Networking method and device of network nodes, storage medium and electronic equipment

Abstract

The invention discloses a networking method and device of network nodes, a storage medium and electronic equipment, and relates to the technical field of communication. The method comprises the steps of receiving a target operation performed by a target person on a target page, the target page being used for displaying a connection state among N network nodes in a target range environment, and the target operation comprising performing a dragging operation on a target node in the N network nodes; triggering a target event according to the target operation, updating the position information of the target node by executing the target event, and broadcasting the position change information of the target node in the target range environment; and on the basis of the updated position information of the target node, connection among the N network nodes is adjusted through a feature matching engine, and networking of the N updated network nodes is obtained. According to the method and the device, the technical problems that in a dynamically changing target range environment, the efficiency of a transmitted unified networking mode is low, and the environment change is difficult to quickly adapt are solved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a networking method, device, storage medium and electronic device for network nodes. Background Art

[0002] Traditional networking technologies face unprecedented challenges in the dynamic environment of a test range. As venues for aerospace testing and complex industrial experiments, test ranges place far greater demands on network connectivity than is typically required. These not only require high-bandwidth, low-latency communications, but also must maintain connectivity and stability amidst frequent node movement and rapidly changing environmental parameters. However, the limitations of traditional networking approaches based on static configurations are becoming increasingly apparent in test range environments, becoming a key bottleneck restricting operational efficiency and safety.

[0003] First, the dynamic nature of the range environment requires the network to be able to quickly respond to changes in node locations. Traditional networking relies on pre-defined network architectures and manual configuration. Once node locations change, the network reconstruction process is time-consuming and error-prone, seriously impacting the continuity and responsiveness of range missions. Second, the complex terrain and variable climatic conditions within the range place higher demands on network communication quality. Traditional networking methods lack real-time monitoring and adaptive adjustment mechanisms, making it difficult to maintain stable link quality and network performance in the range environment. This results in inefficient data transmission and frequent communication interruptions.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] The embodiments of the present application provide a networking method, device, storage medium and electronic device for network nodes to at least solve the technical problem that traditional networking methods are inefficient and difficult to quickly adapt to environmental changes in a dynamically changing shooting range environment.

[0006] According to one aspect of an embodiment of the present application, a method for networking network nodes is provided, comprising: receiving a target operation performed by a target person on a target page, wherein the target page is used to display the connection status between N network nodes in a shooting range environment, and the target operation comprises dragging a target node among the N network nodes, wherein the target operation of the target page synchronously affects the network nodes in the shooting range environment, and each of the N network nodes comprises the initial position information of the network node; triggering a target event according to the target operation, updating the position information of the target node by executing the target event, and broadcasting the position change information of the target node in the shooting range environment; adjusting the connection between the N network nodes based on the updated position information of the target node by a feature matching engine to obtain an updated networking of the N network nodes, wherein the feature matching engine is used to determine the matching degree of the N network nodes based on a matching degree strategy in combination with the position information of the target node.

[0007] Optionally, based on the updated location information of the target node, the connection between the N network nodes is adjusted through the feature matching engine, including: based on the updated location information of the target node, obtaining the target information of the current N network nodes through the feature matching engine, wherein the target information includes at least the location information, signal strength and security level of the network node; determining the target distance between adjacent network nodes in the N network nodes based on the location information of the N network nodes, and obtaining S target distances, wherein S is an integer greater than or equal to 1; determining the channel quality between adjacent network nodes in the N network nodes based on the signal strength of the N network nodes, and obtaining S channel qualities; determining the target factor based on the security level of the N network nodes, wherein the target factor is used to characterize the impact of the security level of the N network nodes on the connection matching degree between network nodes; adjusting the connection between the N network nodes based on the target factor, the S target distances and the S channel qualities.

[0008] Optionally, the connection between N network nodes is adjusted according to the target factor, S target distances and S channel qualities, including: obtaining a first coefficient, a second coefficient and a third coefficient, wherein the first coefficient is used to characterize the weight of the target distance, the second coefficient is used to characterize the weight of the channel quality, and the third coefficient is used to characterize the weight of the target factor; determining S matching degrees according to the first coefficient, the second coefficient, the third coefficient, the target factor, the S target distances and the S channel qualities; when the matching degree is greater than or equal to a first preset threshold, determining to establish a connection between two adjacent network nodes corresponding to the matching degree; when the matching degree is less than the first preset threshold, disconnecting the two adjacent network nodes corresponding to the matching degree.

[0009] Optionally, after adjusting the connection between N network nodes according to the feature matching engine based on the updated location information of the target node, the method also includes: obtaining status information of the target range environment, wherein the status information includes at least the location information, link load information and channel quality of the N network nodes; based on the status information, using a target algorithm to determine the target strategy for each network node according to the status information and the global network environment information, wherein the target strategy is used to adjust the communication parameters of the network node; and adjusting the N network nodes according to the target strategy.

[0010] Optionally, after adjusting N network nodes according to the target strategy, the method includes: collecting feedback information, wherein the feedback information is used to characterize the performance parameters of the N network nodes after adjustment according to the target strategy in the target range environment, wherein the performance parameters include at least a first value, a second value, and a third value, wherein the first value is used to characterize the amount of data transmitted per unit time in the target range environment, the second value is used to characterize the transmission time delay between data network nodes, and the third value is used to characterize the energy consumption of each network node in data transmission; determining a reward value based on the first value, the second value, and the third value, wherein the reward value is used to quantitatively evaluate the performance of the N network nodes after adjustment in the target range environment; and updating the target algorithm based on the reward value.

[0011] Optionally, before receiving the target operation performed by the target person on the target page, it includes: deploying N network nodes in the shooting range environment, wherein each network node includes at least attribute information, a positioning module, a communication module and an environmental sensor, wherein the attribute information includes at least the unique identification, type label and security level of the network node; performing an initialization operation on the N network nodes, wherein the initialization operation is used to initially network the N network nodes through a self-organizing network protocol; uploading the attribute information of the N network nodes after the initialization operation to the central server.

[0012] Optionally, the security levels of N network nodes are detected; when the difference between the security levels of the i-th network node and the j-th network node among the N network nodes is less than a second preset threshold, the connection between the i-th network node and the j-th network node is maintained, where i and j are both integers greater than or equal to 1 and less than or equal to N; when the difference between the security levels of the i-th network node and the j-th network node among the N network nodes is greater than or equal to the second preset threshold, the connection between the i-th network node and the j-th network node is disconnected, and an early warning is issued.

[0013] According to another aspect of the present application, a networking device for network nodes is also provided, including: a receiving unit, receiving a target operation performed by a target person on a target page, wherein the target page is used to display the connection status between N network nodes in a shooting range environment, and the target operation includes dragging a target node among the N network nodes, wherein the target operation of the target page synchronously affects the network nodes in the shooting range environment, and each of the N network nodes includes the initial position information of the network node; an updating unit, used to trigger a target event according to the target operation, update the position information of the target node by executing the target event, and broadcast the position change information of the target node in the shooting range environment; a connecting unit, based on the updated position information of the target node, adjusts the connection between the N network nodes through a feature matching engine to obtain the updated networking of the N network nodes, wherein the feature matching engine is used to determine the matching degree of the N network nodes based on a matching degree strategy and in combination with the position information of the target node.

[0014] According to another aspect of the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program runs, the device where the computer-readable storage medium is located executes the above-mentioned network node networking method.

[0015] According to another aspect of the present application, an electronic device is also provided, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned network node networking method.

[0016] In the present application, a target operation performed by a target person on a target page is first received, wherein the target page is used to display the connection status between N network nodes in a shooting range environment, and the target operation includes dragging a target node among the N network nodes, wherein the target operation on the target page synchronously affects the network nodes in the shooting range environment, and each of the N network nodes includes the initial position information of the network node. Then, a target event is triggered according to the target operation, and the position information of the target node is updated by executing the target event, and the position change information of the target node is broadcast in the shooting range environment. Then, based on the updated position information of the target node, the connection between the N network nodes is adjusted through a feature matching engine to obtain an updated network of the N network nodes, wherein the feature matching engine is used to determine the matching degree of the N network nodes based on a matching degree strategy and in combination with the position information of the target node. That is, through interactive dragging and real-time dynamic networking based on the feature matching engine, the purpose of quickly responding to node position changes and automatically updating the network configuration is achieved, thereby achieving the technical effect of efficient and adaptive network reconstruction, thereby solving the technical problem that the traditional networking method is inefficient and difficult to quickly adapt to environmental changes in a dynamically changing shooting range environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 This is a process of an optional network node networking method according to an embodiment of the present application Figure 1 ;

[0019] Figure 2 is a flow chart of an optional feature matching engine according to an embodiment of the present application;

[0020] Figure 3 This is a process of an optional network node networking method according to an embodiment of the present application Figure 2 ;

[0021] Figure 4 This is a schematic diagram of an optional networking device of network nodes according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0024] It should be noted that the collected information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this application are information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation portals for users to choose to authorize or refuse. For example, an interface is set up between this system and relevant users or institutions to provide users with corresponding operation portals for users to choose to agree or refuse the automated decision-making results; if the user chooses to refuse, the expert decision-making process will be entered.

[0025] According to an embodiment of the present application, a method embodiment of a networking method of network nodes is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] It should be noted that an intelligent networking system can be used as the execution subject of the network node networking method of the embodiment of the present application. It is understandable that the network node networking method provided in the embodiment of the present application can also be executed by other systems or devices, and the embodiment of the present application does not specifically limit this.

[0027] Figure 1 This is a process of an optional network node networking method according to an embodiment of the present application Figure 1 ,like Figure 1 As shown, the method includes the following steps:

[0028] Step S101: receiving a target operation performed by a target person on a target page.

[0029] In step S101 , a target page is used to display the connection status between N network nodes in a shooting range environment, and a target operation includes dragging a target node among the N network nodes.

[0030] In step S101 , a target operation of a target page synchronously affects network nodes in a range environment, and each of the N network nodes includes initial position information of the network node.

[0031] Optionally, the target page refers to a 3D visualization interface built using WebGL technology (used to render interactive 2D and 3D graphics in a web browser without relying on any additional plug-ins), which is used to intuitively display the connection status between N network nodes in the shooting range environment. The operator can use this page to intuitively operate the network nodes, such as dragging nodes, drawing connections, and editing topology.

[0032] Optionally, the target operation refers to a drag operation performed by the target person on one or more nodes among the N network nodes, with the purpose of changing the physical position of the node in the range environment and the resulting update of the network connection status.

[0033] Optionally, by receiving operation instructions through the target page, the intelligent networking system converts physical operations (such as dragging) into signals that the system can recognize, ensuring that network nodes in the shooting range environment can respond to the operator's intentions in real time and realize dynamic adjustment of the network topology.

[0034] Step S102 : triggering a target event according to the target operation, updating the position information of the target node by executing the target event, and broadcasting the position change information of the target node in the shooting range environment.

[0035] Optionally, a target event is an internal system event triggered by a target user's drag operation, which notifies the system to update the target node's location information. For example, if a user drags node A to coordinates (x, y) on the interface, the event EVENT_DRAG(A, x, y) is triggered, and the system updates node A's location and broadcasts it to the entire network.

[0036] Optionally, position change information refers to the updated position data calculated by the system after the target node moves from an initial position to a new position, including the node's new coordinates, direction and other information; broadcasting refers to sending the target node's position change information to each of the N network nodes through a communication protocol in a shooting range environment to ensure information synchronization among all nodes in the network.

[0037] Optionally, this step transitions from user action to system response, ensuring real-time updates and broadcasts of network node location information, providing accurate location data for subsequent network connection status adjustments. Through broadcasting, all network nodes can promptly obtain the target node's new location, allowing them to prepare to respond to potential network changes.

[0038] Step S103 : Based on the updated location information of the target node, the connection between the N network nodes is adjusted by a feature matching engine to obtain an updated network of the N network nodes.

[0039] In step S103, the feature matching engine is used to determine the matching degrees of the N network nodes based on the matching degree strategy and in combination with the location information of the target node.

[0040] Optionally, the feature matching engine is an algorithm engine that can calculate the matching degree between nodes based on the new location information of the target node and the features of N network nodes (such as type label, security level, channel quality, etc.).

[0041] Optionally, the matching strategy refers to an algorithm or rule based on which the feature matching engine is used to evaluate the suitability of connections between N network nodes.

[0042] Optionally, a feature matching engine automatically evaluates the suitability of connections between network nodes and dynamically adjusts network connections based on the calculated results. This step ensures that the network topology can quickly adapt to changes in the range environment, such as node movement, while also taking into account factors such as signal quality and security level, thereby improving network stability and security.

[0043] It can be seen from the contents of steps S101 to S103 that, in this application, the target operation performed by the target person on the target page is first received, wherein the target page is used to display the connection status between N network nodes in the shooting range environment, and the target operation includes dragging the target node in the N network nodes, wherein the target operation of the target page synchronously affects the network nodes in the shooting range environment, and each network node in the N network nodes includes the initial position information of the network node, and then the target event is triggered according to the target operation, and the position information of the target node is updated by executing the target event, and the position change information of the target node is broadcast in the shooting range environment, and then Then, based on the updated position information of the target node, the connection between the N network nodes is adjusted through the feature matching engine to obtain the updated networking of the N network nodes. Among them, the feature matching engine is used to determine the matching degree of the N network nodes based on the matching degree strategy and the position information of the target node. That is, through interactive dragging and real-time dynamic networking based on the feature matching engine, the purpose of quickly responding to node position changes and automatically updating the network configuration is achieved, thereby achieving the technical effect of efficient and adaptive network reconstruction, and then solving the technical problem that the traditional networking method is inefficient and difficult to quickly adapt to environmental changes in the dynamically changing target range environment.

[0044] In an optional embodiment, the intelligent networking system obtains the target information of the current N network nodes through a feature matching engine based on the updated location information of the target node, wherein the target information includes at least the location information, signal strength and security level of the network node; then, the target distance between adjacent network nodes in the N network nodes is determined according to the location information of the N network nodes, and S target distances are obtained, wherein S is an integer greater than or equal to 1; the channel quality between adjacent network nodes in the N network nodes is determined according to the signal strength of the N network nodes, and S channel qualities are obtained; the target factor is determined according to the security level of the N network nodes, wherein the target factor is used to characterize the security level of the N network nodes and its impact on the connection matching degree between network nodes; finally, the connection between the N network nodes is adjusted according to the target factor, the S target distances and the S channel qualities.

[0045] Optionally, the intelligent networking system receives a drag operation performed by the target person through the target page. This operation immediately triggers a target event within the system. The execution of the target event causes the location information of the target node to be updated, and this updated location information will be immediately synchronized to all N network nodes in the target range environment through the broadcast mechanism, ensuring that the entire network has instant understanding of the new location of the target node. Then, the feature matching engine extracts the updated location information, signal strength detection data and node security level information as the basis for matching calculation. The target information mentioned here includes three key dimensions: location information, signal strength and security level. This information reflects the key characteristics of the current state of the network node.

[0046] Optionally, the feature matching engine then accurately calculates the target distances between the N network nodes based on their location information, for a total of S target distances. This target distance calculation takes into account the three-dimensional spatial distribution of network nodes, ensuring an assessment of the feasibility of physical connections (e.g., whether the actual distance between two nodes is close enough to establish a valid connection). The S value reflects the number of possible connections in the actual network, which varies with network size and topology. Simultaneously, the feature matching engine determines the channel quality of adjacent network nodes between the N network nodes based on the signal strength data from the N network nodes, resulting in S channel quality values. This process takes into account the effectiveness and stability of signal transmission. Higher channel quality indicates better communication quality between the two nodes, making them more suitable for establishing a direct connection. Next, the feature matching engine evaluates the security level information of the N network nodes and calculates a target factor. The target factor is designed to quantify the impact of differences in security levels between network nodes on connection compatibility. When the security levels of two nodes differ significantly, the target factor reduces their compatibility, thereby reducing potential security risks. Finally, the feature matching engine uses the target factor, S target distances, and S channel qualities to calculate the matching degrees of all possible connections according to the established matching degree strategy, and automatically adjusts the connection status between N network nodes based on the matching degrees.

[0047] From the above content, it can be seen that by implementing the above steps, the intelligent networking system can quickly respond to the physical movement of network nodes in the ever-changing range environment, automatically adjust the connection status between nodes, and ensure that the network connection is both efficient and secure. Specifically, the overall effect of the system is reflected in the following aspects: the system can quickly capture the movement of nodes and adjust the connection relationship accordingly, so that the network is always in the optimal or suboptimal state, reducing the need for manual intervention; with the computing power of the feature matching engine, the system can intelligently evaluate the matching degree between network nodes, and based on the comprehensive consideration of location, signal strength and security level, automatically adjust the connection between N network nodes, avoiding invalid connections caused by weak signals or mismatched security levels; by introducing the target factor to consider the difference in security levels, the system can effectively prevent the establishment of improper connections between network nodes of different security levels, thereby reducing the potential security risks of the network and improving the overall network security.

[0048] In an optional embodiment, the intelligent networking system obtains a first coefficient, a second coefficient, and a third coefficient, wherein the first coefficient is used to characterize the weight of the target distance, the second coefficient is used to characterize the weight of the channel quality, and the third coefficient is used to characterize the weight of the target factor. Then, S matching degrees are determined based on the first coefficient, the second coefficient, the third coefficient, the target factor, S target distances, and S channel qualities. When the matching degree is greater than or equal to a first preset threshold, it is determined to establish a connection between two adjacent network nodes corresponding to the matching degree. When the matching degree is less than the first preset threshold, the two adjacent network nodes corresponding to the matching degree are disconnected.

[0049] Optionally, the intelligent networking system first reads the first, second, and third coefficients, which correspond to the weights of the target distance, channel quality, and target factor, respectively. During system initialization, these weights can be set to default values ​​(e.g., 0.4, 0.3, 0.3). However, in more advanced application scenarios, they can be dynamically adjusted based on specific needs to more accurately reflect the impact of different factors on network connection compatibility.

[0050] Optionally, the feature matching engine uses the first coefficient, the second coefficient, and the third coefficient, combined with the target factor, the S target distances, and the S channel qualities, to determine S matching degrees using a matching degree calculation formula. Each matching degree value reflects the suitability of the connection between the corresponding two network nodes.

[0051] Optionally, for each calculated matching value, the feature matching engine compares it with a pre-set first threshold (e.g., θ, which can be initially set to 0.7). If the matching degree is greater than or equal to the first preset threshold, the connection between the two adjacent network nodes is considered appropriate, and the networking system automatically establishes or maintains the connection. Conversely, if the matching degree is lower than the first preset threshold, the connection between the two nodes is considered inappropriate, and the system automatically disconnects the connection to avoid unnecessary communication burden or security risks.

[0052] Optionally, the matching degree between nodes i and j is calculated as shown in Formula 1:

[0053]

[0054] Among them, D ij Refers to the Euclidean distance (target distance) between nodes i and j; CQI ij refers to the channel quality indicator (channel quality is determined by parameters such as signal strength and bit error rate); L1 and L2 refer to the security levels of nodes i and j; ω1, ω2, and ω3 refer to weight coefficients (default 0.4, 0.3, and 0.3), which can be adjusted dynamically; λ refers to the security level difference attenuation factor (default 0.5).

[0055] Optionally, Figure 2 This is a flow chart of an optional feature matching engine according to an embodiment of the present application. Figure 2 As shown, the feature matching engine first collects the current information of all network nodes, including the precise location of the node (obtained through GPS or other positioning technologies), signal strength (based on the signal quality of communication technologies such as Wi-Fi 6 and LoRaWAN), and pre-set security levels (reflecting the security status of network nodes, such as sensitivity and permission level). This data is the basis for calculating the matching degree between nodes. Then, the Euclidean distance between two adjacent network nodes is calculated. The closer the distance, the better the communication effect, which is an important factor in the matching degree calculation. At the same time, the attenuation factor of the channel quality and security level difference is calculated. Finally, the data calculated in the previous steps is summed up to calculate the matching degree between nodes. Based on the matching degree, the corresponding decision is made.

[0056] From the above content, it can be seen that by introducing the first coefficient, the second coefficient and the third coefficient, the intelligent networking system can more carefully balance the impact of target distance, channel quality and target factors on network connection, and realize the refined management of connection status; the system can dynamically adjust the connection according to the actual status of the network node, and can not only respond quickly when the network environment changes, but also actively optimize the network topology and improve the overall network performance; the introduction of target factors, especially through the consideration of security level differences, effectively avoids the potential risks caused by security level mismatch and strengthens the network's security management mechanism; using the matching degree calculation formula, the system can independently judge the suitability of the connection between network nodes, reduce the uncertainty brought by human decision-making, and improve the intelligence level of network connection decision-making.

[0057] In an optional embodiment, the intelligent networking system obtains status information of the target range environment after adjusting the connection between N network nodes according to the feature matching engine based on the updated location information of the target node, wherein the status information includes at least the location information, link load information and channel quality of the N network nodes. Then, based on the status information, a target algorithm is used to determine the target strategy for each network node according to the status information and the global network environment information, wherein the target strategy is used to adjust the communication parameters of the network node. Finally, the N network nodes are adjusted according to the target strategy.

[0058] Optionally, after the feature matching engine completes the connection adjustment between network nodes, the intelligent networking system immediately collects real-time status information from the range environment and network nodes, including but not limited to the current location information of N network nodes, link load information, and channel quality data. This information serves as the basis for subsequent optimization of network communication parameters, ensuring that network adjustments are based on the most up-to-date and realistic conditions.

[0059] Optionally, the intelligent networking system activates a target algorithm based on the acquired state information. The target algorithm can be a deep learning model, such as deep deterministic policy gradient, or a rule-based algorithm, such as a genetic algorithm or simulated annealing, depending on the system design and optimization objectives. The algorithm calculates a target policy for each network node based on the state information and global network environment information, such as node distribution and environmental interference. The target policy may include adjusting transmit power, switching communication frequency bands, modifying routing tables, etc., with the goal of optimizing network communication efficiency and reducing energy consumption while ensuring uncompromised communication quality.

[0060] Optionally, the target algorithm module issues adjustment instructions to N network nodes based on the calculated target strategy. Upon receiving the instructions, each network node adjusts its communication parameters in real time, such as adjusting transmit power from 20dBm to 18dBm, to adapt to changes in the range environment and optimize network performance. This process ensures the immediacy and effectiveness of network adjustments, enabling each node to quickly respond to the optimization strategy and improve its communication status.

[0061] From the above content, it can be seen that the intelligent networking system can not only quickly respond to changes in node position and adjust connections, but also further optimize the communication parameters of each node through intelligent algorithms based on the status information of the target range environment, significantly improving the overall communication efficiency and throughput of the network; the implementation of the target strategy helps network nodes to dynamically adjust communication parameters such as transmission power according to the current link load and channel quality, thereby effectively reducing network energy consumption and extending battery life, which is particularly suitable for mobile and energy-constrained target range environments; the dynamic generation and implementation of target strategies enhance the system's adaptability, and can automatically adjust the network's communication strategy when the target range environmental conditions change, maintaining stable network performance; by using target algorithms for strategy calculation, the system realizes data-driven intelligent decision-making, replacing traditional manual intervention, and improving the level of automation in network management and optimization.

[0062] In an optional embodiment, after adjusting N network nodes according to the target strategy, the intelligent networking system collects feedback information, wherein the feedback information is used to characterize the performance parameters of the N network nodes after adjustment according to the target strategy in the target range environment, wherein the performance parameters include at least a first value, a second value, and a third value, wherein the first value is used to characterize the amount of data transmitted per unit time in the target range environment, the second value is used to characterize the transmission time delay between data network nodes, and the third value is used to characterize the energy consumption of each network node in data transmission, and then a reward value is determined based on the first value, the second value, and the third value, wherein the reward value is used to quantitatively evaluate the performance of the N network nodes after adjustment in the target range environment, and finally the target algorithm is updated based on the reward value.

[0063] Optionally, after the intelligent networking system adjusts the communication parameters of N network nodes according to the target strategy, the system immediately collects feedback information on the adjusted network performance. This information covers the actual operating status of the network after adjustment and serves as the basis for subsequent evaluation and optimization. Among them, the most important performance parameters in the feedback information include the first value, the second value, and the third value, which respectively correspond to the amount of data transmitted per unit time (throughput), the transmission time delay between data network nodes (latency), and the energy consumption of each network node during the data transmission process. These values ​​are obtained by real-time monitoring of the communication activities of network nodes, ensuring the accuracy and timeliness of the feedback information.

[0064] Optionally, the intelligent networking system calculates a reward value based on the collected first, second, and third values ​​using a preset reward function. This reward function comprehensively considers three key metrics: throughput, latency, and energy consumption, and uses a specific calculation formula to quantitatively evaluate the overall performance of the adjusted network nodes. The reward value reflects the degree of proximity between the current network state and the optimization target; a higher value indicates a closer match between network performance and the target.

[0065] Optionally, the reward value is calculated as shown in formula (2):

[0066] R = η1·throughput - η2·end-to-end delay - η3·energy consumption (2)

[0067] Optionally, η1, η2, η3 represent normalization coefficients used to balance and adjust the relative importance of different performance indicators in the reward function.

[0068] Optionally, based on the calculated reward value, the intelligent networking system will provide feedback to the target algorithm for self-correction and optimization. In this embodiment, the target algorithm may use Deep Deterministic Policy Gradient (DDPG) or other reinforcement learning algorithms. These algorithms have the ability to self-learn and adjust, and continuously optimize their decision-making strategies through accumulated reward values, thereby improving the accuracy and efficiency of network adjustments. The reward value feedback mechanism enables the system to adjust algorithm parameters such as weight coefficients and security level difference attenuation factors based on actual results, thereby achieving better results in subsequent network optimization decisions.

[0069] From the above content, we can see that by introducing the concept of reward value, the intelligent networking system can convert network performance parameters (throughput, latency, energy consumption) into intuitive quantitative evaluation results, which is convenient for algorithm modules to understand and learn. The reward value feedback mechanism enables the target algorithm to self-adjust and optimize the decision-making strategy according to the actual effect of network adjustment, thereby improving the intelligence and adaptability of the algorithm. Based on the algorithm update of reward value, the system can optimize the communication parameters of network nodes, such as transmission power and communication frequency band, so as to improve the network performance in many aspects such as throughput, latency and energy consumption. The entire implementation process reflects the system's real-time monitoring and feedback of network status, ensuring the immediacy and accuracy of network adjustment strategies, and improving the stability and reliability of network operation.

[0070] In an optional embodiment, before receiving the target operation performed by the target person on the target page, the intelligent networking system deploys N network nodes in the shooting range environment, wherein each network node includes at least attribute information, a positioning module, a communication module and an environmental sensor, wherein the attribute information includes at least the unique identification, type label and security level of the network node, and then performs an initialization operation on the N network nodes, wherein the initialization operation is used to initially network the N network nodes through the self-organizing network protocol, and then uploads the attribute information of the N network nodes after the initialization operation to the central server.

[0071] Optionally, the intelligent networking system deploys N network nodes in a range environment. Each network node is equipped with necessary hardware components, including a positioning module (such as a GPS (Global Positioning System) module), a communication module (supporting multiple frequency bands such as Wi-Fi 6 (the standard for the sixth-generation wireless network technology) and LoRaWAN (a wireless communication protocol)), an environmental sensor (used to monitor environmental parameters such as temperature, humidity, and signal strength), and a control unit that stores attribute information. Attribute information is an important identifier of a network node, and at least includes a unique identifier of the network node (such as a node ID), a type tag (such as a relay node, a terminal node, a control node, etc.), and a security level (used to distinguish the security level of the node in the range environment).

[0072] Optionally, after deployment is complete, the intelligent networking system initializes N network nodes. This process is accomplished through self-organizing networking protocols (such as Ad-hoc On-Demand Distance Vector Routing (AODV)), which allow network nodes to spontaneously establish connections and form a preliminary network topology. In a range environment, this self-organizing mechanism can rapidly respond to the addition and removal of nodes, providing a dynamically adaptable network infrastructure for subsequent operations.

[0073] Optionally, after initialization, the intelligent networking system uploads the attribute information of N network nodes to the central server. This upload process ensures that the central server can obtain detailed information about each node, including its unique identifier, type label, and security level, providing comprehensive data support for subsequent network management and optimization. The central server not only stores this information but also performs preliminary network status analysis based on the attribute information, providing data preparation for subsequent functions such as feature matching and network optimization.

[0074] From the above content, it can be seen that the intelligent networking system is equipped with a positioning module, a communication module and an environmental sensor for each network node, ensuring the compatibility at the hardware level and the versatility of the network nodes in the target range environment, providing a solid foundation for subsequent network operations; through the initialization operation of the self-organizing network protocol, the system can establish a preliminary network structure in a relatively short time, reducing the complexity of manual configuration and improving the efficiency of network deployment and initial networking; uploading node attribute information to the central server realizes the centralized management and analysis of network node data, facilitates subsequent feature matching, network optimization decisions, etc., and improves the intelligence and systematization level of network management; the introduction of the self-organizing network mechanism provides support for the dynamic joining and exit of network nodes, so that the network can be quickly adjusted when the target range environment changes, enhancing the flexibility and adaptability of the network; the security level in the attribute information provides a guarantee for the security and compliance of subsequent network connections, ensuring that the communication between network nodes complies with the security requirements of the target range environment.

[0075] In an optional embodiment, the intelligent networking system detects the security levels of N network nodes; when the difference between the security levels of the i-th network node and the j-th network node among the N network nodes is less than a second preset threshold, the connection between the i-th network node and the j-th network node is maintained, where i and j are both integers greater than or equal to 1 and less than or equal to N; when the difference between the security levels of the i-th network node and the j-th network node among the N network nodes is greater than or equal to the second preset threshold, the connection between the i-th network node and the j-th network node is disconnected, and an early warning is issued.

[0076] Optionally, the intelligent networking system monitors the security levels of N network nodes in real time. The security level is one of the key attributes predefined for each network node in the system, used to distinguish the security features and permissions of different nodes in the range environment. It is usually expressed on a scale of 1 to 5, with level 1 representing the lowest security level and level 5 representing the highest security level.

[0077] Optionally, the system's feature matching engine periodically (for example, every 500 milliseconds) calculates the security level difference between any two of the N network nodes (denoted as the i-th network node and the j-th network node). This security level difference is obtained by comparing the security level values ​​of the two nodes and reflects the difference in security attributes between the two nodes. The calculated security level difference is then compared with a second preset threshold set by the system. The second preset threshold (for example, set to level 3) is a critical value defined by the network system to maintain network security and is used to determine whether the difference in security level between two network nodes allows them to remain connected. If the difference in security level between the i-th and j-th network nodes is less than the second preset threshold, the system determines that the security difference between the two nodes is within an acceptable range and maintains their connection, ensuring normal network communication and data exchange. If the difference in security level between the i-th and j-th network nodes is greater than or equal to the second preset threshold, the system determines that the security difference between the two nodes is excessive, posing a potential communication security risk. In this case, the intelligent networking system will automatically disconnect the connection between the two nodes and send an alert to the network administrator or target personnel through the early warning system, reminding them to pay attention to the security status of specific network nodes and the possible need for further security checks or network reconstruction.

[0078] Optionally, Figure 3 This is a process of an optional network node networking method according to an embodiment of the present application Figure 2 ,like Figure 3As shown, it includes: a visual drag-and-drop operation interface, node position management, feature matching engine, network optimization control, security policy enforcement, and physical layer communication. Among them, the visual drag-and-drop operation interface: users adjust the position of network nodes on the virtual map through intuitive dragging actions, thereby controlling the actual network layout in the shooting range. The interface provides real-time feedback on the network status after dragging, ensuring that operators can immediately see the impact of their operations on the network; node position management: responsible for maintaining and updating the location information of all network nodes. When the user drags a node on the operation interface, the node position management system immediately records these changes and provides accurate location data for subsequent functional modules. In addition, this module may also be integrated with positioning technologies such as GPS to automatically update the actual location of the node; feature matching engine: by calculating the matching degree between nodes (based on features such as distance and channel quality), it determines which nodes should be connected. This engine is the core component of the present invention. Based on machine learning algorithms, it can intelligently analyze and adjust network topology to ensure efficient and safe operation of the network in a target range environment. Network optimization control: Utilizes deep learning models to dynamically optimize network parameters, including adjusting transmit power, communication frequency bands, and routing strategies. The goal is to maximize network performance while ensuring efficient energy utilization and communication stability. Security policy execution: Responsible for monitoring the security status of the network and evaluating the security of the connection based on the security level differences between nodes. If a potential security risk is detected, such as a large difference in security levels between nodes, the system will automatically disconnect and trigger an alarm mechanism to ensure the security of the network in a target range environment. Physical layer communication: Enables wireless communication between nodes, including the application of technologies such as Wi-Fi6 and LoRaWAN. This layer is responsible for data transmission and reception and is the foundation of the entire network architecture. By intelligently adjusting transmit power and communication frequency bands, physical layer communication can adapt to changes in the target range environment and provide stable and efficient communication services.

[0079] From the above content, it can be seen that by real-time detection of the security level of network nodes and dynamic adjustment of the connection status between nodes based on the comparison results of the security level difference and the preset threshold, the security of the network in the target range environment is significantly enhanced, and the potential risks caused by security level mismatch are reduced; the intelligent networking system can quickly respond to changes in the security level of network nodes and adjust the network connection status in time, thereby improving the network's dynamic response capability and self-repair capability when facing security threats; the automatic disconnection and early warning mechanism provides network administrators with timely security information, helping them to quickly identify and deal with security risks in the network, avoiding the spread and impact of security incidents; ensuring that the communication between network nodes of different security levels in the network complies with the security policies and compliance requirements of the target range environment, and maintaining the legality and standardization of network operations.

[0080] The present application also provides a network node networking device. It should be noted that the network node networking device of the present application embodiment can be used to execute the network node networking method provided in the present application embodiment. The network node networking device provided in the present application embodiment is introduced below.

[0081] According to an embodiment of the present application, a device for implementing the above-mentioned network node networking method is also provided. Figure 4 is a schematic diagram of an optional networking device of a network node according to an embodiment of the present application, such as Figure 4 As shown, the device includes: a receiving unit 401, an updating unit 402, and a connecting unit 403.

[0082] Optionally, a receiving unit 401 receives a target operation performed by a target person on a target page, wherein the target page is used to display the connection status between N network nodes in a shooting range environment, and the target operation includes dragging a target node among the N network nodes, wherein the target operation of the target page synchronously affects the network nodes in the shooting range environment, and each of the N network nodes includes the initial position information of the network node; an updating unit 402 is used to trigger a target event according to the target operation, update the position information of the target node by executing the target event, and broadcast the position change information of the target node in the shooting range environment; a connection unit 403 adjusts the connection between the N network nodes through a feature matching engine based on the updated position information of the target node to obtain an updated networking of the N network nodes, wherein the feature matching engine is used to determine the matching degree of the N network nodes based on a matching degree strategy and in combination with the position information of the target node.

[0083] Optionally, the connection unit 403 includes: a first acquisition subunit, a first determination subunit, a second determination subunit, a third determination subunit, and a first adjustment subunit. The first acquisition subunit is configured to acquire target information of the current N network nodes through a feature matching engine based on the updated location information of the target node, wherein the target information includes at least the location information, signal strength, and security level of the network node; the first determination subunit is configured to determine target distances between adjacent network nodes in the N network nodes based on the location information of the N network nodes, obtaining S target distances, where S is an integer greater than or equal to 1; the second determination subunit is configured to determine channel qualities between adjacent network nodes in the N network nodes based on the signal strengths of the N network nodes, obtaining S channel qualities; the third determination subunit is configured to determine a target factor based on the security level of the N network nodes, wherein the target factor is used to characterize the impact of the security level of the N network nodes on the connection matching degree between the network nodes; and the first adjustment subunit is configured to adjust the connection between the N network nodes based on the target factor, the S target distances, and the S channel qualities.

[0084] Optionally, the first adjustment subunit includes: a first acquisition module, a first determination module, a second determination module, and a first processing module. The first acquisition module is configured to acquire a first coefficient, a second coefficient, and a third coefficient, wherein the first coefficient is used to characterize the weight of the target distance, the second coefficient is used to characterize the weight of the channel quality, and the third coefficient is used to characterize the weight of the target factor; the first determination module is configured to determine S matching degrees based on the first coefficient, the second coefficient, the third coefficient, the target factor, S target distances, and S channel qualities; the second determination module is configured to determine, when the matching degree is greater than or equal to a first preset threshold, to establish a connection between two adjacent network nodes corresponding to the matching degree; and the first processing module is configured to disconnect the two adjacent network nodes corresponding to the matching degree when the matching degree is less than the first preset threshold.

[0085] Optionally, the networking device of the network node further includes: a first acquisition unit, a first determination unit, and a first adjustment unit. The first acquisition unit is configured to acquire state information of the range environment, wherein the state information includes at least location information, link load information, and channel quality of N network nodes; the first determination unit is configured to determine a target strategy for each network node based on the state information and global network environment information using a target algorithm, wherein the target strategy is used to adjust communication parameters of the network node; and the first adjustment unit is configured to adjust the N network nodes according to the target strategy.

[0086] Optionally, the networking device of the network node further includes: a first collection unit, a second determination unit, and a first update unit. The first collection unit is configured to collect feedback information, wherein the feedback information is used to characterize the performance parameters of N network nodes after adjustment according to the target strategy in the target range environment, wherein the performance parameters include at least a first value, a second value, and a third value, wherein the first value is used to characterize the amount of data transmitted per unit time in the target range environment, the second value is used to characterize the transmission time delay between data network nodes, and the third value is used to characterize the energy consumption of each network node in data transmission; the second determination unit is configured to determine a reward value based on the first value, the second value, and the third value, wherein the reward value is used to quantitatively evaluate the performance of the N network nodes after adjustment in the target range environment; and the first update unit is configured to update the target algorithm based on the reward value.

[0087] Optionally, the networking device of the network node further includes: a first deployment unit, a first processing unit, and a first uploading unit. The first deployment unit is used to deploy N network nodes in a shooting range environment, wherein each network node includes at least attribute information, a positioning module, a communication module, and an environmental sensor, wherein the attribute information includes at least the unique identifier, type tag, and security level of the network node; the first processing unit is used to initialize the N network nodes, wherein the initialization operation is used to initially network the N network nodes through a self-organizing network protocol; and the first uploading unit is used to upload the attribute information of the N network nodes after the initialization operation to a central server.

[0088] Optionally, the networking device of the network node further includes: a first detection unit, a second processing unit, and a third processing unit. The first detection unit is configured to detect the security levels of N network nodes; the second processing unit is configured to maintain the connection between the i-th network node and the j-th network node when the difference between the security levels of the i-th network node and the j-th network node among the N network nodes is less than a second preset threshold, where i and j are both integers greater than or equal to 1 and less than or equal to N; and the third processing unit is configured to disconnect the i-th network node from the j-th network node and issue an early warning when the difference between the security levels of the i-th network node and the j-th network node among the N network nodes is greater than or equal to the second preset threshold.

[0089] According to another aspect of an embodiment of the present application, a computer-readable storage medium is further provided, in which a computer program is stored. When the computer program runs, the device where the computer-readable storage medium is located executes the above-mentioned network node networking method.

[0090] According to another aspect of an embodiment of the present application, an electronic device is also provided, including one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned network node networking method.

[0091] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0092] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0094] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0095] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0096] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0097] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for networking network nodes, characterized in that: include: Receiving a target operation performed by a target person on a target page, wherein the target page is used to display the connection status between N network nodes in a shooting range environment, the target operation includes dragging a target node among the N network nodes, wherein the target operation on the target page synchronously affects the network nodes in the shooting range environment, and each of the N network nodes includes initial position information of the network node; triggering a target event according to the target operation, updating the position information of the target node by executing the target event, and broadcasting the position change information of the target node in the shooting range environment; Based on the updated location information of the target node, the connection between the N network nodes is adjusted through the feature matching engine to obtain the updated networking of the N network nodes, wherein the feature matching engine is used to determine the matching degree of the N network nodes based on the matching degree strategy and combined with the location information of the target node.

2. The method for networking network nodes according to claim 1, wherein: Adjusting the connections between the N network nodes based on the updated location information of the target node by a feature matching engine includes: Based on the updated location information of the target node, obtaining target information of the current N network nodes through the feature matching engine, wherein the target information includes at least the location information, signal strength, and security level of the network node; Determining target distances between adjacent network nodes among the N network nodes according to the location information of the N network nodes, to obtain S target distances, where S is an integer greater than or equal to 1; determining channel qualities between adjacent network nodes among the N network nodes according to the signal strengths of the N network nodes, to obtain S channel qualities; Determining a target factor according to the security levels of the N network nodes, wherein the target factor is used to represent the impact of the security levels of the N network nodes on the connection matching degree between the network nodes; The connections between the N network nodes are adjusted according to the target factor, the S target distances, and the S channel qualities.

3. The method for networking network nodes according to claim 2, wherein: Adjusting the connections between the N network nodes according to the target factor, the S target distances, and the S channel qualities includes: Obtaining a first coefficient, a second coefficient, and a third coefficient, wherein the first coefficient is used to represent the weight of the target distance, the second coefficient is used to represent the weight of the channel quality, and the third coefficient is used to represent the weight of the target factor; Determining S matching degrees according to the first coefficient, the second coefficient, the third coefficient, the target factor, the S target distances, and the S channel qualities; When the matching degree is greater than or equal to a first preset threshold, determining to establish a connection between two adjacent network nodes corresponding to the matching degree; When the matching degree is less than a first preset threshold, the two adjacent network nodes corresponding to the matching degree are disconnected.

4. The method for networking network nodes according to claim 1, wherein: After adjusting the connections between the N network nodes based on the updated location information of the target node using a feature matching engine, the method further includes: Acquiring status information of the range environment, wherein the status information includes at least location information, link load information, and channel quality of N network nodes; Based on the state information, using a target algorithm to determine a target strategy for each of the network nodes according to the state information and global network environment information, wherein the target strategy is used to adjust communication parameters of the network node; According to the target strategy, the N network nodes are adjusted.

5. The method for networking network nodes according to claim 4, characterized in that: After adjusting the N network nodes according to the target strategy, the method includes: Collecting feedback information, wherein the feedback information is used to characterize performance parameters of the N network nodes in the range environment after adjustment according to the target strategy, wherein the performance parameters include at least a first value, a second value, and a third value, wherein the first value is used to characterize the amount of data transmitted per unit time in the range environment, the second value is used to characterize the transmission time delay between the network nodes, and the third value is used to characterize the energy consumption of each network node in data transmission; Determining a reward value according to the first value, the second value, and the third value, wherein the reward value is used to quantitatively evaluate the performance of the N network nodes after adjustment in the shooting range environment; The target algorithm is updated based on the reward value.

6. The method for networking network nodes according to claim 1, wherein: Before receiving the target action performed by the target person on the target page, including: Deploying N network nodes in the shooting range environment, wherein each network node includes at least attribute information, a positioning module, a communication module, and an environmental sensor, wherein the attribute information includes at least a unique identifier, a type tag, and a security level of the network node; Performing an initialization operation on the N network nodes, wherein the initialization operation is used to initially network the N network nodes through a self-organizing network protocol; Uploading the attribute information of the N network nodes after the initialization operation to the central server.

7. The method for networking network nodes according to claim 1, wherein: The method further comprises: detecting the security levels of N of the network nodes; When a difference between the security levels of the i-th network node and the j-th network node among the N network nodes is less than a second preset threshold, maintaining the connection between the i-th network node and the j-th network node, where i and j are both integers greater than or equal to 1 and less than or equal to N; When the difference between the security levels of the ith network node and the jth network node among the N network nodes is greater than or equal to the second preset threshold, the connection between the ith network node and the jth network node is disconnected, and an early warning is issued.

8. A networking device for network nodes, characterized in that: include: A receiving unit receives a target operation performed by a target person on a target page, wherein the target page is used to display the connection status between N network nodes in a shooting range environment, and the target operation includes dragging a target node among the N network nodes, wherein the target operation on the target page synchronously affects the network nodes in the shooting range environment, and each of the N network nodes includes initial position information of the network node; an updating unit, configured to trigger a target event according to the target operation, update the position information of the target node by executing the target event, and broadcast the position change information of the target node in the shooting range environment; The connection unit adjusts the connection between the N network nodes through a feature matching engine based on the updated location information of the target node to obtain an updated network of the N network nodes, wherein the feature matching engine is used to determine the matching degree of the N network nodes based on a matching degree strategy and in combination with the location information of the target node.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the network node networking method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The method comprises one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the networking method of the network node according to any one of claims 1 to 7.

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