Dynamic management method and system for network elements of core network

Abstract

The invention discloses a core network element dynamic management method and system, and the method comprises the steps: collecting the first state information of a core network, and the first state information comprises the number of network element devices in an active state and the number of network element devices in a to-be-activated state in each logic pool in the core network; acquiring second state information of an external network in communication connection with the core network, wherein the second state information comprises types of request messages from the user equipment and the number of each type of request messages; processing the first state information and the second state information based on an intelligent model to obtain network element adjustment information; and adjusting the state of the network element equipment in each logic pool based on the network element adjustment information, so that the service capability of the logic pool is adapted to the network flow demand. According to the method, network element management can be more intelligent, dynamic control over the number of activated network element devices is achieved so as to adapt to changes of network flow, resource consumption can be effectively optimized, and operation cost can be reduced.

Description

Technical Field

[0001] The present invention relates to the field of mobile communication technology, and in particular to a core network element dynamic management method and system. Background Art

[0002] In modern communication networks, the core network is an important bridge connecting user devices and Internet services. Its performance and efficiency directly affect the overall service quality. With the rapid expansion of mobile Internet and Internet of Things applications, one of the main challenges facing the core network is how to effectively manage the growing network traffic, especially how to reduce operating costs while ensuring service quality. Although the traditional core network load sharing method has solved the early problems to a certain extent, it has gradually exposed a series of significant limitations when dealing with current and future network needs.

[0003] A major problem with traditional load sharing methods is the serious waste of resources. In order to cope with the large number of requests that may occur during peak network traffic hours, operators usually deploy a large number of network elements of the same type in each pool. These network elements remain in operation even when traffic is low, resulting in unnecessary energy consumption and waste of hardware resources. Specifically, continuously running network elements not only consume a lot of electricity, but also generate additional heat dissipation requirements, further increasing energy consumption. In addition, a fixed number of network elements means a huge initial hardware investment, especially when it is necessary to cope with potential large traffic shocks, sufficient redundant resources must be reserved. This fixed resource configuration method will cause a large number of resources to be idle when daily traffic is low, thereby increasing operating costs.

[0004] Secondly, traditional load sharing methods perform poorly in terms of resource management and dynamic adaptability. In traditional methods, the number and configuration of network elements are usually fixed and cannot be dynamically adjusted according to actual business needs. When network traffic suddenly surges, the number of existing network elements may not be enough to cope with it, and temporarily adding new network elements requires a long time to complete the purchase, installation and configuration of equipment, which cannot respond quickly to emergencies. On the contrary, when network traffic is low, a large number of network elements are idle and resource utilization is low. In addition, the fixed number of network elements limits the flexibility of the system, making it difficult to effectively allocate tasks according to real-time network conditions, affecting the overall service quality and user experience. For example, the traffic in a specific area may be much higher than that in other areas during certain time periods, and the traditional method cannot dynamically adjust resource allocation, resulting in some network elements being overloaded while other network elements are idle, further exacerbating resource waste and performance bottlenecks. Summary of the invention

[0005] The object of the present invention is to provide a core network element dynamic management method and system which can dynamically adjust the number of corresponding active network elements based on changes in network traffic.

[0006] In order to achieve the above-mentioned object, the present invention provides a core network network element dynamic management method, wherein the core network is provided with a plurality of logical pools corresponding to different types of network elements, each of the logical pools is provided with a plurality of network element devices having the same function; in each of the logical pools, the state of each of the network element devices includes an active state in normal operation and a silent state to be activated; the dynamic management method comprises: Collecting first status information of the core network, where the first status information includes the number of the network element devices in an active state and the number of the network element devices in a to-be-activated state in each of the logical pools in the core network; Collecting second status information of an external network that is communicatively connected to the core network, the second status information including types of request messages from user equipment and the number of each type of request messages; Processing the first state information and the second state information based on an intelligent model to obtain network element adjustment information; the intelligent model is constructed based on a self-learning neural network model and pre-trained; The status of the network element devices in each of the logical pools is adjusted based on the network element adjustment information, so that the service capacity of the logical pool is adapted to the network traffic demand.

[0007] Preferably, the first status information further includes any one or more of the following information: The size of virtual memory used by the process corresponding to the network element device; The size of the process corresponding to the network element device currently residing in the physical memory; The percentage of CPU time occupied by the process corresponding to the network element device; The percentage of physical memory occupied by the process corresponding to the network element device; Network error rate; Packet loss rate; Retransmission rate; Network element equipment delay time; Length of the internal task queue of the network element device.

[0008] Preferably, the type of the request message in the second status information includes one or more of a voice message, a text message, and a video message.

[0009] Preferably, the first status information and the second status information are collected regularly according to a time interval set by a timer.

[0010] Preferably, the network element adjustment information and the second state information are also stored, and the network element adjustment information generated in the current time period and the second state information collected in the next time period are coupled into a data pair; During a preset idle time period, the intelligent model reads the data pair for training, and updates the neural network parameters of the intelligent model according to the training results.

[0011] Preferably, the intelligent model is a reinforcement learning model.

[0012] Preferably, the intelligent model is arranged in a network data analysis function of the core network.

[0013] The present invention also provides a core network element dynamic management system, which includes a system controller, and the system controller works based on the core network element dynamic management method as described above.

[0014] The present invention also provides a core network element dynamic management system, which includes: one or more processors; Memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the programs include instructions for executing the core network element dynamic management method as described above.

[0015] The present invention also provides a computer-readable storage medium, which includes a computer program, and the computer program can be executed by a processor to implement the core network element dynamic management method as described above.

[0016] Compared with the prior art, the core network network element dynamic management method provided by the present invention processes the first status information reflecting the status of the network element equipment in each logical pool of the core network and the second status information reflecting the network traffic of the external network through an intelligent model to output network element adjustment information, and adjusts the status of each type of network element equipment in the current core network based on the network element adjustment information, so that the service capability of the network element equipment in the active state is equivalent to the current network demand; it can be seen that the above-mentioned network element dynamic management method can make network element management more intelligent, realize dynamic control of the number of activated network element equipment to adapt to changes in network traffic, and can effectively optimize resource consumption and reduce operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The present invention is a flowchart of a method for dynamically managing core network elements in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to explain the technical content, structural features, achieved objectives and effects of the present invention in detail, the following is a detailed description in conjunction with the implementation methods and the accompanying drawings.

[0019] This embodiment discloses a core network element dynamic management method to achieve dynamic adjustment of core network elements according to dynamic changes in network traffic.

[0020] First of all, it should be noted that the core network of this embodiment is provided with several logical pools corresponding to different types of network elements, and each of the logical pools is provided with multiple network element devices with the same function. In each of the logical pools, the status of each of the network element devices includes an active state in normal operation and a silent state to be activated. Specifically, for multiple network element devices in any logical pool, a corresponding number of network element devices can be enabled according to demand, and the unenabled network element devices are in a state to be activated.

[0021] Based on this, the dynamic management method includes the following processes: S10: Collecting first status information of the core network, the first status information including the number of active network element devices and the number of network element devices to be activated in each logical pool in the core network. The first status information reflects the current service capability and scalability of the logical pool.

[0022] S11: Collect second state information of an external network connected to the core network, the second state information including types of request messages from user equipment and the number of each type of request messages. The second state information reflects network traffic of the external network.

[0023] S12: Process the first state information and the second state information based on an intelligent model to obtain network element adjustment information. The intelligent model is constructed based on a self-learning neural network model and is pre-trained.

[0024] S13: adjusting the status of the network element devices in each of the logical pools based on the network element adjustment information, so that the service capability of the logical pool is adapted to the network traffic demand.

[0025] Based on this management method, the first status information reflecting the status of network element devices in each logical pool of the core network and the second status information reflecting the network traffic of the external network are processed through an intelligent model to output network element adjustment information, and the status of each type of network element devices in the current core network is adjusted based on the network element adjustment information, so that the service capability of the network element devices in the active state is commensurate with the current network demand.

[0026] It can be seen that the above-mentioned network element dynamic management method can make network element management more intelligent and realize dynamic control of the number of activated network element devices to adapt to changes in network traffic.

[0027] Moreover, the above management method can reduce the number of active network element devices during low-peak traffic periods, significantly reducing energy consumption and hardware resource waste. At the same time, it can increase the number of active network element devices according to actual needs during peak traffic periods to ensure the stability and reliability of the communication system, so as to effectively optimize resource consumption and reduce operating costs.

[0028] Specifically, the first status information further includes any one or more of the following information: The size of virtual memory used by the process corresponding to the network element device; The size of the process corresponding to the network element device currently residing in the physical memory; The percentage of CPU time occupied by the process corresponding to the network element device; The percentage of physical memory occupied by the process corresponding to the network element device; Network error rate; Packet loss rate; Retransmission rate; Network element equipment delay time; Length of the internal task queue of the network element device.

[0029] In addition, the type of the request message in the second status information includes one or more of a voice message, a text message, and a video message. In this way, the activation quantity of the corresponding network element device is adjusted according to different types of network traffic.

[0030] On the other hand, since changes in network traffic require time to accumulate, in order to reduce the energy requirements for the operation of the management method, the first status information and the second status information are regularly collected according to the time interval set by the timer, and then the status of the network element devices in the logical pool is updated according to the time interval.

[0031] On the other hand, the accuracy of the intelligent model output strategy is continuously improved, the network element adjustment information and the second status information are also stored, and the network element adjustment information generated in the current time period and the second status information collected in the next time period are coupled into a data pair.

[0032] During a preset idle time period, the intelligent model reads the data pairs for training, and updates the neural network parameters of the intelligent model according to the training results, so that the prediction ability of the intelligent model is improved in real time.

[0033] Specifically, the intelligent model is a reinforcement learning model.

[0034] On the other hand, the intelligent model is arranged in the network data analysis function NWAD of the core network.

[0035] In another preferred embodiment of the present invention, a core network element dynamic management system is also disclosed, which includes a system controller. The system controller works based on the core network element dynamic management method in the above embodiment.

[0036] The present invention also discloses another core network element dynamic management system, which includes one or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the program includes instructions for executing the core network element dynamic management method as described above. The processor can adopt a general central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits to execute relevant programs to implement the functions required to be executed by the modules in the core network element dynamic management system of the embodiment of the present application, or to execute the core network element dynamic management method of the method embodiment of the present application.

[0037] The present invention also discloses a computer-readable storage medium, which includes a computer program, and the computer program can be executed by a processor to complete the core network element dynamic management method as described above. 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 or a data center that includes one or more available media integrated. The available medium can be a read-only memory (ROM), or a random access memory (RAM), or a magnetic medium, such as a floppy disk, a hard disk, a tape, a magnetic disk, or an optical medium, such as a digital versatile disc (DVD), or a semiconductor medium, such as a solid state disk (SSD), etc.

[0038] The embodiment of the present application also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of an electronic device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the electronic device executes the above-mentioned core network element dynamic management method.

[0039] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of rights of the present invention. Therefore, equivalent changes made according to the scope of the patent application of the present invention are still within the scope covered by the present invention.

Claims

1. A core network element dynamic management method, characterized in that: The core network is provided with a plurality of logical pools corresponding to different types of network elements, each of which is provided with a plurality of network element devices having the same function; In each of the logical pools, the status of each of the network element devices includes an active state in normal operation and a silent state to be activated; The dynamic management method comprises: Collecting first status information of the core network, where the first status information includes the number of the network element devices in an active state and the number of the network element devices in a to-be-activated state in each of the logical pools in the core network; Collecting second status information of an external network that is communicatively connected to the core network, the second status information including types of request messages from user equipment and the number of each type of request messages; Processing the first state information and the second state information based on an intelligent model to obtain network element adjustment information; the intelligent model is constructed based on a self-learning neural network model and pre-trained; The status of the network element devices in each of the logical pools is adjusted based on the network element adjustment information, so that the service capacity of the logical pool is adapted to the network traffic demand.

2. The core network element dynamic management method according to claim 1, characterized in that: The first status information also includes any one or more of the following information: The size of virtual memory used by the process corresponding to the network element device; The size of the process corresponding to the network element device currently residing in the physical memory; The percentage of CPU time occupied by the process corresponding to the network element device; The percentage of physical memory occupied by the process corresponding to the network element device; Network error rate; Packet loss rate; Retransmission rate; Network element equipment delay time; Length of the internal task queue of the network element device.

3. The core network element dynamic management method according to claim 1, characterized in that: The type of the request message in the second status information includes one or more of a voice message, a text message, and a video message.

4. The core network element dynamic management method according to claim 1, characterized in that: The first state information and the second state information are collected regularly according to the time interval set by the timer.

5. The core network element dynamic management method according to claim 1, characterized in that: further storing the network element adjustment information and the second state information, and coupling the network element adjustment information generated in the current time period with the second state information collected in the next time period into a data pair; During a preset idle time period, the intelligent model reads the data pair for training, and updates the neural network parameters of the intelligent model according to the training results.

6. The core network element dynamic management method according to claim 1, characterized in that: The intelligent model is a reinforcement learning model.

7. The core network element dynamic management method according to claim 1, characterized in that: The intelligent model is arranged in the network data analysis function of the core network.

8. A core network element dynamic management system, characterized in that: It comprises a system controller, and the system controller operates based on the core network element dynamic management method described in any one of claims 1 to 7.

9. A core network element dynamic management system, characterized in that: include: one or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the programs include instructions for executing the core network element dynamic management method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: It includes a computer program, which can be executed by a processor to complete the core network element dynamic management method as described in any one of claims 1 to 7.

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