to the steps executed by the NS _ SO _ COF in the methods of fig. 3 to fig. 7.

A sending module 903, configured to send a self-optimization coordination configuration message and a self-optimization coordination solution message to the NSS _ SO _ F, and send a self-optimization coordination policy to the NSS _ SO _ COF. Optionally, the receiving module 901 is configured to send the self-optimization coordination solution result to the operator.

Fig. 10 is a schematic structural diagram of an NSS _ SO _ COF according to an embodiment of the present disclosure. As shown in fig. 10, the network element NSS _ SO _ COF 1000 includes a processor 1001, a memory 1002, and a communication interface 1003. The processor 1001 is connected to the memory 1002 and the communication interface 1003, for example, the processor 1001 may be connected to the memory 1002 and the communication interface 1003 by a bus. The NSS _ SO _ COF in the embodiment of the present application may be located in the NSSMF, may exist independently of the NSSMF, and may also be the NSSMF.

The processor 1001 is configured to support NSS _ SO _ COF to perform corresponding functions in the above-described method. The Processor 1001 may be a Central Processing Unit (CPU), a Network Processor (NP), a hardware chip, or any combination thereof. The hardware chip may be an Application-Specific Integrated Circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA), a General Array Logic (GAL), or any combination thereof.

The memory 1002 is used for storing signaling and data that the NSS _ SO _ COF needs to send and receiving signaling and data from the NS _ SO _ COF, and the like. The Memory 1002 may include a Volatile Memory (Volatile Memory), such as a Random-Access Memory (RAM); the Memory 1002 may also include a Non-Volatile Memory (Non-Volatile Memory), such as a Read-Only Memory (ROM), a Flash Memory (Flash Memory), a Hard Disk Drive (Hard Disk Drive, HDD) or a Solid-State Drive (SSD); the memory 1002 may also comprise a combination of the above-described types of memory.

The communication interface 1003 is used for NSS _ SO _ COF and NS _ SO _ COF to communicate, and to receive and transmit signaling and data involved in the above method with the NS _ SO _ COF.

The processor 1001 may perform the following operations:

performing self-optimization coordination according to a self-optimization coordination strategy; the self-optimization coordination policy sent by the NS _ SO _ COF and the self-optimization coordination solution sent to the NS _ SO _ COF are received through the communication interface 1003. Please refer to the steps executed by the NSS _ SO _ COF in the method of fig. 3 to fig. 7.

Fig. 11 is a schematic structural diagram of another NSS _ SO _ COF provided in this embodiment of the present application. As shown in fig. 11, the NSS _ SO _ COF 1100 includes a receiving module 1101, a processing module 1102, and a sending module 1103. The NSS _ SO _ COF in the embodiment of the present application may be located in the NSSMF, may exist independently of the NSSMF, and may also be the NSSMF.

A receiving module 1101, configured to receive a self-optimization coordination policy sent by the NS _ SO _ COF.

A processing module 1102, configured to perform self-optimization coordination according to a self-optimization coordination policy; the self-optimization coordination strategy sent by the NS _ SO _ COF and the self-optimization coordination solution sent to the NS _ SO _ COF are received by the receiving module 1101. Please refer to the steps executed by the NSS _ SO _ COF in the method of fig. 3 to fig. 7.

A sending module 1103, configured to send the self-optimization coordination solution result to the NS _ SO _ COF.

Fig. 12 is a schematic structural diagram of NSS _ SO _ F according to an embodiment of the present disclosure. As shown in fig. 12, the NSS _ SO _ F1200 includes a processor 1201, a memory 1202, and a communication interface 1203. The processor 1201 is connected to the memory 1202 and the communication interface 1203, for example, the processor 1201 may be connected to the memory 1202 and the communication interface 1203 by a bus. The NSS _ SO _ F in the embodiment of the present application may be located in the NSSMF, may exist independently of the NSSMF, or may be the NSSMF.

The processor 1201 is configured to support NSS _ SO _ F to perform the corresponding functions in the above-described method. The Processor 1201 may be a Central Processing Unit (CPU), a Network Processor (NP), a hardware chip, or any combination thereof. The hardware chip may be an Application-Specific Integrated Circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA), a General Array Logic (GAL), or any combination thereof.

The memory 1202 is used for storing signaling and data that the NSS _ SO _ F needs to transmit and receiving signaling and data from the NS _ SO _ COF, and the like. The Memory 1202 may include a Volatile Memory (Volatile Memory), such as a Random-Access Memory (RAM); the Memory 1202 may also include a Non-Volatile Memory (Non-Volatile Memory), such as a Read-Only Memory (ROM), a Flash Memory (Flash Memory), a Hard Disk Drive (Hard Disk Drive, HDD) or a Solid-State Drive (SSD); memory 1202 may also comprise a combination of the above types of memory.

The communication interface 1203 is used for NSS _ SO _ F and NS _ SO _ COF to communicate with each other, and to receive and transmit signaling and data involved in the above method with the NS _ SO _ COF.

The processor 1201 may perform the following operations:

performing, by the communication interface 1203, at least one of: receiving a self-optimization coordination configuration message, running a self-optimization algorithm, sending a self-optimization algorithm result, receiving a self-optimization coordination solution message, executing a self-optimization coordination solution, and sending a self-optimization coordination solution result. Please refer to the steps executed by NSS _ SO _ F in the method of fig. 3 to 7.

Fig. 13 is a schematic structural diagram of another NSS _ SO _ F according to an embodiment of the present disclosure. As shown in fig. 13, the NSS _ SO _ F1300 includes a receiving module 1301, a processing module 1302, and a transmitting module 1303. The NSS _ SO _ F in the embodiment of the present application may be located in the NSSMF, may exist independently of the NSSMF, or may be the NSSMF.

A receiving module 1301, configured to receive a self-optimization coordination configuration message and a self-optimization coordination solution message sent by the NS _ SO _ COF.

A processing module 1302, configured to receive, through the receiving module 1301, a self-optimization coordination configuration message sent by the NS _ SO _ COF; running a self-optimization algorithm; sending the self-optimization algorithm result to the NS _ SO _ COF through the sending module 1303; receiving a self-optimization coordination solution message sent by the NS _ SO _ COF through the receiving module 1301; executing self-optimization coordination solution; the self-optimization coordination solution result is sent to the NS _ SO _ COF through the sending module 1303. Please refer to the steps executed by NSS _ SO _ F in the method of fig. 3 to 7.

And a sending module 1303, configured to send the self-optimization algorithm result and the self-optimization coordination solution result to the NS _ SO _ COF.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present patent application or a part of the technical solution that substantially contributes to the prior art may be embodied in the form of a software product stored in a storage medium and containing instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present patent application. And the aforementioned storage medium comprises: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present patent application shall be subject to the protection scope of the claims.

Claims

1. A network slice self-optimization coordination method is characterized by comprising the following steps: the network slice self-optimization coordination function sends a self-optimization coordination message to the network slice subnet self-optimization function, and the self-optimization coordination message is used for coordinating the self-optimization of the self-optimization functions of a plurality of network slice subnets in the network slice subnets;

the network slice self-optimization coordination function receives a self-optimization coordination solution result sent by the network slice subnet self-optimization function;

wherein the self-optimization coordination message comprises a self-optimization coordination configuration message or a self-optimization coordination solution message;

when the self-optimization coordination message comprises a self-optimization coordination configuration message, the self-optimization coordination configuration message is used for indicating the self-optimization function of the network slice subnet to report a self-optimization algorithm result to the network slice self-optimization coordination function before the self-optimization is executed, wherein the self-optimization coordination configuration message is used for indicating the self-optimization algorithm result not to be executed after the network slice subnet optimization function runs the self-optimization algorithm according to the condition of the self-optimized network slice subnet instance; when the self-optimization coordination message comprises a self-optimization coordination solution message, the self-optimization coordination solution message is used for indicating the self-optimization function of the network slice subnet to execute self-optimization coordination solution;

before the network slice self-optimization coordination function sends a self-optimization coordination message, the method further includes:

the network slice self-optimization coordination function obtains a self-optimization coordination strategy and determines a self-optimization function and parameters needing to be coordinated; wherein the content of the first and second substances,

the self-optimization coordination strategy comprises the following steps: self-optimization priorities among network slice examples, priorities of different self-optimization functions and self-optimization parameters when self-optimizing 1 network slice example, parameters which need to be detected and generate conflicts, and different parameters which can generate conflicts;

wherein the parameters causing the conflict comprise network slice instance capacity, and the different parameters which may cause the conflict comprise self-optimized mobility support and self-optimized delay.

2. The method of claim 1, wherein the network slice self-optimization coordination function, prior to sending a self-optimization coordination solution message, further comprises:

and the network slice self-optimization coordination function decides self-optimization coordination according to the self-optimization coordination strategy.

3. A network slice self-optimization coordination method is characterized by comprising the following steps: the network slice subnet self-optimization function receives a self-optimization coordination message sent by the network slice self-optimization coordination function;

the network slice subnet self-optimization function carries out self-optimization coordination processing according to the self-optimization coordination message;

the network slice subnet self-optimization function sends a self-optimization coordination processing result to the network slice self-optimization coordination function;

when the self-optimization coordination message comprises a self-optimization coordination configuration message, the self-optimization coordination configuration message is used for indicating the self-optimization function of the network slice subnet to report a self-optimization algorithm result to the network slice self-optimization coordination function before the self-optimization is executed; the self-optimization coordination configuration message is used for indicating that the self-optimization algorithm is not executed after the network slice subnet optimization function runs the self-optimization algorithm according to the condition of the self-optimized network slice subnet instance; when the self-optimization coordination message comprises a self-optimization coordination solution message, the self-optimization coordination solution message is used for indicating the self-optimization function of the network slice subnet to execute self-optimization coordination solution;

the network slice self-optimization coordination function is used for obtaining a self-optimization coordination strategy before sending a self-optimization coordination message and determining a self-optimization function and parameters needing to be coordinated;

the self-optimization coordination strategy comprises the following steps: self-optimization priorities among network slice examples, priorities of different self-optimization functions and self-optimization parameters when self-optimizing 1 network slice example, parameters which need to be detected and generate conflicts, and different parameters which can generate conflicts; wherein the parameters causing the conflict comprise network slice instance capacity, and the different parameters which may cause the conflict comprise self-optimized mobility support and self-optimized delay.

4. The method of claim 3, wherein the self-optimization coordination process comprises running a self-optimization algorithm and/or performing a self-optimization coordination solution.

5. The method according to any one of claims 3 to 4, wherein the self-optimization function of the network slice subnet runs a self-optimization algorithm after receiving the self-optimization coordination configuration message, and reports the result of the self-optimization algorithm to the self-optimization coordination function of the network slice.

6. The method according to any one of claims 3 to 4, wherein the self-optimization function of the network slice subnet executes self-optimization coordination solution after receiving the self-optimization coordination solution message, and reports the result of the self-optimization coordination solution to the self-optimization coordination function of the network slice.

7. A network slice self-optimization coordination function, comprising:

the sending module is used for sending a self-optimization coordination message to a self-optimization function of the network slice subnet;

the processing module is used for configuring the content of a self-optimization coordination message, and the self-optimization coordination message is used for coordinating the self-optimization of the self-optimization functions of a plurality of network slice subnets in a network slice subnet; and

the receiving module is used for receiving a self-optimization coordination solution result sent by the self-optimization function of the network slice subnet;

wherein the self-optimization coordination message comprises a self-optimization coordination configuration message and/or a self-optimization coordination solution message;

before sending the self-optimization coordination message, the network slice self-optimization coordination function further includes: the network slice self-optimization coordination function obtains a self-optimization coordination strategy and determines a self-optimization function and parameters needing to be coordinated;

wherein the content of the first and second substances,

8. The network slice self-optimizing coordination function of claim 7, wherein said network slice self-optimizing coordination function further comprises, prior to sending a self-optimizing coordination resolution message:

9. A network slice subnet self-optimization function comprising:

the receiving module is used for receiving a self-optimization coordination message sent by a network slice self-optimization coordination function;

the processing module is used for carrying out self-optimization coordination processing according to the self-optimization coordination message; and

the sending module is used for sending a self-optimization coordination processing result to the network slice self-optimization coordination function;

10. The network slice subnet self-optimization function of claim 9, wherein the self-optimization coordination process comprises running a self-optimization algorithm and/or performing a self-optimization coordination solution.

11. The network slice subnet self-optimization function of any of claims 9 to 10, wherein the network slice subnet self-optimization function runs a self-optimization algorithm after receiving the self-optimization coordination configuration message and reports a result of the self-optimization algorithm to the network slice self-optimization coordination function.

12. The network slice subnet self-optimization function of any of claims 9 to 10, wherein the network slice subnet self-optimization function executes a self-optimization coordination solution after receiving the self-optimization coordination solution message, and reports a result of the self-optimization coordination solution to the network slice self-optimization coordination function.