Network state-aware intelligent converged terminal access optimization method and system

Abstract

This invention discloses a method and system for optimizing access to intelligent converged terminals based on network state awareness, relating to the field of communication access management. The method includes: acquiring access request data from intelligent converged terminals to a communication network system; performing access availability detection on the communication network system under network state awareness to determine the current primary and backup networks; using the primary network as the access subject, combining an access game evaluation model to perform access configuration game optimization for the intelligent converged terminals and obtain a baseline access strategy; performing subject protection compensation under subject passive threat inversion to obtain a terminal access optimization strategy; and constructing a terminal access backup mechanism based on the backup network to perform primary / backup access switching control and dynamic adjustment of access strategies for the intelligent converged terminals. This application solves the technical problems of insufficient dynamic adaptation and robustness assurance in existing terminal access management, achieving the technical effects of improving the dynamic adaptation capability of terminal access and enhancing the robustness and reliability of network access.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication access management, in particular to an intelligent fusion terminal access optimization method and system based on network state perception. BACKGROUND

[0002] Multi-network cooperative access of intelligent fusion terminals is a key link to ensure stable operation of communication systems and efficient bearing of services, and directly affects terminal access reliability, transmission quality and overall system operation efficiency. Traditional terminal access control mainly adopts fixed network priority assignment, single network link detection and static parameter configuration implementation, relying on preset rules to complete the selection of local networks and wide area networks and the allocation of access parameters. Such static configuration and fixed rules are difficult to adapt to real-time state fluctuations of the network, and are prone to problems such as imbalance of network resource matching, insufficient access stability, and switching lag in abnormal scenarios.

[0003] In the related art, there are technical problems of insufficient dynamic adaptation and robustness guarantee in terminal access control in a multi-network environment. SUMMARY

[0004] The present application provides an intelligent fusion terminal access optimization method and system based on network state perception, which obtains access request data of intelligent fusion terminals facing local communication networks and wide area communication networks, detects the access availability of the two types of networks based on network state perception and determines the primary and backup networks, takes the primary network as the access subject, constrains and screens multiple access schemes and scores optimization through an access game evaluation model to obtain a benchmark access strategy, performs passive threat inversion and vulnerability identification on the primary network, protects and compensates the benchmark strategy through link redundancy, traffic offloading and security enhancement, obtains a terminal access optimization strategy, constructs a backup access mechanism based on the backup network, performs primary and backup switching prediction, pre-deployment and switching according to the state of the primary network, and dynamically adjusts the access strategy, thereby solving the technical problems of insufficient dynamic adaptation and robustness guarantee in terminal access control in a multi-network environment, and achieving the technical effects of improving terminal access dynamic adaptation, enhancing network access robustness and reliability.

[0005] This application provides a network state-aware intelligent converged terminal access optimization method, comprising: acquiring access request data of the intelligent converged terminal to a communication network system, wherein the communication network system includes a local communication network and a wide area communication network; performing access availability detection of the communication network system under network state awareness based on the access request data to determine the current access primary network and the current access backup network; taking the current access primary network as the access subject and combining an access game evaluation model to perform access configuration game optimization for the intelligent converged terminal to obtain a baseline access strategy; performing subject protection compensation under subject passive threat inversion on the baseline access strategy to obtain a terminal access optimization strategy; constructing a terminal access backup mechanism based on the current access backup network, and performing primary / backup access switching control and dynamic adjustment of the access strategy for the intelligent converged terminal according to the terminal access backup mechanism and the terminal access optimization strategy.

[0006] In a possible implementation, based on the access request data, the communication network system undergoes network status-aware access availability detection to determine the current primary access network and the current backup access network. The following processes are then performed: acquiring local network status data and local network capability feature data corresponding to the local communication network, and synchronously loading wide area network status data and wide area network capability feature data corresponding to the wide area communication network; evaluating the matching degree of the local network capability feature data and the wide area network capability feature data based on the access request data to obtain a network capability matching evaluation set; evaluating the health of the local network status data and the wide area network status data to obtain a network health evaluation set; calculating access availability based on predetermined weight conditions of the network capability matching evaluation set and the network health evaluation set to obtain an access availability set; and determining the primary / backup status of the communication network system based on the access availability set to identify the current primary access network and the current backup access network.

[0007] In a possible implementation, taking the current access main network as the access subject, and combining the access game evaluation model to perform access configuration game optimization for the intelligent converged terminal, a baseline access strategy is obtained, and the following processes are performed: Based on the access subject, multimodal access configuration decisions are made for the intelligent converged terminal to obtain a group of terminal access schemes; the group of terminal access schemes is evaluated from multiple perspectives according to the access game evaluation model to obtain an access game evaluation space; access evaluation constraints are obtained, including access quality score constraints and access risk score constraints; based on the access game evaluation space, the group of terminal access schemes is subjected to constraint verification optimization according to the access evaluation constraints to obtain a group of terminal access candidates; the access game evaluation space is used to iteratively optimize the access game score of the group of terminal access candidates to generate the baseline access strategy.

[0008] In a possible implementation, based on the access subject, multimodal access configuration decisions are made for the intelligent converged terminal to obtain a group of terminal access schemes, and the following processes are performed: multidimensional state characteristics are analyzed for the access subject to establish a main network characteristic map; link configuration parameters are parsed for the intelligent converged terminal based on the main network characteristic map to obtain a link configuration decision set; service bearer configuration parameters are parsed for the intelligent converged terminal based on the main network characteristic map to obtain a service bearer configuration decision set; transmission control configuration parameters are parsed for the intelligent converged terminal based on the main network characteristic map to obtain a transmission control configuration decision set; the link configuration decision set, the service bearer configuration decision set, and the transmission control configuration decision set are randomly combined to obtain multiple initial access schemes; feedback adjustment under conflict identification is performed on each initial access scheme to generate the group of terminal access schemes.

[0009] In a possible implementation, the terminal access scheme group is evaluated from multiple perspectives based on the access game evaluation model to obtain the access game evaluation space. The following processes are then performed: dynamic modeling is performed based on the current access main network to obtain a main network twin model; multi-scheme virtual access is executed for the intelligent converged terminal in conjunction with the terminal access scheme group to obtain multiple access response virtual data; the access game evaluation model is activated, which includes an access quality scoring layer, an access risk scoring layer, and an access game evaluation layer; the multiple access response virtual data are input into the access quality scoring layer to obtain multiple access quality scores. The multiple access response virtual data are input into the access risk scoring layer to obtain multiple access risk scores; the concentration of quality scores and the concentration of risk scores are calculated, and the access game evaluation layer is adjusted based on the concentration of quality scores and the concentration of risk scores to obtain an access game scoring function; the multiple access quality scores and the multiple access risk scores are input into the access game scoring function to obtain multiple access game scores; the terminal access scheme group is mapped based on the multiple access quality scores, the multiple access risk scores, and the multiple access game scores to obtain the access game evaluation space.

[0010] In a possible implementation, the baseline access strategy is subjected to subject protection compensation under subject passive threat inversion to obtain a terminal access optimization strategy, and the following processing is performed: Based on the baseline access strategy, multi-dimensional passive threat inversion is performed on the access subject to obtain a main network vulnerability profile; according to the main network vulnerability profile, the weak link areas, weak service carrying areas, and weak protection links of the access subject are determined; a link redundancy compensation strategy is generated for the weak link areas, a service diversion compensation strategy is generated for the weak service carrying areas, and a security enhancement compensation strategy is generated for the weak protection links; the baseline access strategy is reconstructed and optimized according to the link redundancy compensation strategy, the service diversion compensation strategy, and the security enhancement compensation strategy to obtain the terminal access optimization strategy.

[0011] In a possible implementation, the terminal access backup mechanism performs the following processes: predicting the switching timing based on the network status change trend of the current access main network to obtain the primary / backup switching timing characteristics; if the primary / backup switching timing characteristics meet the switching timing constraints, performing backup link pre-establishment, service status pre-synchronization, and access parameter pre-loading on the intelligent converged terminal based on the current access backup network to obtain the backup access pre-deployment result; verifying the switching feasibility of the current access backup network based on the backup access pre-deployment result to obtain the primary / backup switching pre-confirmation result; and controlling the intelligent converged terminal to switch from the current access main network to the current access backup network based on the primary / backup switching pre-confirmation result.

[0012] In a possible implementation, the following processing is performed: the predetermined weight conditions include network capability matching weights and network health weights.

[0013] In a possible implementation, the following processing is performed: the access game evaluation layer includes access quality score weights and access risk score weights.

[0014] This application also provides a network state-aware intelligent converged terminal access optimization system, comprising: an access request module for acquiring access request data from the intelligent converged terminal to a communication network system, the communication network system including a local communication network and a wide area communication network; an access availability detection module for performing access availability detection on the communication network system under network state awareness based on the access request data, and determining the current access primary network and the current access backup network; an access configuration game optimization module for performing access configuration game optimization on the intelligent converged terminal using the current access primary network as the access subject and combining an access game evaluation model to obtain a baseline access strategy; a subject protection compensation module for performing subject protection compensation under subject passive threat inversion on the baseline access strategy, and obtaining a terminal access optimization strategy; and an access control module for constructing a terminal access backup mechanism based on the current access backup network, and performing primary / backup access switching control and dynamic adjustment of the access strategy for the intelligent converged terminal according to the terminal access backup mechanism and the terminal access optimization strategy.

[0015] The proposed method and system for optimizing access to intelligent converged terminals based on network state awareness, as described in this application, first acquires access request data from intelligent converged terminals to a communication network system, including a local communication network and a wide area communication network. Then, based on the access request data, it performs access availability detection under network state awareness to determine the current primary access network and the current backup access network. Next, using the current primary access network as the access subject, it performs access configuration game optimization for the intelligent converged terminal using an access game evaluation model to obtain a baseline access strategy. Then, it applies subject protection compensation under subject passive threat inversion to the baseline access strategy to obtain a terminal access optimization strategy. Finally, based on the current backup access network, it constructs a terminal access backup mechanism and performs primary / backup access switching control and dynamic adjustment of the access strategy for the intelligent converged terminal according to the terminal access backup mechanism and the terminal access optimization strategy. The method and system proposed in this application achieve the technical effects of improving the dynamic adaptation capability of terminal access and enhancing the robustness and reliability of network access. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1This is a flowchart illustrating the network state awareness-based intelligent converged terminal access optimization method provided in this application embodiment.

[0018] Figure 2 This is a schematic diagram of the structure of the network state-aware intelligent converged terminal access optimization system provided in the embodiments of this application.

[0019] Explanation of reference numerals in the attached diagram: 10 for access request module, 20 for access availability detection module, 30 for access configuration game optimization module, 40 for main protection compensation module, and 50 for access control module. Detailed Implementation

[0020] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the following description, references to "some embodiments" describe a subset of all possible embodiments; however, it is understood that "some embodiments" may be the same or different subsets of all possible embodiments and may be combined with each other without conflict. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0023] This application provides an intelligent converged terminal access optimization method based on network state awareness, such as... Figure 1 As shown, the method includes:

[0024] Step S100: Obtain access request data from the intelligent converged terminal to the communication network system, wherein the communication network system includes a local communication network and a wide area communication network.

[0025] Specifically, the intelligent converged terminal actively collects access request data using its built-in communication module. The collection tool is a network request collector integrated into the terminal. The input is the original request information initiated by the intelligent converged terminal when it initiates access, including the terminal device identifier, access service type, service data transmission requirements, access priority, and terminal hardware configuration parameters. The output is standardized access request data. During the collection process, the terminal communication module collects request data every 100 milliseconds. The collected raw data is processed using a data cleaning algorithm to remove noise, outliers, and redundant data. Outliers are judged as deviating from the normal request data range by ±30%, and redundant data is deleted using a duplicate data removal algorithm. The final result is access request data with a uniform format and complete data. For example, if the intelligent converged terminal is an industrial control terminal, the access service type is real-time data transmission, the service data transmission requirement is 10MB per second, the access priority is high, and the terminal hardware configuration parameters are a CPU clock speed of 2.8GHz and 8GB of memory, the corresponding standardized access request data will be obtained after collection and cleaning.

[0026] Step S200: Based on the access request data, perform access availability detection on the communication network system under network status awareness to determine the current access to the main network and the current access to the backup network.

[0027] Specifically, a network status-aware gateway is used as the detection device, equipped with a network availability detection system. During the detection process, a communication connection is first established with the core switches of the local communication network and the wide area communication network through the network status-aware gateway to obtain real-time operating data of the two types of networks. Then, an access availability detection algorithm is used to comprehensively evaluate the two types of networks. The evaluation indicators include network capability matching degree and network health. Based on the evaluation results, the network with higher access availability is selected as the current primary access network, and the other type of network is selected as the current backup access network. For example, if the access availability of the local communication network is 89% and the access availability of the wide area communication network is 76%, then the local communication network is determined to be the current primary access network and the wide area communication network is determined to be the current backup access network.

[0028] In one possible implementation, based on the access request data, access availability detection under network status awareness is performed on the communication network system to determine the current access to the primary network and the current access to the backup network. Step S200 further includes step S210, acquiring local network status data and local network capability characteristic data corresponding to the local communication network, and synchronously loading wide area network status data and wide area network capability characteristic data corresponding to the wide area communication network. Specifically, a network status acquisition device is used to collect data from the local communication network and the wide area communication network respectively, with a collection frequency of once every 50 milliseconds. The input is the network node operation information of the communication network system, and the output is local network status data, local network capability characteristic data, wide area network status data, and wide area network capability characteristic data. The local network status data includes local network link latency, link jitter, packet loss rate, bandwidth utilization, and node load. Local network capability characteristic data includes local network maximum transmission rate, concurrent access capacity, service capacity limit, and latency threshold. Wide area network status data includes wide area network link latency, link jitter, packet loss rate, bandwidth utilization, and node load. Wide area network capability characteristic data includes wide area network maximum transmission rate, concurrent access capacity, service capacity limit, and latency threshold. After data collection, a data synchronization transmission protocol is used to synchronously load the four types of data to the network status analysis server, ensuring the real-time nature and consistency of data loading. For example, the local network status data may have a link latency of 15 milliseconds and a packet loss rate of 0.8%, and a maximum transmission rate of 100 MB / s in the local network capability characteristic data. The wide area network status data may have a link latency of 45 milliseconds and a packet loss rate of 2.3%, and a maximum transmission rate of 80 MB / s in the wide area network capability characteristic data. These data are then collected, synchronized, and loaded onto the server.

[0029] Step S220: Based on the access request data, evaluate the matching degree of the local network capability feature data and the wide area network capability feature data to obtain a network capability matching evaluation set. Specifically, the network capability matching evaluation set includes the local network capability matching degree and the wide area network capability matching degree. First, extract the service requirement parameters from the access request data, including service transmission rate requirements, concurrent access requirements, service bearer requirements, and latency requirements. Then, compare these parameters with the local network capability feature data and the wide area network capability feature data item by item, and calculate the matching coefficient for each parameter. The matching coefficients for service transmission rate requirements, concurrent access requirements, and service bearer requirements are calculated as the ratio of the actual network capability parameters to the service requirement parameters. If the ratio is greater than or equal to 1, the matching coefficient is 1; if the ratio is less than 1, the matching coefficient is... The number represents the actual ratio. Due to the special characteristics of the latency requirement indicator, the matching coefficient calculation rule is as follows: when the network latency threshold is ≤ the access request latency requirement, the matching coefficient is 1; when the network latency threshold is > the access request latency requirement, the matching coefficient is the ratio of the access request latency requirement to the network latency threshold. Then, the matching coefficients of each parameter are weighted and summed. The weights are allocated as follows: transmission rate requirement accounts for 30%, concurrent access requirement accounts for 25%, service carrying requirement accounts for 25%, and latency requirement accounts for 20%. The weighted summation result is the corresponding network capability matching degree. Finally, a network capability matching evaluation set including the local network capability matching degree and the wide network capability matching degree is obtained.

[0030] Step S230: Health assessments are performed on the local network status data and the wide area network status data respectively to obtain a network health assessment set. Specifically, the network health assessment set includes the local network health and the wide area network health. First, network health assessment indicators are determined, including link latency, link jitter, packet loss rate, bandwidth utilization, and node load. Each indicator has a corresponding evaluation level and scoring standard. Link latency ≤20 milliseconds is excellent (100 points), 20-50 milliseconds is good (80 points), 50-100 milliseconds is acceptable (60 points), and >100 milliseconds is unacceptable (40 points); link jitter ≤5 milliseconds is excellent (100 points), 5-10 milliseconds is good (80 points), 10-20 milliseconds is acceptable (60 points), and >20 milliseconds is unacceptable (40 points); packet loss rate ≤1% is excellent (100 points), 1%-3% is good (80 points), 3%-5% is acceptable (60 points), and >5% is unacceptable. The network health score is calculated as follows: ≤60% is excellent (100 points), 60%-80% is good (80 points), 80%-90% is satisfactory (60 points), and >90% is unsatisfactory (40 points); ≤70% is excellent (100 points), 70%-85% is good (80 points), 85%-95% is satisfactory (60 points), and >95% is unsatisfactory (40 points). Then, the various indicators in the local network status data and the wide area network status data are scored. The scores of each indicator are then weighted and summed, with the weights allocated as follows: link latency 20%, link jitter 20%, packet loss rate 20%, bandwidth utilization 20%, and node load 20%. The weighted sum is the corresponding network health score, ultimately resulting in a network health evaluation set that includes both the local network health score and the wide area network health score.

[0031] Step S240: Calculate access availability for the network capability matching evaluation set and the network health evaluation set according to predetermined weight conditions to obtain an access availability set. The predetermined weight conditions include network capability matching weight and network health weight. Specifically, the predetermined weight conditions include network capability matching weight and network health weight, where the network capability matching weight is set to 60% and the network health weight is set to 40%. This weight setting is based on the principle that service adaptability has a higher priority than the real-time network operating status in access requests. An access availability calculation algorithm is used to perform the calculation operation. The algorithm uses a weighted summation algorithm. The specific calculation process is as follows: Access Availability = Network Capability Matching Degree × Network Capability Matching Weight + Network Health Degree (converted to decimal form) × Network Health Weight. The network health degree is converted to decimal form by dividing the network health degree score by 100. The access availability of the local communication network and the wide area communication network are calculated separately to obtain the access availability set.

[0032] Step S250: Based on the access availability set, perform a primary / backup determination on the communication network architecture to determine the current primary access network and the current backup access network. Specifically, compare the two access availability values ​​in the access availability set, select the network with the larger access availability value as the current primary access network, and the network with the smaller access availability value as the current backup access network. If the two access availability values ​​are equal, prioritize selecting the local communication network as the current primary access network.

[0033] Step S300: Taking the current access main network as the access subject, and combining the access game evaluation model, perform access configuration game optimization on the intelligent fusion terminal to obtain the baseline access strategy.

[0034] Specifically, based on the current network characteristics and access request data of the main network, multiple terminal access schemes are generated. Then, an access game evaluation model is used to comprehensively evaluate and optimize each access scheme, selecting the optimal access scheme as the baseline access strategy. This ensures that the baseline access strategy can meet the business requirements in the access request while taking into account access quality and access risk. For example, if the current main network is a local communication network and the access request is real-time data transmission from an industrial control terminal, the baseline access strategy obtained after game optimization is as follows: fiber optic link configuration, dedicated channel service bearing configuration, TCP transmission protocol transmission control configuration, transmission rate set to 50MB / s, and access priority set to high.

[0035] In one possible implementation, the current access main network is taken as the access subject. An access game evaluation model is used to optimize the access configuration of the intelligent converged terminal to obtain a baseline access strategy. Step S300 further includes step S310, where multimodal access configuration decisions are made for the intelligent converged terminal based on the access subject to obtain a terminal access scheme group. Specifically, the network characteristics of the access subject are first analyzed to determine the configurable parameters such as link configuration, service carrying, and transmission control. Then, combined with the hardware configuration and service requirements of the intelligent converged terminal, different access configuration combinations are generated, forming multiple initial access schemes. After conflict detection and feedback adjustment, a terminal access scheme group is obtained, containing at least five different access schemes to ensure the diversity and feasibility of the schemes. For example, if the access entity is the local communication network and the intelligent fusion terminal is the industrial control terminal, the generated terminal access scheme group includes Scheme 1 (fiber optic link, dedicated channel, TCP protocol), Scheme 2 (fiber optic link, shared channel, UDP protocol), Scheme 3 (twisted pair link, dedicated channel, TCP protocol), Scheme 4 (twisted pair link, shared channel, UDP protocol), and Scheme 5 (fiber optic + twisted pair redundant link, dedicated channel, TCP protocol).

[0036] Step S320: The terminal access scheme group is evaluated from multiple perspectives according to the access game evaluation model to obtain the access game evaluation space. Specifically, the access process of each access scheme is first simulated using a mainnet twin model to obtain access response data. Then, each scheme is scored using different evaluation layers of the access game evaluation model to obtain access quality score, access risk score, and access game score. Finally, the three scores are mapped to the corresponding access schemes to form the access game evaluation space, which can intuitively reflect the comprehensive performance of each access scheme. For example, the five schemes in the terminal access scheme group, after evaluation, respectively obtain corresponding access quality scores, access risk scores, and access game scores. These scores are mapped one-to-one with the schemes to form the access game evaluation space.

[0037] Step S330: Obtain access evaluation constraints, which include access quality score constraints and access risk score constraints. Specifically, the constraint configuration module performs the operation, with the business requirements and industry standards in the access request data as input, and the access evaluation constraints as output. The access quality score constraint is set to an access quality score of no less than 85 points, based on the quality requirements for industrial-grade intelligent converged terminal access. The access risk score constraint is set to an access risk score of no more than 20 points, based on network access security industry standards. Both scores range from 0 to 100 points; higher scores indicate better access quality and higher access risk. For example, if the access request is for real-time data transmission from an industrial control terminal, and the business requirements are high transmission stability and low security risk, then based on industry standards, an access quality score ≥ 85 points and an access risk score ≤ 20 points are set as access evaluation constraints.

[0038] Step S340: Based on the access game evaluation space, perform constraint verification and optimization on the terminal access scheme group according to the access evaluation constraints to obtain a terminal access candidate group. Specifically, traverse each access scheme in the access game evaluation space, and check whether the access quality score and access risk score of each scheme meet the access evaluation constraints. Access schemes that simultaneously meet both constraints are selected to form the terminal access candidate group. If no scheme simultaneously meets both constraints, the constraints are appropriately relaxed, such as an access quality score ≥ 80 points and an access risk score ≤ 25 points, and the scheme is re-selected to ensure that the terminal access candidate group contains at least two access schemes. For example, among the five schemes in the terminal access scheme group, after verification, Scheme 1 (access quality score 92 points, access risk score 15 points) and Scheme 5 (access quality score 95 points, access risk score 12 points) meet the constraints; therefore, the terminal access candidate group is {Scheme 1, Scheme 5}.

[0039] Step S350: Based on the access game evaluation space, iterative optimization of the access game score for the terminal access candidate group is performed to generate the benchmark access strategy. Specifically, the access game score of each scheme in the terminal access candidate group is extracted. Using the access game score as the optimization objective, iterative optimization is performed. During the iteration process, only the access game score of each scheme is repeatedly verified and calculated; no configuration parameters of any access scheme are adjusted to ensure the accuracy of the scoring results. The number of iterations is set to 10, and each iteration only recalculates the access game score to avoid misjudging the optimal scheme due to calculation errors. Finally, the scheme with the highest access game score is selected as the benchmark access strategy. For example, if scheme 1 in the terminal access candidate group has an access game score of 90 and scheme 5 has an access game score of 96, after 10 iterations, it is confirmed that scheme 5 has the highest access game score and no calculation error; therefore, scheme 5 is determined as the benchmark access strategy.

[0040] In one possible implementation, based on the access subject's multimodal access configuration decision for the intelligent converged terminal, a group of terminal access schemes is obtained. Step S310 further includes step S311, which involves sorting out the multidimensional state characteristics of the access subject and establishing a main network characteristic map. Specifically, firstly, multidimensional state characteristic data of the access subject is collected, including link characteristics (link type, link bandwidth, link latency, link stability), node characteristics (number of nodes, node load, node processing capacity), service characteristics (service bearing type, service bearing limit, concurrent processing capacity), and protection characteristics (security authentication method, protection level, anti-interference capability). Then, a graph neural network algorithm is used to process this data to construct a main network characteristic map. The map contains various characteristic nodes of the access subject and the relationships between nodes, which can reflect the overall state of the access subject.

[0041] Step S312: Parse the link configuration parameters of the intelligent converged terminal based on the main network characteristic map to obtain a link configuration decision set. Specifically, extract the link characteristic data of the access subject from the main network characteristic map, and combine it with the service transmission rate and latency requirements of the intelligent converged terminal to parse out adaptable link configuration parameters, including link type, link bandwidth, link encoding method, and link redundancy configuration. Each parameter corresponds to multiple optional values, forming a link configuration decision set. For example, the link type in the main network characteristic map includes fiber optic and twisted pair; the link bandwidth includes 100MB / s, 500MB / s, and 1000MB / s; the link encoding method includes NRZ encoding and Manchester encoding; and the link redundancy configuration includes redundancy and no redundancy. Combined with the intelligent converged terminal's service transmission rate of 50MB / s and latency requirement of ≤30 milliseconds, the parsed link configuration decision set is {Link type: fiber optic, twisted pair; Link bandwidth: 100MB / s, 500MB / s; Link encoding method: NRZ encoding, Manchester encoding; Link redundancy configuration: redundancy and no redundancy}.

[0042] Step S313: Parse the service bearer configuration parameters of the intelligent converged terminal based on the main network characteristic map to obtain a service bearer configuration decision set. Specifically, extract the service characteristic data of the access subject from the main network characteristic map, and combine it with the service type and service data volume of the intelligent converged terminal to parse out the adaptable service bearer configuration parameters, including bearer channel type, bearer priority, data caching strategy, and service isolation method. Each parameter corresponds to multiple optional values, forming a service bearer configuration decision set. For example, the bearer channel type in the main network characteristic map includes dedicated channel and shared channel; the bearer priority includes high, medium, and low; the data caching strategy includes local caching and cloud caching; and the service isolation method includes VLAN isolation and VPN isolation. Combined with the intelligent converged terminal's service type being real-time data transmission and service data volume being 80GB, the parsed service bearer configuration decision set is {bearer channel type: dedicated channel, shared channel; bearer priority: high, medium; data caching strategy: local caching; service isolation method: VLAN isolation, VPN isolation}.

[0043] Step S314: Parse the transmission control configuration parameters of the intelligent converged terminal based on the main network characteristic map to obtain a transmission control configuration decision set. Specifically, extract the transmission control characteristic data of the access subject from the main network characteristic map, and combine it with the transmission reliability and transmission efficiency requirements of the intelligent converged terminal to parse out adaptable transmission control configuration parameters, including transmission protocol, transmission rate control, retransmission mechanism, and flow control method. Each parameter corresponds to multiple optional values, forming a transmission control configuration decision set. For example, the transmission protocol in the main network characteristic map includes TCP and UDP; the transmission rate control includes fixed rate and dynamic rate; the retransmission mechanism includes automatic retransmission and manual retransmission; and the flow control method includes sliding window and congestion control. Combining the high transmission reliability and medium transmission efficiency requirements of the intelligent converged terminal, the parsed transmission control configuration decision set is {Transmission protocol: TCP, UDP; Transmission rate control: fixed rate, dynamic rate; Retransmission mechanism: automatic retransmission; Flow control method: sliding window, congestion control}.

[0044] Step S315: Randomly combine the link configuration decision set, the service bearer configuration decision set, and the transmission control configuration decision set to obtain multiple initial access schemes. Specifically, a random combination algorithm is used to randomly select one optional value for each parameter from the link configuration decision set, one optional value for each parameter from the service bearer configuration decision set, and one optional value for each parameter from the transmission control configuration decision set. The selected parameter values ​​are combined to form an initial access scheme. This process is repeated to generate at least 10 initial access schemes to ensure scheme diversity. For example, selecting fiber optic cable, 100MB / s, NRZ encoding, and redundancy from the link configuration decision set; selecting dedicated channel, high priority, local buffering, and VLAN isolation from the service bearer configuration decision set; and selecting TCP protocol, fixed rate, automatic retransmission, and sliding window from the transmission control configuration decision set, can form an initial access scheme. Repeating this combination yields 10 different initial access schemes.

[0045] Step S316: Perform feedback adjustment for each initial access scheme under conflict identification to generate the terminal access scheme group. Specifically, a rule matching algorithm is selected to detect conflicts in each initial access scheme. Conflict types include parameter conflicts (such as mismatch between link bandwidth and transmission rate), resource conflicts (such as insufficient service carrying capacity), and performance conflicts (such as latency failing to meet requirements). For schemes with detected conflicts, feedback adjustment is performed based on the main network characteristic map and access request data to adjust the optional values ​​of conflict parameters until all conflicts are eliminated. Schemes without detected conflicts are directly retained. Finally, at least 5 conflict-free and feasible access schemes are selected to form the terminal access scheme group.

[0046] In one possible implementation, the terminal access scheme group is evaluated from multiple perspectives according to the access game evaluation model to obtain the access game evaluation space. Step S320 further includes step S321, which involves dynamically modeling the current access main network to obtain a main network twin model. The smart converged terminal then performs multi-scheme virtual access based on the terminal access scheme group to obtain multiple access response virtual data. Specifically, the Unity3D modeling algorithm is used, and a main network twin model corresponding to the physical main network at a 1:1 ratio is constructed based on the physical structure, network characteristics, and operating parameters of the current access main network. The model can map the operating status of the physical main network in real time. Each access scheme in the terminal access scheme group is sequentially input into the main network twin model to simulate the access process of the smart converged terminal. The simulation duration for each scheme is set to 10 minutes. Access response data during the simulation process is collected, including access success rate, transmission latency, transmission rate, packet loss rate, and security risk value. Each scheme corresponds to a complete set of access response virtual data.

[0047] Step S322: Activate the access game evaluation model. The access game evaluation model includes an access quality scoring layer, an access risk scoring layer, and an access game evaluation layer. The access game evaluation layer includes access quality score weights and access risk score weights. Specifically, start the access game evaluation model and load the model's preset parameters. The access quality scoring layer is used to score access quality-related indicators in the access response virtual data. The access risk scoring layer is used to score access risk-related indicators in the access response virtual data. The access game evaluation layer is used to calculate the access game score by weighting and deducting risks based on the access quality score and the access risk score. The access quality score weight is set to 70%, and the access risk score weight is set to 30%. This weight setting is based on the principle that access quality takes precedence over access risk. After activation, the model is initialized and calibrated to ensure the accuracy of the model's scoring.

[0048] Step S323: Input the multiple access response virtual data into the access quality scoring layer to obtain multiple access quality scores, and input the multiple access response virtual data into the access risk scoring layer to obtain multiple access risk scores. Specifically, the access quality scoring layer extracts access quality indicators from each access response virtual data, including access success rate, transmission latency, transmission rate, and packet loss rate. Each indicator has a set scoring standard: access success rate ≥99% is 100 points, 95%-99% is 80 points, 90%-95% is 60 points, and <90% is 40 points; transmission latency ≤20 milliseconds is 100 points, 20-50 milliseconds is 80 points, 50-100 milliseconds is 60 points, and >100 milliseconds is 40 points; transmission latency ≤20 milliseconds is 100 points, 20-50 milliseconds is 80 points, 50-100 milliseconds is 60 points, and >100 milliseconds is 40 points; A score of 100 is given for transmission rate ≥ service requirements, 80 points for 80%-100% service requirements, 60 points for 60%-80% service requirements, and 40 points for <60% service requirements; a score of 100 points is given for packet loss rate ≤1%, 80 points for 1%-3%, 60 points for 3%-5%, and 40 points for >5%. After scoring each indicator, a weighted sum is calculated, with the weights allocated as follows: access success rate 25%, transmission latency 25%, transmission rate 25%, and packet loss rate 25%, to obtain the access quality score for each solution. The access risk scoring layer extracts access risk indicators from the virtual data of each access response, including security risk value, link interruption probability, and data leakage probability. Each indicator has a defined scoring standard: security risk value ≤ 20 points = 40 points, 20-40 points = 60 points, 40-60 points = 80 points, and > 60 points = 100 points; link interruption probability ≤ 0.1% = 40 points, 0.1%-0.5% = 60 points, 0.5%-1% = 80 points, and > 1% = 100 points; data leakage probability ≤ 0.01% = 40 points, 0.01%-0.05% = 60 points, 0.05%-0.1% = 80 points, and > 0.1% = 100 points. After scoring each indicator, a weighted sum is calculated, with the weights allocated as follows: security risk value 40%, link interruption probability 30%, and data leakage probability 30%, resulting in the access risk score for each solution.

[0049] Step S324: Calculate the concentration of quality scores and the concentration of risk scores, and adjust the access game evaluation layer based on the concentration of quality scores and the concentration of risk scores to obtain the access game scoring function. Specifically, a variance calculation algorithm is used to calculate the variance of multiple access quality scores. The variance is calculated by summing the squares of the differences between each access quality score and the average of all access quality scores, dividing by the number of access quality scores, and then calculating the reciprocal of the variance to obtain the quality score concentration. The same method is used to calculate the variance of multiple access risk scores, and then the reciprocal of the variance is calculated to obtain the risk score concentration. The weights of the access game evaluation layer are adjusted based on the concentration of quality scores and the concentration of risk scores. The adjustment rules are as follows: the quality score adjustment coefficient equals the quality score concentration divided by the sum of the quality score concentration and the risk score concentration; the risk score adjustment coefficient equals the risk score concentration divided by the sum of the quality score concentration and the risk score concentration; the adjusted access quality score weight is the product of the original access quality score weight and the quality score adjustment coefficient; and the adjusted access risk score weight is the product of the original access risk score weight and the risk score adjustment coefficient. Then, an access game scoring function is constructed based on the adjusted weights. The access game scoring function is: Access Game Score = Access Quality Score × Adjusted Access Quality Score Weight - Access Risk Score × Adjusted Access Risk Score Weight.

[0050] Step S325: Input the multiple access quality scores and the multiple access risk scores into the access game scoring function to obtain multiple access game scores. Specifically, substitute the access quality score and access risk score corresponding to each access scheme into the access game scoring function in sequence, perform multiplication and addition operations, and obtain the access game score corresponding to each access scheme.

[0051] Step S326: Map the terminal access scheme group according to the multiple access quality scores, multiple access risk scores, and multiple access game scores to obtain the access game evaluation space. Specifically, taking each access scheme in the terminal access scheme group as the core, the access quality score, access risk score, and access game score corresponding to each scheme are used as three-dimensional evaluation indicators to construct a three-dimensional evaluation space. Each access scheme corresponds to a coordinate point in the evaluation space, and the coordinate values ​​are the access quality score, access risk score, and access game score, respectively. These coordinate points constitute the access game evaluation space.

[0052] Step S400: Perform subject protection compensation under subject passive threat inversion on the benchmark access strategy to obtain the terminal access optimization strategy.

[0053] Specifically, based on the execution logic of the baseline access strategy and the operational characteristics of the access subject, a multi-dimensional passive threat inversion is performed on the access subject to identify vulnerabilities in links, service carrying, protection, and other aspects, construct a main network vulnerability profile, identify weak areas and links based on the vulnerability profile, generate various targeted protection and compensation strategies, and finally integrate the compensation strategies into the baseline access strategy to complete the reconstruction and optimization, resulting in a terminal access optimization strategy that can avoid passive threats and make up for weak links, ensuring the stability and security of intelligent converged terminal access and meeting access requirements.

[0054] In one possible implementation, subject protection compensation under subject passive threat inversion is performed on the benchmark access strategy to obtain terminal access optimization strategy. Step S400 further includes step S410, which, based on the benchmark access strategy, performs multi-dimensional passive threat inversion on the access subject to obtain a main network vulnerability profile. Specifically, passive threats include link latency disturbances, link jitter disturbances, packet loss fluctuations, path switching anomalies, security authentication anomalies, etc. A reverse reasoning algorithm is selected, and the execution process of the benchmark access strategy is used as a clue to simulate the impact of various passive threats on the access subject. The operating status data of the access subject under different passive threats is collected, and the vulnerabilities of the access subject in terms of links, service carrying, and protection are analyzed to construct a main network vulnerability profile. The profile includes weak link areas, weak service carrying areas, weak protection links, and their corresponding vulnerability levels. For example, after simulating link latency disturbances, it is found that the latency fluctuation of a certain fiber optic link in the access subject exceeds 50 milliseconds, which is determined to be a weak link area; after simulating security authentication anomalies, it is found that the password authentication mechanism of the access subject has vulnerabilities, which is determined to be a weak protection link, and finally, a main network vulnerability profile is formed.

[0055] Step S420: Based on the main network vulnerability profile, determine the weak link areas, weak service carrying areas, and weak protection links of the access entity. Specifically, traverse all vulnerabilities in the main network vulnerability profile, and classify and identify them according to their type and location. Vulnerabilities located in link transmission links with a vulnerability level higher than a preset threshold are identified as weak link areas; vulnerabilities located in service carrying links with a vulnerability level higher than a preset threshold are identified as weak service carrying areas; and vulnerabilities located in protection links with a vulnerability level higher than a preset threshold are identified as weak protection links. The specific location and vulnerability manifestations of each weak area and link are clearly defined.

[0056] Step S430: Generate a link redundancy compensation strategy for the weak link area, a service diversion compensation strategy for the weak service carrying area, and a security enhancement compensation strategy for the weak protection link. Specifically, for the weak link area, a link redundancy configuration is adopted, adding a backup link to form a redundant backup with the original weak link. The parameters of the backup link are consistent with the original link. At the same time, link switching trigger conditions are set, such as the original link latency exceeding 30 milliseconds, generating a link redundancy compensation strategy. For the weak service carrying area, a service diversion method is adopted, diverting some of the services carried in this area to other service carrying areas. The diversion ratio is set according to the service priority, with 50% of high-priority services retained and 80% of low-priority services diverted, generating a service diversion compensation strategy. For the weak protection link, a security enhancement method is adopted, upgrading the security authentication mechanism, such as upgrading password authentication to password + fingerprint dual authentication, adding a security monitoring module to monitor the operation status of the protection link in real time, and generating a security enhancement compensation strategy.

[0057] Step S440: The baseline access strategy is reconstructed and optimized according to the link redundancy compensation strategy, the service diversion compensation strategy, and the security enhancement compensation strategy to obtain the terminal access optimization strategy. Specifically, the three compensation strategies are integrated into the baseline access strategy, and the corresponding configuration parameters of the baseline access strategy are adjusted. Specifically, the link configuration parameters are adjusted according to the link redundancy compensation strategy, adding a backup link configuration; the service bearer configuration parameters are adjusted according to the service diversion compensation strategy, optimizing the service allocation method; and the transmission control and security configuration parameters are adjusted according to the security enhancement compensation strategy, upgrading the security authentication and monitoring configuration. The feasibility of the reconstructed strategy is verified by simulating the execution of the reconstructed strategy to ensure no parameter conflicts and that access requirements are met, ultimately obtaining the terminal access optimization strategy.

[0058] Step S500: Based on the current access backup network, construct a terminal access backup mechanism, and perform primary / backup access switching control and dynamic adjustment of access strategy for the intelligent converged terminal according to the terminal access backup mechanism and the terminal access optimization strategy.

[0059] Specifically, firstly, a terminal access backup mechanism is constructed by combining the network characteristics of the current access backup network and the operational status of the current access main network. This mechanism clarifies the switching timing, backup deployment process, and switching verification standards. Then, based on the backup mechanism and terminal access optimization strategies, the operational status of the current access main network is monitored in real time. When an anomaly occurs in the main network, the intelligent converged terminal is controlled to switch to the current access backup network. Simultaneously, the configuration parameters of the terminal access optimization strategy are dynamically adjusted according to the operational status of the backup network to ensure the stability and security of the access. For example, if the current access backup network is a wide area communication network, the constructed terminal access backup mechanism clarifies that the switching timing is when the main network access availability is below 80%, the backup deployment process involves pre-establishing a backup link and pre-synchronizing service status, and the switching verification standard is that the backup network access availability is ≥85%. When the main network access availability drops to 78%, the terminal is controlled to switch to the wide area communication network, and the transmission rate configuration parameters in the optimization strategy are adjusted to adapt to the network characteristics of the backup network.

[0060] In one possible implementation, the terminal access backup mechanism, step S500 further includes step S510, which involves predicting the handover timing based on the current network status change trend of the accessed main network to obtain the primary / backup handover timing characteristics. Specifically, an LSTM neural network algorithm is selected, and the network status data of the current accessed main network over the past 24 hours and real-time network status data are input to train a prediction model. This model predicts the network status change trend of the main network within the next hour, extracts key nodes in the trend, and determines the triggering conditions for primary / backup handover, such as a continuous decline in access availability and a link interruption probability exceeding 1%. This forms the primary / backup handover timing characteristics, which include the handover triggering conditions, the handover warning time, and the handover priority. For example, if the prediction finds that the access availability of the main network will drop from 90% to 75% within the next 30 minutes, and the link interruption probability will reach 1.2%, then the primary / backup handover timing characteristics are: handover triggering conditions (access availability < 80% or link interruption probability > 1%), a handover warning time of 30 minutes, and a high handover priority.

[0061] Step S520: If the primary / backup switchover timing characteristics meet the switchover timing constraints, perform backup link pre-establishment, service status pre-synchronization, and access parameter pre-loading on the intelligent converged terminal according to the current access backup network to obtain the backup access pre-deployment result. Specifically, determine whether the primary / backup switchover timing characteristics meet the switchover timing constraints. The switchover timing constraints are set as follows: the switchover triggering condition has been triggered or the switchover warning time is ≤30 minutes. If the constraints are met, start the backup access pre-deployment process. Establish a backup link between the current access backup network and the intelligent converged terminal, with the link parameters consistent with the primary network link parameters. Synchronize the current service data and operating status of the intelligent converged terminal to the backup network. Preload the access parameters in the terminal access optimization strategy to the access control module of the backup network. After pre-deployment, detect the connectivity of the backup link, the synchronization rate of the service status, and the completeness of the loading of access parameters to obtain the backup access pre-deployment result.

[0062] Step S530: Based on the backup access pre-deployment result, perform a handover feasibility verification on the current access backup network to obtain a primary / backup handover pre-confirmation result. Specifically, set handover feasibility verification indicators, including backup link connectivity ≥99%, service status synchronization rate ≥99%, access parameter loading integrity 100%, and backup network access availability ≥85%. Verify the backup access pre-deployment result and the backup network real-time operation data. If all indicators meet the requirements, the primary / backup handover pre-confirmation result is switchable. If any indicator is not met, adjust the backup access pre-deployment process, such as resynchronizing service status, reloading access parameters, and verifying again until all indicators are met, obtaining a switchable result. If, after multiple adjustments, any indicator is still not met, the pre-confirmation result is non-switchable.

[0063] Step S540: Based on the pre-confirmation result of the primary / backup switchover, control the intelligent converged terminal to switch from the current access primary network to the current access backup network. Specifically, if the pre-confirmation result of the primary / backup switchover is switchable, a switchover control command is sent to the access control modules of the intelligent converged terminal and the primary and backup networks to control the intelligent converged terminal to disconnect from the current access primary network and simultaneously access the current access backup network. After the switchover is completed, the connection status and service transmission status between the terminal and the backup network are checked to confirm the switchover is successful. If an abnormality occurs during the switchover process, such as service interruption, the system immediately switches back to the current access primary network and re-executes the backup access pre-deployment and switchover feasibility verification.

[0064] This application embodiment obtains access request data from intelligent converged terminals to local communication networks and wide area communication networks. Based on network status awareness, it performs access availability detection on the two types of networks and determines the primary and backup networks. Taking the primary network as the access subject, it obtains a baseline access strategy by constraining, screening, scoring, and optimizing multiple access schemes through an access game evaluation model. It performs passive threat inversion and vulnerability identification on the primary network, and provides protection compensation for the baseline strategy through link redundancy, service diversion, and security enhancement to obtain an optimized terminal access strategy. Based on the backup network, it constructs a backup access mechanism, performs primary and backup switching prediction, pre-deployment, and switching based on the primary network status, and dynamically adjusts the access strategy. These technical means solve the technical problems of insufficient dynamic adaptation and robustness guarantee in the existing terminal access management in multi-network environments, and achieve the technical effects of improving the dynamic adaptation capability of terminal access and enhancing the robustness and reliability of network access.

[0065] In the above text, refer to Figure 1 This paper describes in detail the intelligent converged terminal access optimization method based on network state awareness according to embodiments of the present invention. Next, we will refer to... Figure 2 This invention describes a network-state-aware intelligent converged terminal access optimization system according to an embodiment of the present invention.

[0066] The network-state-aware intelligent converged terminal access optimization system according to embodiments of the present invention addresses the technical problems of insufficient dynamic adaptation and robustness assurance in existing terminal access management under multi-network environments, achieving the technical effects of improving the dynamic adaptation capability of terminal access and enhancing the robustness and reliability of network access. The network-state-aware intelligent converged terminal access optimization system includes: an access request module 10, an access availability detection module 20, an access configuration game-theoretic optimization module 30, a main protection compensation module 40, and an access control module 50.

[0067] The access request module 10 is used to acquire access request data from the intelligent converged terminal to the communication network system, which includes a local communication network and a wide area communication network. The access availability detection module 20 is used to perform access availability detection on the communication network system under network status awareness based on the access request data, and determine the current access main network and the current access backup network. The access configuration game optimization module 30 is used to perform access configuration game optimization on the intelligent converged terminal with the current access main network as the access subject and in combination with the access game evaluation model to obtain a baseline access strategy. The subject protection compensation module 40 is used to perform subject protection compensation under subject passive threat inversion on the baseline access strategy to obtain a terminal access optimization strategy. The access control module 50 is used to construct a terminal access backup mechanism based on the current access backup network, and perform primary and backup access switching control and dynamic adjustment of the access strategy for the intelligent converged terminal according to the terminal access backup mechanism and the terminal access optimization strategy.

[0068] The detailed description of the specific configuration of the access availability detection module 20 is explained as follows: As described above, the access availability detection module 20 performs network status awareness-based access availability detection on the communication network system based on the access request data to determine the current access main network and the current access backup network. The access availability detection module 20 may further include: a network status data acquisition unit for acquiring local network status data and local network capability feature data corresponding to the local communication network, and synchronously loading wide area network status data and wide area network capability feature data corresponding to the wide area communication network; a matching degree evaluation unit for performing matching degree evaluation on the local network capability feature data and the wide area network capability feature data respectively based on the access request data to obtain a network capability matching evaluation set; a health evaluation unit for performing health evaluation on the local network status data and the wide area network status data respectively to obtain a network health evaluation set; an access availability calculation unit for performing access availability calculation on the network capability matching evaluation set and the network health evaluation set according to predetermined weight conditions to obtain an access availability set; and a main / backup determination unit for performing main / backup determination on the communication network system based on the access availability set to determine the current access main network and the current access backup network.

[0069] The detailed description of the specific configuration of the access configuration game optimization module 30 is as follows: As mentioned above, taking the current access main network as the access subject, and combining the access game evaluation model, the access configuration game optimization is performed on the intelligent converged terminal to obtain a benchmark access strategy. The access configuration game optimization module 30 may further include: a multimodal access configuration decision unit for making multimodal access configuration decisions for the intelligent converged terminal based on the access subject to obtain a terminal access scheme group; a multi-angle evaluation unit for performing multi-angle evaluation on the terminal access scheme group based on the access game evaluation model to obtain an access game evaluation space; an access evaluation constraint condition acquisition unit for obtaining access evaluation constraints, which include access quality score constraints and access risk score constraints; a constraint verification optimization unit for performing constraint verification optimization on the terminal access scheme group based on the access game evaluation space and the access evaluation constraints to obtain a terminal access candidate group; and an access game score iterative optimization unit for performing access game score iterative optimization on the terminal access candidate group based on the access game evaluation space to generate the benchmark access strategy.

[0070] The multimodal access configuration decision unit, which performs multimodal access configuration decisions on the intelligent converged terminal based on the access subject to obtain a group of terminal access schemes, may further include: a multidimensional state characteristic analysis subunit for analyzing the multidimensional state characteristics of the access subject and establishing a main network characteristic map; a link configuration parameter parsing subunit for parsing the link configuration parameters of the intelligent converged terminal based on the main network characteristic map to obtain a link configuration decision set; a service bearer configuration parameter parsing subunit for parsing the service bearer configuration parameters of the intelligent converged terminal based on the main network characteristic map to obtain a service bearer configuration decision set; a transmission control configuration parameter parsing subunit for parsing the transmission control configuration parameters of the intelligent converged terminal based on the main network characteristic map to obtain a transmission control configuration decision set; a random combination subunit for randomly combining the link configuration decision set, the service bearer configuration decision set, and the transmission control configuration decision set to obtain multiple initial access schemes; and a feedback adjustment subunit for performing feedback adjustment on each initial access scheme under conflict identification to generate the group of terminal access schemes.

[0071] The evaluation process involves evaluating the terminal access scheme group from multiple perspectives based on the access game evaluation model to obtain an access game evaluation space. The multi-perspective evaluation unit may further include: a multi-scheme virtual access subunit for dynamically modeling the current access main network, obtaining a main network twin model, and executing multi-scheme virtual access for the intelligent converged terminal in conjunction with the terminal access scheme group to obtain multiple access response virtual data; an access game evaluation model activation subunit for activating the access game evaluation model, which includes an access quality scoring layer, an access risk scoring layer, and an access game evaluation layer; and a scoring subunit for inputting the multiple access response virtual data into the access quality scoring layer to obtain multiple access quality scores. The multiple access response virtual data are input into the access risk scoring layer to obtain multiple access risk scores; the access game scoring function acquisition subunit is used to calculate the quality score concentration and risk score concentration, and to perform feedback adjustment on the access game evaluation layer based on the quality score concentration and the risk score concentration to obtain the access game scoring function; the access game scoring subunit is used to input the multiple access quality scores and the multiple access risk scores into the access game scoring function to obtain multiple access game scores; the scheme group mapping subunit is used to map the terminal access scheme group based on the multiple access quality scores, the multiple access risk scores and the multiple access game scores to obtain the access game evaluation space.

[0072] The specific configuration of the main protection compensation module 40 is described in detail below: As mentioned above, the main protection compensation module 40 performs main passive threat inversion on the benchmark access strategy to obtain a terminal access optimization strategy. The module may further include: a multi-dimensional passive threat inversion unit for performing multi-dimensional passive threat inversion on the access subject based on the benchmark access strategy to obtain a main network vulnerability profile; a weakness information determination unit for determining the weak link area, weak service carrying area, and weak protection link of the access subject based on the main network vulnerability profile; a compensation strategy generation unit for generating a link redundancy compensation strategy for the weak link area, a service diversion compensation strategy for the weak service carrying area, and a security enhancement compensation strategy for the weak protection link; and a reconstruction optimization unit for reconstructing and optimizing the benchmark access strategy based on the link redundancy compensation strategy, the service diversion compensation strategy, and the security enhancement compensation strategy to obtain the terminal access optimization strategy.

[0073] The detailed description of the specific configuration of the access control module 50 is explained as follows: As described above, the terminal access backup mechanism may further include: a handover timing prediction unit for predicting the handover timing based on the network status change trend of the current access main network and obtaining the primary / backup handover timing characteristics; a backup access pre-deployment result acquisition unit for performing backup link pre-establishment, service status pre-synchronization, and access parameter pre-loading on the intelligent converged terminal according to the current access backup network if the primary / backup handover timing characteristics meet the handover timing constraints, and obtaining the backup access pre-deployment result; a handover feasibility verification unit for performing handover feasibility verification on the current access backup network according to the backup access pre-deployment result and obtaining the primary / backup handover pre-confirmation result; and a handover unit for controlling the intelligent converged terminal to switch from the current access main network to the current access backup network based on the primary / backup handover pre-confirmation result.

[0074] The access availability calculation unit may further include: the predetermined weight conditions include network capability matching weight and network health weight.

[0075] The access game evaluation model activation sub-unit may further include: the access game evaluation layer includes access quality score weights and access risk score weights.

[0076] The network-state-aware intelligent converged terminal access optimization system provided in this embodiment of the invention can execute the network-state-aware intelligent converged terminal access optimization method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0077] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0078] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for optimizing intelligent converged terminal access based on network state awareness, characterized in that, The method includes: Acquire access request data from the intelligent converged terminal to the communication network system, wherein the communication network system includes a local communication network and a wide area communication network; Based on the access request data, the communication network system is subjected to access availability detection under network status awareness to determine the current access to the main network and the current access to the backup network. Using the current access main network as the access subject, and combining the access game evaluation model, the intelligent fusion terminal is subjected to access configuration game optimization to obtain the benchmark access strategy; Subject protection compensation under subject passive threat inversion is performed on the benchmark access strategy to obtain terminal access optimization strategy; Based on the current access backup network, a terminal access backup mechanism is constructed, and the intelligent converged terminal is subjected to primary / backup access switching control and dynamic adjustment of access strategy according to the terminal access backup mechanism and the terminal access optimization strategy.

2. The intelligent converged terminal access optimization method based on network state awareness as described in claim 1, characterized in that, Based on the access request data, the communication network system is subjected to network status-aware access availability detection to determine the current access to the primary network and the current access to the backup network, including: Obtain the local network status data and local network capability characteristic data corresponding to the local communication network, and synchronously load the wide area network status data and wide area network capability characteristic data corresponding to the wide area communication network. Based on the access request data, the matching degree of the local network capability feature data and the wide area network capability feature data is evaluated to obtain a network capability matching evaluation set. Health assessments are performed on the local network status data and the wide area network status data respectively to obtain a network health assessment set; Based on predetermined weight conditions, the network capability matching evaluation set and the network health evaluation set are used to calculate access availability, thereby obtaining an access availability set. The communication network system is determined based on the access availability set, identifying the current primary network and the current backup network.

3. The intelligent converged terminal access optimization method based on network state awareness as described in claim 1, characterized in that, Using the current access main network as the access subject, and combining the access game evaluation model, the intelligent converged terminal is subjected to access configuration game optimization to obtain a baseline access strategy, including: Based on the access subject, a multimodal access configuration decision is made for the intelligent converged terminal to obtain a group of terminal access schemes; The terminal access scheme group is evaluated from multiple perspectives based on the access game evaluation model to obtain the access game evaluation space. Obtain access evaluation constraints, which include access quality score constraints and access risk score constraints; Based on the access game evaluation space, the terminal access scheme group is subjected to constraint verification and optimization according to the access evaluation constraints to obtain the terminal access candidate group. Based on the access game evaluation space, the terminal access candidate group is iteratively optimized through access game scoring to generate the benchmark access strategy.

4. The intelligent converged terminal access optimization method based on network state awareness as described in claim 3, characterized in that, Based on the access subject, a multimodal access configuration decision is made for the intelligent converged terminal to obtain a group of terminal access schemes, including: The access entities are analyzed for multi-dimensional state characteristics, and a main network characteristic map is established. Based on the main network characteristic map, the link configuration parameters of the intelligent fusion terminal are parsed to obtain the link configuration decision set; Based on the main network characteristic map, the intelligent converged terminal is analyzed for service bearer configuration parameters to obtain a service bearer configuration decision set. Based on the main network characteristic map, the transmission control configuration parameters of the intelligent fusion terminal are parsed to obtain the transmission control configuration decision set; Randomly combine the link configuration decision set, the service bearer configuration decision set, and the transmission control configuration decision set to obtain multiple initial access schemes; Feedback adjustment is performed on each initial access scheme under conflict identification to generate the terminal access scheme group.

5. The intelligent converged terminal access optimization method based on network state awareness as described in claim 3, characterized in that, The terminal access scheme group is evaluated from multiple perspectives based on the access game evaluation model to obtain the access game evaluation space, including: Dynamic modeling is performed based on the current access to the main network to obtain the main network twin model. The intelligent converged terminal performs multi-scheme virtual access in combination with the terminal access scheme group to obtain multiple access response virtual data. Activate the access game evaluation model, which includes an access quality scoring layer, an access risk scoring layer, and an access game evaluation layer; The multiple access response virtual data are input into the access quality scoring layer to obtain multiple access quality scores, and the multiple access response virtual data are input into the access risk scoring layer to obtain multiple access risk scores; Calculate the concentration of quality scores and the concentration of risk scores, and adjust the access game evaluation layer based on the concentration of quality scores and the concentration of risk scores to obtain the access game scoring function; Input the multiple access quality scores and the multiple access risk scores into the access game scoring function to obtain multiple access game scores; The terminal access scheme group is mapped based on the multiple access quality scores, the multiple access risk scores, and the multiple access game scores to obtain the access game evaluation space.

6. The intelligent converged terminal access optimization method based on network state awareness as described in claim 1, characterized in that, The baseline access strategy is subjected to subject protection compensation under subject passive threat inversion to obtain terminal access optimization strategy, including: Based on the baseline access strategy, multi-dimensional passive threat inversion is performed on the access subject to obtain a vulnerability profile of the main network; Based on the main network vulnerability profile, the weak link areas, weak service carrying areas, and weak protection links of the access entity are identified. A link redundancy compensation strategy is generated for the weak link area, a service diversion compensation strategy is generated for the weak service carrying area, and a security enhancement compensation strategy is generated for the weak protection link. The baseline access strategy is reconstructed and optimized based on the link redundancy compensation strategy, the service diversion compensation strategy, and the security enhancement compensation strategy to obtain the terminal access optimization strategy.

7. The intelligent converged terminal access optimization method based on network state awareness as described in claim 1, characterized in that, The terminal access backup mechanism includes: Based on the current network status change trend of the main network, the switching timing is predicted to obtain the main / standby switching timing characteristics. If the primary / backup switching timing characteristics meet the switching timing constraints, the intelligent converged terminal performs backup link pre-establishment, service status pre-synchronization, and access parameter pre-loading according to the current access backup network to obtain the backup access pre-deployment result; Based on the pre-deployment results of the backup access, the feasibility of switching the current access backup network is verified, and the pre-confirmation result of the primary / backup switchover is obtained. Based on the pre-confirmation result of the primary / backup switchover, the intelligent converged terminal is controlled to switch from the currently accessed primary network to the currently accessed backup network.

8. The intelligent converged terminal access optimization method based on network state awareness as described in claim 2, characterized in that, The predetermined weight conditions include network capability matching weight and network health weight.

9. The intelligent converged terminal access optimization method based on network state awareness as described in claim 5, characterized in that, The access game evaluation layer includes access quality score weights and access risk score weights.

10. A network-state-aware intelligent converged terminal access optimization system, characterized in that, The system is used to implement the network state-aware intelligent converged terminal access optimization method according to any one of claims 1-9, and the system includes: The access request module is used to obtain access request data from the intelligent converged terminal to the communication network system, which includes a local communication network and a wide area communication network. The access availability detection module is used to perform access availability detection on the communication network system under network status awareness based on the access request data, and to determine the current access to the main network and the current access to the backup network. The access configuration game optimization module is used to perform access configuration game optimization on the intelligent fusion terminal with the current access main network as the access subject and in combination with the access game evaluation model to obtain the baseline access strategy; The main protection compensation module is used to perform main protection compensation under the main passive threat inversion on the benchmark access strategy to obtain the terminal access optimization strategy; The access control module is used to construct a terminal access backup mechanism based on the current access backup network, and to perform primary / backup access switching control and dynamic adjustment of access strategy for the intelligent converged terminal according to the terminal access backup mechanism and the terminal access optimization strategy.

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