CN113535402A - Load balancing processing method and device based on 5G MEC and electronic equipment - Google Patents
Load balancing processing method and device based on 5G MEC and electronic equipment Download PDFInfo
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Abstract
The invention discloses a load balancing processing method and device based on 5G MEC and electronic equipment. Wherein, the method comprises the following steps: receiving a request message, wherein the request message is used for requesting to process a predetermined service; sending the request message to a load balancer, wherein the load balancer is created in a User Port Function (UPF) network element in advance; and selecting an application server through the load balancer to process the preset service. The invention solves the technical problems of high cost, poor stability and lower performance in the process of realizing load balancing in the related technology.
Description
Technical Field
The invention relates to the field of communication, in particular to a load balancing processing method and device based on 5G MEC and electronic equipment.
Background
In a scene that an internet of things terminal is large in scale, multiple in resource types and multiple in task requests, a problem to be faced by an "MEC (Multi-Access Edge Computing) Edge cloud" is how to schedule virtual machine resources to improve the utilization rate of physical machine resources and reduce the phenomenon of too high or too low load. In the related art, since there is no load balancing function in the standard functions of the UPF at present, there are two types of common implementation methods: (1) the hardware is realized directly through an intelligent switch, the processing capacity of the hardware load balancer is strong, and the hardware load balancer is irrelevant to a system, so that the hardware load balancer is more suitable for scenes of batch equipment, large-scale access and simple application; (2) the software implementation and the load balancer based on the system and the application can better batch loads according to the conditions of the system and the application, and are suitable for complex service scenes. However, when the above method is used for implementation, the operation and maintenance cost is high, and the load balancing system is heavy in task and performance is reduced.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a load balancing processing method and device based on 5G MEC and electronic equipment, and aims to at least solve the technical problems of high cost, poor stability and lower performance in the process of realizing load balancing in the related technology.
According to an aspect of the embodiments of the present invention, there is provided a load balancing processing method, including: receiving a request message, wherein the request message is used for requesting to process a predetermined service; sending the request message to a load balancer, wherein the load balancer is created in a User Port Function (UPF) network element in advance; and selecting an application server to process the predetermined service through the load balancer.
Optionally, before the sending the request message to the load balancer, the method further includes: selecting the UPF network element for creating the load balancer through a scheduler; acquiring logic structure information for creating the load balancer; and creating the load balancer in the selected UPF network element based on the logic structure information.
Optionally, the creating the load balancer in the selected UPF network element based on the logical structure information includes: sending a creation request message to a driver through a proxy network element based on a message queue, wherein the message queue comprises one or more creation request messages for requesting to create a load balancer; creating, by the driver, the load balancer in the selected UPF network element based on the logical structure information.
Optionally, the creating the load balancer in the selected UPF network element based on the logical structure information includes: and under the condition that a plurality of selected UPF network elements exist, creating the load balancer in batches on the selected plurality of UPF network elements based on the logic structure information.
Optionally, the selecting, by the load balancer, an application server to process the predetermined service includes: determining a load balancing pool for processing the predetermined service through a listening port designated by the load balancer, wherein the load balancing pool comprises one or more application servers; selecting a target application server from one or more application servers included in the load balancing pool; and processing the predetermined service by adopting the target application server.
Optionally, selecting a target application server from one or more application servers included in the load balancing pool includes: detecting a status of the one or more application servers included in the load balancing pool; deleting the abnormal application server from the load balancing pool under the condition that the abnormal application server is detected to obtain the load balancing pool in a normal state; and selecting a target application server from the load balancing pool in the normal state.
Optionally, the load balancing processing method is applied to an OpenStack system.
According to another aspect of the embodiments of the present invention, there is provided a load balancing processing apparatus, including: a receiving module, configured to receive a request message, where the request message is used to request processing of a predetermined service; a sending module, configured to send the request message to a load balancer, where the load balancer is created in a user port function UPF network element in advance; and the processing module is used for selecting an application server to process the predetermined service through the load balancer.
According to another aspect of an embodiment of the present invention, there is provided an electronic apparatus including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement any of the load balancing processing methods.
According to another aspect of the embodiments of the present invention, there is provided a computer-readable storage medium, wherein instructions of the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform any one of the load balancing processing methods.
In the embodiment of the invention, the request information for requesting to process the predetermined service is sent to the load balancer, and the complex balancer selects the corresponding application server to process the service, so that the purpose of realizing the predetermined service under the condition of load balancing is achieved, the technical effect of processing the predetermined service in a targeted manner is realized, and the technical problems of high cost, poor stability and lower performance in the process of realizing the load balancing in the related technology are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flowchart of a load balancing processing method according to an embodiment of the present invention;
fig. 2 is a system topology structure diagram in a load balancing processing method according to an alternative embodiment of the present invention;
fig. 3 is a system logic structure diagram in the load balancing processing method according to the alternative embodiment of the present invention;
FIG. 4 is a diagram of a load balancing service technology implementation architecture in accordance with an alternative embodiment of the present invention;
fig. 5 is a block diagram of a load balancing processing apparatus according to an embodiment of the present invention;
fig. 6 is a block diagram illustrating a structure of a terminal according to an exemplary embodiment.
Detailed Description
In accordance with an embodiment of the present invention, there is provided an embodiment of a load balancing processing method, it should be noted that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that herein.
Fig. 1 is a load balancing processing method according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, receiving a request message, wherein the request message is used for requesting to process a predetermined service;
step S104, sending the request message to a load balancer, wherein the load balancer is created in a User Port Function (UPF) network element in advance;
and step S106, selecting an application server through the load balancer to process the preset service.
Through the steps, the request information for requesting processing of the preset service is sent to the load balancer, and the complex balancer selects the corresponding application server to process the service, so that the purpose of realizing load balancing of the preset service in a service providing mode is achieved, the technical effects of realizing the load balancing target flexibly, efficiently and at low cost are achieved, and the technical problems of high cost, poor stability and low performance in the process of realizing load balancing in the related technology are solved.
The load balancing processing method can be applied to an OpenStack system. The method can be applied to an open-source cloud computing management platform system, has strong controllability, can meet various service requirements, and has the advantages of strong compatibility, strong expansibility, high flexibility and the like.
As an alternative embodiment, a request message is received, wherein the request message is used to request processing of a predetermined service. The request information may be received in many ways, for example, the request information may be received through an access network, and in particular, may be received through a radio access network. In addition, the predetermined service requested to be processed can be various, can be a service function realized in various modes, can be based on a service scene applied by a mobile phone terminal, and can also be based on a service application scene of the internet of things, so that the requirements of personal communication, game entertainment and the like can be met, and the application requirements of intelligent transportation, unmanned driving, intelligent home, intelligent factories and the like can also be met.
As an alternative embodiment, the request message is sent to the load balancer, where the load balancer is created in a User Port Function (UPF) network element in advance. The received request information requesting for processing the predetermined service is sent to the load balancer to execute the operation, wherein the load balancer distributes the predetermined service contained in the request information to a plurality of execution operation units to execute, and the predetermined service is completed together. The method can be used for distributing load in a plurality of resources, namely a plurality of execution operation units, so as to optimize resource utilization and prevent overload, and can also be used for solving the problems of large flow, high concurrency and high availability. The load balancing service is deployed and maintained in an automatic operation and maintenance mode by processing the predetermined service through the load balancing device, so that the management and deployment flexibility of the load balancing device is improved, the operation and maintenance cost is reduced, the network data processing capacity is enhanced, and the availability and flexibility of the network are improved.
As an alternative embodiment, before sending the request message to the load balancer, the method further includes: selecting a UPF network element for creating a load balancer through a scheduler; acquiring logic structure information for creating a load balancer; and creating a load balancer in the selected UPF network element based on the logic structure information. That is, the load balancer is created in the UPF network element based on certain logical structure information, that is, it can be implemented based on a virtual machine, that is, it does not need hardware facilities to implement, because no hardware facilities are used, but open source software is run in the UPF network element to implement the function of load balancing, the effect of load balancing is achieved, it is not necessary to use redundancy and tedious design for improving stability, and the hardware facilities are expensive, which increases cost, so that it can implement the effect of load balancing by creating the load balancer through the UPF network element, which can reduce cost and improve flexibility.
As an alternative embodiment, creating a load balancer in the selected UPF network element based on the logical structure information includes: sending a creating request message to a driver through a proxy network element based on a message queue, wherein the message queue comprises one or more creating request messages for requesting to create a load balancer; and creating a load balancer in the selected UPF network element through the driver based on the logic structure information. Before the load balancer is created in the selected UPF network element based on the logical structure information, the scheduler is responsible for selecting which UPF network element to create the load balancer, and sends the related information of the UPF network element to the proxy network element, and sends the created request information to the driver through the proxy network element. Specifically, the processing may be performed by a plug-in module (where the plug-in module is a service provided as referred to above), for example, the relevant information of the UPF network element is returned to the plug-in module, and the plug-in module sends the message to the proxy network element through the message queue. At this point, the message queue is the bridge for communication between the plug-in module and the proxy network element. And after receiving the creation request message, the proxy network element sends the creation request message to a driver, and starts the UPF network element to create a load balancer.
It should be noted that, creating a load balancer in the selected UPF network element based on the logical structure information includes: and in the case that the number of the selected UPF network elements is multiple, creating load balancers in batches in the selected multiple UPF network elements based on the logical structure information. The load balancing service operates in a UPF network element, can be deployed in batch to form a load balancer cluster, improves the stability and performance of the system, and is convenient to migrate to other servers; compared with the software load balancer in the related technology, the software load balancer does not need to be separately deployed, and when the redundancy design is adopted, one software load balancer does not need to be additionally deployed and configured to form a main-standby relation with the other load balancer. So that the operation flow is simpler.
As an alternative embodiment, selecting an application server by a load balancer to process a predetermined service includes: determining a load balancing pool for processing a predetermined service through a listening port designated by a load balancer, wherein the load balancing pool comprises one or more application servers; selecting a target application server from one or more application servers included in a load balancing pool; and processing the predetermined service by adopting the target application server. Namely, the load balancing service is deployed as a single service in the 5G edge UPF, can also be deployed together with other services, can be managed through a cloud platform, and simplifies operation procedures such as creation and maintenance.
As an alternative embodiment, selecting a target application server from one or more application servers included in the load balancing pool includes: detecting the states of one or more application servers included in a load balancing pool; deleting the abnormal application server from the load balancing pool under the condition that the abnormal application server is detected to obtain the load balancing pool in a normal state; and selecting a target application server from the load balancing pool in the normal state. The method can be used for monitoring the state of the application servers in the load balancing pool, and the state of the application servers can be queried in various ways, for example, the state of each application server is queried in a polling way, and if the application server does not respond within a specified time, the application server is removed from a distribution list, so that abnormal response causing load balancing is avoided.
As an alternative embodiment, the application server is selected by the load balancer to process the predetermined service. In 5G enterprise application or industrial application, the application server is mainly deployed at a local cloud end, namely, the application server is implemented on an edge cloud, and the predetermined service is completed by selecting the application server corresponding to the predetermined service.
Based on the above embodiments and alternative embodiments, an alternative implementation is provided, which is described in detail below.
In the related technology, the 5G Mobile Communication network service target mainly has three application scenarios, namely, eMBB (Enhanced Mobile Broadband), mtc (Massive Machine Type Communication), URLLC (Ultra reliable and low latency Communication), wherein eMBB is mainly a service scenario applied by a Mobile phone terminal, and mtc and URLLC are mainly service application scenarios of the internet of things, so that the 5G network will carry more diversified service demands, and can meet the personal demands of personal Communication, game entertainment and the like, as well as the application demands of the internet of things such as intelligent transportation, unmanned driving, smart home, smart factory and the like. In order to achieve the three major service objectives of the 5G network, the 5G network adopts a technical scheme of UPF (User Port Function) sinking and MEC (Multi-Access Edge Computing), that is, the connection and computation capabilities are migrated from the core network to the Edge closer to the data source. The 'MEC edge cloud' is one of key technologies of a 5G network, and mainly solves the requirements of a communication network on higher bandwidth, more connections, lower time delay and higher computing power caused by the rapid increase of data sources of the Internet of things. The MEC edge cloud is generally formed by an edge UPF and an MEC host, provides the service capability of communication connection and calculation, and enables more applications to be operated in a local data network. In a scene that an internet of things terminal is large in scale, multiple in resource types and multiple in task requests, one problem to be faced by the MEC edge cloud is how to schedule virtual machine resources to improve the utilization rate of physical machine resources, reduce the phenomenon that the load is too high or too low, and achieve the maximization of the overall performance and the resource utilization rate of cloud services, which requires that the 5G MEC edge cloud has load balancing capability.
In the related art, since there is no load balancing function in the standard functions of the UPF at present, there are two types of common implementation methods: (1) the hardware is realized directly through an intelligent switch, the processing capacity of the hardware load balancer is strong, and the hardware load balancer is irrelevant to a system, so that the hardware load balancer is more suitable for scenes of batch equipment, large-scale access and simple application; (2) the software implementation and the load balancer based on the system and the application can better batch loads according to the conditions of the system and the application, and are suitable for complex service scenes.
However, when the above scheme is adopted to solve the problem, for 5G enterprise applications or industrial applications, the application server is mainly deployed at a local cloud, i.e., an edge cloud, and the problems of the above two modes are as follows: 1) the hardware load balancer is adopted, expensive hardware equipment needs to be purchased, and redundant configuration is usually needed to avoid single-point failure, so that the deployment is difficult; in addition, professional operation and maintenance personnel are also needed, the hardware cost and the labor cost are high, and therefore, the hardware load balancer is usually used in the data center; meanwhile, the states of the server and the application cannot be effectively mastered by using the hardware load balancer, when the processing capacity of the system is seriously reduced, a network layer may not sense the state and still perform network transmission, and finally the server is crashed 2) a single software load balancer is adopted, the tasks are heavy and the performance is reduced for the flow distribution of the 5G Internet of things service with large service volume, the deployment of a plurality of software load balancers is time-consuming, and the coordination, the flexibility and the control are poor.
In view of this, the optional embodiment of the present invention is applied to load scheduling for deploying 5G MEC edge cloud in the scene of internet of things, and is implemented by using a technology of load balancing service based on an OpenStack architecture. The load balancing service is provided in a plug-in form and is deployed in the edge UPF. Because the load balance is used as a service, the load balance service can be deployed and maintained in an automatic operation and maintenance mode, so that the flexibility of management and deployment of the load balancer is improved, and the operation and maintenance cost is reduced; meanwhile, the load balancing service can be deployed by adopting a container technology, one or more container images for running the load balancing service can be started at any time according to needs, and can also be migrated to other platforms supporting the container technology for use, when the service is upgraded, only the container images for deploying the new service need to be started, and the original images are closed, so that the flexibility and the compatibility are improved.
Fig. 2 is a system topology structure diagram in the load balancing processing method according to the alternative embodiment of the present invention, as shown in fig. 2, which is described in detail below;
the client terminal ue (user experience) is responsible for sending a network request message to an application server in the edge cloud. And the edge UPF is responsible for converting a destination IP address requested by a user into an edge cloud intranet IP address and sending a request message to the load balancer. And after receiving the request, the load balancer selects a proper application server in the edge cloud according to the configured processing algorithm, and sends the request message to the server for processing.
Fig. 3 is a system logic structure diagram in the load balancing processing method according to an alternative embodiment of the present invention, as shown in fig. 3, which is described below;
as can be seen from the contents of fig. 3, the load balancer is in the UPF, wherein the load balancer is created in the UPF virtual machine and acquires an IP address from a subnet of the edge cloud. The listener assigns a listening port for the load balancer and listens for request messages on the assigned port. The load balancing pool is composed of application servers providing the same content. The member is an application server for processing network requests in the load balancing pool, has an IP address and provides services to the outside through a monitoring port. The health monitor only makes sense after being associated with the load balancing pool and is used for monitoring the states of the members in the load balancing pool, inquiring the state of each member in a polling mode, and removing the member from the distribution list if the member does not respond within a specified time so as to avoid abnormal response causing load balancing.
Fig. 4 is a structural diagram of a technical implementation of load balancing service according to an alternative embodiment of the present invention, as shown in fig. 4, and described in detail below;
the extended interface in fig. 4 is an interface for processing a user request and forwarding a request message sent by the user to the plug-in. The plug-in is a core logic module for processing and creating the load balancer, and stores the logic structure information of creating the load balancer into the database. The dispatcher is responsible for selecting which virtual machine to create the load balancer, and returning the device-related information to the plug-in module, and then the plug-in module sends the message to the agent through the message queue. The message queue is a bridge for communication between the plug-in and the agent. And after receiving the message, the agent sends the message to the driver, and starts the new virtual machine to create the load balancer.
It should be noted that:
1) in the implementation of the load balancing service, the function of the load balancer is implemented by running open source software in the UPF virtual machine instead of hardware, and a redundant design is not needed to be adopted for improving the stability like a hardware load balancer, so that expensive hardware equipment needs to be purchased, the cost is increased, and the cost can be reduced and the flexibility is improved.
2) Because the load balancer is used as a service to provide the function of load balancing, an automatic operation and maintenance tool and a container technology can be adopted, so that the deployment work is flexible and simple, the maintenance difficulty is reduced, the upgrading is convenient, a professional maintenance worker is not needed for maintaining like a hardware load balancer, and the maintenance cost is also reduced.
3) The load balancing service is used as a single service in the 5G edge UPF and is deployed together with other services, management can be performed through a cloud platform, and operation processes such as creation and maintenance are simplified.
4) The load balancing service can run in a virtual machine, can be deployed in batch to form a load balancer cluster, improves the stability and performance of the system, and is convenient to migrate to other servers; unlike a software load balancer, the software load balancer needs to be separately deployed, when a redundancy design is adopted, one software load balancer needs to be additionally deployed and configured to form a primary-standby relationship with another load balancer, and the operation flow is complex.
Namely, through the above alternative embodiment, at least the following advantages can be achieved:
(1) load balancing between virtual machines and between servers can be supported and used;
(2) the deployment can be realized by adopting a container or automatic operation and maintenance, the maintenance cost is reduced, and the flexibility is increased;
(3) the cluster type deployment mode can be realized, and the performance and the stability of the load balancer are improved.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
Example 2
According to an embodiment of the present invention, there is also provided an apparatus for implementing the load balancing processing method, where fig. 5 is a block diagram of a structure of the load balancing processing apparatus according to the embodiment of the present invention, and as shown in fig. 5, the apparatus includes: a receiving module 502, a sending module 504 and a processing module 506, which will be described in detail below.
A receiving module 502, configured to receive a request message, where the request message is used to request processing of a predetermined service; a sending module 504, connected to the receiving module 502, configured to send the request message to a load balancer, where the load balancer is created in a user port function UPF network element in advance; and a processing module 506, connected to the sending module 504, configured to select an application server through the load balancer to process the predetermined service.
It should be noted here that the receiving module 502, the sending module 504 and the processing module 506 correspond to steps S102 to S106 in the method for implementing load balancing, and the modules are the same as the corresponding steps in the implementation example and application scenario, but are not limited to the disclosure in embodiment 1.
Example 3
Embodiments of the present disclosure may provide an electronic device, which may be a terminal. In this embodiment, the electronic device may be any one of computer terminal devices in a computer terminal group as a terminal. Optionally, in this embodiment, the terminal may also be a terminal device such as a mobile terminal.
Optionally, in this embodiment, the terminal may be located in at least one network device of a plurality of network devices of a computer network.
Alternatively, fig. 6 is a block diagram illustrating a structure of a terminal according to an exemplary embodiment. As shown in fig. 6, the terminal may include: one or more processors 61 (only one shown), a memory 62 for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement any of the load balancing processing methods described above.
The memory may be configured to store software programs and modules, such as program instructions/modules corresponding to the load balancing processing method and apparatus in the embodiments of the present disclosure, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, implements the load balancing processing method. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory located remotely from the processor, and these remote memories may be connected to the computer terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor can call the information and application program stored in the memory through the transmission device to execute the following steps: receiving a request message, wherein the request message is used for requesting to process a predetermined service; sending the request message to a load balancer, wherein the load balancer is created in a User Port Function (UPF) network element in advance; and selecting an application server through the load balancer to process the preset service.
Optionally, the processor may further execute the program code of the following steps: before sending the request message to the load balancer, the method further comprises: selecting a UPF network element for creating a load balancer through a scheduler; acquiring logic structure information for creating a load balancer; and creating a load balancer in the selected UPF network element based on the logic structure information.
Optionally, the processor may further execute the program code of the following steps: creating a load balancer in the selected UPF network element based on the logical structure information, comprising: sending a creating request message to a driver through a proxy network element based on a message queue, wherein the message queue comprises one or more creating request messages for requesting to create a load balancer; and creating a load balancer in the selected UPF network element through the driver based on the logic structure information.
Optionally, the processor may further execute the program code of the following steps: creating a load balancer in the selected UPF network element based on the logical structure information, comprising: and in the case that the number of the selected UPF network elements is multiple, creating load balancers in batches in the selected multiple UPF network elements based on the logical structure information.
Optionally, the processor may further execute the program code of the following steps: selecting an application server through a load balancer to process the preset service, wherein the method comprises the following steps: determining a load balancing pool for processing a predetermined service through a listening port designated by a load balancer, wherein the load balancing pool comprises one or more application servers; selecting a target application server from one or more application servers included in a load balancing pool; and processing the predetermined service by adopting the target application server.
Optionally, the processor may further execute the program code of the following steps: selecting a target application server from one or more application servers included in a load balancing pool, comprising: detecting the states of one or more application servers included in a load balancing pool; deleting the abnormal application server from the load balancing pool under the condition that the abnormal application server is detected to obtain the load balancing pool in a normal state; and selecting a target application server from the load balancing pool in the normal state.
Optionally, the processor may further execute the program code of the following steps: the load balancing processing method is applied to the OpenStack system.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
Example 4
In an exemplary embodiment, there is also provided a computer-readable storage medium comprising instructions which, when executed by a processor of a terminal, enable the terminal to perform any one of the load balancing processing methods described above. Alternatively, the computer readable storage medium may be a non-transitory computer readable storage medium, for example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
Optionally, in this embodiment, the computer-readable storage medium may be configured to store program codes executed by the load balancing processing method provided in the foregoing embodiment.
Optionally, in this embodiment, the computer-readable storage medium may be located in any one of a group of computer terminals in a computer network, or in any one of a group of mobile terminals.
Optionally, in this embodiment, the computer readable storage medium is configured to store program code for performing the following steps: receiving a request message, wherein the request message is used for requesting to process a predetermined service; sending the request message to a load balancer, wherein the load balancer is created in a User Port Function (UPF) network element in advance; and selecting an application server through the load balancer to process the preset service.
Optionally, in this embodiment, the computer readable storage medium is configured to store program code for performing the following steps: before sending the request message to the load balancer, the method further comprises: selecting a UPF network element for creating a load balancer through a scheduler; acquiring logic structure information for creating a load balancer; and creating a load balancer in the selected UPF network element based on the logic structure information.
Optionally, in this embodiment, the computer readable storage medium is configured to store program code for performing the following steps: creating a load balancer in the selected UPF network element based on the logical structure information, comprising: sending a creating request message to a driver through a proxy network element based on a message queue, wherein the message queue comprises one or more creating request messages for requesting to create a load balancer; and creating a load balancer in the selected UPF network element through the driver based on the logic structure information.
Optionally, in this embodiment, the computer readable storage medium is configured to store program code for performing the following steps: creating a load balancer in the selected UPF network element based on the logical structure information, comprising: and in the case that the number of the selected UPF network elements is multiple, creating load balancers in batches in the selected multiple UPF network elements based on the logical structure information.
Optionally, in this embodiment, the computer readable storage medium is configured to store program code for performing the following steps: selecting an application server through a load balancer to process the preset service, wherein the method comprises the following steps: determining a load balancing pool for processing a predetermined service through a listening port designated by a load balancer, wherein the load balancing pool comprises one or more application servers; selecting a target application server from one or more application servers included in a load balancing pool; and processing the predetermined service by adopting the target application server.
Optionally, in this embodiment, the computer readable storage medium is configured to store program code for performing the following steps: selecting a target application server from one or more application servers included in a load balancing pool, comprising: detecting the states of one or more application servers included in a load balancing pool; deleting the abnormal application server from the load balancing pool under the condition that the abnormal application server is detected to obtain the load balancing pool in a normal state; and selecting a target application server from the load balancing pool in the normal state.
Optionally, in this embodiment, the computer readable storage medium is configured to store program code for performing the following steps: the load balancing processing method is applied to the OpenStack system.
In an exemplary embodiment, there is also provided a computer program product, in which a computer program is enabled, when executed by a processor of an electronic device, to perform any of the load balancing processing methods described above.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple 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, units or modules, and may be in an electrical or other form.
The 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 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 invention 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 integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit 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 invention may be embodied in the form of a software product, which is stored in a storage medium and includes 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 invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A load balancing processing method is characterized by comprising the following steps:
receiving a request message, wherein the request message is used for requesting to process a predetermined service;
sending the request message to a load balancer, wherein the load balancer is created in a User Port Function (UPF) network element in advance;
and selecting an application server to process the predetermined service through the load balancer.
2. The method of claim 1, wherein prior to said sending the request message to a load balancer, further comprising:
selecting the UPF network element for creating the load balancer through a scheduler;
acquiring logic structure information for creating the load balancer;
and creating the load balancer in the selected UPF network element based on the logic structure information.
3. The method of claim 2, wherein creating the load balancer in the selected UPF network element based on the logical structure information comprises:
sending a creation request message to a driver through a proxy network element based on a message queue, wherein the message queue comprises one or more creation request messages for requesting to create a load balancer;
creating, by the driver, the load balancer in the selected UPF network element based on the logical structure information.
4. The method of claim 2, wherein creating the load balancer in the selected UPF network element based on the logical structure information comprises:
and under the condition that a plurality of selected UPF network elements exist, creating the load balancer in batches on the selected plurality of UPF network elements based on the logic structure information.
5. The method of claim 1, wherein the selecting, by the load balancer, an application server to process the predetermined traffic comprises:
determining a load balancing pool for processing the predetermined service through a listening port designated by the load balancer, wherein the load balancing pool comprises one or more application servers;
selecting a target application server from one or more application servers included in the load balancing pool;
and processing the predetermined service by adopting the target application server.
6. The method of claim 5, wherein selecting a target application server from the one or more application servers included in the load balancing pool comprises:
detecting a status of the one or more application servers included in the load balancing pool;
deleting the abnormal application server from the load balancing pool under the condition that the abnormal application server is detected to obtain the load balancing pool in a normal state;
and selecting a target application server from the load balancing pool in the normal state.
7. The method according to any one of claims 1 to 6, wherein the load balancing processing method is applied to an OpenStack system.
8. A load balancing processing apparatus, comprising:
a receiving module, configured to receive a request message, where the request message is used to request processing of a predetermined service;
a sending module, configured to send the request message to a load balancer, where the load balancer is created in a user port function UPF network element in advance;
and the processing module is used for selecting an application server to process the predetermined service through the load balancer.
9. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the load balancing processing method of any one of claims 1 to 7.
10. A computer-readable storage medium, wherein instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the load balancing processing method of any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115277571A (en) * | 2022-07-29 | 2022-11-01 | 联想(北京)有限公司 | Processing method and processing system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115277571A (en) * | 2022-07-29 | 2022-11-01 | 联想(北京)有限公司 | Processing method and processing system |
| CN115277571B (en) * | 2022-07-29 | 2024-03-29 | 联想(北京)有限公司 | Processing method and processing system |
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