CN117835257A

CN117835257A - Virtual-real combined trusted WLAN networking AP pre-planning method and system

Info

Publication number: CN117835257A
Application number: CN202410042970.1A
Authority: CN
Inventors: 韩琪; 刘青松; 韩海港; 王志坤; 韩冬; 武鹏飞; 张华�; 马传国; 隋敬麒; 孙宏君; 孙晨鑫; 管朔
Original assignee: Dongying Power Industry Bureau Of State Grid Shandong Electric Power Co
Current assignee: Dongying Power Industry Bureau Of State Grid Shandong Electric Power Co
Priority date: 2024-01-11
Filing date: 2024-01-11
Publication date: 2024-04-05

Abstract

The invention relates to the field of planning methods, and particularly discloses a virtual-real combined trusted WLAN networking AP pre-planning method and system, wherein the method comprises the following steps: s1, determining a target network architecture; s2, collecting requirements and information; s3, establishing a model; s4, planning a virtualized AP; s5, physical environment analysis; s6, credibility evaluation; s7, iterative optimization; s8, deployment implementation. The virtual-real combined trusted WLAN networking AP pre-planning method provided by the invention has the advantages of improving network coverage rate, optimizing network performance, facilitating management, flexibly expanding and improving safety, and is suitable for WLAN network planning and management of various scales and scenes.

Description

Virtual-real combined trusted WLAN networking AP pre-planning method and system

Technical Field

The invention relates to the field of planning methods, in particular to a virtual-real combined trusted WLAN networking AP pre-planning method.

Background

The basic flow of the existing WLAN networking is as follows: network planning and design: including determining the layout, number, power parameters of APs, and planning network topology, IP address assignment. Hardware device and network connection: corresponding wireless devices (e.g., APs, wireless routers) and network cables are purchased, the devices are connected, and network interworking is ensured. Configuring a network device: the network equipment is configured, including SSID, security policy and network address parameters. Client side connection: the client device is searched for available wireless networks and entered with the correct password or other security verification and connected to the WLAN network. Network management and maintenance: and carrying out daily management and maintenance on the network, including monitoring the network state, troubleshooting and security precaution.

Compared with the trusted WLAN networking combining virtual and real, the traditional WLAN networking has the following defects: configuration and management are complex: traditional WLAN networking requires manual configuration and management of network devices, including setting SSID, security policies, network address parameters, is complex to operate, and is prone to error. Network performance optimization is not enough: conventional WLAN networking lacks overall optimization of network performance, including the possible unreasonable situations in AP placement, configuration, and signal coverage, resulting in low network performance. The safety is lower: traditional WLAN networking is relatively low in security and is vulnerable to hacking and network intrusion. The expansibility is not enough: the expansibility of the traditional WLAN networking is relatively poor, and large-scale network deployment and user growth are difficult to support. In summary, the conventional WLAN networking has the disadvantages of complex configuration and management, insufficient network performance optimization, low security and insufficient expansibility.

Disclosure of Invention

The invention provides a virtual-real combined trusted WLAN networking AP pre-planning method for overcoming the defects of the prior art.

In order to achieve the above purpose, the technical scheme of the invention is as follows: a virtual-real combined trusted WLAN networking AP pre-planning method comprises the following steps:

S1, determining a target network architecture: the architecture of the target WLAN network is determined, including network topology, coverage, number of access users, spectrum environment, qoS requirements, security policies, and management policies.

The determining of the target network architecture is one of the important steps of the WLAN networking AP pre-planning, and the specific steps are as follows:

s1.1, determining a network topology structure: according to the actual environment and the requirements, a proper network topology structure is selected, wherein the network topology structure comprises a star type, a tree type and a mesh type, and the connection modes and the topological relations among different APs need to be considered so as to facilitate the subsequent optimization and management.

S1.2, determining coverage: the coverage area and coverage area of each AP are determined according to the actual environment and requirements. Dividing according to building structures and user distribution, and ensuring that each AP can meet coverage requirements.

S1.3, determining the number of access users: and determining the number of users accessed by each AP according to the actual environment and the requirements. The behavior habit and business demand factors of the user need to be considered so as to facilitate the subsequent capacity planning and performance optimization.

S1.4, determining a spectrum environment: and selecting a proper channel according to the actual frequency spectrum environment, and avoiding co-channel interference and adjacent channel interference. The use of channel planning tools to assist in achieving better channel allocation is contemplated.

S1.5, determining QoS requirements: and determining the required QoS level and priority according to the actual service requirement.

S1.6, determining a security policy: and determining a required security policy and a security mechanism according to actual security requirements. By means of WPA3 and WPA2 safety protocols and encryption technology, safety and confidentiality of data transmission are achieved.

S1.7, determining a management strategy: and determining a required management strategy and a management mechanism according to the actual management requirement. By means of the centralized management platform and the automatic management tool, the automatic configuration, monitoring and management of the network are realized.

S2, collecting requirements and information: information related to the network architecture is collected, wherein the information comprises building structures, electromagnetic environments, user behaviors, business requirement information, network performance indexes, security requirement information and network topology structure information, and the information is from existing network planning tools and site survey reports. The collection of information related to network architecture is an important step of performing WLAN networking AP pre-planning, specifically:

s2.1, building structure information is obtained. Building structure information includes the shape, size, building materials, floor number of the building. This information helps predict the propagation characteristics and signal attenuation of the wireless signal inside the building. Such information is obtained using existing tools of building structure models or site survey reports.

S2.2, acquiring electromagnetic environment information. Electromagnetic environment information includes frequency, power, signal interference of wireless signals. Such information is measured and collected using a spectrum analyzer, signal receiver device.

S2.3, acquiring user behavior information. The user behavior information comprises the number, distribution and movement track of the users. By monitoring and analyzing the existing network, the information is acquired, and has important significance for network optimization and management.

S2.4, acquiring service demand information. The service requirement information includes required service type, data rate and time delay. And acquiring relevant service requirement information in cooperation with the service provider.

S2.5, acquiring network performance indexes: network performance metrics include throughput, delay, packet loss rate. Such information is collected using network performance testing tools to facilitate subsequent network performance optimizations. Measurement and calculation of network performance indicators are important links in assessing network performance.

S2.6, safety requirement information: the security requirement information comprises a required security protocol and an encryption algorithm. And in cooperation with a security expert, acquiring related security requirement information.

S2.7, obtaining network topology structure information: the network topology information includes connection mode and topology relation of the AP.

S3, establishing a model. The network model of the WLAN networking AP pre-planning comprises a wireless network propagation model, an interference model, a service model, an AP position model, a channel allocation model, an AP position and channel allocation joint model and a network performance evaluation model, wherein the models are customized and optimized based on actual environment and requirements. The specific steps of the model establishment are as follows:

s3.1, establishing a wireless network propagation model, wherein the propagation model is used for predicting propagation characteristics and signal attenuation conditions of wireless signals in space.

S3.2, establishing an interference model, wherein the interference model is used for predicting interference conditions and interference influences among different APs. Existing interference models are used, including 802.11 protocol-based interference models, signal strength-based interference models.

S3.3, establishing a service model, wherein the service model is used for predicting service demands and flow distribution conditions in the network. And analyzing and modeling according to actual service demands and user behaviors, and describing by using a Simon distribution and Pascal distribution probability model.

S3.4, establishing an AP position model, and determining the position of an access point is usually the first step of WLAN design problem. The distance between the access points should not be too far or too close when selecting the location. The former case may create a coverage gap; however, the latter arrangement increases channel interference. Thus, an effective solution is to achieve the best tradeoff between coverage, throughput, and interference while taking into account the distribution of users in the environment.

S3.5, establishing a channel allocation model, wherein the channel allocation model is used for predicting interference conditions and channel quality among different channels. The channel allocation model is established by using the existing channel allocation algorithm, the channel allocation algorithm based on graph theory and the channel allocation algorithm based on simulated annealing.

S3.6, establishing an AP position and channel allocation joint model

S3.7, establishing a network performance evaluation model: the network performance evaluation model is used for evaluating performance indexes of the network, such as throughput, delay and packet loss rate. The network performance is simulated and predicted using existing network performance assessment tools or developing custom assessment models.

S4, virtualized AP planning: and simulating the layout and configuration of the APs in the virtual environment, and optimizing according to actual requirements. The virtualization technology comprises a software defined network, network function virtualization, a virtual AP simulation tool, a machine learning and artificial intelligence algorithm, a cloud computing and edge cloud cooperation technology and an automation and intelligent management tool, so that dynamic AP planning and deployment are realized. The virtualized AP planning is specifically:

s4.1, software defined networking technology: software defined networking technology separates network control and forwarding, providing a centralized network management and programmable interface. In virtualized AP planning, a virtual network is created using software defined networking techniques, and the APs are configured and managed programmatically to achieve dynamic AP planning and deployment.

S4.2, network function virtualization technology: network function virtualization technology decouples network functions from dedicated hardware devices and runs in software on a general purpose server. In the virtualized AP planning, a network function virtualization technology is used to instantiate a virtual AP, and the functions and performances of the virtual AP are configured and managed through software so as to meet the actual requirements.

S4.3, a virtual AP simulation tool: the virtual AP simulation tool simulates the behavior and performance of the AP in a virtual environment, including signal propagation, interference, throughput. By using a virtual AP simulation tool, different AP layouts and configuration schemes are simulated and evaluated to find the optimal planning scheme.

S4.4, machine learning and artificial intelligence algorithms: machine learning and artificial intelligence algorithms are used to optimize the virtual AP planning process. The network performance and user requirements are predicted by analyzing historical data and user behavior, training a model, and automatically adjusting the layout and configuration of the APs using an optimization algorithm to improve network performance and user satisfaction.

S4.5, cloud computing and edge cloud cooperation technology: cloud computing and edge cloud co-technology provides elastically extensible resource support for virtualized AP planning. By migrating the AP planning and deployment tasks to a cloud or edge cloud cooperative environment, dynamic resource allocation and expansion are realized by utilizing the resource advantages of cloud computing so as to meet network planning tasks with different scales and requirements. Cloud computing and edge cloud co-technology provides elastically extensible resource support for virtualized AP planning. By migrating the AP planning and deployment tasks to a cloud or edge cloud cooperative environment, dynamic resource allocation and expansion are realized by utilizing the resource advantages of cloud computing so as to meet network planning tasks with different scales and requirements.

S4.6, an automation and intelligent management tool: the automated and intelligent management tool simplifies the flow of virtualized AP planning and improves efficiency. By using an automatic script, an intelligent recommendation algorithm and a visual interface, manual participation and errors are reduced, and automatic AP planning and deployment are realized. Virtualized AP planning requires a combination of techniques and tools to achieve dynamic AP planning and deployment. By comprehensively considering the actual environment and the requirements, a proper virtualization technology and optimization algorithm are selected, so that the network performance is improved, the cost is reduced, and the requirements of users are met. The automated and intelligent management tool greatly simplifies the flow of virtualized AP planning and improves efficiency.

S5, physical environment analysis: the actual physical environment is analyzed, including the building structure, electromagnetic environment, signal propagation characteristics. And correcting and perfecting the virtual AP planning according to the analysis result. In virtual AP planning, it is a very important step to analyze the actual physical environment. By evaluating the building structure, electromagnetic environment and signal propagation characteristics, the actual situation is better known, and therefore the virtual AP planning is corrected and perfected. The method comprises the following specific steps:

S5.1, collecting data: it is necessary to collect data about the actual physical environment, including building block diagrams, electromagnetic environment data, signal propagation characteristics. These data are obtained by means of field measurements, surveys.

S5.2, analyzing data: the collected data is analyzed in detail. The effect of building structure on signal propagation, the extent of signal interference by electromagnetic environment, and the performance of signal propagation characteristics under various environments are analyzed.

S5.3, evaluating virtual AP planning: and evaluating the existing virtual AP planning scheme according to the analysis result. Analysis of which areas have problems of insufficient signal coverage or severe signal interference and correction and refinement of these problems are proposed.

S5.4, correcting and perfecting virtual AP planning: and correcting and perfecting the virtual AP planning according to the evaluation result. The position, number and power parameters of the APs are adjusted to optimize network coverage and signal quality. The virtual AP plan is now modified and refined based on the evaluation results. The modification and refinement includes adjusting the position, number and power parameters of the APs in order to optimize network coverage and signal quality.

S5.5, repeating the steps: if the verification and test results are not ideal, the physical environment needs to be re-analyzed, and further correction and improvement are carried out on the virtual AP planning. This process may need to be repeated until satisfactory results are obtained.

S6, credibility evaluation: in performing AP pre-planning, a trust evaluation, including an evaluation in terms of security, reliability, and performance, needs to be performed. And verifying the robustness and the safety of the network by simulating an attack scene and a performance test. In performing AP pre-planning, it is a very important step to perform a reliability assessment, including an assessment in terms of security, reliability and performance. The following are the detailed steps:

s6.1, safety evaluation: security assessment is primarily to assess the risk of a network being attacked and threatened. The security and robustness of the network are tested by simulating various attack scenarios, such as malicious attacks, denial of service attacks. At the same time, the validity of the encryption algorithm and the security protocol needs to be evaluated to ensure the security of data transmission.

S6.2, reliability evaluation: reliability assessment is mainly to assess the stability and availability of the network. The fault tolerance and recovery capabilities of the network are tested by simulating network faults and abnormal conditions, such as network disconnection and AP faults. At the same time, it is also necessary to evaluate the validity of the backup and restore policies to ensure availability and stability of the network.

S6.3, performance evaluation: performance assessment is mainly to assess the processing power and transmission speed of the network. Performance metrics and user awareness of the network are tested by performing performance tests, such as throughput tests, delay tests. At the same time, there is also a need to evaluate the validity of network architecture and protocols to ensure the performance and efficiency of the network.

S6.4, robustness assessment: the robustness assessment is mainly to assess the resistance and recovery of the network when it is under attack or abnormal conditions. The robustness and stability of the network is tested by simulating network attacks or anomalies. Meanwhile, the effectiveness of the network security monitoring and alarm system needs to be evaluated to ensure that network problems are found and handled in time.

S6.5, validation and test tools: performing the trust evaluation requires the use of various verification and testing tools, such as vulnerability scanning tools, performance testing tools, security monitoring systems. These tools help discover and address potential security risks and performance issues, thereby improving the trustworthiness and reliability of the network.

S7, iterative optimization: and according to the actual environment and the change of the demand, the AP pre-planning scheme is continuously and iteratively optimized. And combining artificial intelligence and machine learning technologies, automatic and intelligent AP planning and management are realized. Iterative optimization is the process of continuously adjusting and optimizing the AP pre-planning scheme according to the actual environment and the change of the demand. The method comprises the following specific steps:

s7.1, data collection and analysis: the actual network data such as flow data, performance indexes and user behaviors are collected and analyzed to know the actual conditions and user requirements of the network, so that data support is provided for iterative optimization.

S7.2, automatic adjustment and optimization: and (3) realizing automatic adjustment and optimization of the AP pre-planning scheme by using an automatic technology and tool. And using artificial intelligence and machine learning algorithms to automatically adjust the layout, configuration and management strategy of the AP according to actual network data and user requirements so as to realize better network performance and user satisfaction.

S7.3, intelligent decision and support: by using artificial intelligence and machine learning techniques, intelligent decision making and support for AP pre-planning schemes is achieved. Classifying users by using a clustering algorithm, and providing different AP service strategies for users of different categories; or predicting future network traffic and performance trends using the predictive model to make AP planning and adjustments in advance.

S7.4, real-time monitoring and alarming: network problems are discovered and handled in time by monitoring network status and performance indexes in real time. When abnormal conditions or performance bottlenecks occur, an alarm mechanism is triggered to inform an administrator or an automation script to perform corresponding processing and adjustment.

S7.5, continuous improvement and evaluation: iterative optimization is a continuous process that requires continuous improvement and assessment of the effectiveness and robustness of the AP pre-planning scheme. And obtaining feedback and advice by periodically performing network performance tests, security evaluation and user satisfaction investigation modes so as to further optimize the AP pre-planning scheme.

S7.6, participants: the participants include network administrators, planning specialists, data analysts, and security specialists. Different personnel participate in the iterative optimization process of AP pre-planning together according to the respective expertise and skill.

S8, deployment implementation: and applying the pre-planned AP configuration and layout to an actual WLAN network for deployment and implementation. In the deployment process, the indexes in the aspects of network performance and security need to be closely focused, and timely adjustment and optimization are needed. Deployment implementation is the process of applying a pre-planned AP configuration and layout into an actual WLAN network. The method comprises the following specific steps:

s8.1, AP deployment and installation: and deploying and installing the AP at a proper position according to the pre-planned AP layout and configuration, and ensuring that the connection and power supply of the AP and the network equipment are normal. In the deployment process, signal coverage, interference and security factors of the AP need to be considered.

S8.2, configuration management: each AP is configured and managed, including IP address, wireless parameters, security protocols. It is necessary to ensure configuration consistency, correctness and security of each AP.

S8.3, network performance test: after deployment is completed, network performance tests are carried out, including throughput, delay and packet loss rate indexes. Network performance bottlenecks and problems are found through testing, and configuration and layout of the APs are adjusted and optimized in time.

S8.4, safety evaluation: after deployment is completed, security assessment is performed, including firewall configuration, encryption protocol, access control. There is a need to ensure robustness and security of the network against unauthorized access and attacks.

S8.5, monitoring and maintaining: after deployment, the network is monitored and maintained in real time, and network problems are found and treated in time. Periodic checks of network performance indicators, security logs, and fault reports are required to ensure stability and availability of the network.

S8.6, optimizing and adjusting: and optimizing and adjusting the configuration and layout of the AP according to the actual network environment and the change of the user demand. Network performance and security are continuously improved and optimized through data collection and analysis, performance testing and security assessment modes.

S8.7, participants: the participants include network administrators, engineers, planning specialists, and security specialists. Different personnel participate in the deployment implementation and maintenance optimization process of the AP together according to the respective expertise and skills.

A system for executing the virtual-real combined trusted WLAN networking AP pre-planning method,

the system comprises a target network architecture determining module, a demand and information collecting module, a model building module, a virtualized AP planning module, a physical environment analyzing module, a credibility evaluating module, an iterative optimizing module and a deployment implementing module, and is characterized in that:

The method comprises the steps of determining a target network architecture module, and determining the architecture of a target WLAN (wireless local area network) network, wherein the architecture comprises a network topology structure, coverage area, the number of access users, a spectrum environment, qoS (quality of service) requirements, a security policy and a management policy;

the system comprises a demand and information collection module, a network architecture collection module and a network topology management module, wherein the demand and information collection module collects information related to a network architecture, the information comprises building structures, electromagnetic environments, user behaviors, business demand information, network performance indexes, security demand information and network topology structure information, and the information is from existing network planning tools and site survey reports;

the model building module comprises a wireless network propagation model, an interference model, a service model, an AP position model, a channel allocation model, an AP position and channel allocation joint model and a network performance evaluation model, wherein the network model of the WLAN networking AP pre-planning is customized and optimized based on the actual environment and the requirements;

the virtualized AP planning module simulates the layout and configuration of the APs in a virtual environment and optimizes the APs according to actual requirements; the virtualization technology comprises a software defined network, network function virtualization, a virtual AP simulation tool, a machine learning and artificial intelligence algorithm, a cloud computing and edge cloud cooperation technology and an automation and intelligent management tool, so that dynamic AP planning and deployment are realized;

The physical environment analysis module is used for analyzing the actual physical environment, including evaluating the building structure, the electromagnetic environment and the signal propagation characteristics; correcting and perfecting the virtual AP planning according to the analysis result; when virtual AP planning is performed, the analysis of the actual physical environment is a very important step; the actual situation is better known by evaluating the building structure, the electromagnetic environment and the signal propagation characteristics, so that the virtual AP planning is corrected and perfected;

the credibility evaluation module is used for carrying out credibility evaluation, including evaluation in the aspects of safety, reliability and performance, when AP pre-planning is carried out; verifying the robustness and safety of the network by simulating an attack scene and a performance test; in AP pre-planning, it is a very important step to perform a reliability assessment, including an assessment in terms of security, reliability and performance;

the module is subjected to iterative optimization, and the AP pre-planning scheme is continuously subjected to iterative optimization according to the actual environment and the change of the requirements; combining artificial intelligence and machine learning technology, realizing automatic and intelligent AP planning and management; iterative optimization is a process of continuously adjusting and optimizing an AP pre-planning scheme according to the change of the actual environment and the demand;

The deployment implementation module is used for applying the pre-planned AP configuration and layout to an actual WLAN network to deploy and implement; in the deployment process, the indexes in the aspects of network performance and safety are required to be closely focused, and timely adjustment and optimization are required; deployment implementation is the process of applying a pre-planned AP configuration and layout into an actual WLAN network.

The beneficial effects are that:

(1) Network coverage rate is improved: by carrying out detailed analysis on the actual physical environment, the influence of building structure, electromagnetic environment and signal propagation characteristic factors on signal propagation is better known, so that the layout and configuration of the AP are optimized, and the network coverage and signal quality are improved;

(2) Intelligent recommendation algorithm optimization: according to historical data, user behaviors and network performance prediction, an optimization suggestion of AP layout and configuration is given by using an intelligent recommendation algorithm, wherein the optimization suggestion comprises the position, the number and the power parameters of the APs so as to realize more efficient network performance optimization;

(3) Visual interface display: through a visual interface, the result of AP planning, network performance prediction and optimization suggestion are intuitively displayed, so that an administrator can more easily understand and make decisions;

(4) Automation and intelligent management: and an automatic script and an intelligent recommendation algorithm are used, so that the AP planning process is simplified, the efficiency is improved, and the manual participation and the error rate are reduced. Meanwhile, the visual interface is combined, so that network management and monitoring are conveniently performed;

(5) Flexibility and extensibility: the virtual-real combined trusted WLAN networking AP pre-planning method has higher flexibility and expansibility. In practical application, the layout and configuration of the AP are flexibly adjusted and optimized according to different requirements and scenes. At the same time, the network scale and capacity are conveniently expanded to accommodate the ever-increasing user demands and business developments.

(6) High network security and reliability: by introducing a trusted technology, the security and the credibility of WLAN networking are enhanced. And by utilizing a trusted computing technology, security detection and authentication are performed when the AP is started, so that the validity and the credibility of the AP are ensured. Meanwhile, the security and the credibility of the whole network are further improved by combining other security measures.

In summary, the virtual-real combined trusted WLAN networking AP pre-planning method has the advantages of improving network coverage, optimizing network performance, facilitating management, flexibly expanding and improving safety, and is suitable for WLAN network planning and management of various scales and scenes.

Drawings

FIG. 1 is a flow chart of the method of the present invention;

Detailed Description

The invention is further described below with reference to the drawings and examples.

As shown in fig. 1, a virtual-real combined trusted WLAN networking AP pre-planning method includes the following steps:

S1.5, determining QoS requirements: and determining the required QoS level and priority according to the actual service requirement. Priority scheduling and guarantee among different services are realized by means of QoS technology, such as 802.1p and WMM. The method comprises the following specific steps: identifying a business requirement: knowing the type of service required, such as voice, video, data, and their characteristics and requirements; analyzing the traffic flow: evaluating the magnitude and the change trend of the network traffic so as to allocate proper bandwidths and priorities for different services; determining a QoS level: determining required QoS levels for different services according to service requirements and flow analysis results; configuring QoS strategy: configuring QoS strategy on router and exchanger network equipment to ensure priority scheduling and guarantee between different services; monitoring and adjusting: and monitoring the configured QoS strategy to ensure the normal work of the QoS strategy, and adjusting the QoS strategy according to actual requirements.

In determining the target network architecture, the above factors need to be comprehensively considered, and trade-off and compromise are carried out according to actual situations. Meanwhile, the auxiliary decision and optimization are needed to be carried out by means of the existing network planning tools and technologies, such as network simulation and propagation models.

S2, collecting requirements and information: information related to the network architecture is collected, wherein the information comprises building structures, electromagnetic environments, user behaviors, business requirement information, network performance indexes, security requirement information and network topology structure information, and the information is from existing network planning tools and site survey reports. Collecting information related to network architecture is an important step in performing WLAN networking AP pre-planning, specifically

Among them, a building structure model tool is a digitizing tool for creating, simulating and analyzing various information of building items. It is a computable digital information used in building design and construction processes, created through three-dimensional digital techniques, that helps architects, engineers and constructors to better understand and manage building projects.

The building structure model tool simulates various factors in the building design and construction process, including geometric figure, size, material and construction process information of building components, performance, cost and safety information of a building system, and the information is automatically managed by a program system, so that various files automatically calculated by the digital information have the characteristics of mutual superposition and coincidence.

The building structure model tool not only improves collaboration efficiency, reduces risk, saves time and cost, but also predicts and solves potential problems at an early stage, thereby reducing rework and waste. The system provides a cooperative working platform for each professional design team so as to realize data sharing and information exchange and improve the design quality and efficiency.

In addition, building structure model tools also perform building performance analysis, including energy consumption, insolation, ventilation, to achieve more sustainable and environmentally friendly building designs. It also performs construction management and coordination, and construction operation and maintenance management.

The building structure model tool mainly comprises the following parts:

three-dimensional model: the core components simulate and present various aspects of a building by creating a three-dimensional model of the building in a computer. This three-dimensional model includes the geometry of the building, the structural system, the equipment and facilities.

Database: all information of the building is stored in a database including materials, dimensions, construction methods. The database is used for automatically generating drawings, simulating construction processes and calculating material consumption.

The acquisition of the frequency, the power and the signal interference parameters of the wireless signals of the electromagnetic environment information is mainly realized by the following means:

spectrum analyzer: a spectrum analyzer is an instrument for measuring the spectrum of a signal, and measures the frequency and power parameters of a wireless signal. It converts the received signal from the time domain to the frequency domain by fourier transforming it, thereby obtaining the spectrum information of the signal. The spectrum analyzer detects each frequency component in the signal, including the interference signal, and is a very important electromagnetic environment information acquisition means.

And (3) a power meter: a power meter is an instrument for measuring the power of a signal, directly measuring the power of a wireless signal. The power meter generally calculates the power of the signal by measuring the voltage and current of the signal, and is used for detecting the transmission power and the reception power parameters of the wireless signal.

Radio monitoring system: the radio monitoring system is a system for monitoring radio signals, and monitors frequency, power and modulation mode parameters of the radio signals in real time. Radio monitoring systems typically consist of a plurality of monitoring stations covering an area where wireless signals are monitored and analyzed.

Electromagnetic environment monitoring software: the electromagnetic environment monitoring software is a software tool for monitoring the electromagnetic environment, and is used for monitoring and analyzing the frequency, the power and the interference parameters of wireless signals in real time. Electromagnetic environment monitoring software is typically integrated with various sensors and monitoring devices to enable automated monitoring and data analysis.

Field intensity meter: the field intensity meter is an instrument for measuring the intensity of an electromagnetic field and measures the field intensity distribution of a wireless signal in space. Field strength instruments are commonly used to assess the coverage and network performance of wireless communication systems and also to detect interfering signals in electromagnetic environments.

Interference location and analysis system: the interference position and analysis system is a system for positioning and analyzing an interference source in an electromagnetic environment, and the accurate position and analysis of the interference source are performed by analyzing the frequency, power and modulation mode parameters of a wireless signal and combining a geographic information system and a signal processing technology.

The frequency, power and signal interference parameters of the wireless signals of the electromagnetic environment information are obtained in various ways, and proper means are selected for monitoring and analysis according to actual requirements and conditions.

S2.3, acquiring user behavior information. The user behavior information comprises the number, distribution and movement track of the users. By monitoring and analyzing the existing network, the information is acquired, and has important significance for network optimization and management. The information is acquired through monitoring and analysis of the existing network, and the specific steps are as follows:

s2.3.1, data collection: relevant data in the network is collected, including user equipment information, network traffic data, signal strength data, which are collected through network monitoring equipment, application channels on the user equipment.

S2.3.2, data preprocessing: the collected raw data needs to be preprocessed, including data cleaning, format conversion and data compression steps. The preprocessing aims to remove noise and redundant information in the data and improve the quality and usability of the data.

S2.3.3, data analysis: the pre-processed data were further analyzed. The number and distribution condition of the users are obtained by carrying out statistics and analysis on the user equipment information; and analyzing the network flow data and the signal intensity data to obtain the movement track and behavior habit information of the user.

S2.3.4, data visualization: in order to facilitate understanding and analysis of user behavior information, the analysis results are visually displayed. Displaying the distribution and movement track of the user in the form of thermodynamic diagrams and track diagrams; and displaying the quantity and behavior habit information of the users in the form of pie charts and bar charts.

S2.3.5, real-time monitoring: in order to ensure the real-time performance and accuracy of the user behavior information, the network needs to be monitored in real time. By monitoring network flow and signal strength parameters in real time, the problems in the network are found and solved in time, and meanwhile, the user behavior information is acquired and analyzed in real time.

S2.3.5, data mining: in addition to analyzing and visually displaying the existing data, deeper user behavior information is also discovered through a data mining technology. And discovering group characteristics and behavior pattern information of the user by using cluster analysis and association rule technology.

Acquiring and analyzing user behavior information is one of the important steps of network optimization and management. By monitoring and analyzing the existing network and combining data preprocessing, data analysis and data visualization technical means, user behavior information is effectively acquired and analyzed, and powerful support is provided for network optimization and management.

S2.4, acquiring service demand information. The service requirement information includes required service type, data rate and time delay. And acquiring relevant service requirement information in cooperation with the service provider. The service requirement information is an important basis for network planning and design, and in order to acquire relevant service requirement information, the service requirement information cooperates with a service provider, and the specific steps are as follows:

s2.4.1, determining a business requirement investigation target: the goal of the traffic demand investigation needs to be clarified, including determining what type of traffic is needed, what data rate and latency needs to be met. These goals will provide directions and guidance for subsequent investigation.

S2.4.2, communicate with service providers: communication with the service provider is a key step in acquiring the service requirement information. Service providers are informed of the type of service they offer, the data rate, the delay parameters, and the specific requirements and constraints of these parameters. At the same time, service providers are also informed of their network architecture and deployment conditions to better understand the service requirements.

S2.4.3, collecting business documents and materials: in the process of communicating with service providers, they are required to provide relevant service documents and materials, including service specifications and technical specifications. These documents and materials will provide important references for subsequent analysis and design.

S2.4.4, on-site investigation: if the conditions allow, the site investigation is carried out, and the network architecture, the equipment configuration and the service deployment condition of the service provider are known in depth. Through on-site investigation, the service requirements and the limiting conditions of the service provider are more intuitively known, and more accurate information is provided for subsequent network planning and design.

S2.4.5, data arrangement and analysis: the collected business requirement information needs to be sorted and analyzed. The collected data is classified, counted and analyzed to extract useful information including data rate and delay requirements of various service types, network architecture and deployment condition of service provider.

S2.4.6, making network planning and design scheme: and according to the service demand information after arrangement and analysis, a corresponding network planning and design scheme is formulated. The network planning and design scheme meeting the actual requirements is made by considering the requirements and the limiting conditions of various service types and the network architecture and equipment configuration factors.

S2.4.7, confirm with service provider: finally, the service provider needs to confirm whether the formulated network plan and design scheme meet the service requirements. If any problem or deficiency exists, timely adjustment and improvement are needed, and network planning and design schemes can meet the actual demands of service providers.

Cooperation with a service provider is an important way to obtain service demand information. Related business demand information is obtained through communication, document and data collection and on-site investigation means, and powerful support is provided for network planning and design.

S2.5, acquiring network performance indexes: network performance metrics include throughput, delay, packet loss rate. Such information is collected using network performance testing tools to facilitate subsequent network performance optimizations. Measurement and calculation of network performance indicators are important links in assessing network performance. The following is a specific step of collecting network performance indicators:

s2.5.1, select network performance test tools: appropriate network performance testing tools are selected, including Wireshark, iperf, ping, with appropriate tools being selected according to actual requirements.

S2.5.2, determining test targets and ranges: the network range and the target to be tested are determined, including testing the connection performance between specific devices and testing the throughput of the whole network.

S2.5.3, performing the test: network performance testing is performed according to the specifications and operating guidelines of the selected tool. The testing process comprises the following steps:

a. selecting a proper test time: the testing is avoided in the peak period or the network congestion period so as to ensure the accuracy of the testing result;

b. Determining test parameters: according to the test target and the range, setting proper test parameters including test duration and data packet size;

c. collecting test data: in the test process, relevant test data including throughput, delay and packet loss rate indexes are collected;

throughput (Throughput) refers to the amount of data that a network successfully transmits within a particular time period. Calculated using the following formula: throughput = (total data amount/test time) ×8 (bits/byte), where total data amount refers to the sum of all data amounts transmitted during network performance test and test time refers to the duration of the test.

Delay (Latency) refers to the time required for a network to transmit data from a sender to a receiver. Calculated using the following formula: delay= (transmission time/(transmission time+round trip time)). 2, where transmission time refers to the time required to send a packet to receive a packet, and round trip time refers to the time required to send a packet from the sender to the receiver to return a response.

Packet Loss Rate (Packet Loss Rate) refers to the ratio of the number of packets lost during network transmission to the total number of packets. Calculated using the following formula: packet loss rate= (number of packets lost/total number of packets) 100%

S2.5.4, analytical test results: the collected test data is collated and analyzed to extract useful information and indicators.

Among them, the security protocol and the encryption algorithm in the security requirement information are information necessary for ensuring network security.

Security protocol: the security protocol is a specification for establishing, managing and terminating secure connections in internet communications. It specifies how the parties involved in the communication should operate to ensure the security of the data. Security protocols include SSL (Secure Sockets Layer), TLS (Transport Layer Security), and IPSec (Internet Protocol Security).

SSL is a protocol that provides communication security, which establishes a secure connection between a client and a server, ensuring confidentiality and integrity of data. TLS is a successor to SSL, which provides greater security, including protection of message integrity. IPSec is a network layer-based protocol that provides end-to-end security protection, supporting data encryption, authentication, and integrity check functions.

Encryption algorithm: an encryption algorithm is a mathematical method that converts plaintext data into unreadable ciphertext. The encryption algorithm includes a symmetric encryption algorithm and an asymmetric encryption algorithm.

Symmetric encryption algorithms use the same key to encrypt and decrypt data. The algorithm has the advantages of high speed and high security, but key management is difficult. Symmetric encryption algorithms include DES (Data Encryption Standard), 3DES and AES (Advanced Encryption Standard).

Asymmetric encryption algorithms use two different keys: one public key is used to encrypt data and the other private key is used to decrypt data. The advantage of this algorithm is high security but slower speed. Asymmetric encryption algorithms include RSA (Rivest-Shamir-Adleman), ECC (Elliptic Curve Cryptography), and elliptic curve cryptography.

In practical applications, various security protocols and encryption algorithms are commonly used in combination to ensure network security. In HTTPS, the SSL/TLS protocol is used to encrypt communications, while a symmetric encryption algorithm is used to encrypt transmitted data. The selection of the appropriate security protocols and encryption algorithms requires evaluation and selection according to the specific application scenario and security requirements.

The specific steps of cooperation with the security specialist are as follows:

s2.6.1, determining a security requirement investigation target: the goal of explicit security requirement investigation is needed, including determining what type of security protocol and encryption algorithm is needed. These goals will provide directions and guidance for subsequent investigation;

s2.6.2, communicate with security specialists: communication with security specialists is a key step in acquiring security requirement information. Security specialists are informed of the security protocols and encryption algorithms they recommend, as well as the specific requirements and constraints of these protocols and algorithms. At the same time, security specialists are also informed of their opinion and advice on network security in order to better understand the security requirements;

2.6.3, collecting security documents and materials: in communicating with security specialists, they are required to provide relevant security documents and profiles, including security assessment reports, security standards and specifications. These documents and materials will provide important references for subsequent analysis and design;

s2.6.4, on-site investigation: if the conditions allow, the site investigation is conducted, and the security architecture, the security equipment and the security measures of the network are known in depth. Through on-site investigation, the safety requirement and the limiting condition of the network are more intuitively known, and more accurate information is provided for subsequent safety planning and design;

S2.6.5, security risk assessment: in the process of acquiring the security requirement information, security risk assessment is required. Through security analysis and evaluation of the network, potential security risks and threats are identified, and corresponding countermeasures are formulated;

s2.6.6, making a safety plan and design scheme: and (5) according to the sorted and analyzed safety requirement information, a corresponding safety plan and design scheme are formulated. The requirements and the limiting conditions of various security protocols and encryption algorithms, as well as network architecture and equipment configuration factors need to be considered, and security planning and design schemes which meet the actual requirements are made;

s2.6.7, and security expert validation: finally, the security expert needs to confirm whether the formulated security plan and design scheme meet the security requirement of the network. If any problem or deficiency exists, timely adjustment and improvement are needed, and the safety planning and design scheme can meet the actual requirement of the network.

S2.7, obtaining network topology structure information: the network topology information includes connection mode and topology relation of the AP. Using a network simulation tool to simulate and predict the performance and behavior of a network topology, the specific steps are as follows:

S2.7.1, determining a network topology: the network topology structure, including the connection modes and positions of various network devices (such as routers, switches and servers) is determined by drawing a network topology diagram.

S2.7.2, configuring a network device: after determining the network topology, the network device needs to be configured. This includes setting IP address, port number, device type parameters for each device.

S2.7.3, adding and configuring security protocols and encryption algorithms: depending on security requirements, appropriate security protocols (e.g. SSL, TLS) and encryption algorithms (e.g. AES, RSA) need to be added. This requires a corresponding security protocol and encryption algorithm to be configured on each network device.

S2.7.4, analog network traffic: in order to test the performance and behavior of the network topology, it is necessary to simulate network traffic. This is accomplished by generating a network traffic model or using existing network traffic data.

S2.7.5, running simulations and collecting data: the network simulation tool is started, a simulation is run, and relevant performance data such as throughput, delay, packet loss rate are collected.

S2.7.6, analytical data: analyzing the collected data and evaluating the performance and behavior of the network topology. This includes identifying potential performance bottlenecks, safety hazards.

S2.7.7, optimization and tuning: and optimizing and adjusting the network topology structure and related parameters according to the analysis result. This may include changing the connection of the network device, adjusting the security protocol and setting of the encryption algorithm.

S2.7.8, repeated simulation and data analysis: repeating the above steps until satisfying network performance and security requirements are reached.

Network simulations are effective tools to evaluate and predict network performance and behavior, but they do not completely replace testing and verification of actual networks. Therefore, prior to actual deployment, actual testing and verification of the network is also required.

In wireless communications, a wireless network propagation model is used to predict the propagation characteristics and signal attenuation of wireless signals in space. Including a path loss model and a propagation model.

The distance path loss model is a propagation model that takes into account the effects of obstacles and reflections in the real environment.

Power of received signal according to distance path loss modelPower of the transmitted signal>Distance->And the path loss index n has the following relationship:

/>

wherein,is the reference distance, typically 1 meter. The path loss index n is a constant greater than 2, depending on the environment and topography.

The distance path loss model is suitable for wireless communication in urban environments and complex terrain. In this model, the signal power gradually drops with increasing distance, but at a slower rate than in the free space propagation model. This suggests that in urban environments, the signal may travel farther and have more reflection and scattering paths.

The signal propagation model is further derived from the distance path loss model,

in practice, the optimization of AP placement should be performed prior to AP deployment, and a suitable signal propagation model is selected to predict RSS measurements at any reference point, where the signal propagation model is used to describe indoor propagation of the wireless network, and the specific mathematical model is:

wherein,is the average path loss at distance d from the AP, < >>Is +.>Average path loss at >Is the path loss index,/">Is the number of class i disorders between the current AP and receiver pair, there are m disorders in total, +.>Is the penetration loss of the i-th type of barrier.

S3.2, establishing an interference model, wherein the interference model is used for predicting interference conditions and interference influences among different APs. Existing interference models are used, including 802.11 protocol-based interference models, signal strength-based interference models. In wireless networks, interference is an important problem that affects the quality and stability of the transmission of wireless signals. The following is a detailed description of the 802.11 protocol-based interference model and the signal strength-based interference model:

the interference model based on the 802.11 protocol is a wireless interference model aiming at the 802.11 standard and variants thereof. The model takes into account basic operation and signaling mechanisms in 802.11 Wireless Local Area Networks (WLANs), including CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) mechanisms and hidden node problems.

Based on the interference model assumption of the 802.11 protocol, when two or more APs transmit data simultaneously, they may collide, resulting in data transmission failure. Such collisions are avoided by the CSMA/CA mechanism. The CSMA/CA mechanism requires the AP to monitor the channel before transmitting data, and if the channel is idle, then transmitting data; if the channel is busy, it is tried again after a period of time. Hidden node problems are also an important consideration in interference models based on the 802.11 protocol. A hidden node problem refers to the fact that in some cases one node may not hear the signal of another node, but hear the signal of the other node. This may result in collisions and data transmission failures. The interference model based on the 802.11 protocol is suitable for the 802.11 WLAN environment, and helps analyze and optimize the performance and stability of the network.

The interference model based on signal strength is a model that predicts interference conditions based on the strength of wireless signals. The model assumes that two or more APs may interfere with each other when the signal strength transmitted by them is sufficiently strong.

The signal strength based interference model typically uses a signal strength threshold to determine whether interference is present. Two or more APs may interfere with each other if their transmitted signal strengths exceed a certain threshold. This threshold is adjusted according to the environment and device type. The interference model based on the signal intensity is suitable for application scenes such as a wireless sensor network and the Internet of things, in which the signal intensity needs to be measured and controlled. By measuring and comparing signal strengths, the model provides information about interference conditions and effects, helping to optimize configuration and parameter settings of the network.

Simoene distribution: the simonine distribution is a discrete probability distribution that describes the number of events that occur in a fixed time interval. In a network, simoun distribution is used to describe the number of event occurrences of network traffic Comprising network request, packet arrival, probability thereof +.>The calculation formula is as follows: />

Wherein the method comprises the steps ofIs the average number of occurrences of an event per unit time.

When using the simon distribution for traffic modeling, it is necessary to determine the average number of occurrences and the time interval. The average occurrence times are estimated according to historical data or service demands, and the time interval is set according to actual service scenes.

Pascal distribution: the pascal distribution is a discrete probability distribution describing the probability distribution of the number of successes in n independent yes/no trials. In the network, pascal distribution is used for describing the distribution situation of network traffic, including the click rate and the download rate of a user accessing a webpage.

The calculation formula is as follows:

where C (n, k) is the number of combinations, p is the probability of success of a single test, and n is the number of tests. When using pascal distribution for business modeling, the number of tests n and the success rate p need to be determined. The test times n are estimated according to historical data or service demands, and the success rate p is set according to actual service scenes.

A general explanation of the AP location problem is defined as follows, accessing a 2D geographic map denoted a, which depicts the location of the required areas including libraries, laboratories, cafes, hotspots. Assuming a is a square area that is discretized into square cells, the units are defined as normalized physical distances (e.g., 1 meter), area a is a square with sides equal to n units, each square cell of a will be referred to by the centroid of a, which means that an access point or test point is located at the centroid of a cell containing p when the access point or test point is located at point p e a. Consider also a set of Test Points (TPs) located in a, denoted T. Each test point represents the user's needs in the area and must be covered by at least one access point.

The goal is to find an access point deployment solution to the following multi-objective optimization problem:

1. minimizing the number of deployed access points,

2. each test point is guaranteed to be within the coverage range of at least one access point.

Expressed as a set coverage problem, defined by a given set T, the main purpose of which is to find a familyIs a subset of (i.e->,/>) Its minimum radix is such that- >。

Definition of binary variablesIf and only if the access point is located at point j +.>Equal to 1, otherwise equal to 0, each variable +.>If test point i is within the coverage area of the access point at point jEqual to 1, if the Received Signal Strength Indication (RSSI) generated by the radio signal generated by AP i and received by TP j is above a minimum power threshold +.>And the test point i is in the coverage range of the AP i.

When two nodes on opposite sides of a located AP hear activity from the AP, but cannot hear activity from each other due to distance or abstraction, problems of hidden terminals occur, transmit power and receive power (respectivelyAnd->) Is related by the following formula:>

wherein,is the distance separating TP j from its serving AP i, K is a dimensionless constant, empirically determined, sometimes assumed to be equal to the reference distance +.>Free space attenuation at λ is the path loss index. Given the parameters defined above, the AP deployment problem is defined as:

。

s3.5, establishing a channel allocation model, wherein the channel allocation model is used for predicting interference conditions and channel quality among different channels. The channel allocation model is established by using the existing channel allocation algorithm, the channel allocation algorithm based on graph theory and the channel allocation algorithm based on simulated annealing. . The implementation steps are described in detail below:

Graph theory-based channel allocation algorithm, which is a method for solving the channel allocation problem by using the dyeing problem in the graph theory. The basic idea is to represent the network topology as a graph and then dye the nodes to achieve channel allocation that minimizes interference.

The realization steps are as follows: (1) constructing a network topology graph: according to the network topology, an undirected graph is constructed in which nodes represent APs or users and edges represent channels. (2) defining a staining function: a dyeing function is defined to map each node onto a channel to achieve channel allocation that minimizes interference. (3) calculating an interference matrix: an interference matrix is calculated based on the network topology and the channel allocation scheme, wherein each element represents the interference situation between two channels. Interference matrix: r= (r_ij) where r_ij represents the interference situation between channel i and channel j.

(4) Solving the dyeing problem: and dyeing the network topological graph by using a dyeing problem solving method in graph theory, so that adjacent nodes allocate different channels as much as possible, and simultaneously, the total interference in an interference matrix is minimized. Dyeing problem objective function: minimize R F (the Frobenius norm of the minimized interference matrix). (5) output channel allocation scheme: and outputting the channel allocated by each node according to the dyeing result. Constraint conditions: the channel allocations are as different as possible for neighboring nodes.

The channel allocation algorithm based on the simulated annealing is a method for carrying out channel allocation by using the idea of the simulated annealing. The algorithm finds the optimal solution by continually iterating and adjusting the channel allocation scheme.

The realization steps are as follows: (1) initializing: and randomly initializing a channel allocation scheme according to the network topology structure and service requirements. (2) calculating an objective function: according to the current channel allocation scheme, an objective function, namely the Frobenius norm of the interference matrix, is calculated. Objective function: minimize R F (the Frobenius norm of the minimized interference matrix). (3) random adjustment scheme: a node and a channel are randomly selected and switched from the current channel to the new channel. (4) calculating a new objective function: a new objective function is calculated based on the new channel allocation scheme. (5) judging acceptance or rejection: comparing the values of the new objective function and the old objective function, and accepting the new scheme if the new scheme is better; otherwise, accept the new scheme with a certain probability. The probability formula is p=exp ((e_old-e_new)/T), where e_old and e_new represent the objective function values of the old and new schemes, respectively, and T represents the current temperature. (6) updating the temperature: and reducing the temperature according to the temperature updating rule of the simulated annealing algorithm. (7) termination condition: judging whether a termination condition is reached (such as reaching the maximum iteration times or the temperature is lower than a certain threshold value), if so, terminating the algorithm, and outputting the current optimal solution; otherwise, returning to the step 2 to continue iteration.

Channel allocation model to complete the WLAN design process, channels must be allocated to installed access points to ensure good communication quality between the access points and their associated users. In this section, the channel allocation problem will be formulated in the case of limited and overlapping frequency channels. The output of the AP location problem is a set of APs, denoted asFocusing now on assigning radio channels to the final WLAN topology, let D be the set of available frequencies, defining the frequency assignment problem as selecting a set of frequencies to minimize the total interference per access point, AP->For AP->Induced transient disturbance->Can be expressed as:

wherein,is at AP->Perception of where->Signal power intensity,/->Is a suppression factor characterizing two adjacent channels +.>And->Overlapping portions therebetween. />And->AP->And->Is provided.

The channel allocation problem is now expressed as follows:

the objective function is to minimize the instantaneous interference of the entire APWhile the constraint indicates that only one channel needs to be +_ provided that the selected channel has to be selected in the set of available frequencies>Assigned to each AP to reduce interference at TP locations。

S3.6, establishing an AP position and channel allocation joint model

Combining AP location and channel allocation from an optimization standpoint, the AP location and channel allocation are formulated as a global optimization problem, which is combined and handled together.

The goal is to increase the throughput per TP, which is directly related to SINR. At TP j, SINR is given by:

wherein,is the thermal noise power; />Is the received power transmitted by the AP server i, which other APs consider as interference sources +.>，/>，/>When two different channels are used +.>And->And an inhibitor of the same.

Improving network performance by increasing the SINR of the TP locations is related to channel allocation problems. The latter modeled as constraint satisfaction problem, where the goal is to meet the minimum threshold required for each TP，

，

If the cumulative interference is minimized and kept below acceptable limits, the SINR at TP j is increased, expressed as:

the sum of the accumulated interference must be below a specified thresholdEach interfering signal contributing to TPj must be below a predetermined threshold, these constraints being reduced to the binary constraint: -j>

Therefore, in order to reduce the interference impact at TP j, it is important to increase the minimum separation of the electromagnetic spectrum between the channels allocated to the AP pair. This targets channel allocation to allocate one frequency for each AP while minimizing interference. The goal is to design a WLAN that optimizes the following goals:

1. minimizing the number of deployed access points,

3. Maximizing the nominal throughput of TP locations.

The formula for the multi-objective problem is as follows:

the first objective function aims to minimize the number of APs deployed, while the second objective function seeks to maximize SINR per TP, the first constraint specifying that one TP is covered at least once. The second constraint ensures that if the perceived power of the TP is greater than or equal to the threshold valueTP is covered.

Initial APs deployment, channel allocation should be enhanced to fulfill the requirements of the defined multi-objective problem, a virtual force based wireless lan planning algorithm is developed, a robust and fast heuristic based on adjusting the location of deployed access points, the basic principle is to move the access points to better locations, define a potential field to represent targets and constraints, and formulate motion such that the derived virtual force moves the AP from a high potential state to a low potential state, although this approach is widely used in a variety of applications, each AP i is subject to forceAction of force->Is the gradient of the scalar potential field U (i). />

Scalar potential field function depends on AP positionThe AP moves using the force introduced by the potential field, which is evaluated at the AP location. Two virtual forces are constructed between the TPs and the APs, so that a subset of the TPs repel or attract the associated APs. These two driving forces are derived from the potential repulsive fields +. >And potential attraction->。

Defining the potential repulsive field function in such a way that each AP node is subject to the forces exerted by a set of TPs covered by the node but not associated with it, the goal being to minimize the effect of interference on a subset of TPs located in the interference region, meaning that AP i must be repelled until the power it generates becomes negligible, considering only that this decision may introduce undesirable consequences, including increasing the distance between the associated AP i and its associated TPs, or rejecting AP i entirely outside of environment a, which may result in too small a network scale, defining the repulsive potential field as follows:

the summation is the set of all the TPs nodes that are within but not associated with the interference region of AP node iGo on, ->Is the signal-to-interference-and-noise ratio calculated in TP j served by AP i, and +.>Is the required SINR level. The repulsive force of the x-axis is expressed as:

by analogy with the repulsive force component according to the x-axis, the component according to the y-axis is deduced, thus obtaining:

deriving its expression taking into account the attractive potential fieldSuch that each AP node is surrounded by its associated set of TPsAttraction to meet the required +.>While achieving the optimal position. The following formula is presented to represent the attractive potential field while the virtual force it derives attempts to bring the APs to the center of gravity of the TPs to which it is attached.

Calculation of virtual force component by interpolation equationAnd->：

/>

The forces are derived and the position and orientation of a given AP relative to the reference frame can be calculated. According to the previous expression, there are two parameters to control in the position adjustment process, amplitude and direction. Notably, there are two opposing forces, and the direct application of the calculated force also introduces oscillations in the solution. The position adjustment strategy is to keep the AP moving gradually to find the equilibrium position, moving the AP by one unit (1 m in the example). Coverage and throughput are two criteria that determine whether to grant or prohibit AP movement. So it is checked at each algorithm iteration. The idea employed here is to apply virtual forces alternately, so that only one virtual force is considered per iteration. Virtually moving several access points at a time. However, the goal of converging to a globally optimal solution is to grant movement of only one AP, which significantly increases throughput in the network. The AP is iteratively processed, so for each iteration, the potential AP locations are determined, as well as the gain of nominal throughput by applying a virtual force. The gains provided by the movements of each AP are compared and the one that maximizes the total throughput is authorized. The movement is performed and a test has to be performed in order to check for changes in the interferograms. If the interference pattern changes, a new frequency allocation must be provided, otherwise the existing frequency allocation is maintained. The same process is repeated, this time using virtual forces that were not used in the previous iteration. The algorithm stops once it cannot further increase the throughput, or when it reaches a maximum predefined number of iterations. The interferogram does not change in each iteration, considering the limited step size of the movement, and therefore, for practical reasons, the frequency of allocation continues to be readjusted when the final position is obtained. The location of each access point is adjusted to increase the throughput of the network, attempting to place APs in an iterative fashion using alternately attractive and repulsive virtual forces. The attractive virtual force attempts to place the AP at the center of gravity of its associated set of TPs. Nulling the virtual force positions the AP away from the interfering AP. Only one point represents the center of gravity of a set of TPs and a set of points in the environment under consideration, where the interference from neighboring APs is low. In an attempt to find a compromise from this set of points, an AP is placed very close to its associated TPs and very far from interfering APs.

The network performance assessment model includes:

benchmark test model: benchmark models are a way to evaluate network performance through actual measurements. The delay, packet loss rate, and bandwidth index of the network are measured using existing network performance testing tools, such as ping, traceroute, iperf. The method is suitable for evaluating the basic performance of the network, but attention is paid to the limitations of the test tools, such as the test range and the size of the test data packet.

Simulation model: a simulation model is a method of evaluating network performance by modeling network traffic and topology. Network simulation software such as NS-2 and MATLAB is used for constructing a network model and simulating different traffic modes and topological structures so as to evaluate the performance index of the network. The method simulates complex network environment and traffic patterns, but requires full knowledge of network topology and traffic patterns.

Machine learning model: the machine learning model is a method of predicting network performance through a machine learning algorithm. The method requires collecting a large amount of network performance data and using machine learning algorithms, such as support vector machines, neural networks, to train the model and predict the performance index of the network. This approach handles complex network environments and traffic patterns, but requires full consideration of data quality and algorithm accuracy.

Creating a virtual network by using a software-defined network technology in the virtualized AP planning, and configuring and managing the AP in a programming mode to realize dynamic AP planning and deployment, wherein the method comprises the following specific steps of:

s4.1.1, determining network requirements: including the type of traffic, topology, security requirements that need to be supported.

S4.1.2, constructing a virtual network: a virtual network is created on a virtualized platform using software defined networking technology and a virtual AP is configured.

S4.1.3, defining network behavior: through the OpenFlow protocol, the behavior of the AP is dynamically configured and managed according to service requirements and network states.

S4.1.4, realizing flow control: and dynamically adjusting the flow path and the load balancing strategy according to the service requirement and the network state by utilizing the centralized control capability of the software-defined network controller.

S4.1.5, monitoring and optimization: the monitoring function of the network controller is defined by software, the network state and the service requirement are analyzed in real time, the network configuration and the behavior are dynamically adjusted, and the network performance is optimized.

In a word, through the software-defined network technology, more flexible and intelligent network management and control are realized, and the continuously-changing service demands are met.

The virtual AP is instantiated by using a network function virtualization technology in the virtual AP planning, and functions and performances of the virtual AP are configured and managed through software so as to meet actual requirements, and the method specifically comprises the following steps:

S4.2.1, determining network function requirements: and analyzing the traffic types, topological structures and security requirements to be supported, and determining the required network functions.

S4.2.1 selecting a proper network function virtualization platform: a network function virtualization platform is selected that has a virtualization function that is capable of supporting running network functions on a generic server.

S4.2.3 instantiating a virtual AP: a Virtual Machine (VM) is created on the network function virtualization platform and virtual AP software is installed and configured on the virtual machine.

S4.2.4, configuring virtual AP functions: according to actual requirements, the functions and the performances of the virtual AP are configured through software. This may include setting wireless parameters (e.g., frequency, power, modulation), configuring Access Control Lists (ACLs), enabling encryption and authentication.

S4.2.5, testing and validation: and testing the functions and the performances of the virtual AP on the virtual machine, ensuring the normal operation of the virtual AP and meeting the actual requirements.

S4.2.6, deployment and monitoring: and deploying the virtual machine to a corresponding server, and monitoring the performance and the state of the virtual AP through a network monitoring tool.

By using network function virtualization technology, more flexible and efficient AP planning and management is achieved. The functions and performances of the virtual APs are dynamically instantiated, configured and adjusted according to actual requirements to meet changing business requirements. Meanwhile, as the virtual AP is realized by software, the cost is reduced, the expandability is improved, and the energy consumption is reduced.

S4.3, a virtual AP simulation tool: the virtual AP simulation tool simulates the behavior and performance of the AP in a virtual environment, including signal propagation, interference, throughput. By using a virtual AP simulation tool, different AP layouts and configuration schemes are simulated and evaluated to find the optimal planning scheme. The steps of simulating and evaluating using the virtual AP simulation tool are as follows:

s4.3.1, defining a simulation scene: in the virtual simulation tool, the required simulation scene is defined, including spatial layout, buildings, roads, vegetation environment elements. At the same time, parameters of the wireless device such as transmit power, antenna height and gain need to be set.

S4.3.2, configuring a virtual AP: in the simulation scenario, the number, location and wireless parameters of the virtual APs are configured. Different configuration schemes are set according to actual requirements so as to simulate and analyze.

S4.3.3, running simulation: the virtual AP simulation tool may simulate signal propagation, interference, throughput wireless communication processes by starting the simulation process. During this process, simulation results are observed and recorded.

S4.3.4, analysis simulation results: and analyzing the performances of different AP layouts and configuration schemes according to simulation results. This includes signal coverage, interference conditions, throughput. And (5) finding an optimal AP planning scheme through comparison and analysis.

S4.3.5, optimizing the planning scheme: and optimizing the layout and configuration scheme of the AP according to the analysis of the simulation result. Consider adjusting the position of APs, increasing or decreasing the number of APs, changing wireless parameters.

S4.3.6, repeating the simulation process: after optimizing the planning scheme, repeating the simulation process, and analyzing the optimized scheme performance again. Through multiple iterations and optimizations, the optimal AP planning scheme is gradually approached.

The virtual AP simulation tool provides a near real simulation environment, but still has some errors. Therefore, when using simulation results, actual testing and verification are required to ensure the accuracy and effectiveness of the planning scheme.

S4.4, machine learning and artificial intelligence algorithms: machine learning and artificial intelligence algorithms are used to optimize the virtual AP planning process. The network performance and user requirements are predicted by analyzing historical data and user behavior, training a model, and automatically adjusting the layout and configuration of the APs using an optimization algorithm to improve network performance and user satisfaction. The following are steps for optimizing a virtual AP planning process using machine learning and artificial intelligence algorithms:

s4.4.1, data collection: data is collected from historical network performance data, user behavior data, and environmental data for training and optimizing models.

S4.4.2, feature extraction: useful features are extracted from the collected data, which features are to be used in constructing a machine learning model. Extracting network traffic, user density and equipment type characteristics.

S4.4.3, model selection and training: a machine learning or artificial intelligence model is selected that suits the problem and the model is trained using the extracted features. A neural network, a decision tree, and a support vector machine model are selected.

S4.4.4, prediction and optimization: and predicting by using the trained model, and automatically adjusting the layout and configuration of the AP according to the prediction result. This is achieved by the following steps: a. predicting network performance: and inputting the current AP layout and configuration by using the trained model, and predicting the network performance. This helps to understand network performance under the current layout and configuration. b. Analyzing the predicted result: bottlenecks and potential problems of the network are analyzed based on the predicted network performance. If the prediction results show that the network throughput is low, it may be necessary to increase the number of APs or adjust the configuration to improve performance. c. Automatically adjusting AP layout and configuration: and automatically adjusting the layout and configuration of the AP by using an optimization algorithm according to the analysis result. Genetic algorithm, ant colony optimization algorithm are used to find the optimal AP layout and configuration combination.

S4.4.5, real-time monitoring and adjustment: after automatic adjustment is implemented, network performance and user satisfaction need to be monitored in real time to evaluate the effect of the adjustment. If network performance and user satisfaction are not improved, the model needs to be reselected or model parameters need to be adjusted, and the process is repeated. The specific calculation formula depends on the machine learning and artificial intelligence algorithms used and the specific optimization algorithm. In selecting and using these algorithms, adjustments and optimizations are required according to specific problems and data.

S4.5, cloud computing and edge cloud cooperation technology: cloud computing and edge cloud co-technology provides elastically extensible resource support for virtualized AP planning. By migrating the AP planning and deployment tasks to a cloud or edge cloud cooperative environment, dynamic resource allocation and expansion are realized by utilizing the resource advantages of cloud computing so as to meet network planning tasks with different scales and requirements. Cloud computing and edge cloud co-technology provides elastically extensible resource support for virtualized AP planning. By migrating the AP planning and deployment tasks to a cloud or edge cloud cooperative environment, dynamic resource allocation and expansion are realized by utilizing the resource advantages of cloud computing so as to meet network planning tasks with different scales and requirements. The method comprises the following specific steps:

S4.5.1, defining cloud or edge cloud collaborative environments: and selecting a proper cloud computing platform or an edge cloud cooperative solution, and defining the required resource types, quantity and performance requirements.

S4.5.2, migration AP planning and deployment tasks: the AP planning task is migrated to a cloud or edge cloud collaborative environment, which includes the creation, configuration and management tasks of the virtual AP.

S4.5.3 dynamic resource allocation and expansion: and the resource advantages of cloud computing are utilized, and computing, storage and network resources are dynamically allocated and expanded according to network planning tasks with different scales and requirements.

S4.5.4, monitoring and management: and monitoring the resource use condition of the cloud or the edge cloud cooperative environment and the execution state of the AP planning task, and carrying out necessary adjustment and management.

S4.5.5, optimization and tuning: and optimizing and adjusting the AP planning task and the resource allocation strategy according to the actual requirements and performance so as to improve the network performance and the resource utilization rate. S4.5.6 current task size: the type and amount of resources required are determined based on the current network size and requirements.

S4.5.7, historical data and analysis results: and predicting network performance and resource requirements in a future period of time by using the historical data and the analysis result.

S4.5.8 resource availability and cost: the most suitable resources are selected for allocation, taking into account the available cloud computing resource types, amounts and costs.

S4.5.9, load balancing and scalability: considering load balancing and extensibility requirements, resources are distributed among multiple virtual machines or containers to achieve better performance and extensibility. Through cloud computing and edge cloud cooperation technology, more flexible, efficient and elastic virtualized AP planning and management are realized. This helps network administrators better handle network planning tasks of different scales and demands, improving network performance and resource utilization.

S4.6, an automation and intelligent management tool: the automated and intelligent management tool simplifies the flow of virtualized AP planning and improves efficiency. By using an automatic script, an intelligent recommendation algorithm and a visual interface, manual participation and errors are reduced, and automatic AP planning and deployment are realized. Virtualized AP planning requires a combination of techniques and tools to achieve dynamic AP planning and deployment. By comprehensively considering the actual environment and the requirements, a proper virtualization technology and optimization algorithm are selected, so that the network performance is improved, the cost is reduced, and the requirements of users are met. The automated and intelligent management tool greatly simplifies the flow of virtualized AP planning and improves efficiency. The following are specific steps for AP planning using these tools:

S4.6.1, determining the requirements and objectives: the requirements and objectives of AP planning, including network coverage, throughput, user density, are well defined.

S4.6.2 selecting appropriate automation and intelligent management tools: based on the requirements, a tool is selected that can support automation scripts, intelligent recommendation algorithms, and visualization interfaces.

S4.6.3, data input and preprocessing: relevant network data, user data and environmental data are entered into the tool and necessary pre-processing, such as data cleansing, format conversion, etc.

S4.6.4, automated script execution: conventional AP planning tasks, such as virtual AP creation, configuration, performance testing, are performed using automation scripts. This reduces human involvement and improves execution efficiency.

S4.6.5, intelligent recommendation algorithm application: and (3) utilizing an intelligent recommendation algorithm to give optimization suggestions for AP layout and configuration according to historical data, user behavior and network performance prediction. These suggestions include the location, number, power settings of the APs.

S4.6.6, visual interface display: and displaying the result of AP planning, network performance prediction and optimization suggestion through a visual interface. This helps the administrator to more intuitively understand the network status and make decisions.

S4.6.7, adjusting and optimizing: and carrying out necessary adjustment and optimization according to the display result of the visual interface so as to meet the actual requirements.

The automatic and intelligent management tool can simplify the AP planning process, reduce manual participation and errors, improve efficiency and help an administrator to more scientifically conduct network planning and decision by combining an automatic script, an intelligent recommendation algorithm and a visual interface.

S5, physical environment analysis: the actual physical environment is analyzed, including the building structure, electromagnetic environment, signal propagation characteristics. And correcting and perfecting the virtual AP planning according to the analysis result.

In virtual AP planning, it is a very important step to analyze the actual physical environment. By evaluating the building structure, electromagnetic environment and signal propagation characteristics, the actual situation is better known, and therefore the virtual AP planning is corrected and perfected. The method comprises the following specific steps:

The data collection is the first step in virtual AP planning, and related data, including building block diagrams, electromagnetic environment data and signal propagation characteristics, need to be obtained from the actual physical environment. The method comprises the following specific steps:

S5.1.1, determining a data collection range: and determining the range and the key area of data to be collected according to the requirement of virtual AP planning.

S5.1.2, select data collection method: according to the actual situation, a proper data collection method is selected, including on-site measurement, questionnaire and database query.

S5.1.3, preparing a data collection tool: according to the selected data collection method, corresponding tools including measuring instruments, questionnaires and computers are prepared.

S5.1.4, implement data collection: data collection is performed according to predetermined plans and steps, ensuring accuracy and integrity of the data.

S5.1.5, sorting and analyzing data: the collected data is collated and analyzed to extract useful information and metrics.

Analyzing data is one of the important steps in virtual AP planning, and detailed analysis of the collected data is required. The method comprises the following steps:

influence of building structure on signal propagation:

(1) The type and material of the building structure are analyzed to determine the degree of obstruction to signal propagation. (2) calculating propagation loss of the signal in the building.

Where the propagation distance is the distance the signal propagates and the wavelength is the wavelength of the signal. (3) The layout and the partition material in the building are analyzed to determine their effect on signal propagation.

Degree of signal interference by electromagnetic environment:

(1) Interference sources in an electromagnetic environment are analyzed, including other wireless devices, power lines. (2) The intensity and frequency of the interference signal are measured, and the interference degree of the interference signal to the virtual AP is determined. (3) The degree of interference of the virtual AP to the electromagnetic environment was evaluated using an electromagnetic compatibility (EMC) test method.

Signal propagation characteristics behave in various environments:

(1) Signal propagation characteristics including signal attenuation, noise interference, multipath effects are analyzed. (2) Propagation characteristics of signals under various circumstances are simulated using a propagation model or simulation software. (3) The effect of different environmental factors on signal propagation characteristics, including building blockage, terrain variation, atmospheric conditions, is analyzed.

The steps help virtual AP planners better understand the influence of the actual physical environment on signal propagation, so that effective virtual AP planning and optimization are performed.

S5.3, evaluating virtual AP planning: and evaluating the existing virtual AP planning scheme according to the analysis result. Analysis of which areas have problems of insufficient signal coverage or severe signal interference and correction and refinement of these problems are proposed. The specific steps for evaluating virtual AP planning are as follows:

s5.3.1, determining an evaluation criterion: specific criteria for evaluating virtual AP planning need to be determined, including signal coverage, signal quality, interference conditions. These criteria are selected and adjusted according to the actual requirements.

S5.3.2, analysis of signal coverage: signal coverage is simulated using a signal propagation model or simulation software based on the virtual AP planning scheme and the actual physical environment data. Which areas are analyzed for insufficient signal coverage or severe signal interference problems.

S5.3.3, evaluating signal quality: the signal quality in the virtual AP planning scheme is evaluated by analyzing signal quality evaluation indicators including signal-to-noise ratio (SNR), bit Error Rate (BER). And analyzing which areas have the problem of poor signal quality.

S5.3.4, analysis of interference conditions: and evaluating the interference condition in the virtual AP planning scheme by analyzing the position, the intensity and the frequency parameters of the interference source. Analyzing which areas have serious interference problems.

S5.3.5, propose corrective and perfecting advice: based on the analysis results, correction and perfection proposals are made for the existing problems. Increasing the number of APs or adjusting the location and power parameters of the APs to improve signal coverage and quality.

The method helps the evaluator quantitatively evaluate the effect of virtual AP planning, so that correction and perfection can be better performed.

S5.4, correcting and perfecting virtual AP planning: and correcting and perfecting the virtual AP planning according to the evaluation result. The position, number and power parameters of the APs are adjusted to optimize network coverage and signal quality. The virtual AP plan is now modified and refined based on the evaluation results. The modification and refinement includes adjusting the position, number and power parameters of the APs in order to optimize network coverage and signal quality. The method comprises the following steps:

s5.4.1, building an experimental environment: and building a corresponding experimental environment comprising actual network equipment and a test terminal according to the corrected and completed virtual AP plan.

S5.4.2, performing the test: in an experimental environment, a test terminal is used for testing network performance, including signal coverage, signal quality and data transmission rate indexes.

S5.4.3, analytical test results: and analyzing the test result, comparing the test result with the previous test result, and evaluating whether the virtual AP planning after correction and completion is improved.

S5.4.4, adjusting and optimizing: and further adjusting and optimizing the virtual AP planning according to the analysis result, and repeating the verification and the test until a satisfactory effect is achieved. During verification and testing, the following calculation formula was used to evaluate the improvement in network performance: improvement rate = (corrected performance-original performance)/original performance x 100% through the above steps, it is verified and tested whether the corrected and completed virtual AP plan is valid, and it is determined whether the previously existing problem is solved.

Through the steps, the actual physical environment is combined with the virtual AP planning, so that a more scientific and reasonable planning scheme is obtained.

S6, credibility evaluation: in performing AP pre-planning, a trust evaluation, including an evaluation in terms of security, reliability, and performance, needs to be performed. And verifying the robustness and the safety of the network by simulating an attack scene and a performance test.

In performing AP pre-planning, it is a very important step to perform a reliability assessment, including an assessment in terms of security, reliability and performance. The following are the detailed steps:

In summary, reliability assessment is a very important step in AP pre-planning, requiring comprehensive consideration of security, reliability and performance assessment. The robustness and security of the network are verified by simulating attack scenes and performance tests, and various verification and test tools are used to improve the credibility and reliability of the network.

In summary, iterative optimization requires continuous adjustment and optimization of the AP pre-planning scheme using automated techniques and intelligent decision support in combination with changes in actual conditions and requirements. More information and suggestions are obtained through real-time monitoring, data analysis and feedback investigation modes, so that better network performance and user satisfaction are achieved.

S8, deployment implementation: and applying the pre-planned AP configuration and layout to an actual WLAN network for deployment and implementation. In the deployment process, the indexes in the aspects of network performance and security need to be closely focused, and timely adjustment and optimization are needed.

Deployment implementation is the process of applying a pre-planned AP configuration and layout into an actual WLAN network. The method comprises the following specific steps:

In summary, deployment implementation is a key step in applying pre-planned AP configurations and layouts to an actual WLAN network. In the deployment process, network performance, security and availability factors need to be comprehensively considered, and the configuration and layout of the APs are timely adjusted and optimized so as to ensure the stability and availability of the network.

The above-described embodiment represents only one embodiment of the present invention, and is not to be construed as limiting the scope of the present invention. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the spirit of the present invention, which falls within the scope of the present invention.

Claims

1. A virtual-real combined trusted WLAN networking AP pre-planning method comprises the following steps:

s1, determining a target network architecture, and determining the architecture of a target WLAN (wireless local area network) network, wherein the architecture comprises a network topological structure, a coverage area, the number of access users, a spectrum environment, qoS (quality of service) requirements, a security policy and a management policy;

s2, collecting requirements and information, and collecting information related to a network architecture, wherein the information comprises building structures, electromagnetic environments, user behaviors, service requirement information, network performance indexes, security requirement information and network topology structure information, and the information is from the existing network planning tools and site survey reports;

s3, establishing a model, wherein a network model of the WLAN networking AP pre-planning comprises a wireless network propagation model, an interference model, a service model, an AP position model, a channel allocation model, an AP position and channel allocation joint model and a network performance evaluation model, and customizing and optimizing the models based on actual environments and requirements;

s4, planning a virtualized AP, simulating the layout and configuration of the AP in a virtual environment, and optimizing according to actual requirements; the virtualization technology comprises a software defined network, network function virtualization, a virtual AP simulation tool, a machine learning and artificial intelligence algorithm, a cloud computing and edge cloud cooperation technology and an automation and intelligent management tool, so that dynamic AP planning and deployment are realized;

S5, physical environment analysis: analyzing the actual physical environment, including evaluating building structure, electromagnetic environment, signal propagation characteristics; correcting and perfecting the virtual AP planning according to the analysis result; when virtual AP planning is performed, the analysis of the actual physical environment is a very important step; the actual situation is better known by evaluating the building structure, the electromagnetic environment and the signal propagation characteristics, so that the virtual AP planning is corrected and perfected;

s6, credibility evaluation: during AP pre-planning, reliability assessment is needed, including safety, reliability and performance assessment; verifying the robustness and safety of the network by simulating an attack scene and a performance test; in AP pre-planning, it is a very important step to perform a reliability assessment, including an assessment in terms of security, reliability and performance;

s7, iterative optimization: according to the actual environment and the change of the demand, continuously iterating and optimizing an AP pre-planning scheme; combining artificial intelligence and machine learning technology, realizing automatic and intelligent AP planning and management; iterative optimization is a process of continuously adjusting and optimizing an AP pre-planning scheme according to the change of the actual environment and the demand;

S8, deployment implementation: applying the pre-planned AP configuration and layout to an actual WLAN network for deployment and implementation; in the deployment process, the indexes in the aspects of network performance and safety are required to be closely focused, and timely adjustment and optimization are required; deployment implementation is the process of applying a pre-planned AP configuration and layout into an actual WLAN network.

2. The virtual-actual combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S1 specifically includes:

s1.1, determining a network topology structure: selecting a proper network topology structure according to the actual environment and the requirements, wherein the network topology structure comprises star-shaped, tree-shaped and net-shaped, and the connection modes and the topological relations among different APs need to be considered so as to facilitate the subsequent optimization and management;

s1.2, determining coverage: according to the actual environment and the requirements, determining the coverage area and coverage area of each AP; dividing according to building structures and user distribution, and ensuring that each AP can meet coverage requirements;

s1.3, determining the number of access users: determining the number of users accessed by each AP according to the actual environment and the requirements; the behavior habit and business demand factors of the user need to be considered so as to facilitate the subsequent capacity planning and performance optimization;

S1.4, determining a spectrum environment: selecting a proper channel according to an actual frequency spectrum environment, and avoiding co-channel interference and adjacent channel interference; consider the use of a channel planning tool to assist in achieving a better channel allocation;

s1.5, determining QoS requirements: determining a required QoS level and priority according to actual service requirements;

s1.6, determining a security policy: determining a required security policy and a security mechanism according to actual security requirements; by means of WPA3 and WPA2 safety protocols and encryption technology, safety and confidentiality of data transmission are realized;

s1.7, determining a management strategy: determining a required management strategy and a management mechanism according to actual management requirements; by means of the centralized management platform and the automatic management tool, the automatic configuration, monitoring and management of the network are realized.

3. The virtual-real combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S2 specifically includes:

s2.1, building structure information is obtained; building structure information includes the shape, size, building materials, floor number of the building; such information helps predict the propagation characteristics and signal attenuation of the wireless signal inside the building; using existing tools of building structure models or site survey reports to obtain this information;

S2.2, acquiring electromagnetic environment information; the electromagnetic environment information comprises the frequency, power and signal interference of a wireless signal; using a spectrum analyzer, a signal receiver device to measure and collect such information;

s2.3, obtaining user behavior information; the user behavior information comprises the number, distribution and movement track of users; the information is acquired through monitoring and analyzing the existing network, and has important significance for network optimization and management;

s2.4, acquiring service demand information; the service demand information comprises the required service type, data rate and time delay; the method comprises the steps of cooperating with a service provider to acquire related service demand information;

s2.5, acquiring network performance indexes: the network performance indexes comprise throughput, delay and packet loss rate; collecting such information using a network performance testing tool to facilitate subsequent network performance optimizations; the measurement and calculation of the network performance index is an important link for evaluating the network performance;

s2.6, safety requirement information: the security requirement information comprises a required security protocol and an encryption algorithm; the method comprises the steps of cooperating with a security expert to obtain related security requirement information;

4. The virtual-actual combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S3 specifically includes: s3.1, establishing a wireless network propagation model, wherein the propagation model is used for predicting propagation characteristics and signal attenuation conditions of wireless signals in space;

s3.2, establishing an interference model, wherein the interference model is used for predicting interference conditions and interference influences among different APs; using existing interference models, including an interference model based on 802.11 protocol, an interference model based on signal strength;

s3.3, establishing a service model, wherein the service model is used for predicting service demands and flow distribution conditions in a network; analyzing and modeling according to actual service demands and user behaviors, and describing by using a Simon distribution and Pascal distribution probability model;

s3.4, establishing an AP position model, wherein determining the position of an access point is usually the first step of WLAN design problem; when selecting a location, the distance between access points should not be too far or too close; the former case may create a coverage gap; however, the latter arrangement increases channel interference; thus, an effective solution is to achieve the best tradeoff between coverage, throughput, and interference while taking into account the distribution of users in the environment;

S3.5, establishing a channel allocation model, wherein the channel allocation model is used for predicting interference conditions and channel quality among different channels; using the existing channel allocation algorithm, establishing a channel allocation model based on a graph theory channel allocation algorithm and a channel allocation algorithm based on simulated annealing;

s3.6, establishing an AP position and channel allocation joint model

S3.7, establishing a network performance evaluation model: the network performance evaluation model is used for evaluating performance indexes of the network, such as throughput, delay and packet loss rate; the network performance is simulated and predicted using existing network performance assessment tools or developing custom assessment models.

5. The virtual-actual combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S4 specifically includes:

s4.1, software defined networking technology: the software defined network technology separates network control and forwarding and provides centralized network management and programmable interfaces; in the virtualized AP planning, a virtual network is created by using a software defined network technology, and the APs are configured and managed in a programming mode, so that dynamic AP planning and deployment are realized;

s4.2, network function virtualization technology: the network function virtualization technology decouples network functions from special hardware equipment and operates the network functions on a general server in a software form; in the virtualized AP planning, a network function virtualization technology is used for instantiating the virtual AP, and the functions and the performances of the virtual AP are configured and managed through software so as to meet the actual requirements;

S4.3, a virtual AP simulation tool: the virtual AP simulation tool simulates the behavior and performance of the AP in a virtual environment, including signal propagation, interference and throughput; simulating and evaluating different AP layouts and configuration schemes by using a virtual AP simulation tool so as to find an optimal planning scheme;

s4.4, machine learning and artificial intelligence algorithms: the machine learning and artificial intelligence algorithm is used for optimizing the virtual AP planning process; the network performance and the user demands are predicted by analyzing historical data and user behaviors, training a model, and the layout and the configuration of the AP are automatically adjusted by using an optimization algorithm so as to improve the network performance and the user satisfaction;

s4.5, cloud computing and edge cloud cooperation technology: the cloud computing and edge cloud cooperation technology provides an elastically extensible resource support for virtualized AP planning; the AP planning and deployment tasks are migrated to a cloud or edge cloud cooperative environment, and dynamic resource allocation and expansion are realized by utilizing the resource advantages of cloud computing so as to meet network planning tasks with different scales and requirements; the cloud computing and edge cloud cooperation technology provides an elastically extensible resource support for virtualized AP planning; the AP planning and deployment tasks are migrated to a cloud or edge cloud cooperative environment, and dynamic resource allocation and expansion are realized by utilizing the resource advantages of cloud computing so as to meet network planning tasks with different scales and requirements;

S4.6, an automation and intelligent management tool: the automatic and intelligent management tool simplifies the flow of the virtualized AP planning and improves the efficiency; by using an automatic script, an intelligent recommendation algorithm and a visual interface, manual participation and errors are reduced, and automatic AP planning and deployment are realized; virtualized AP planning requires a combination of various technologies and tools to achieve dynamic AP planning and deployment; by comprehensively considering the actual environment and the requirements, selecting a proper virtualization technology and optimization algorithm, improving the network performance, reducing the cost and meeting the requirements of users; the automated and intelligent management tool greatly simplifies the flow of virtualized AP planning and improves efficiency.

6. The virtual-real combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S5 specifically includes:

s5.1, collecting data: related data of the actual physical environment needs to be collected, including building structure diagrams, electromagnetic environment data and signal propagation characteristics; the data are obtained by means of field measurement and investigation;

s5.2, analyzing data: analyzing the collected data in detail; analyzing the influence of the building structure on signal propagation, the degree of signal interference by an electromagnetic environment and the performance of signal propagation characteristics under various environments;

S5.3, evaluating virtual AP planning: according to the analysis result, evaluating the existing virtual AP planning scheme; analyzing which areas have problems of insufficient signal coverage or serious signal interference, and proposing correction and perfection aiming at the problems;

s5.4, correcting and perfecting virtual AP planning: correcting and perfecting the virtual AP planning according to the evaluation result; adjusting the position, the number and the power parameters of the AP to optimize the network coverage and the signal quality; at present, the virtual AP planning is corrected and perfected according to the evaluation result; correcting and perfecting the position, quantity and power parameters of the APs, wherein the aim is to optimize the network coverage and the signal quality;

s5.5, repeating the steps: if the verification and test results are not ideal, the physical environment needs to be re-analyzed, and further correction and improvement are carried out on the virtual AP planning; this process may need to be repeated until satisfactory results are obtained.

7. The virtual-actual combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S6 specifically includes:

s6.1, safety evaluation: the security assessment is mainly to assess the risk of the network from attack and threat; the security and the robustness of the network are tested by simulating various attack scenes, such as malicious attack and denial of service attack; meanwhile, the effectiveness of an encryption algorithm and a security protocol needs to be evaluated so as to ensure the security of data transmission;

S6.2, reliability evaluation: reliability assessment is mainly to assess the stability and availability of the network; testing the fault tolerance and recovery capability of the network by simulating network faults and abnormal conditions such as network disconnection and AP faults; meanwhile, the validity of the backup and recovery strategies needs to be evaluated to ensure the availability and stability of the network;

s6.3, performance evaluation: the performance evaluation mainly evaluates the processing capacity and the transmission speed of the network; testing performance indexes and user perception of the network by performing performance tests, such as throughput tests and delay tests; meanwhile, the validity of the network architecture and the protocol needs to be evaluated to ensure the performance and the efficiency of the network;

s6.4, robustness assessment: the robustness assessment is mainly to assess the resistance and recovery capability of the network when the network is under attack or abnormal conditions; the robustness and stability of the network are tested by simulating network attack or abnormal conditions; meanwhile, the effectiveness of a network security monitoring and alarming system needs to be evaluated so as to ensure that network problems can be found and processed in time;

s6.5, validation and test tools: performing the trust evaluation requires the use of various verification and testing tools, such as vulnerability scanning tools, performance testing tools, security monitoring systems; these tools help discover and address potential security risks and performance issues, thereby improving the trustworthiness and reliability of the network.

8. The virtual-actual combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S7 specifically includes:

s7.1, data collection and analysis: the actual network data such as flow data, performance indexes and user behaviors are collected and analyzed to know the actual conditions and user requirements of the network, so that data support is provided for iterative optimization;

s7.2, automatic adjustment and optimization: utilizing an automation technology and a tool to realize automatic adjustment and optimization of the AP pre-planning scheme; using artificial intelligence and machine learning algorithm, automatically adjusting layout, configuration and management strategy of AP according to actual network data and user demand to realize better network performance and user satisfaction;

s7.3, intelligent decision and support: by using artificial intelligence and machine learning techniques, intelligent decision making and support of an AP pre-planning scheme are realized; classifying users by using a clustering algorithm, and providing different AP service strategies for users of different categories; or predicting future network flow and performance trend by using a prediction model so as to make AP planning and adjustment in advance;

s7.4, real-time monitoring and alarming: network problems are found and processed in time by monitoring network states and performance indexes in real time; when abnormal conditions or performance bottlenecks occur, an alarm mechanism is triggered to inform an administrator or an automation script to perform corresponding processing and adjustment;

S7.5, continuous improvement and evaluation: iterative optimization is a continuous process that requires continuous improvement and evaluation of the effectiveness and robustness of the AP pre-planning scheme; the feedback and advice are obtained by periodically carrying out network performance test, security evaluation and user satisfaction investigation modes so as to further optimize the AP pre-planning scheme;

s7.6, participants: the participators comprise network administrators, planning specialists, data analysts and security specialists; different personnel participate in the iterative optimization process of AP pre-planning together according to the respective expertise and skill.

9. The virtual-actual combined trusted WLAN networking AP pre-planning method according to claim 1, wherein step S8 specifically includes:

s8.1, AP deployment and installation: according to the pre-planned AP layout and configuration, the AP is deployed and installed at a proper position, and the connection and power supply of the AP and network equipment are ensured to be normal; in the deployment process, the signal coverage, interference and security factors of the AP need to be considered;

s8.2, configuration management: each AP is configured and managed, including an IP address, wireless parameters and a security protocol; configuration consistency, correctness and security of each AP need to be ensured;

S8.3, network performance test: after deployment is completed, network performance testing is carried out, wherein the network performance testing comprises throughput, delay and packet loss rate indexes; network performance bottlenecks and problems are found through testing, and configuration and layout of the APs are timely adjusted and optimized;

s8.4, safety evaluation: after deployment is completed, security assessment is carried out, wherein the security assessment comprises firewall configuration, encryption protocol and access control; the robustness and security of the network need to be ensured to prevent unauthorized access and attacks;

s8.5, monitoring and maintaining: after deployment, the network is monitored and maintained in real time, and network problems are found and treated in time; periodically checking network performance indexes, security logs and fault reports to ensure the stability and availability of the network;

s8.6, optimizing and adjusting: optimizing and adjusting the configuration and layout of the AP according to the actual network environment and the change of the user demand; continuously improving and optimizing network performance and security through data collection and analysis, performance test and security evaluation modes;

s8.7, participants: the participators comprise network administrators, engineers, planning specialists and security specialists; different personnel participate in the deployment implementation and maintenance optimization process of the AP together according to the respective expertise and skills.

10. A system for performing the virtual-real combined trusted WLAN networking AP pre-planning method of any one of claims 1-9, characterized by: