CN108769100A - A kind of implementation method and its device based on kubernetes number of containers elastic telescopics - Google Patents

Abstract

This application provides a method and device for implementing elastic scaling based on the number of kubernetes containers, including: obtaining the number of visits of different services of the container cluster; obtaining the load status of each POD of the container cluster, and determining each The maximum number of service visits carried by POD under the service; determine the threshold of the amount of POD different service visits that can be processed. When the index of the number of service visits in the container cluster reaches the set threshold, a dynamic adjustment mechanism is triggered to adjust the number of containers. Through monitoring Calculate the number of PODs that need to be adjusted according to the number of business requests and the overall load of the PODs that handle the business, and then dynamically adjust the number of PODs according to kubernetes. , closing redundant PODs saves server resources, improves the efficiency and stability of container operation, and enhances the efficiency of resource scheduling in the Kubernetes-based container cluster management system.

Description

A method and device for implementing elastic scaling based on the number of kubernetes containers

technical field

The present invention relates to the technical field of cloud computing, in particular to a method and device for implementing elastic scaling based on the number of kubernetes containers.

Background technique

Kubernetes is a container-based cluster management system. It mainly includes components such as Service, ReplicationController, and Pod. It is built on containers such as Docker. It provides functions such as application deployment, maintenance, and expansion mechanisms. Using Kubernetes can easily manage containers running across machines. application. Deployment is the core management process of kubernetes. It is responsible for managing the entire life cycle of POD (another name for containers in the kubernetes system). The number of PODs can be customized in the definition script of deployment. Through the automatic detection mechanism, the number of PODs in the kubernetes system is consistent. maintained at a defined quantity. When a POD is abnormal and cannot be used, a new POD will be created to replace the abnormal POD to continue working; when the abnormal POD returns to normal, the redundant POD will be killed. The automatic detection mechanism of the deploment's definition script only maintains the number of PODs through the numbers defined in the script, and cannot dynamically adjust the number of PODs according to the fluctuation of business pressure.

Therefore, there is an urgent need for an implementation method and device based on elastic scaling of the number of kubernetes containers, which can dynamically adjust the number of PODs according to the number of monitoring service requests and the overall load of the service PODs.

Contents of the invention

Aiming at the deficiencies of the prior art, the present invention provides a method and device based on elastic expansion and contraction of the number of kubernetes containers, which can monitor the number of business requests and the overall load of PODs for processing business, dynamically adjust the number of PODs, and when the business peak period, Rapidly increase the number of PODs to achieve the effect of diversion and decompression; when the business is calm, close redundant PODs to save server resources.

In the first aspect, an implementation method for elastic scaling based on the number of kubernetes containers is provided, including:

Obtain the number of visits of different services of the container cluster;

Obtain the load status of each POD in the container cluster, and determine the maximum number of service accesses carried by the POD under each service according to the load status of each POD;

Determine the threshold value of the processable amount of POD different service accesses. When the index of the number of service accesses in the container cluster reaches the set threshold, the dynamic adjustment mechanism is triggered to adjust the number of containers (add or delete containers).

Wherein, the acquisition of the number of visits of different services of the container cluster includes accessing corresponding services on different servers through a load balancer method, and the number of visits of a certain service may be obtained through an additional balancer.

Wherein, the acquiring the load status of each POD of the container cluster, and determining the maximum number of service visits carried by the POD under each service according to the load status of each POD include:

Obtain the load status of each POD through the kubelet component on the host where the POD is located, such as CPU usage and memory usage, and obtain the load status of each service POD through label classification and statistics of the average CPU and memory usage of the POD, and then determine The maximum number of service accesses carried by the POD under each service.

Among them, determine the threshold value of the processable access volume of different POD services. When the index of service access volume of the container cluster reaches the set threshold, a dynamic adjustment mechanism is triggered to adjust the number of containers (addition or deletion of containers), including:

Determine the upper and lower limits of the POD service access throughput threshold based on the maximum CPU usage or maximum memory usage when the container is running.

Among them, determine the threshold value of the processable access volume of different POD services. When the index of service access volume of the container cluster reaches the set threshold, a dynamic adjustment mechanism is triggered to adjust the number of containers, including:

According to the access quantity of different services of the obtained container cluster and the determined threshold of the POD different service access throughput, it is judged whether the service access volume of the container cluster is greater than the upper limit of the POD service access throughput threshold; if so, Then send expansion commands to the deployment component to increase the number of PODs.

Among them, determine the threshold value of the processable access volume of different POD services. When the index of service access volume of the container cluster reaches the set threshold, a dynamic adjustment mechanism is triggered to adjust the number of containers, including:

According to the access quantity of different services of the obtained container cluster and the determined threshold of the POD different service access throughput, it is judged whether the service access volume of the container cluster is less than the lower limit of the POD service access throughput threshold; if so, Then send a shrink command to the deployment component to reduce the number of PODs.

In the second aspect, an implementation device for elastic scaling based on the number of kubernetes containers is provided, including:

An acquisition unit, the acquisition unit is used to acquire the number of visits of different services of the container cluster; the acquisition unit is also used to acquire the load situation of each POD of the container cluster;

A determination unit, the determination unit is used to determine the maximum number of service visits carried by the POD under each service according to the load situation of each POD; the determination unit is also used to determine the threshold value of the processable amount of POD different service visits;

The elastic scaling management unit triggers a dynamic adjustment mechanism to adjust the number of containers (adding or deleting containers) after determining that the index of service visits of the container cluster reaches a set threshold.

Wherein, the obtaining unit is used to obtain corresponding services on different servers through a load balancer method, and the number of visits to a certain service can be obtained through an additional balancer.

Wherein, the determination unit is used to obtain the load status of each POD according to the kubelet component on the host machine where the POD is located, such as the usage of CPU and the usage of memory, and obtain the average value of the CPU and memory usage of the POD through label classification and statistics. The load of the service POD, and then determine the maximum number of service accesses carried by the POD under each service.

Wherein, the determination unit is configured to determine the upper limit and lower limit of the POD service access throughput threshold according to the maximum CPU usage or the maximum memory usage when the container is running.

Wherein, the elastic scaling management unit includes:

The first judging unit judges whether the service access volume of the container cluster is greater than the upper limit of the POD service access throughput threshold according to the acquired access quantity of different services of the container cluster and the determined threshold value of the processable amount of different service accesses of the POD ; If so, send an expansion command to the deployment component to increase the number of PODs;

Wherein, the elastic scaling management unit also includes:

The second judging unit is configured to judge whether the service access volume of the container cluster is less than the POD service access processable amount according to the obtained access quantity of different services of the container cluster and the determined threshold value of the processable amount of different service accesses of the POD The lower limit of the volume threshold; if so, send a shrink command to the deployment component to reduce the number of PODs.

In a third aspect, there is provided a controlled terminal, including: a processor; a memory for storing execution instructions of the processor; wherein, the processor is configured as the first aspect or any possible implementation of the first aspect .

In a fourth aspect, a computer storage medium is provided, and instructions are stored in the computer-readable storage medium, and when run on a computer, the computer is made to execute the methods described in the above aspects.

In a fifth aspect, a computer program product containing instructions is provided, and when it is run on a computer, it causes the computer to execute the methods described in the above aspects.

Therefore, the present invention calculates the number of PODs that need to be adjusted by monitoring the number of business requests and the overall load of the processing business PODs, and then dynamically adjusts the number of PODs according to kubernetes. Function; when the business is calm, closing redundant PODs saves server resources, improves the efficiency and stability of container operation, and enhances the efficiency of resource scheduling in the Kubernetes-based container cluster management system. .

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, In other words, other drawings can also be obtained from these drawings on the premise of not paying creative work.

Fig. 1 is a schematic flowchart of a method according to an embodiment of the present application.

Fig. 2 is a schematic flowchart of a method according to another embodiment of the present application.

Fig. 3 is a schematic block diagram of a device according to an embodiment of the present application.

FIG. 4 is a schematic structural diagram of a controlled terminal provided by an embodiment of the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention. In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

Key terms appearing in this application are explained below.

Fig. 1 is a schematic flowchart of a method according to an embodiment of the present application.

As shown in Figure 1, this solution is implemented based on the kubernetes system. The core idea is divided into two parts: the first part is the monitoring of service visits and the overall performance (cpu, memory) of the POD that provides the service; the second part According to the monitoring structure of service visits and Pod performance, adjust the number of PODs defined in the deployment script, realize the kubernetes automatic management mechanism to dynamically adjust the number of PODs, and then realize the elastic scaling function of PODs.

Fig. 2 is a schematic flowchart of a method according to an embodiment of the present application. Wherein, the execution subject in Figure 2 may be a device implemented based on elastic scaling of the number of kubernetes containers.

As shown in Figure 2, the method 200 includes:

Step 210, obtaining the number of visits of different services of the container cluster;

Step 220, obtain the load of each POD of the container cluster, and determine the maximum service access capacity of the POD under each service according to the load of each POD;

Step 230, determine the threshold value of the processable amount of POD different service accesses, and when the index of the number of service accesses in the container cluster reaches the set threshold, a dynamic adjustment mechanism is triggered to adjust the number of containers (add or delete containers).

Therefore, the embodiment of the present application can calculate the number of PODs that need to be adjusted by monitoring the number of business requests and the overall load of the PODs that process the business, and then dynamically adjust the number of PODs according to kubernetes, and quickly increase the number of PODs during peak business periods to achieve traffic distribution The role of decompression; when the business is calm, shut down redundant PODs to save server resources. The present invention is an upgrade to the kubernetes system. It is aimed at e-commerce enterprises with large ups and downs in service visits, such as some shopping e-commerce websites. During the promotion stage, the number of visits to the website will explode. Across systems, if you directly set up a large number of PODs for peak periods, resources will be wasted during off-peak periods.

Optionally, as an embodiment of the present application, the acquiring the number of visits of different services of the container cluster includes: accessing corresponding services on different servers through a load balancer method, and the number of visits to a service can be obtained through additional balancing device to obtain.

Optionally, as an embodiment of the present application, the acquiring the load status of each POD in the container cluster, and determining the maximum number of service visits carried by the POD under each service according to the load status of each POD include: through the host machine where the POD is located Get the load status of each POD through the kubelet component, such as CPU usage and memory usage, and obtain the load status of each service POD by counting the average CPU and memory usage of the POD by label classification, and then determine the maximum load capacity of the POD under each service of service visits.

Optionally, as an embodiment of the present application, the threshold value of the processable amount of POD different service access is determined, and when the index of the service access amount of the container cluster reaches the set threshold, a dynamic adjustment mechanism is triggered to adjust the number of containers (new Adding or deleting containers) includes: determining the upper limit and lower limit of the POD service access processable threshold according to the maximum CPU usage or maximum memory usage when the container is running.

Optionally, as an embodiment of the present application, the threshold value of the access capacity of different services of the POD is determined, and when the index of service access volume of the container cluster reaches the set threshold, triggering a dynamic adjustment mechanism to adjust the number of containers includes: According to the number of visits of different services of the obtained container cluster and the determined threshold value of the POD different service visits that can be handled, it is judged whether the service visits of the container cluster are greater than the upper limit of the POD service visits throughput threshold; The deployment component sends expansion commands to increase the number of PODs.

Optionally, as an embodiment of the present application, the threshold value of the access capacity of different services of the POD is determined, and when the index of service access volume of the container cluster reaches the set threshold, triggering a dynamic adjustment mechanism to adjust the number of containers includes: According to the access quantity of different services of the obtained container cluster and the determined threshold of the POD different service access throughput, it is judged whether the service access volume of the container cluster is less than the lower limit of the POD service access throughput threshold; if so, Then send a shrink command to the deployment component to reduce the number of PODs.

The specific method is: when the maximum number of service visits carried by a POD for a certain service is 100, and there are now 10 PODs processing this service request, set the upper limit of the dynamic adjustment threshold to 90%. When the external requests reach 900, you need to Trigger the dynamic adjustment mechanism, adjust the number of PODs defined in the deployment, and increase the number of PODs to evacuate the access pressure of other PODs; the number that needs to be increased is calculated by the formula:

Increase the number of PODs = (external visits – each POD can handle * 70% * existing POD) / 70;

Set the dynamic adjustment lower limit to 50%. Assume that the processing capacity of each POD is still 100, and there are already 10 PODs. When the external request volume is lower than 500, the dynamic adjustment mechanism will be triggered, and the number defined in the delployment will be reset to reduce The number of PODs, to avoid waste of resources, the number that needs to be reduced is calculated by the formula:

Reduce the number of PODs = (each POD can handle * 70% * existing POD - external visits) / 70

Fig. 3 shows a schematic block diagram of an apparatus according to an embodiment of the present application.

As shown in Figure 3, the device 300 includes:

The obtaining unit 310, the obtaining unit is used to obtain the number of visits of different services of the container cluster; the obtaining unit is also used to obtain the load situation of each POD of the container cluster,

Determination unit 320, the determination unit is used to determine the maximum number of service visits carried by PODs under each service according to the load situation of each POD; the determination unit is also used to determine the threshold value of the processable amount of POD different service visits

The elastic scaling management unit 330 triggers a dynamic adjustment mechanism to adjust the number of containers (adding or deleting containers) after determining that the index of the service access volume of the container cluster reaches a set threshold.

Optionally, as an embodiment of the present application, the obtaining unit is configured to obtain corresponding services on different servers through a load balancer method, and the access quantity of a certain service may be obtained through an additional balancer.

Optionally, as an embodiment of the present application, the determination unit is used to obtain the load status of each POD according to the kubelet component on the host machine where the POD is located, such as CPU usage and memory usage, and classify and count the POD by label The average CPU and memory usage is used to obtain the load of each service POD, and then determine the maximum number of service accesses carried by the POD under each service.

Optionally, as an embodiment of the present application, the determining unit is configured to determine an upper limit and a lower limit of a POD service access throughput threshold according to a maximum CPU usage or a maximum memory usage when the container is running.

Optionally, as an embodiment of the present application, the elastic scaling management unit includes:

The first judging unit is configured to judge whether the service access volume of the container cluster is greater than the POD service access throughput threshold according to the acquired access quantity of different services of the container cluster and the determined threshold value of the POD different service access throughput. upper limit; if so, send expansion commands to the deployment component to increase the number of PODs;

Optionally, as an embodiment of the present application, the elastic scaling management unit further includes:

The second judging unit is configured to judge whether the service access volume of the container cluster is less than the POD service access processable amount according to the obtained access quantity of different services of the container cluster and the determined threshold value of the processable amount of different service accesses of the POD The lower limit of the volume threshold; if so, send a shrink command to the deployment component to reduce the number of PODs.

The specific method is: when the maximum number of service visits carried by a POD for a certain service is 100, and there are now 10 PODs processing this service request, set the upper limit of the dynamic adjustment threshold to 90%, and when the external requests reach 900, the above The first judging unit of the elastic scaling management unit makes a judgment and triggers a dynamic adjustment mechanism to adjust the number of PODs defined in the deployment and increase the number of PODs to evacuate the access pressure of other PODs; the number to be increased is calculated by the formula:

Increase the number of PODs = (external visits – each POD can handle * 70% * existing POD) / 70;

Set the dynamic adjustment lower limit to 50%. Assume that the processing capacity of each POD is still 100, and there are already 10 PODs. When the external request volume is lower than 500, the second judgment unit of the elastic scaling management unit judges and triggers The dynamic adjustment mechanism resets the quantity defined in the delployment, reduces the number of PODs, and avoids waste of resources. The quantity to be reduced is calculated by the formula:

Reduce the number of PODs = (each POD can handle * 70% * existing POD - external visits) / 70

FIG. 4 is a schematic structural diagram of a controlled terminal 300 provided by an embodiment of the present invention. The controlled terminal 300 can be used to implement the method for implementing elastic scaling based on the number of kubernetes containers provided in FIG. 1 of the embodiment of the present application.

Wherein, the controlled terminal 400 may include: a processor 410 , a memory 420 and a communication unit 430 . These components communicate through one or more buses. Those skilled in the art can understand that the structure of the server shown in the figure does not constitute a limitation to the present application. It can be a bus structure, a star structure, or a More or fewer components than shown, or combinations of certain components, or different arrangements of components may be included.

Wherein, the memory 420 can be used to store the execution instructions of the processor 410, and the memory 420 can be implemented by any type of volatile or non-volatile storage device or their combination, such as static random access memory (SRAM), electronic Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Magnetic Disk or Optical Disk . When the execution instructions in the memory 420 are executed by the processor 410, the terminal 400 is enabled to perform some or all of the steps in the following above-mentioned method embodiments.

The processor 410 is the control center of the storage device, using various interfaces and lines to connect various parts of the entire electronic device, by running or executing software programs and/or modules stored in the memory 420, and calling data stored in the memory, To perform various functions of the electronic device and/or process data. The processor may be composed of an integrated circuit (Integrated Circuit, IC for short), for example, may be composed of a single packaged IC, or may be composed of multiple packaged ICs connected with the same function or different functions. For example, the processor 410 may only include a central processing unit (Central Processing Unit, CPU for short). In the embodiments of the present application, the CPU may be a single computing core, or may include multiple computing cores.

The communication unit 430 is configured to establish a communication channel, so that the storage device can communicate with other devices. Receive user data sent by other devices or send user data to other devices.

Those of ordinary skill in the art can realize that, in combination with the various method steps and units described in the embodiments disclosed herein, they can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the possibility of hardware and software For interchangeability, in the above description, the steps and components of each embodiment have been generally described according to their functions. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Those of ordinary skill in the art may use different methods to implement the described functions for each particular application, but such implementation should not be regarded as exceeding the scope of the present invention.

The methods or steps described in connection with the embodiments disclosed herein may be implemented by hardware, software programs executed by a processor, or a combination of both. The software program can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other Any other known storage medium.

For the same and similar parts among the various embodiments in this specification, please refer to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for relevant details, refer to the description in the method embodiment.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods may be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.

Although the present invention has been described in detail in conjunction with preferred embodiments with reference to the accompanying drawings, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, those skilled in the art can make various equivalent modifications or replacements to the embodiments of the present invention, and these modifications or replacements should be within the scope of the present invention/any Those skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention, and all should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims (10)

1. a kind of implementation method based on kubernetes elastic telescopic number of containers, which is characterized in that including：

Obtain the access number of the different services of container cluster；

The loading condition for obtaining each POD of container cluster, determines that POD is most under each service according to the loading condition of each POD The service access quantity of carrying；

Determine POD differences service access can treating capacity threshold values, when the index of the service access quantity of container cluster reaches setting After threshold value, then triggers dynamic adjustment mechanism and number of containers is adjusted.

2. according to the method described in claim 1, it is characterized in that, the access number of the different services for obtaining container cluster Including：

By the corresponding with service in load equalizer method to different server, for the access number of some service, Ke Yitong Cross additional equalizer acquisition.

3. method according to claim 1 or 2, which is characterized in that the loading condition for obtaining each POD of container cluster, Determine that the service access quantity that POD is at most carried under each service includes according to the loading condition of each POD：

The loading condition of each POD, such as the usage amount of CPU, memory are obtained by kubelet components on the host where POD Usage amount, by labeling count POD CPU, memory usage amount average value obtain it is each service POD loading condition, into And determine the service access quantity that POD is at most carried under each service.

4. according to the method described in claim 3, it is characterized in that, determine POD differences service access can treating capacity threshold values, when After the index of the service access amount of container cluster reaches given threshold, then triggers dynamic adjustment mechanism and number of containers is adjusted Including：

According to the access numbers of the different services of the container cluster of acquisition and the POD differences service access of determination can treating capacity valve Value, judge the container cluster service access amount whether be more than POD service access can treating capacity threshold value the upper limit；If so, Dilatation instruction, which is sent, to deployment components increases POD quantity.

5. according to the method described in claim 3, it is characterized in that, determine POD differences service access can treating capacity threshold values, when After the index of the service access amount of container cluster reaches given threshold, then triggers dynamic adjustment mechanism and number of containers is adjusted Including：

According to the access numbers of the different services of the container cluster of acquisition and the POD differences service access of determination can treating capacity valve Value, judges whether the service access amount of the container cluster is less than corresponding second metrics-thresholds in the elastic telescopic strategy； If so, sending capacity reducing instruction to deployment components reduces POD quantity.

6. a kind of realization device based on kubernetes number of containers elastic telescopics, which is characterized in that including：

Acquiring unit, the acquiring unit are used to obtain the access number of the different services of container cluster；The acquiring unit is also Loading condition for obtaining each POD of container cluster；

Determination unit, the determination unit are used to determine that POD is at most carried under each service according to the loading condition of each POD Service access quantity；The determination unit be additionally operable to determine POD differences service access can treating capacity threshold values；

Elastic telescopic manages unit, and the index of service access amount of the elastic telescopic management unit when judgement container cluster reaches After given threshold, triggering dynamic adjustment mechanism is adjusted number of containers.

7. device according to claim 6, which is characterized in that the acquiring unit is specifically used for：

By the corresponding with service in load equalizer method to different server, for the access number of some service, Ke Yitong Cross additional equalizer acquisition.

8. device according to claim 6, which is characterized in that the detection unit is specifically used for：

The loading condition of each POD, such as the usage amount of CPU, memory are obtained according to kubelet components on the host where POD Usage amount, by labeling count POD CPU, memory usage amount average value obtain it is each service POD loading condition, into And determine the service access quantity that POD is at most carried under each service.

9. according to claim 6-8 any one of them devices, which is characterized in that the elastic telescopic manages unit and includes：

First judging unit, for being taken according to the different access numbers serviced of container cluster and the POD differences of determination of acquisition Business access can treating capacity threshold values, judge whether the service access amount of the container cluster can treating capacity more than POD service access The upper limit of threshold value；If so, sending dilatation instruction to deployment components increases POD quantity；

Second judgment unit, for being taken according to the different access numbers serviced of container cluster and the POD differences of determination of acquisition Business access can treating capacity threshold values, judge the container cluster service access amount whether be less than the POD service access can locate The lower limit of reason amount threshold value；If so, sending capacity reducing instruction to deployment components reduces POD quantity.

10. a kind of controlled terminal, which is characterized in that including：

Processor；

The memory executed instruction for storing processor；

Wherein, the processor is configured as perform claim and requires 1-4 any one of them methods.