Method and device for adjusting wireless gateway equipment

Abstract

The embodiment of the invention provides a method and a device for adjusting wireless gateway equipment. The method comprises the following steps: determining capacity index data of a service corresponding to a network slice according to operation data of the network slice in a wireless network; operation indication information of the network slice is determined according to the capacity index data, and the operation indication information is used for indicating execution of capacity management operation on wireless gateway equipment in the network slice; based on the operation indication information of the network slice, the capacity management operation is executed on the wireless gateway devices in the network slice, and the capacity management operation is used for managing the number of the wireless gateway devices in the network slice. According to the embodiment of the invention, the problem that the wireless gateway equipment in the wireless mesh network cannot be flexibly scheduled in the related technology, so that the wireless gateway equipment of partial network slices is insufficient in flow and large in service load is solved.

Description

Technical Field

[0001] The present invention relates to the field of communications, and more specifically, to a method and apparatus for adjusting a wireless gateway device. Background Technology

[0002] Traditional Ethernet technology uses physical links such as network cables and fiber optic cables combined with switching equipment for networking, and incorporates Virtual Local Area Networks (VLANs), Virtual Extensible LANs (VXLANs), and Virtual Routing and Forwarding (VRFs) for traffic management. Because data communication between servers relies on physical lines, dedicated personnel are needed to cable, label, and network a large number of physical lines to meet line regularity requirements. Therefore, when server service attributes, data communication service objects, or previously laid network services need to be changed, significant time and manpower are required to re-lay or dismantle existing physical lines and replace them with new ones. Furthermore, because data packets can only be sent in a fixed flow (e.g., data from AC can only pass through AB and BC), dynamic flexibility is extremely poor, and bandwidth contention is severe, requiring highly skilled communication experts for configuration, management, and maintenance. Clearly, traditional Ethernet technology no longer meets the network operation and maintenance requirements of modern data environments.

[0003] Wireless network transmission technology can solve some of the above problems. For example, server data can be accessed wirelessly via wireless gateway devices to overcome the drawbacks of physical line connections, or to achieve point-to-point (AC) pass-through. However, existing wireless access methods still have many management problems and flexibility limitations. For example, they cannot flexibly schedule wireless gateway devices in a wireless mesh network, leading to redundancy in some network slices and insufficient wireless gateway devices in others, resulting in heavy traffic loads. Summary of the Invention

[0004] This invention provides a method and apparatus for adjusting wireless gateway devices, which at least solves the problem in related technologies where the wireless gateway devices in a wireless mesh network cannot be flexibly scheduled, resulting in insufficient wireless gateway devices and high traffic load in some network slices.

[0005] According to an embodiment of the present invention, a method for adjusting a wireless gateway device is provided, comprising: determining capacity index data of a service corresponding to a network slice based on operational data of a network slice in a wireless network; determining operation instruction information of the network slice based on the capacity index data, wherein the operation instruction information is used to instruct the wireless gateway device in the network slice to perform a capacity management operation; and performing the capacity management operation on the wireless gateway device in the network slice based on the operation instruction information of the network slice, wherein the capacity management operation is used to manage the number of wireless gateway devices in the network slice.

[0006] According to another embodiment of the present invention, an adjustment device for a wireless gateway device is provided, comprising: a first determining module, configured to determine capacity index data of a service corresponding to a network slice based on operational data of a network slice in a wireless network; a second determining module, configured to determine operation instruction information of the network slice based on the capacity index data, wherein the operation instruction information is used to instruct the wireless gateway device in the network slice to perform a capacity management operation; and an adjustment module, configured to perform the capacity management operation on the wireless gateway device in the network slice based on the operation instruction information of the network slice, wherein the capacity management operation is used to manage the number of wireless gateway devices in the network slice.

[0007] According to yet another embodiment of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0008] According to yet another embodiment of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0009] According to yet another embodiment of the present invention, a computer program product is also provided, comprising a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0010] Through the above embodiments of the present invention, the capacity index data of the service corresponding to the network slice is determined based on the operation data of the network slice in the wireless network; and the operation instruction information of the network slice is determined based on the capacity index data. Thus, capacity management operations can be performed on the wireless gateway devices in the network slice according to the operation instruction information of the network slice, that is, the wireless devices can be scheduled according to the operation instruction information of the network slice. Therefore, it can solve the problem in related technologies that the wireless gateway devices in the wireless mesh network cannot be flexibly scheduled, resulting in insufficient wireless gateway devices and high traffic service load in some network slices, thereby improving the networking flexibility of the wireless mesh network. Attached Figure Description

[0011] Figure 1 This is a hardware structure block diagram of the computer terminal used in the embodiments of the method of the present invention;

[0012] Figure 2 This is a schematic diagram of the structure of a wireless network management system according to an embodiment of the present invention;

[0013] Figure 3 This is a flowchart illustrating the adjustment method of a wireless gateway device according to an embodiment of the present invention;

[0014] Figure 4 This is a flowchart illustrating a method for determining operation instruction information for network slices based on a voting algorithm according to an embodiment of the present invention.

[0015] Figure 5 This is a schematic diagram of the wireless gateway device adjustment method flow according to an embodiment of the present invention;

[0016] Figure 6 This is a structural block diagram of the adjustment device of a wireless gateway device according to an embodiment of the present invention. Detailed Implementation

[0017] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples.

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0019] The methods and embodiments provided in this application can be executed on a computer terminal or similar computing device. Taking running on a computer terminal as an example, Figure 1 This is a hardware structure block diagram of the computer terminal used in the embodiments of the method of the present invention. For example... Figure 1 As shown, a computer terminal may include one or more ( Figure 1Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0020] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the adjustment method of the wireless gateway device in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 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 instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0021] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the computer terminal. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0022] With the development of digital infrastructure, data center server equipment is being managed centrally. The traditional method of data exchange using physical network cables / fiber optic cables and switches is becoming increasingly inflexible. For example, equipment is grouped by purpose, storage devices are racked nearby for networking, and point-to-point networking through physical cabling and patch cords is used to establish data communication between servers. This networking method can no longer meet the needs of some servers that require real-time dynamic switching based on actual business requirements. Furthermore, because data traffic must be exchanged through backbone switches, the bandwidth consumption of the backbone switches is increased, leading to traffic congestion. This inflexible data exchange method is increasingly unable to meet the needs of flexible networking. In addition, the networking difficulty of new server equipment during network initialization or joining a business cluster is also increasing.

[0023] Traditional wireless network transmission technologies can solve some of the problems associated with traditional Ethernet technology. In traditional wireless network transmission technologies, server data accesses a wireless gateway wirelessly, overcoming the drawbacks of physical line connections and even enabling point-to-point direct connections in some cases. However, this traditional wireless access method still has many management problems and flexibility limitations. For example: during the wireless data transmission of server clusters, high- and low-value data are mixed, and wireless gateway devices cannot identify data types or manage transmission rates; there is no isolation between service data types, with different types of service data traffic mixed in a single wireless LAN network slice (referred to as a wireless network slice); server wireless communication requires additional wireless network cards, and username / password authentication is required when accessing the wireless network, resulting in poor security and unclear management targets; there is a lack of precise management, making it impossible to manage and optimize transmission capacity when high concurrency, high bandwidth, and high transmission quality communication requirements arise; there is a lack of flexible scheduling capabilities, and wireless gateway clusters cannot work collaboratively; for redundant switching gateways, there is no management capability, leading to energy waste and low returns as service data load decreases; and for spectrum, there is a lack of frequency management and planning capabilities, resulting in severe co-channel interference.

[0024] This invention provides a wireless network management system capable of utilizing wireless mesh networks and possessing flexible scheduling / management capabilities. It meets the needs of flexible grouping and dynamic optimization, enabling wireless interconnection between server clusters and rack clusters. This allows for direct point-to-point, high-speed, and high-capacity data transmission of service data between servers / racks. Simultaneously, it incorporates data type analysis and value service mining weighting algorithms to self-tune the wireless transmission rate. This achieves more flexible and intelligent wireless data traffic management, completing high-value data transmission, ensuring high priority / high QoS, and implementing a refined business management model for low-value services with low cost and low resource investment.

[0025] The wireless network management system in this embodiment of the invention involves wireless parameters and services such as data centers, wireless bridges, gateways, frequency bands / channels, as well as server cluster wireless data exchange and data wireless IPaction communication technologies.

[0026] Figure 2 This is a schematic diagram of the structural block diagram of a wireless network management system according to an embodiment of the present invention, such as... Figure 2 As shown, the wireless network management system includes the following modules:

[0027] The data acquisition module 21 is used to collect various types of wireless data, including but not limited to the following types of data: wireless gateway port traffic, wireless channel, wireless channel frequency band, number of connection sessions under the wireless gateway, wireless gateway CPU load, antenna power parameters, antenna angle, list of downstream access devices, average traffic, peak traffic, current configuration parameters of the wireless gateway, and current operating parameters of the wireless gateway including channel, SSID name, physical spatial location information (relative / absolute location information), power parameters, antenna angle, antenna data, and wireless service QoS configuration threshold.

[0028] The data acquisition module 21 is also used to collect data after parsing the client packet header data, and business value assessment data for each slice network.

[0029] The data classification module 22 is used to identify data types such as images, audio, video, logs, and API call requests using deep learning technology, and to classify the data according to business characteristics.

[0030] The data classified by the data classification module 22 will be used for the preliminary evaluation of the value of network slices. That is, the business data in the network slice is a mixture of multiple types of data. The data classification module 22 will preliminarily and roughly determine the value of the network slice through weighted calculation, and will execute the wireless network slice capacity voting algorithm on the network slices whose value is preliminarily evaluated as high value to more accurately determine the value of the network slice.

[0031] In this embodiment of the invention, "value" is used to describe the probability that a network slice tends to expand or shrink. For example, in practical applications, determining the value of a network slice means determining the probability value of the network slice's expansion operation and the probability value of its shrinkage operation.

[0032] The data transmission module 23 is used to automatically adjust the transmission rate based on the data type, transmission requirements, and the scheduled transmission time of the data task. It selects the optimal transmission method and path based on the size, type, and corresponding value markers of various data types; for example, it uses a high rate to transmit large files and a low rate to transmit small files.

[0033] The data caching module 24 is used to temporarily cache the data that needs to be transmitted and distribute it in the wireless network cluster so that the wireless network management system can divide and compress various types of data according to the current network load before transmission.

[0034] The wireless channel optimization module 25 monitors the wireless operating parameters of the entire system, interacts with the data acquisition module 21, and collects the operating parameters of the wireless gateway device using message queues, proxy reporting, and other methods. It also cleans and calculates the collected data. Furthermore, it dynamically optimizes wireless channel parameters, inspects network slices of all current wireless LANs, performs global planning for current wireless network communication, and completes the calculation of global wireless operating parameter optimization.

[0035] The wireless client hardware daughter card 26, installed on the rack / server, can be programmed with a wireless network authentication key. This key is a unique identifier for the physical server already registered on the wireless network management system. It is encrypted to form a scrambling code and sent to the wireless LAN network slice for authentication. This allows all service ports and management ports of the server device to automatically access the wireless slice network, achieving secure access requirements.

[0036] The wireless gateway configuration management module 27 is used to perform capacity management operations on the wireless gateway devices in the network slice according to the determined operation instruction information; it is also used to automatically generate configuration files for the wireless gateway devices and modify configuration parameters, as well as to distribute configuration files and activate / enable configuration information.

[0037] The configuration parameters of the wireless gateway device include, but are not limited to: management address, username, password, configuration distribution function, and configuration activation function.

[0038] Unique ID management for wireless gateway devices includes: device manufacturer management and asset information management.

[0039] The configuration information management of the wireless sub-card includes the server information to which this wireless sub-card is mapped, that is, which physical servers this sub-card is mapped to.

[0040] Wireless gateway device (access point) 28 is used for the underlying physical cluster of wireless networking to complete the access layer services of wireless network.

[0041] The layout optimization calculation module 29 is used to pre-set the threshold model with configured parameters. The input parameters are the persistent data in the data acquisition module 21. It selects the best wireless model suitable for the current data center based on the K-fold crossover algorithm. Through AI iterative calculation, within the selected most suitable model package, it performs layout optimization calculations based on the spatial distribution of the current environment, wireless signal strength distribution, physical server service types, wireless gateway device deployment density, and other information, and adjusts the physical location layout of the wireless gateway devices.

[0042] QoS (Quality of Service) is a measure of communication quality. Factors affecting wireless transmission quality include increased wireless service load, longer transmission distances, decreased wireless module power, improper antenna angles, co-channel interference, and concentrated wireless frequency points. A higher QoS threshold requires more wireless gateway devices to be simultaneously connected, while minimizing transmission attenuation. Conversely, a lower QoS threshold allows for longer transmission distances between the server and wireless gateways, reducing the number of simultaneous wireless gateways. However, this also increases packet loss, corruption, and the number of fragments requiring retransmission.

[0043] In one embodiment, a QoS threshold is set as a transmission guarantee based on a QoS standard fluctuation of 95-99.5%.

[0044] In one embodiment, a 98% QoS standard is used as the QoS access threshold for transmission guarantees.

[0045] In this embodiment of the invention, the physical environment for deploying the wireless network management system is a data center area with sufficient space to deploy wireless switches, wireless access points, and related network switching equipment. Server clusters and wireless switching gateways transmit data via wireless signals. Servers within the data center have a need to dynamically switch between business operation modes. Through dynamic wireless network slicing and automatic configuration, the data center servers can transmit data to any target system within the data center without requiring adjustments to the physical wiring layout or configuration support from highly skilled network maintenance personnel.

[0046] This invention also provides a method for adjusting a wireless gateway device based on the aforementioned wireless network management system. This method can run on the aforementioned computer terminal. It achieves energy-saving control of wireless relays based on service load through a dynamic hibernation algorithm for wireless relay gateways, and realizes automated parameter configuration for data center wireless gateways and wireless relays. It manages the dynamic wireless networking of data center server cluster data transmission services through wireless link communication management capabilities. When the service load is high or there is a need to ensure high-value services, it can wake up redundant energy-saving wireless gateways or migrate wireless gateway devices running in other slice networks. Through wireless mesh network technology, it joins a designated slice wireless LAN, dynamically distributing terminal wireless traffic to the newly joined slice gateway, thus completing the load balancing of traffic services. It can smoothly perform energy-saving standby, migrating wireless traffic services to other wireless gateways in the mesh slice network before hibernation, completing a smooth dynamic service switchover.

[0047] The adjustment method for wireless gateway devices in this invention primarily involves classifying acquired operational data, assigning value assessments to the various types of service data after classification, and setting corresponding data type labels. Each type of service data is then evaluated with an independent value score. In a wireless network slice, multiple types of service data are mixed. Based on the score values ​​of each type of service data, a weighted algorithm is used to derive the comprehensive value assessment of the wireless network slice. Based on this value weight assessment and voting algorithm mechanism, it is determined whether the number of wireless gateways served by the current wireless network slice meets the requirements for the next operational phase. A rough calculation of the operational trend is performed to identify higher-value network slices. Then, through a voting algorithm incorporating value weight parameters, the wireless network is dynamically and automatically optimized and adjusted while prioritizing higher-value network slices. This enables the management of the operational status of all wireless network slices under the wireless network management system, including transmission quality, bandwidth, and latency. The operational trend may involve expansion, contraction, or maintaining the status quo. Expansion will wake up standby wireless gateway devices in the current network slice or schedule deactivated wireless gateway devices from other slices to join the current network slice. The scaling-down process will select gateway devices that can be decommissioned and smoothly decommissioned using existing mesh technology. Voting results indicating a desire to maintain the status quo will skip this operational trend determination. Value weights are used to determine the operational trend for the corresponding network slice, i.e., whether the network slice needs to be scaled up, scaled down, or left unchanged.

[0048] Figure 3 This is a flowchart illustrating the adjustment method of a wireless gateway device according to an embodiment of the present invention, as shown below. Figure 3 As shown, the process includes the following steps:

[0049] Step S302: Determine the capacity index data of the service corresponding to the network slice based on the operation data of the network slice in the wireless network;

[0050] Before step S302 in this embodiment, the wireless network management system automatically configures the wireless gateway device according to the server's service needs, uses mesh technology to create wireless network slices corresponding to the service type, and completes the management of the network slices. It dynamically adjusts the server's wireless network parameters to complete wireless data communication between server clusters. The proportion of different data types varies for different service type network slices; for example, storage data accounts for the largest proportion in type A network slices, while service data accounts for the largest proportion in type B network slices.

[0051] Before step S302 in this embodiment, the method further includes: collecting running data through a data acquisition module.

[0052] Specifically, the data acquisition module collects key business data from server clusters and wireless switching gateways, so that different AI plugins can be used to determine the operational trends of different services based on the operational data, thereby determining the operational trends of the next operational phase of the network slice, completing the operational status analysis of the wireless service cluster in the current data center, and completing the monitoring object modeling of the wireless service system.

[0053] In this embodiment, the network slice service includes monitoring at least one of the following parameters: wireless gateway device port traffic, wireless channel occupancy, number of wireless network sessions, historical traffic ratio, wireless power parameters, wireless angle, and route tracing. The data acquisition module collects the operational data of various services, that is, it collects the operational data corresponding to the above-mentioned parameters monitored by the data acquisition module. Each service corresponds to one parameter.

[0054] In step S302 of this embodiment, determining the capacity index data of the service corresponding to the network slice based on the operation data of the network slice in the wireless network includes: classifying the operation data of the network slice according to the data type to obtain multiple sets of operation sub-data, wherein the data type includes at least one of the following: service type, media type, configuration type, and storage type; determining the coarse operation indication information of the network slice according to multiple weight values ​​corresponding to the multiple sets of operation sub-data, wherein the coarse operation indication information is used to preliminarily evaluate the probability value of the network slice expansion operation and the probability value of the network slice reduction operation; inputting the operation data of the network slice and the coarse operation indication information into the capacity index data determination model to obtain two capacity index data for each service in multiple services, wherein one of the two capacity index data for each service is used to indicate the probability value of the expansion operation corresponding to the service, and the other of the two capacity index data for each service is used to indicate the probability value of the reduction operation corresponding to the service.

[0055] In one embodiment, the collected operational data is classified, and based on the classified data and a preset QoS threshold, coarse operation indication information is determined to roughly determine the operational trend of the corresponding network slice in the next operational phase. Under the preset QoS threshold, the capacity indicator data of different network slices may show conflicting calculation results. For example, at the same time point, for the next operational phase, network slice A's expansion trend is higher than its contraction trend, while network slice B's expansion trend is lower than its contraction trend.

[0056] In one embodiment, the model used to determine the capacity metric data consists of multiple pre-trained AI plugins, wherein the multiple AI plugins include, but are not limited to: AI-112, AI-106, AI-175, AI-177, AI-101, AI-131, and AI-99.

[0057] In one exemplary embodiment, the collected operational data is input into AI-112, AI-106, AI-175, AI-177, AI-101, and AI-131 respectively to obtain the value weights of different services, namely the probability values ​​of expansion and reduction operations for different services; the value weights of all services are input into AI-99 to synthesize the value weights of all services and obtain the coarse operation indication information of the network slice, thereby evaluating the operation trend of the corresponding network slice in the next operation phase.

[0058] In one exemplary embodiment, network slice operation data and coarse operation instruction information are input into a capacity indicator data determination model to obtain two capacity indicator data for each of the multiple services. This includes inputting the network slice operation data and coarse operation instruction information into an AI plugin carrying a pre-trained machine learning model to obtain expansion and contraction operation probability values ​​for the various services of the network slice through the AI ​​plugin. The network slice operation data includes operation data for multiple services, and the capacity indicator data includes expansion and contraction operation probability values; each service corresponds to an expansion operation probability value P. action_kn and a shrinkage operation probability value P action_sn n is an integer greater than or equal to, representing the nth service item; the sum of the expansion and contraction probability values ​​for the same service is 1, i.e., P. action_kn +P action_sn =1. Table 1 illustrates the capacity index data for various services—P action_kn P action_sn .

[0059] Table 1

[0060]

[0061] As shown in Table 1, different AI plugins calculate the probability values ​​for scaling up and scaling down operations for different services.

[0062] In an exemplary embodiment, the data classification module classifies the running data in each network slice and performs a weighted data value assessment calculation on each type of data in all currently running network slices according to the data type. The assessment results of each network slice can reflect the value of the data being transmitted in all currently running network slices. Then, based on the value of the data being transmitted in all currently running network slices, the data classification module roughly calculates the rough operation indication information of each network slice through the AI-99 plugin, i.e., whether it tends to expand or shrink.

[0063] Step S304: Determine the operation instruction information for the network slice based on the capacity index data, wherein the operation instruction information is used to instruct the wireless gateway device in the network slice to perform capacity management operations.

[0064] This invention also provides a voting algorithm mechanism for capacity management indicators based on services corresponding to network slices, based on the operation probability values ​​(P) of different AI plugins. action_kn / sn As an independent voting weight, the introduced value weight trend has a relatively high voting weight. The higher the value assessment of the slice, the smaller the shrinking trend and the larger the expansion trend in the next operation phase. Combined with the trend indicators of other objects, to a certain extent, adaptive control can be exercised over the transmission quality, bandwidth, and latency of the currently operating network slice.

[0065] The voting algorithm determines whether the number of wireless gateway devices served by each wireless network slice in its current operating state meets the requirements for the next operating phase, and calculates the operational trend for the next phase. This operational trend may result in three outcomes: expansion, reduction, or maintaining the status quo. Expansion includes waking up standby wireless gateway devices or scheduling decommissioned wireless gateway devices from other network slices to join the current wireless network slice; reduction includes selecting decommissionable gateway devices and smoothly decommissioning them using existing Mesh network technology; and maintaining the status quo will skip this operational trend determination.

[0066] By using a voting algorithm that incorporates value weight parameters, higher-value wireless network slices can be guaranteed. This enables dynamic and automatic optimization and adjustment of the number of wireless gateway devices in each network slice, ensuring the transmission quality and operational status indicators such as bandwidth and latency of all network slices under the wireless network management system.

[0067] In one embodiment, the capacity indicator data of the service corresponding to the network slice includes two capacity indicator data for each of the multiple services. One of the two capacity indicator data for each service indicates the probability value of an expansion operation, and the other indicates the probability value of a reduction operation. Under the voting algorithm mechanism, step S304 of this embodiment may include: summing the expansion operation probability values ​​corresponding to each of the multiple services to obtain the expansion operation probability value corresponding to the network slice; summing the reduction operation probability values ​​corresponding to each of the multiple services to obtain the reduction operation probability value corresponding to the network slice; and determining the operation indication information for the network slice based on the expansion operation probability value and the reduction operation probability value corresponding to the network slice.

[0068] In one embodiment, under the voting algorithm mechanism, determining the operation indication information of a network slice based on the expansion operation probability value and the shrinkage operation probability value corresponding to the network slice may include: determining preliminary indication information of the network slice based on the comparison result of the expansion operation probability value and the shrinkage operation probability value corresponding to the network slice, wherein the preliminary indication information is used to instruct the wireless gateway device in the network slice to perform a shrinkage operation or an expansion operation; determining the operation indication information of the network slice based on the preliminary indication information, the product result of the first probability value, and the product result of the second probability value, wherein the first probability value product result is the value obtained by multiplying the expansion operation probability value corresponding to each of the multiple services, and the second probability value product result is the value obtained by multiplying the shrinkage operation probability value corresponding to each of the multiple services.

[0069] In one embodiment, under the voting algorithm mechanism, determining the preliminary indication information of a network slice based on the comparison result between the probability value of the expansion operation and the probability value of the reduction operation corresponding to the network slice may include: if the probability value of the expansion operation is greater than the probability value of the reduction operation, determining the preliminary indication information of the network slice to instruct the wireless gateway device in the network slice to perform an expansion operation; if the probability value of the expansion operation is less than the probability value of the reduction operation, determining the preliminary indication information of the network slice to instruct the wireless gateway device in the network slice to perform a reduction operation; and if the probability value of the expansion operation is equal to the probability value of the reduction operation, determining the preliminary indication information of the network slice to instruct the current wireless gateway device in the network slice to remain unchanged.

[0070] In one embodiment, under the voting algorithm mechanism, determining the operation instruction information of the network slice based on the preliminary indication information of the network slice, the product result of the first probability value, and the product result of the second probability value may include: if the preliminary indication information of the network slice indicates that an expansion operation should be performed on the wireless gateway device in the network slice, dividing the product result of the first probability value by the product result of the second probability value to obtain a first division result; dividing the first division result by a predetermined network slice communication quality threshold to obtain a second division result; and multiplying the second division result by a predetermined network slice scheduling positivity factor to obtain a first determination value; if the first determination value is greater than or equal to a preset first threshold, determining the operation instruction information of the network slice as indicating that an expansion operation should be performed on the wireless gateway device in the network slice.

[0071] In one embodiment, the method further includes: if the first determination value is less than a first threshold, maintaining the wireless gateway device in the network slice unchanged.

[0072] Through the dynamic scheduling of wireless devices in the above embodiments of the present invention, energy-saving control of wireless relays based on service load can be achieved, enabling automated parameter configuration of data center wireless gateways and wireless relays. The wireless link communication management capabilities can manage the dynamic wireless networking of data center server cluster data transmission services. Furthermore, when the service load is high or high-value services require protection, redundant energy-saving wireless gateways can be activated or wireless gateway devices running in other slice networks can be migrated. By joining a designated slice wireless LAN using wireless mesh network technology, the terminal wireless traffic of services can be dynamically distributed to the newly joined slice gateway, completing the load balancing of traffic services. Simultaneously, it is also possible to smoothly decommission wireless gateway devices for energy-saving standby, and before hibernation, migrate wireless traffic services to other wireless gateways in the mesh slice network, completing a smooth dynamic service switchover.

[0073] In one embodiment, under the voting algorithm mechanism, determining the operation instruction information of the network slice based on the preliminary indication information of the network slice, the product result of the first probability value, and the product result of the second probability value may include: if the preliminary indication information of the network slice indicates that a scaling-down operation should be performed on the wireless gateway device in the network slice, dividing the product result of the second probability value by the product result of the first probability value to obtain a third division result; multiplying the third division result sequentially by a predetermined network slice communication quality threshold and a predetermined network slice scheduling positivity factor to obtain a second determination value; if the second determination value is greater than or equal to a preset second threshold, determining the operation instruction information of the network slice as indicating that a scaling-down operation should be performed on the wireless gateway device in the network slice.

[0074] In one embodiment, the method further includes: maintaining the wireless gateway device in the network slice unchanged if the second determination value is less than the second threshold. The first threshold may be equal to the second threshold; for example, both the first and second thresholds may be equal to 1.

[0075] The operating status of the wireless gateway device in the next operational phase is calculated through voting. The configuration data module automatically generates the configuration data file for the gateway device, distributes configuration parameters, and performs loading / activation operations. After scheduling is complete, the wireless channel optimization module is invoked to optimize the wireless operating parameters of all wireless network slices, selecting different channels to eliminate co-channel interference.

[0076] Figure 4 This is a flowchart illustrating a method for determining operation instruction information for network slices based on a voting algorithm according to an embodiment of the present invention, as shown below. Figure 4 As shown, for any network slice, the operation instruction information for the network slice is determined based on a voting algorithm, including the following steps:

[0077] Step S402: Determine the flag value based on the obtained expansion operation probability value and shrinkage operation probability value of each service.

[0078] Specifically, the P of each acquired business action_kn P action_sn Substitute into formula (1) to obtain a flag value, where the flag value is used to determine the directional direction of the operation trend of the corresponding network slice.

[0079] Flag value = ΣP action_kn -ΣP action_sn Formula (1)

[0080] The flag value is a preliminary indication, which can be used to determine the initial operational trend. For example, if the flag value is positive, i.e., ΣP action_kn Greater than ΣP action_sn This indicates that the initial indication information is used to instruct the wireless gateway device in the network slice to perform a capacity expansion operation; the flag value is negative, i.e., ΣP action_kn Less than ΣP action_sn This indicates that the initial instruction information is used to instruct the wireless gateway device in the network slice to perform a scaling-down operation.

[0081] In scenarios where the flag value is 0, the current decision process ends, and the process awaits the next vote calculation. Generally, the flag value is very unlikely to be 0.

[0082] Step S404: Perform a secondary determination based on the flag value, and determine the operation instruction information for network slicing based on the result of the secondary determination.

[0083] Specifically, the secondary determination includes:

[0084] Based on formulas (2) and (3), P for each business is calculated. action_kn P action_sn Perform weighted calculation;

[0085] Expand ActionRe = P action_k1 *P action_k2 *……*P action_kn Formula (2)

[0086] Shrink ActionRe = P action_s1 *P action_s2 *……*P action_sn Formula (3)

[0087] If the initial indication information indicates that an expansion operation should be performed on the wireless gateway device in the network slice, then the operation trend of the network slice should be determined a second time according to formula (4):

[0088] OptRe = W * (Paction_expansion / Paction_shrinkage / QoS threshold) Formula (4)

[0089] If the initial indication information indicates that a scaling-down operation should be performed on the wireless gateway device in the network slice, then the operation trend of the network slice should be determined a second time according to formula (5):

[0090] OptRe = W * (Paction_shrinking / Paction_expanding) * QoS threshold formula (5)

[0091] Where W is the active adjustment factor and QoS threshold is the threshold parameter for wireless network quality.

[0092] In one embodiment, the aggressiveness adjustment factor W can be maintained by the user in the wireless network management system according to their own needs, so that the user tends to configure the aggressiveness after the network slice reassembly / scheduling decision. Generally, the value of W is between 1.5 and 4. The larger the value of W, the more aggressive the wireless slice network action is, and the smaller the value of W, the more inert the wireless slice network action is. (Default W = 2).

[0093] The smaller the QoS threshold, the more difficult it is to execute the scaling-down action in a scaling-down scenario; the larger the QoS threshold, the more difficult it is to execute the scaling-up action in a scaling-up scenario.

[0094] Determine the result value of OptRe:

[0095] If the result value of OptRe is greater than 1, the expansion or reduction of the wireless gateway in that slice network will be triggered.

[0096] If the result value of OptRe is less than 1, no operation will be performed, and the operation judgment will be skipped.

[0097] Step S306: Perform capacity management operation on the wireless gateway device in the network slice based on the operation instruction information of the network slice, wherein the capacity management operation is used to manage the number of wireless gateway devices in the network slice.

[0098] Step S306 in this embodiment includes: when the operation instruction information instructs the wireless gateway device in the network slice to perform a scaling-down operation, performing a smooth shutdown operation on one or more wireless gateway devices in the network slice to put them into standby mode, thereby achieving energy saving and consumption reduction.

[0099] In step S306 of this embodiment, the following steps are included: when the operation instruction information instructs the wireless gateway device in the network slice to perform an expansion operation, the wireless gateway device in other network slices besides itself is accessed, and the wireless gateway device is authenticated according to the scrambling code of the accessed wireless gateway device; wherein, the wireless gateway device includes wireless gateway devices that have been smoothly decommissioned in other network slices and redundant standby wireless gateway devices.

[0100] In other words, when the operation instruction information instructs the wireless gateway device in the network slice to perform a capacity expansion operation, the wireless gateway device that is smoothly decommissioned during the capacity reduction operation will have a new running configuration file generated by the wireless gateway configuration management module and distributed to the smoothly decommissioned wireless gateway device to automatically load or activate the smoothly decommissioned wireless gateway device, thus completing the flexible scheduling process of the network slice that needs to perform a capacity expansion operation on its own.

[0101] In one embodiment, when there are no wireless gateway devices available for flexible scheduling, the wireless network management system records the failure of this flexible scheduling and records the specific information of the scheduling failure, providing it to the system administrator for manual decision-making on whether more gateway devices need to be purchased.

[0102] Following step S306 in this embodiment, the method further includes invoking the wireless channel optimization module to optimize the wireless operating parameters of all network slices, selecting different channels, eliminating co-channel interference between different channels, and performing wireless channel optimization. Based on the dynamically adjusted results of the wireless network slices, the wireless channel optimization module is invoked to complete the scheduled wireless network optimization process, and based on the optimized state, it awaits the execution of subsequent algorithms.

[0103] In this embodiment of the invention, the wireless client sub-card uses the authentication key provided by the wireless network management system and the unique hardware information code in the currently inserted physical server hardware information as parameters to form a scrambling code through encryption calculation. The scrambling code is sent to the wireless gateway device in the wireless slicing network for wireless communication authentication, enabling all service network ports and management network ports of the server device to automatically access the wireless slicing network, achieving the requirement of secure access. This means that the key is coupled with the hardware, thereby generating a key based on the hardware's characteristic information for use.

[0104] Through the above steps, the capacity index data of the corresponding service of the network slice is determined based on the operation data of the network slice in the wireless network; and the operation instruction information of the network slice is determined based on the capacity index data. Thus, capacity management operations can be performed on the wireless gateway devices in the network slice according to the operation instruction information of the network slice. In other words, wireless devices can be scheduled according to the operation instruction information of the network slice. Therefore, it can solve the problem in related technologies that the wireless gateway devices in the wireless mesh network cannot be flexibly scheduled, resulting in insufficient wireless gateway devices and high traffic service load in some network slices, and improve the networking flexibility of the wireless mesh network.

[0105] Figure 5 This is a schematic diagram of the wireless gateway device adjustment method flow according to an embodiment of the present invention, and the method is illustrated with the data in Table 2.

[0106] Table 2

[0107]

[0108] like Figure 5 As shown, the method includes the following steps:

[0109] Step S501: The wireless network management system selects any of the created wireless network slices.

[0110] Step S502: Obtain the expansion operation probability value and reduction operation probability value of all services under the network slice from the wireless network management system.

[0111] The probability values ​​for scaling up and scaling down operations for all services are calculated based on the corresponding AI plugins in Table 2.

[0112] Step S503: Determine the flag value based on the expansion operation probability value and the reduction operation probability value of all services.

[0113] Sum the probability values ​​of scaling down operations for all services:

[0114] ΣP action_sn =0.22+0.67+0.58+0.20+0.37+0.56+0.41=3.01;

[0115] Sum the probability values ​​of capacity expansion operations for all services:

[0116] ΣP action_kn =0.78+0.33+0.42+0.80+0.63+0.44+0.59=4.09;

[0117] ΣP action_sn and ΣP action_kn Substituting into the above formula (1), we obtain the flag value.

[0118] The flag value = 4.09 - 3.01 = 1.08, which means that the flag value indicates that the wireless gateway device needs to be expanded in the network slice.

[0119] Step S504: Further determine the operational trend of network slices based on the flag value, network slice scheduling motivation factor W, and QoS threshold.

[0120] Multiply the probability values ​​of capacity expansion operations for all services:

[0121] The expansion ActionRe = 0.78 * 0.33 * 0.42 * 0.80 * 0.63 * 0.44 * 0.59 = 0.0141447;

[0122] Multiply the probability values ​​of scaling down operations for all services:

[0123] The reduction in capacity is calculated as: ActionRe = 0.22 * 0.67 * 0.58 * 0.20 * 0.37 * 0.56 * 0.41 = 0.0014525;

[0124] In this embodiment, W is set to 2 by default, and the QoS threshold is 98%.

[0125] When the flag value indicates that a network slice needs to be expanded, the expansion OptRe is determined by formula (4);

[0126] Expansion OptRe = 2 * (0.0141447 / 0.0014525 / 0.98) = 9.937

[0127] If the result of OptRe is greater than 1, it is determined that the wireless network slice needs to undergo automated expansion.

[0128] In step S505, based on the determination result in step S504 that an expansion operation is required, wireless gateways that have been smoothly deactivated or redundant standby wireless gateway devices in other network slices are scheduled to be added to this network slice, thus completing automatic and flexible scheduling.

[0129] Step S506: Based on the results of dynamic adjustment of the wireless network slicing, call the wireless channel optimization module to complete the wireless network optimization steps after scheduling.

[0130] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0131] This embodiment also provides an adjustment device for a wireless gateway device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0132] Figure 6 This is a structural block diagram of the adjustment device of the wireless gateway device according to an embodiment of the present invention, such as... Figure 6 As shown, the device includes: a first determining module 61, a second determining module 62, and an adjusting module 63.

[0133] The first determining module 61 is used to determine the capacity index data of the service corresponding to the network slice based on the operation data of the network slice in the wireless network;

[0134] The second determining module 62 is used to determine the operation instruction information of the network slice based on the capacity index data, wherein the operation instruction information is used to instruct the wireless gateway device in the network slice to perform capacity management operation;

[0135] In one embodiment, the first determining module 61 and the second determining module 62 may be disposed on the data classification module 22 in the above embodiment, that is, the data classification module 22 functionally includes the functions of the first determining module 61 and the second determining module 62.

[0136] The adjustment module 63 is used to perform the capacity management operation on the wireless gateway devices in the network slice based on the operation instruction information of the network slice, wherein the capacity management operation is used to manage the number of wireless gateway devices in the network slice.

[0137] In one embodiment, the adjustment module 63 may be disposed on the wireless gateway configuration management module 27 in the above embodiment, that is, the wireless gateway configuration management module 27 includes the function of the adjustment module 63.

[0138] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0139] The wireless network management system, wireless gateway device adjustment method, and apparatus described in the above embodiments of the present invention can be applied to scenarios including but not limited to the following:

[0140] Application 1: Wireless Network Optimization

[0141] An AI-driven wireless network management system can monitor and analyze wireless networks in real time, identify bottlenecks and problems, and propose corresponding solutions, such as adjusting channels and antenna orientation, to improve network performance and stability.

[0142] Application 2: Network Security Protection

[0143] Wireless network management systems can perform in-depth analysis of network traffic, identify potential network attacks and security threats, and take corresponding protective measures, such as blocking specific IP action addresses or ports. If an abnormally compromised wireless gateway device is detected, it can be isolated, reconfigured and initialized, and the compromised wireless gateway device can be modified to protect network security.

[0144] Application 3: Business Awareness and Scheduling

[0145] The wireless network management system can perceive and schedule services in the wireless network based on parameters such as the SRC / DEST IPaction_ address range of the service, the port number of the microservice, and the service attributes of the target cluster, combined with the analysis results of the current wireless network topology, transmission load, and service data packets, so as to realize the dynamic allocation and optimization of network resources.

[0146] Application 4: Automated Equipment Configuration

[0147] Through AI iterative algorithms, the configuration and activation of wireless gateway devices can be completed automatically, reducing human error and configuration time, and improving configuration efficiency. By analyzing the operating parameters of the wireless gateway, such as CPaction_U load, port traffic, and number of connection sessions, energy consumption management of the wireless gateway can be achieved, such as intelligent scheduling and energy-saving control, to reduce network energy consumption and operating costs.

[0148] Application 5: Improved network transmission quality

[0149] By improving the QoS transmission quality of high-value services and tuning the transmission resources, bandwidth, and rate of low-value services, network quality can be optimized, thereby improving the overall network transmission efficiency and increasing economic benefits.

[0150] Application 6: High Availability of Services in Extreme Situations

[0151] Through the automated management capabilities of the wireless network management system, security intrusions can be addressed, ensuring uninterrupted wireless network services in the data center even after partial power line failures, achieving high availability without service interruption. Furthermore, due to the introduction of a voting algorithm for high-value protection, the system can automatically abandon services for low-value services, maximizing its capacity to guarantee uninterrupted high-value services, thus ensuring reliable communication for high-value services even in extreme scenarios.

[0152] The above embodiments of the present invention solve the problem of disordered competition in traditional wireless data transmission by servers. By identifying different data types through a data classification and recognition module, different types of data are isolated for communication. A voting algorithm is used for flexible scheduling. Combined with a wireless gateway configuration management module and a layout optimization module, the wireless gateway device group can work collaboratively. Valuable services are identified and communication quality is guaranteed and optimized. Redundant, low-load gateway devices are shut down, saving energy and reducing consumption.

[0153] A wireless network management system enables granular management of wireless transmission and switching equipment clusters, wireless frequency points / spectrum resources, and wireless service data traffic, achieving data transmission at a lower cost. Its precise management capabilities, combining flexibility and stability, create greater value for customers.

[0154] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0155] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0156] Embodiments of the present invention also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0157] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor. The input / output device is connected to the processor.

[0158] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0159] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0160] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for adjusting a wireless gateway device, characterized in that, include: The capacity index data of the service corresponding to the network slice is determined based on the operational data of the network slice in the wireless network; The operation instruction information of the network slice is determined based on the capacity index data, wherein the operation instruction information is used to instruct the wireless gateway device in the network slice to perform capacity management operations; The capacity management operation is performed on the wireless gateway devices in the network slice based on the operation instruction information of the network slice, wherein the capacity management operation is used to manage the number of wireless gateway devices in the network slice.

2. The method according to claim 1, characterized in that, in, The network slice corresponds to services that include monitoring at least one of the following parameters: wireless gateway device port traffic, number of wireless channels occupied, number of wireless network sessions, historical traffic ratio, wireless power parameters, wireless angle, and route tracing.

3. The method according to claim 1, characterized in that, The step of determining the capacity index data of the service corresponding to the network slice based on the operational data of the network slice in the wireless network includes: The network slice's operational data is categorized according to data type to obtain multiple sets of operational sub-data, wherein the data type includes at least one of the following: business type, media type, configuration type, and storage type. Based on the multiple weight values ​​corresponding to the multiple sets of running sub-data, the coarse operation instruction information of the network slice is determined, wherein the coarse operation instruction information is used to coarsely instruct the wireless gateway device in the network slice to perform capacity management operations. The network slice's operational data and the coarse operation indication information are input into the capacity indicator data determination model to obtain two capacity indicator data for each service in the network slice's corresponding service. One of the two capacity indicator data for each service is used to indicate the probability value of the expansion operation corresponding to that service, and the other of the two capacity indicator data for each service is used to indicate the probability value of the shrinkage operation corresponding to that service.

4. The method according to claim 1, characterized in that, The capacity indicator data for the network slice corresponding to the service includes two capacity indicator data for each of the multiple services. One of the two capacity indicator data for each service indicates the probability value of a capacity expansion operation for that service, and the other indicates the probability value of a capacity reduction operation for that service. The step of determining the operation indication information for the network slice based on the capacity indicator data includes: The expansion operation probability value corresponding to each of the indicated multiple services is added together to obtain the expansion operation probability value corresponding to the network slice. The probability values ​​of scaling down operations corresponding to each of the indicated multiple services are added together to obtain the probability value of scaling down operations corresponding to the network slice. Based on the expansion operation probability value and the shrink operation probability value corresponding to the network slice, the operation instruction information of the network slice is determined.

5. The method according to claim 4, characterized in that, The step of determining the operation indication information of the network slice based on the expansion operation probability value and the shrinkage operation probability value corresponding to the network slice includes: Based on the comparison result between the expansion operation probability value and the shrink operation probability value corresponding to the network slice, preliminary indication information of the network slice is determined, wherein the preliminary indication information is used to indicate whether to perform a shrink operation or an expansion operation on the wireless gateway device in the network slice. Based on the preliminary indication information of the network slice, the product result of the first probability value, and the product result of the second probability value, the operation indication information of the network slice is determined. The product result of the first probability value is the value obtained by multiplying the expansion operation probability value corresponding to each of the multiple services, and the product result of the second probability value is the value obtained by multiplying the shrinkage operation probability value corresponding to each of the multiple services.

6. The method according to claim 5, characterized in that, The step of determining the preliminary indication information of the network slice based on the comparison result between the expansion operation probability value and the shrinkage operation probability value corresponding to the network slice includes: If the probability value of the expansion operation corresponding to the network slice is greater than the probability value of the reduction operation corresponding to the network slice, the preliminary indication information of the network slice is determined as an indication to perform an expansion operation on the wireless gateway device in the network slice. If the probability value of the expansion operation corresponding to the network slice is less than the probability value of the shrink operation corresponding to the network slice, the preliminary indication information of the network slice is determined as an indication to perform a shrink operation on the wireless gateway device in the network slice. If the probability value of the expansion operation corresponding to the network slice is equal to the probability value of the shrinkage operation corresponding to the network slice, the preliminary indication information of the network slice is determined to indicate that the current wireless gateway device in the network slice should remain unchanged.

7. The method according to claim 5, characterized in that, The step of determining the operation instruction information for the network slice based on the preliminary instruction information, the product result of the first probability value, and the product result of the second probability value includes: When the preliminary indication information of the network slice indicates that an expansion operation should be performed on the wireless gateway device in the network slice, the product result of the first probability value is divided by the product result of the second probability value to obtain the first division result; Divide the first division result by a predetermined network slice communication quality threshold to obtain a second division result, and multiply the second division result by a predetermined network slice scheduling positivity factor to obtain a first determination value; If the first determination value is greater than or equal to a preset first threshold, the operation instruction information of the network slice is determined to instruct the wireless gateway device in the network slice to perform a capacity expansion operation.

8. The method according to claim 7, characterized in that, The method further includes: If the first determination value is less than the first threshold, the wireless gateway device in the network slice remains unchanged.

9. The method according to claim 5, characterized in that, The step of determining the operation instruction information for the network slice based on the preliminary instruction information, the product result of the first probability value, and the product result of the second probability value includes: When the preliminary indication information of the network slice indicates that a scaling-down operation is performed on the wireless gateway device in the network slice, the product result of the second probability value is divided by the product result of the first probability value to obtain the third division result; The third division result is multiplied sequentially by a predetermined network slice communication quality threshold and a predetermined network slice scheduling positivity factor to obtain a second judgment value; If the second determination value is greater than or equal to a preset second threshold, the operation instruction information of the network slice is determined to instruct the wireless gateway device in the network slice to perform a scaling-down operation.

10. The method according to claim 9, characterized in that, The method further includes: If the second determination value is less than the second threshold, the wireless gateway device in the network slice remains unchanged.

11. The method according to claim 1, characterized in that, The operation of performing the capacity management operation on the wireless gateway device in the network slice based on the operation instruction information of the network slice includes: When the operation instruction information instructs the wireless gateway device in the network slice to perform a capacity expansion operation, it accesses wireless gateway devices in other network slices besides itself, and authenticates the wireless gateway devices according to the scrambling code of the accessed wireless gateway devices; wherein, the wireless gateway devices include wireless gateway devices that have been smoothly decommissioned in the other network slices and redundant standby wireless gateway devices.

12. An adjustment device for a wireless gateway device, characterized in that, include The first determining module is used to determine the capacity index data of the service corresponding to the network slice based on the operation data of the network slice in the wireless network; The second determining module is used to determine the operation instruction information of the network slice based on the capacity index data, wherein the operation instruction information is used to instruct the wireless gateway device in the network slice to perform capacity management operation; The adjustment module is used to perform the capacity management operation on the wireless gateway devices in the network slice based on the operation instruction information of the network slice, wherein the capacity management operation is used to manage the number of wireless gateway devices in the network slice.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of claims 1 to 11.

14. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 11.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1 to 11.

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