A method and system for adjusting device networking based on the Rand coefficient

Abstract

This invention relates to the field of computer technology and discloses a method and system for adjusting device networking based on the Rand coefficient. The method includes: acquiring a networking scheme and an ideal networking template; calculating the Rand coefficient of the networking scheme based on the ideal networking template and the networking scheme; acquiring a networking model; evaluating whether the networking scheme meets system requirements based on the Rand coefficient and the networking model; if the networking scheme does not meet system requirements, optimizing the networking scheme; re-evaluating whether the optimized networking scheme meets system requirements based on the Rand coefficient and the networking model; optimizing the networking scheme until the networking scheme meets system requirements; and outputting the networking scheme if the networking scheme meets system requirements. This invention uses the Rand coefficient to measure the similarity between the adjusted networking scheme and the ideal template, thereby avoiding the networking scheme from continuously being optimized in a direction that deviates from the ideal networking template.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a device networking adjustment method, system, terminal, and readable storage medium based on the RAND coefficient. Background Technology

[0002] In the Internet of Things (IoT) field, in order to ensure the efficiency of linkage between various smart devices, it is necessary to network the network topology between smart devices to obtain the ideal network structure of the entire IoT. The ideal network structure is generated by analyzing the functional characteristics, geographical location, communication requirements and other information of the devices and based on the super-object model of the devices. Usually, the ideal structure is designed according to the optimal networking requirements, such as the lowest latency and the highest data throughput between devices.

[0003] However, on the one hand, devices in the real environment may experience changes in state (such as movement, increased load, failure, etc.), making it difficult to maintain the ideal structure. On the other hand, network topology may be affected by external factors, such as network congestion, electromagnetic interference, etc., which will prevent the ideal structure from working continuously.

[0004] Therefore, it is necessary to adjust the network structure according to the actual situation to ensure the stable operation of the entire Internet of Things structure. However, the existing adjustment methods only consider latency and resource allocation, which leads to the accumulation of errors in the system components during the adjustment. After multiple adjustments, the system completely deviates from the ideal template, making it difficult to optimize through adjustment and requiring system reconstruction. Summary of the Invention

[0005] The purpose of this invention is to provide a device networking adjustment method, system, terminal, and readable storage medium based on the Rand coefficient, which aims to solve the problem of deviation from the ideal template when adjusting the network structure in the prior art.

[0006] The technical solution adopted by this invention to solve the technical problem is as follows:

[0007] This invention provides a device networking adjustment method based on the RAND coefficient, the method comprising:

[0008] Obtain the networking scheme and ideal networking template, and calculate the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme;

[0009] Obtain the network topology model, evaluate whether the network topology scheme meets the system requirements based on the RAND coefficient and the network topology model, and optimize the network topology scheme based on the RAND coefficient and the network topology model if the network topology scheme does not meet the system requirements.

[0010] Based on the RAND coefficient and the networking model, re-evaluate whether the optimized networking scheme meets the system requirements. If the networking scheme does not meet the system requirements, continue to optimize the networking scheme until it meets the system requirements. If the networking scheme meets the system requirements, output the networking scheme.

[0011] Furthermore, the calculation of the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme specifically includes:

[0012] Determine whether the subnet relationship between any two devices in the network adjustment scheme is consistent with the ideal network template;

[0013] If both devices are in the same subnet in both the network adjustment scheme and the ideal network template, then the combination of the two devices is considered a true TP (Telematics Platform).

[0014] If the two devices are not in the same subnet in the network adjustment scheme and the ideal network template, then the combination of the two devices is judged as a true counterexample TN.

[0015] If two devices are in the same subnet in the network adjustment scheme, but not in the same subnet in the ideal network template, then the combination of the two devices is judged as a false positive (FP).

[0016] If two devices are not in the same subnet in the network adjustment scheme, but are in the same subnet in the ideal network template, then the combination of the two devices is judged as a false counterexample FN;

[0017] Calculate the RAND coefficient of the network adjustment scheme based on the number of true positive examples (TP), true negative examples (TN), false positive examples (FP), and false negative examples (FN):

[0018]

[0019] Where RI represents the Rand coefficient.

[0020] Furthermore, the step of evaluating whether the networking scheme meets the system requirements based on the RAND coefficient and the networking model specifically includes:

[0021] Determine whether the RAND coefficient is lower than a set threshold, and determine whether the networking scheme meets the resource configuration requirements based on the networking model;

[0022] If the RAND coefficient is lower than a set threshold and the networking scheme meets the resource configuration requirements, then the networking scheme meets the system requirements.

[0023] If the RAND coefficient is not lower than a set threshold or the networking scheme does not meet the resource configuration requirements, then the networking scheme does not meet the system requirements.

[0024] Furthermore, optimizing the networking scheme based on the RAND coefficient and the networking model specifically includes:

[0025] Optimize the overall topology and global resource configuration of the network scheme based on the network model;

[0026] Optimize the collaboration and communication efficiency of each subnet in the networking scheme based on the networking model;

[0027] Optimize device roles and resource configurations based on the network model;

[0028] The subnetting of the network scheme is optimized based on the RAND coefficient.

[0029] Furthermore, optimizing the overall topology and global resource configuration of the networking scheme based on the networking model specifically includes:

[0030] Based on the network model, analyze the high-latency nodes, overloaded nodes, and isolated devices in the network scheme;

[0031] For each of the high-latency nodes, optimize the connection path by reconfiguring it or by adding a relay node;

[0032] Optimize the actions of role setting or task decomposition for each of the overloaded nodes;

[0033] An optimization action is performed to classify each isolated device into a subnet.

[0034] Furthermore, the optimization action of classifying each isolated device into a subnet further includes:

[0035] If the number of high-latency nodes, overloaded nodes, and isolated devices exceeds a set number, network reconstruction will be performed.

[0036] Furthermore, optimizing the cooperation and communication efficiency of each subnet in the networking scheme based on the networking model specifically includes:

[0037] Based on the network model, the communication frequency and data exchange volume between any two devices in the subnet are analyzed to obtain the analysis results;

[0038] Optimize the communication path of the subnet based on the analysis results.

[0039] Furthermore, to achieve the above objectives, the present invention also provides a device networking adjustment system based on the RAND coefficient, the device networking adjustment system based on the RAND coefficient comprising:

[0040] The preliminary evaluation module is used to obtain the networking scheme and the ideal networking template, and to calculate the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme.

[0041] The evaluation and optimization module obtains the networking model, evaluates whether the networking scheme meets the system requirements based on the RAND coefficient and the networking model, and optimizes the networking scheme based on the RAND coefficient and the networking model if the networking scheme does not meet the system requirements.

[0042] The feedback output module re-evaluates whether the optimized networking scheme meets the system requirements based on the RAND coefficient and the networking model. If the networking scheme does not meet the system requirements, it returns to the evaluation and optimization module. If the networking scheme meets the system requirements, it outputs the networking scheme.

[0043] In addition, to achieve the above objectives, the present invention also provides a terminal, the terminal comprising: a memory, a processor, and a device networking adjustment program based on the Land coefficient stored in the memory and executable on the processor, wherein when the device networking adjustment program based on the Land coefficient is executed by the processor, the terminal controls the terminal to implement the steps of the device networking adjustment method based on the Land coefficient as described above.

[0044] In addition, to achieve the above objectives, the present invention also provides a readable storage medium storing a device networking adjustment program based on the RAND coefficient, wherein when the device networking adjustment program based on the RAND coefficient is executed by a processor, the device networking adjustment program based on the RAND coefficient implements the steps of the device networking adjustment method based on the RAND coefficient as described above.

[0045] The present invention, by employing the above technical solution, has the following effects:

[0046] This invention uses the RAND coefficient to measure the similarity between the adjusted networking scheme and the ideal template, thereby assessing the rationality of the adjustment and avoiding the problem of continuously optimizing the networking scheme in a direction that deviates from the ideal networking template, leading to difficulties in later optimization and the need for reconstruction. Attached Figure Description

[0047] Figure 1 This is a flowchart of the steps of a device networking adjustment method based on the Rand coefficient in a preferred embodiment of the present invention;

[0048] Figure 2 This is a schematic diagram of a device networking adjustment system based on the Rand coefficient in a preferred embodiment of the present invention.

[0049] Figure 3 This is a schematic diagram of the operating environment of a preferred embodiment of the terminal of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the described embodiments are merely some embodiments of this disclosure, and not all embodiments. The specific embodiments described herein are only used to explain the invention and are not intended to limit the invention. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0051] Example 1

[0052] In this embodiment, by collecting the uploaded device information, the device information includes the device's location information, hardware information, functional information, environmental information, and operating status information. The location information includes the coordinates of the device's location and the height information describing the device's height. The functional information refers to the special functions supported by the device, such as image processing functions.

[0053] Next, a network model is established based on the equipment information. The network model is a super-object model used to describe each device participating in the network. The super-object model is an abstract model used to describe and manage the capabilities of the devices. It is used to provide decision support during the networking process and to provide continuous monitoring and adjustment support after the networking is completed.

[0054] The evaluation of the networking scheme based on the networking model specifically involves distributed monitoring nodes that monitor the status changes of devices in real time and update the network model with the changing data in real time. The monitoring content includes the hardware status of the devices (such as CPU load and memory usage), network status (such as latency and bandwidth), and power status (such as battery level).

[0055] Upon detecting an anomaly or performance degradation, the system will automatically initiate a feedback control process, automatically launching a device networking adjustment method based on the Rand coefficient in this embodiment. The Rand coefficient will be recalculated, the current network structure will be evaluated, and optimization operations will be performed based on the evaluation results. The system can automatically adjust the resource allocation of devices, reconfigure communication paths, or trigger topology reconstruction.

[0056] Specifically, please see Figure 1 This embodiment of a device networking adjustment method based on the Rand coefficient includes the following steps:

[0057] S1. Obtain the networking scheme and ideal networking template, and calculate the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme.

[0058] Obtaining a network topology scheme involves acquiring an existing network topology scheme through a network topology model. An ideal network topology template is an ideal structure defined based on a network topology model and pre-defined standards. Previously, multi-dimensional distance was used to compensate for the problems caused by the complementarity and merging of subnets based solely on geographical division. However, since spatial distance is still the main factor in clustering, incorrect divisions can still occur during the division process.

[0059] Therefore, the Land coefficient is needed to evaluate the rationality of the partitioning. Specifically, the Land coefficient measures the similarity between the network adjustment scheme and the ideal network template to judge the rationality of the device partitioning in this network setup. The higher the similarity between the network adjustment scheme and the ideal network template, the more reasonable the network adjustment scheme is. The lower the similarity between the network adjustment scheme and the ideal network template, the more unreasonable the network adjustment scheme is. When the Land coefficient is lower than the set threshold, it indicates that the network adjustment scheme needs to be improved.

[0060] First, determine whether the subnet relationship between any two devices in the network adjustment scheme is consistent with the ideal network template.

[0061] If two devices are in the same subnet in both the network adjustment scheme and the ideal network template, then the combination of these two devices is determined to be TP (True Positives).

[0062] If two devices are not in the same subnet in the network adjustment scheme and the ideal network template, then the combination of these two devices is determined to be TN (True Negatives).

[0063] If two devices are in the same subnet in the network topology adjustment scheme, but not in the same subnet in the ideal network topology template, then these two devices are judged as FP (False Positives).

[0064] If two devices are not in the same subnet in the network topology adjustment scheme, but are in the same subnet in the ideal network topology template, then these two devices are judged as FN (False Negatives).

[0065] Then, the RAND coefficient of the network adjustment scheme is calculated based on the number of true positive examples (TP), true negative examples (TN), false positive examples (FP), and false negative examples (FN):

[0066]

[0067] Where RI represents the Rand coefficient.

[0068] The Rand coefficient is used to measure how close the network adjustment scheme is to the ideal network template. The larger the Rand coefficient, the closer it is to 1, indicating that the network adjustment scheme is close to the ideal network template.

[0069] S2. Obtain the network topology model, evaluate whether the network topology scheme meets the system requirements based on the RAND coefficient and the network topology model, and optimize the network topology scheme based on the RAND coefficient and the network topology model if the network topology scheme does not meet the system requirements.

[0070] In this embodiment, an algorithm is used to select optimization actions to form an optimization strategy. The specific algorithm can be a heuristic algorithm to automatically select an adjustment scheme based on the evaluation results, or a machine learning model to predict the optimal adjustment strategy through a trained model. For example, the action policy network in reinforcement learning can decide the next optimization action based on environmental feedback.

[0071] Evaluating whether the networking scheme meets the system requirements includes determining whether the networking scheme meets the resource configuration requirements based on the networking model. If it does not meet the requirements, the resource configuration of the networking scheme is optimized based on the networking model. The resource configuration requirements include latency requirements and load requirements.

[0072] Optimizing network topology involves three levels of resource allocation: device-level optimization, subnet-level optimization, and network-wide optimization.

[0073] Network-wide optimization focuses on the topology and global resource configuration of the entire network. Its purpose is to improve the overall performance, stability and robustness of the entire Internet of Things (IoT), including network topology optimization, global resource configuration optimization and network fault tolerance mechanism settings.

[0074] Network topology optimization begins with topology analysis, comprehensively analyzing the current network topology and evaluating its performance in terms of device connectivity, data transmission efficiency, latency, and network load. Based on data from the super-object model, bottlenecks and weak links in the network are identified, such as high-latency nodes, overloaded nodes, or isolated devices.

[0075] Then, based on the topology analysis results, optimization strategies are formulated. These strategies may include reconfiguring device connection paths, adding relay nodes to reduce latency, or reallocating the roles and resources of critical nodes. For example, the tasks of nodes may be decomposed and then allocated.

[0076] If the analysis results meet the reorganization requirements, such as too many bottlenecks and weak links, or the total system latency exceeding a set threshold, then a global network topology reconstruction is performed. This includes re-using the K-Means clustering method to divide the subnets, and then using an algorithm to network each subnet to obtain an initial network topology scheme.

[0077] Specifically, the system is first divided into multiple different regions. A location is selected in each region as the cluster center. Then, K-means clustering is performed using multi-dimensional distances, which include spatial distance and functional distance. Spatial distance is the distance between the coordinate information of the devices, and functional distance is the distance between the hardware information and functional information of the devices. It is obtained by vectorizing the functional information and hardware information of each device and calculating the distance after vectorization. The multi-dimensional distance is the weighted sum of spatial distance and functional distance.

[0078] After clustering is completed, all devices are divided into multiple subnets. Then, an algorithm is used to form a network for each subnet. Specifically, the device information of the networking model is used as the input of the algorithm, and the goal of the algorithm is to minimize the network communication latency and resource waste. The algorithm generates an initial networking scheme that includes detailed information such as subnet allocation, communication path selection and resource configuration for each device.

[0079] Global resource configuration optimization involves the unified scheduling of computing, storage, and communication resources across the entire network to maximize resource utilization and optimize network performance. First, the system analyzes the resource requirements of each device in the network, including computing, storage, and bandwidth requirements. The evaluation criteria include the device's super object model, the current network status, and the specific requirements of the application scenario.

[0080] Next, based on the resource demand analysis results, a global resource allocation strategy is formulated. The goal of the strategy is to ensure that each device can obtain the resources it needs, while avoiding excessive waste of resources. For example, a dynamic resource allocation algorithm can be used to adjust the resource allocation ratio in real time according to the actual needs of the devices and the network status. In addition, a priority mechanism can be introduced to prioritize the resource needs of critical tasks.

[0081] Regarding the setting of network fault tolerance mechanisms, network fault tolerance mechanisms are an important part of network-wide optimization, aiming to improve network robustness and ensure that the network can still maintain efficient operation when failures occur. It includes redundant path design, which designs redundant paths in the network topology so that data can be transmitted through backup paths when the primary path fails. The design of redundant paths is based on the geographical location and communication requirements of the devices, ensuring that the latency of the backup paths is minimized. If no network reconstruction is performed, redundant path design is only performed on the adjusted devices; if reconstruction is performed, redundant path design is performed on all devices.

[0082] In subsequent use, real-time monitoring and intelligent algorithms enable the system to quickly detect network faults, such as node failures and communication interruptions. Once a fault is detected, the system will automatically isolate the faulty node and dynamically adjust the routing to transfer data transmission to a normal node or redundant path, ensuring the continuity of network services. After the fault is isolated and handled, the system can attempt to automatically recover the affected network portion by restarting the failed node, reconfiguring network connections, or reallocating resources to restore normal network operation.

[0083] Subnet-level optimization focuses on the collaboration and communication efficiency between devices. The goal is to improve the collaboration efficiency of devices within the subnet and reduce communication latency. This includes optimizing task allocation and resource sharing within the subnet, as well as optimizing communication paths within the subnet by analyzing the communication frequency and data exchange volume between devices to ensure the lowest possible communication latency between critical devices.

[0084] Device-level optimization involves resetting the role and resource configuration of individual devices in the network. The goal of optimization is to fully utilize the capabilities of devices and improve the overall efficiency of the network. Specifically, it first analyzes the resources of individual devices (such as CPU, memory, storage, bandwidth, etc.), and then sets the role of individual devices in the network based on their resources, such as core node, edge node, data processing node, etc. For example, if a device's CPU resource load is too high and other resource loads are too low, it will be adjusted from a computing node to another node to obtain a more suitable role.

[0085] In this embodiment, the Rand coefficient is used as one of the optimization targets of the optimization algorithm. This allows the optimization algorithm to make action selections based on the Rand coefficient. When selecting optimization actions, the optimization algorithm will consider the similarity between the network topology and the ideal network template. This avoids the network topology from deviating further and further from the ideal network template during multiple optimization processes. It also avoids the situation where the optimization algorithm gets stuck in a local optimum that deviates from the network template or even fails to find the optimal solution after accumulating errors in multiple optimizations.

[0086] Specifically, assessing whether the networking scheme meets the system requirements includes evaluating whether the RAND coefficient is lower than a set threshold. If the RAND coefficient is lower than the set threshold, the subnetting of the networking scheme is adjusted.

[0087] The threshold setting is based on actual needs. The higher the threshold is set, the less flexible the network adjustment becomes, making it difficult to adjust and allocate according to actual needs. The lower the threshold is set, the further the adjusted network scheme deviates from the ideal network template, and the more likely the subnet division problem will occur.

[0088] Optimizing subnetting based on the RAND coefficient involves several steps. These include merging devices with overlapping functions into the same subnet, redistributing devices with complementary functions, and adjusting the subnets to which devices that negatively impact the RAND coefficient are assigned. Devices with some overlapping functions need to be merged into the same subnet, such as sensors targeting the same signal in the same area, to reduce redundant resource usage and improve efficiency. Conversely, some devices need to be assigned to different subnets to provide functional support for each subnet based on that device. For example, devices supporting different communication protocols can provide functional support for different communication protocols within the subnet. Specific details can be determined based on the ideal network template.

[0089] In an optional embodiment, the number of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN) associated with each device can be counted, and the adjustment coefficient for each device can be calculated according to the formula of the RAND coefficient. Devices with low adjustment coefficients can be adjusted to improve the overall RAND coefficient.

[0090] It is worth noting that network optimization based on the Land coefficient and optimization based on the network model can be carried out step by step, or the Land coefficient can be used as a weighting parameter and together with the optimization objective of the network model as the objective of the optimization algorithm. Step-by-step optimization may result in a contradiction between the optimization direction of the Land coefficient and the optimization direction of the network model. However, when carried out step by step, the Land coefficient has a stronger constraint and can better prevent the optimization from deviating from the ideal network template. If the Land coefficient is used as part of the optimization algorithm objective, the advantage is that the optimization algorithm can consider both the objective of the network model and the Land coefficient when selecting optimization methods. The disadvantage is that the weighting value of the network model is usually large, which has a high probability of overcoming the obstacle of the Land coefficient, leading to deviation. The two methods can be selected according to actual needs.

[0091] S3. Based on the RAND coefficient and the networking model, re-evaluate whether the optimized networking scheme meets the system requirements. If the networking scheme does not meet the system requirements, continue to optimize the networking scheme until it meets the system requirements. If the networking scheme meets the system requirements, output the networking scheme.

[0092] Monitoring and feedback are essential during the optimization process. This invention collects various performance indicators in the network in real time during the optimization process, and analyzes and provides feedback on these indicators through intelligent algorithms to form a closed-loop optimization process.

[0093] The performance metrics are collected in real time through a distributed sensor network and monitoring nodes, including but not limited to bandwidth utilization, latency, packet loss rate, node load, and energy consumption. All collected data is transmitted in real time to the central control system for analysis.

[0094] In subsequent iterative optimizations, the system leverages machine learning and big data analytics to conduct in-depth analysis of the collected performance data, identifying potential performance bottlenecks and optimization points. For example, by analyzing trends in latency and packet loss rates, the system can predict potential congestion areas in the network and take preventative measures in advance. Furthermore, the system dynamically adjusts network resource allocation strategies based on the analysis results to achieve continuous optimization of network performance.

[0095] Performance monitoring and feedback form a closed-loop optimization process. After each optimization operation, the system monitors its effect in real time and feeds the data back to the optimization module for further analysis and adjustment. Through multiple iterations, the system can gradually approach the optimal state of the network.

[0096] In addition, although the system can operate automatically in this embodiment, it also provides a user interface that allows administrators to view real-time monitoring data, adjust optimization strategies, or manually intervene in the networking process. For example, when the system detects a potential network bottleneck, the administrator can view a detailed performance analysis report through the interface and manually adjust relevant parameters to guide the system to perform more refined optimization operations.

[0097] Example 2

[0098] Please see Figure 2 Based on the above method, the present invention also provides a device networking adjustment system based on the RAND coefficient, the device networking adjustment system based on the RAND coefficient comprising:

[0099] The preliminary evaluation module 51 is used to obtain the networking scheme and the ideal networking template, and to calculate the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme.

[0100] Evaluation and optimization module 52 obtains the networking model, evaluates whether the networking scheme meets the system requirements based on the RAND coefficient and the networking model, and optimizes the networking scheme based on the RAND coefficient and the networking model if the networking scheme does not meet the system requirements.

[0101] Feedback output module 53 re-evaluates whether the optimized networking scheme meets the system requirements based on the RAND coefficient and the networking model. If the networking scheme does not meet the system requirements, it returns to the evaluation and optimization module. If the networking scheme meets the system requirements, it outputs the networking scheme.

[0102] Example 3

[0103] Please see Figure 3 Based on the above method, the present invention also provides a terminal, the terminal including a processor 10, a memory 20 and a display 30. Figure 3Only some of the terminal components are shown; however, it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0104] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or RAM. In other embodiments, the memory 20 may be an external storage device of the terminal, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 20 may include both internal and external storage devices. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code installed on the terminal. The memory 20 can also be used to temporarily store data that has been output or will be output. In one embodiment, the memory 20 stores a device networking adjustment program 40 based on the RAND coefficient, which can be executed by the processor 10.

[0105] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chip, used to run program code stored in the memory 20 or process data, such as executing the relevant program of the device networking adjustment method based on the Land coefficient.

[0106] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display 30 is used to display information on the terminal and to display a visual user interface. The components of the terminal communicate with each other via a system bus.

[0107] In one embodiment, when the processor 10 executes the device networking adjustment program 40 based on the Rand coefficient in the memory 20, it implements the steps of the device networking adjustment method based on the Rand coefficient as described above.

[0108] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory. In other embodiments, the memory 20 may be an external storage device of the terminal, such as a plug-in hard disk, SmartMediaCard (SMC), SecureDigital (SD) card, or FlashCard. Further, the memory 20 may include both internal and external storage devices. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code installed on the terminal. The memory 20 can also be used to temporarily store data that has been output or will be output. In one embodiment, the memory 20 stores a device networking adjustment program based on the RAND coefficient, which can be executed by the processor 10 to implement the device networking adjustment method based on the RAND coefficient in this application.

[0109] In some embodiments, the processor 10 may be a central processing unit, a microprocessor, or other data processing chip, used to run program code stored in the memory 20 or process data, such as executing the device networking adjustment method based on the Rand coefficient.

[0110] Example 4

[0111] This embodiment provides a storage medium that stores a device networking adjustment program based on the RAND coefficient. When the device networking adjustment program based on the RAND coefficient is executed by a processor, it implements the steps of the device networking adjustment method based on the RAND coefficient as described above.

[0112] In summary, this invention uses the RAND coefficient to measure the similarity between the adjusted networking scheme and the ideal template, thereby assessing the rationality of the adjustment. This avoids the problem of continuously optimizing the networking scheme in a direction that deviates from the ideal networking template, leading to difficulties in later optimization and the need for reconstruction.

[0113] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal that includes that element.

[0114] Of course, those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.). The program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The storage medium can be a memory, magnetic disk, optical disk, etc.

[0115] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for adjusting device networking based on the Rand coefficient, characterized in that, The device networking adjustment method based on the Rand coefficient includes: Obtain the networking scheme and ideal networking template, and calculate the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme; The calculation of the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme specifically includes: Determine whether the subnet relationship between any two devices in the network adjustment scheme is consistent with the ideal network template; If both devices are in the same subnet in both the network adjustment scheme and the ideal network template, then the combination of the two devices is considered a true TP (Telematics Platform). If the two devices are not in the same subnet in the network adjustment scheme and the ideal network template, then the combination of the two devices is judged as a true counterexample TN. If two devices are in the same subnet in the network adjustment scheme, but not in the same subnet in the ideal network template, then the combination of the two devices is judged as a false positive (FP). If two devices are not in the same subnet in the network adjustment scheme, but are in the same subnet in the ideal network template, then the combination of the two devices is judged as a false counterexample FN; Calculate the RAND coefficient of the network adjustment scheme based on the number of true positive examples (TP), true negative examples (TN), false positive examples (FP), and false negative examples (FN): ； Where RI represents the Rand coefficient; Obtain the network topology model, evaluate whether the network topology scheme meets the system requirements based on the RAND coefficient and the network topology model, and optimize the network topology scheme based on the RAND coefficient and the network topology model if the network topology scheme does not meet the system requirements. The step of evaluating whether the networking scheme meets the system requirements based on the RAND coefficient and the networking model specifically includes: Determine whether the RAND coefficient is lower than a set threshold, and determine whether the networking scheme meets the resource configuration requirements based on the networking model; If the RAND coefficient is lower than a set threshold and the networking scheme meets the resource configuration requirements, then the networking scheme meets the system requirements. If the RAND coefficient is not lower than a set threshold or the networking scheme does not meet the resource configuration requirements, then the networking scheme does not meet the system requirements. Based on the RAND coefficient and the networking model, re-evaluate whether the optimized networking scheme meets the system requirements. If the networking scheme does not meet the system requirements, continue to optimize the networking scheme until it meets the system requirements. If the networking scheme meets the system requirements, output the networking scheme.

2. The device networking adjustment method based on the Rand coefficient according to claim 1, characterized in that, The optimization of the networking scheme based on the RAND coefficient and the networking model specifically includes: Optimize the overall topology and global resource configuration of the network scheme based on the network model; Optimize the collaboration and communication efficiency of each subnet in the networking scheme based on the networking model; Optimize device roles and resource configurations based on the network model; The subnetting of the network scheme is optimized based on the RAND coefficient.

3. The device networking adjustment method based on the Rand coefficient according to claim 2, characterized in that, The optimization of the overall topology and global resource configuration of the network scheme based on the network model specifically includes: Based on the network model, analyze the high-latency nodes, overloaded nodes, and isolated devices in the network scheme; For each of the high-latency nodes, optimize the connection path by reconfiguring it or by adding a relay node; Optimize the actions of role setting or task decomposition for each of the overloaded nodes; An optimization action is performed to classify each isolated device into a subnet.

4. The device networking adjustment method based on the Rand coefficient according to claim 3, characterized in that, The optimization action of classifying each isolated device into a subnet further includes: If the number of high-latency nodes, overloaded nodes, and isolated devices exceeds a set number, network reconstruction will be performed.

5. The device networking adjustment method based on the Rand coefficient according to claim 2, characterized in that, The optimization of the cooperation and communication efficiency of each subnet in the networking scheme based on the networking model specifically includes: Based on the network model, the communication frequency and data exchange volume between any two devices in the subnet are analyzed to obtain the analysis results; Optimize the communication path of the subnet based on the analysis results.

6. A device network adjustment system based on the Rand coefficient, characterized in that, The device networking adjustment system based on the Rand coefficient is applied to the device networking adjustment method based on the Rand coefficient as described in any one of claims 1-5, wherein the device networking adjustment system based on the Rand coefficient includes: The preliminary evaluation module is used to obtain the networking scheme and the ideal networking template, and to calculate the RAND coefficient of the networking scheme based on the ideal networking template and the networking scheme. The evaluation and optimization module obtains the networking model, evaluates whether the networking scheme meets the system requirements based on the RAND coefficient and the networking model, and optimizes the networking scheme based on the RAND coefficient and the networking model if the networking scheme does not meet the system requirements. The feedback output module re-evaluates whether the optimized networking scheme meets the system requirements based on the RAND coefficient and the networking model. If the networking scheme does not meet the system requirements, it returns to the evaluation and optimization module. If the networking scheme meets the system requirements, it outputs the networking scheme.

7. A terminal, characterized in that, The terminal includes: a memory, a processor, and a device networking adjustment program based on the Land coefficient stored in the memory and executable on the processor. When the device networking adjustment program based on the Land coefficient is executed by the processor, it controls the terminal to implement the steps of the device networking adjustment method based on the Land coefficient as described in any one of claims 1-5.

8. A readable storage medium, characterized in that, The readable storage medium stores a device networking adjustment program based on the RAND coefficient, which, when executed by a processor, implements the steps of the device networking adjustment method based on the RAND coefficient as described in any one of claims 1-5.

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