Device networking adjustment method and system based on Lam coefficient

Abstract

The invention relates to the technical field of computers, and discloses an equipment networking adjustment method and system based on a Lam coefficient, and the method comprises the steps: obtaining a networking scheme and an ideal networking template, and calculating the Lam coefficient of the networking scheme according to the ideal networking template and the networking scheme; acquiring a networking model, evaluating whether the networking scheme meets system requirements or not according to the Lam coefficient and the networking model, and if the networking scheme does not meet the system requirements, optimizing the networking scheme; and according to the Lam coefficient and the networking model, re-evaluating whether the optimized networking scheme meets system requirements, optimizing the networking scheme until the networking scheme meets the system requirements, and if the networking scheme meets the system requirements, outputting the networking scheme. According to the method, the similarity between the adjusted networking scheme and the ideal template is measured through the Lam coefficient, so that the networking scheme is prevented from being continuously optimized towards the direction far away from the ideal networking template.

Description

Technical Field

[0001] The present 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 a Rand coefficient. Background Art

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

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

[0004] To this end, it is necessary to adjust the networking structure according to the actual situation to ensure the stable operation of the entire Internet of Things structure. However, the adjustment method of the existing technology only takes into account aspects such as latency and resource allocation, which leads to the accumulation of errors in the components of the system during adjustment. After multiple adjustments, the system completely deviates from the ideal template, making it difficult to optimize through adjustment, and the system can only be reconstructed. Summary of the invention

[0005] The purpose of the present 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 the prior art deviating from the ideal template when adjusting the networking structure.

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

[0007] The present invention provides a device networking adjustment method based on the Rand coefficient, and the device networking adjustment method based on the Rand coefficient includes:

[0008] Acquire a networking solution and an ideal networking template, and calculate a Rand coefficient of the networking solution according to the ideal networking template and the networking solution;

[0009] Acquire a networking model, evaluate whether the networking solution meets the system requirements according to the Rand coefficient and the networking model, and if the networking solution does not meet the system requirements, optimize the networking solution according to the Rand coefficient and the networking model;

[0010] According to the Rand coefficient and the networking model, it is evaluated again whether the optimized networking solution meets the system requirements. If the networking solution does not meet the system requirements, the networking solution is continuously optimized until the networking solution meets the system requirements. If the networking solution meets the system requirements, the networking solution is output.

[0011] Further, the calculating the Rand coefficient of the networking scheme according to the ideal networking template and the networking scheme specifically includes:

[0012] Determine whether the subnet relationship between any two devices in the networking adjustment scheme and the ideal networking template is consistent among all devices;

[0013] If the two devices are in the same subnet in the networking adjustment scheme and the ideal networking template, the combination of the two devices is judged to be a true example TP;

[0014] If the two devices are not in the same subnet in the networking adjustment scheme and the ideal networking template, the combination of the two devices is judged to be a true counterexample TN;

[0015] If two devices are in the same subnet in the networking adjustment scheme, but not in the same subnet in the ideal networking template, 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 networking adjustment scheme, but are in the same subnet in the ideal networking template, the combination of the two devices is judged to be a false counterexample FN;

[0017] The Rand coefficient of the network adjustment solution is calculated based on the number of true positive examples TP, true negative examples TN, false positive examples FP, and false negative examples FN:

[0018]

[0019] Among them, RI represents the Rand coefficient.

[0020] Further, the evaluating whether the networking solution meets the system requirements according to 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 solution meets resource configuration requirements based on the networking model;

[0022] If the Rand coefficient is lower than the set threshold and the networking solution meets the resource configuration requirements, then the networking solution meets the system requirements;

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

[0024] Further, the optimizing the networking solution according to the Rand coefficient and the networking model specifically includes:

[0025] Optimizing the overall topology and global resource configuration of the networking solution according to the networking model;

[0026] Optimizing the collaboration and communication efficiency of each subnet in the networking solution according to the networking model;

[0027] Optimizing the roles and resource configuration of devices according to the networking model;

[0028] The subnet division of the networking solution is optimized according to the Rand coefficient.

[0029] Furthermore, the optimizing the overall topology structure and global resource configuration of the networking solution according to the networking model specifically includes:

[0030] Analyze high-latency nodes, overloaded nodes, and isolated devices in the networking solution according to the networking model;

[0031] Performing an optimization action of reconfiguring a connection path or adding a relay node for each of the high-latency nodes;

[0032] Performing an optimization action of role setting or task decomposition on each of the overloaded nodes;

[0033] An optimization action of classifying each of the isolated devices into a subnet is performed.

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

[0035] If the high-latency nodes, overloaded nodes and isolated devices exceed the set number, network reconstruction is performed.

[0036] Further, the optimizing the collaboration and communication efficiency of each subnet in the networking solution according to the networking model specifically includes:

[0037] Analyze the communication frequency and data exchange volume between any two devices in the subnet according to the networking model to obtain analysis results;

[0038] The communication path of the subnet is optimized according to the analysis result.

[0039] In addition, to achieve the above-mentioned purpose, the present invention also provides a device networking adjustment system based on the Rand coefficient, and the device networking adjustment system based on the Rand coefficient includes:

[0040] A preliminary evaluation module, used to obtain a networking solution and an ideal networking template, and calculate a Rand coefficient of the networking solution according to the ideal networking template and the networking solution;

[0041] An evaluation and optimization module obtains a networking model, and evaluates whether the networking solution meets the system requirements according to the Rand coefficient and the networking model; if the networking solution does not meet the system requirements, the networking solution is optimized according to the Rand coefficient and the networking model;

[0042] The feedback output module re-evaluates whether the optimized networking solution meets the system requirements according to the Rand coefficient and the networking model. If the networking solution does not meet the system requirements, the module returns to the evaluation and optimization module. If the networking solution meets the system requirements, the module outputs the networking solution.

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

[0044] In addition, to achieve the above-mentioned purpose, the present invention also provides a readable storage medium, which 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, the steps of the device networking adjustment method based on the Rand coefficient as described above are implemented.

[0045] The present invention adopts the above technical solution to achieve the following effects:

[0046] The present invention measures the similarity between the adjusted networking scheme and the ideal template by the Rand coefficient to measure the rationality of the adjustment, thereby avoiding the problem that the networking scheme is continuously optimized in a direction away from the ideal networking template, resulting in difficulties in subsequent optimization and only reconstruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart 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 It is a schematic diagram of the principle of a device networking adjustment system based on the Rand coefficient in a preferred embodiment of the present invention;

[0049] Figure 3 It is a schematic diagram of the operating environment of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention. All other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0051] Embodiment 1

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

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

[0054] Evaluating the networking solution based on the networking model involves real-time monitoring of device status changes through distributed monitoring nodes, and updating the changed data to the networking model in real time. The monitoring content includes the device's hardware status (such as CPU load, memory usage), network status (such as latency, bandwidth), power status (such as battery power), etc.

[0055] After detecting an abnormality or performance degradation, the system will automatically start the feedback control process, automatically start a device networking adjustment method based on the Rand coefficient of this embodiment, recalculate the Rand coefficient, evaluate the current network structure, and perform optimization operations based on the evaluation results. The system can automatically adjust the resource allocation of the device, reconfigure the communication path, or trigger the reconstruction of the topology structure.

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

[0057] S1. Obtain a networking solution and an ideal networking template, and calculate a Rand coefficient of the networking solution according to the ideal networking template and the networking solution.

[0058] Obtain the networking plan, which is to obtain the existing operating networking plan through the networking model. The ideal networking template is an ideal structure defined based on the networking model and pre-set standards. Multi-dimensional distance has been used before to make up for the problems caused by the complementarity and merging of subnets based solely on geographical division. However, since spatial distance is still the main distance in clustering, incorrect division sometimes still occurs during division.

[0059] To this end, it is necessary to use the Rand coefficient to evaluate the rationality of the division. Specifically, the Rand coefficient judges the rationality of the equipment division during this networking by measuring the similarity between the networking adjustment plan and the ideal networking template. The higher the similarity between the networking adjustment plan and the ideal networking template, the more reasonable the networking adjustment plan is. The lower the similarity between the networking adjustment plan and the ideal networking template, the more unreasonable the networking adjustment plan is. When the Rand coefficient is lower than the set threshold, it indicates that the networking adjustment plan needs to be improved.

[0060] First, it is determined whether the subnet relationship between any two devices in the networking adjustment scheme and the ideal networking template is consistent among all the devices.

[0061] If two devices are in the same subnet in the networking adjustment scheme and the ideal networking template, the combination of the two devices is judged to be TP (True Positives);

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

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

[0064] If two devices are not in the same subnet in the networking adjustment scheme, but are in the same subnet in the ideal networking template, the two devices are judged to be FN (False Negatives).

[0065] Then, the Rand coefficient of the network adjustment scheme is calculated according to the number of true positive examples TP, true negative examples TN, false positive examples FP, and false negative examples FN:

[0066]

[0067] Among them, RI represents the Rand coefficient.

[0068] The Rand coefficient is used to measure the degree of closeness between the networking adjustment plan and the ideal networking template. The larger the Rand coefficient is, the closer it is to 1, indicating that the networking adjustment plan is close to the ideal networking template.

[0069] S2. Acquire a networking model, and evaluate whether the networking solution meets the system requirements according to the Rand coefficient and the networking model; if the networking solution does not meet the system requirements, optimize the networking solution according to the Rand coefficient and the networking model;

[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 plan based on the evaluation results, or a machine learning model to predict the optimal adjustment strategy through a trained model. For example, the action strategy network in reinforcement learning can determine the next optimization action based on environmental feedback.

[0071] Evaluating whether the networking solution meets the system requirements includes determining whether the networking solution meets the resource configuration requirements based on the networking model. If not, optimizing the resource configuration of the networking solution based on the networking model, wherein the resource configuration requirements include delay requirements and load requirements.

[0072] The resource allocation of the optimized networking solution includes three levels of optimization, namely, device-level optimization, subnet-level optimization, and full-network-level optimization.

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

[0074] Among them, network topology optimization first conducts topology analysis, comprehensively analyzes the current network topology, and evaluates its performance in terms of device connectivity, data transmission efficiency, latency, and network load. Based on the data in 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, an optimization strategy is formulated based on the topology analysis results. The optimization strategy may perform actions such as reconfiguring the connection path of the device, adding relay nodes to reduce latency, or reallocating the roles and resources of key nodes. For example, the tasks of the nodes are decomposed and the decomposed tasks are allocated.

[0076] If the analysis results meet the reorganization requirements, such as too many bottlenecks and weak links, or the total system delay is higher than the set threshold, the global network topology reconstruction is performed, including re-using the K-means clustering method to divide the subnets. After that, the algorithm is used to network each subnet to obtain the initial networking plan.

[0077] Specifically, the entire system is first divided into multiple different areas, and a position is selected in each area as the cluster center, that is, the cluster center, and then K-means clustering is performed with multi-dimensional distance. The multi-dimensional distance includes spatial distance and functional distance. The spatial distance is the distance of the coordinate information of the device, and the functional distance is the distance between the hardware information and the functional information of the device. 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 the spatial distance and the functional distance.

[0078] After clustering is completed, all devices are divided into multiple subnets. Then, algorithms are used to network each subnet. Specifically, the device information of the networking model is used as the input of the algorithm, and minimizing the delay and resource waste of network communication is used as the algorithm goal to generate an initial networking plan including details such as subnet allocation, communication path selection and resource configuration for each device.

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

[0080] After that, a global resource allocation strategy is formulated based on the results of the resource demand analysis. The goal of the strategy is to ensure that each device can obtain the required resources 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 device and the network status. In addition, a priority mechanism can be introduced to give priority to meeting the resource needs of critical tasks.

[0081] Regarding the setting of network fault tolerance mechanism, the network fault tolerance mechanism is an important part of the whole network level optimization, which aims to improve the robustness of the network and ensure that the network can still maintain efficient operation when a failure occurs. It includes redundant path design, designing redundant paths in the network topology so that when the main path fails, the data can be transmitted through the backup path. The design of redundant paths is based on the geographical location and communication requirements of the equipment to ensure that the delay of the backup path is as small as possible. Among them, if the network is not reconstructed, the redundant path design is only performed on the adjusted equipment. If reconstruction is performed, redundant paths are designed for all devices.

[0082] In this way, in subsequent use, through real-time monitoring and intelligent algorithms, the system can quickly detect faults in the network, such as node failure, communication interruption, etc. Once a fault is detected, the system will automatically isolate the faulty node and transfer data transmission to normal nodes or redundant paths through dynamic routing adjustments to ensure the continuity of network services. After the fault is isolated and processed, the system can try to automatically restore the affected network part by restarting the failed node, reconfiguring the network connection, or reallocating resources to restore the normal network operation status.

[0083] Subnet-level optimization focuses on the collaboration and communication efficiency between devices. The goal of optimization is to improve the collaboration efficiency of devices within the subnet and reduce communication delays. It includes optimization of task allocation within the subnet and optimization of resource sharing within the subnet, as well as optimization of communication paths within the subnet by analyzing the communication frequency and data exchange volume between devices, ensuring communication optimization with the lowest communication delay between key devices.

[0084] Device-level optimization is to reset the role and resource configuration of a single device in the network. The goal of optimization is to give full play to the capabilities of the device and improve the overall efficiency of the network. Specifically, first analyze the resources of a single device (such as CPU, memory, storage, bandwidth, etc.), and then set the role of the single device in the network according to the resources of the single device, such as core node, edge node, data processing node, etc. For example, if the CPU resource load of a device is too high and the load of other resources is too low, it will be adjusted from a computing node to other nodes to make it obtain a more suitable role.

[0085] In this embodiment, the Rand coefficient is used as one of the optimization targets of the optimization algorithm, so that the optimization algorithm makes action selection based on the Rand coefficient. When selecting the optimization action, the optimization algorithm will take into account the similarity between the networking scheme and the ideal networking template, thereby avoiding the networking scheme and the ideal networking template becoming increasingly distant during multiple optimization processes. This also avoids the situation where the optimization algorithm falls into a local optimal solution that deviates from the networking template or even fails to find the optimal solution after multiple optimization errors are accumulated.

[0086] Specifically, evaluating whether the networking solution 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 subnet division of the networking solution is adjusted.

[0087] The threshold is set according to actual needs. The higher the threshold is set, the less flexibility there is in adjusting the network, and it is difficult to adjust and allocate according to actual needs. The lower the threshold is set, the further the adjusted networking plan deviates from the ideal networking template, and the more likely it is that unreasonable subnet division will occur.

[0088] Optimize subnet division according to the Rand coefficient. Specific operations include merging devices with overlapping functions into the same subnet, reallocating devices with complementary functions, and adjusting the subnets to which devices that have a greater adverse impact on the Rand coefficient belong. Some devices with overlapping functions need to be merged into the same subnet, such as sensors for the same signal in the same area, to reduce redundant use of resources and improve efficiency. Some devices need to be allocated to different subnets to provide each subnet with functional support based on the device, such as devices that support different communication protocols to provide subnets with functional support for different communication protocols. The specific situation can be determined according to the ideal networking template.

[0089] In an optional embodiment, the true positive examples TP, true negative examples TN, false positive examples FP and false negative examples FN related to each device can be counted, and the adjustment coefficient of each device can be calculated according to the formula of the Rand coefficient. The devices with lower adjustment coefficients can be adjusted to improve the overall Rand coefficient.

[0090] It is worth noting that the networking optimization based on the Rand coefficient and the optimization based on the networking model can be carried out in steps, or the Rand coefficient can be used as a weighted parameter and used together with the optimization target of the networking model as the target of the optimization algorithm. The step-by-step process may be due to the contradiction between the optimization direction of the Rand coefficient and the optimization direction of the networking model. However, when the process is carried out in steps, the constraint ability of the Rand coefficient is stronger, which can better avoid the optimization from deviating from the ideal networking template. If the Rand coefficient is used as part of the optimization algorithm target, the advantage is that the optimization algorithm can consider the target of the networking model and the Rand coefficient at the same time when selecting the optimization means. The disadvantage is that the weighted value of the networking model is usually large, and there is a greater probability of overcoming the obstruction of the Rand coefficient, resulting in deviation. The two methods can be selected according to actual needs.

[0091] S3. Re-evaluate whether the optimized networking solution meets the system requirements based on the Rand coefficient and the networking model. If the networking solution does not meet the system requirements, continue to optimize the networking solution until the networking solution meets the system requirements. If the networking solution meets the system requirements, output the networking solution.

[0092] During the optimization process, monitoring and feedback are essential. The present invention collects various performance indicators in the network in real time during the optimization process, and analyzes and feeds back these indicators through intelligent algorithms to form a closed-loop optimization process.

[0093] Among them, the collection of performance indicators is carried out through distributed sensor networks and monitoring nodes, and various performance indicators in the network are collected in real time, including but not limited to bandwidth utilization, delay, packet loss rate, node load, energy consumption, etc. All collected data will be transmitted to the central control system in real time for analysis.

[0094] In subsequent iterative optimization, the system uses machine learning and big data analysis technology to conduct in-depth analysis of the collected performance data and identify potential performance bottlenecks and optimization points. For example, by analyzing the changing trends of latency and packet loss rate, the system can predict possible congestion areas in the network and take preventive measures in advance. In addition, the system will dynamically adjust the allocation strategy of network resources 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, in this embodiment, although the system can run automatically, it also provides a user interaction 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 sophisticated optimization operations.

[0097] Embodiment 2

[0098] See also Figure 2 Based on the above method, the present invention also provides a device networking adjustment system based on the Rand coefficient, and the device networking adjustment system based on the Rand coefficient includes:

[0099] A preliminary evaluation module 51 is used to obtain a networking solution and an ideal networking template, and calculate a Rand coefficient of the networking solution according to the ideal networking template and the networking solution;

[0100] An evaluation and optimization module 52 is configured to obtain a networking model, and evaluate whether the networking solution meets the system requirements according to the Rand coefficient and the networking model. If the networking solution does not meet the system requirements, the networking solution is optimized according to the Rand coefficient and the networking model.

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

[0102] Embodiment 3

[0103] See also Figure 3 Based on the above method, the present invention also provides a terminal, which includes a processor 10, a memory 20 and a display 30. Figure 3Only some components of the terminal are shown, but 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 memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a device networking adjustment program 40 based on the Rand coefficient is stored on the memory 20, and the device networking adjustment program 40 based on the Rand coefficient 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 the program code or process data stored in the memory 20, such as executing related programs of the device networking adjustment method based on the Rand coefficient.

[0106] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. 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, the steps of the device networking adjustment method based on the Rand coefficient as described above are implemented.

[0108] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a device networking adjustment program based on the Rand coefficient is stored on the memory 20, and the device networking adjustment program based on the Rand coefficient can be executed by the processor 10, thereby realizing the device networking adjustment method based on the Rand coefficient in the present application.

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

[0110] Embodiment 4

[0111] This embodiment provides a storage medium, wherein the readable storage medium stores a device networking adjustment program based on a Rand coefficient, and when the device networking adjustment program based on a Rand coefficient is executed by a processor, the steps of the device networking adjustment method based on a Rand coefficient as described above are implemented.

[0112] In summary, the present invention measures the similarity between the adjusted networking scheme and the ideal template through the Rand coefficient to measure the rationality of the adjustment, thereby avoiding the problem that the networking scheme is continuously optimized in a direction away from the ideal networking template, resulting in difficulties in subsequent optimization and only reconstruction.

[0113] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

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

[0115] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A device networking adjustment method based on Rand coefficient, characterized in that: The device networking adjustment method based on the Rand coefficient includes: Acquire a networking solution and an ideal networking template, and calculate a Rand coefficient of the networking solution according to the ideal networking template and the networking solution; Acquire a networking model, evaluate whether the networking solution meets the system requirements according to the Rand coefficient and the networking model, and if the networking solution does not meet the system requirements, optimize the networking solution according to the Rand coefficient and the networking model; According to the Rand coefficient and the networking model, it is evaluated again whether the optimized networking solution meets the system requirements. If the networking solution does not meet the system requirements, the networking solution is continuously optimized until the networking solution meets the system requirements. If the networking solution meets the system requirements, the networking solution is output.

2. The device networking adjustment method based on the Rand coefficient according to claim 1 is characterized in that: The calculating the Rand coefficient of the networking scheme according to the ideal networking template and the networking scheme specifically includes: Determine whether the subnet relationship between any two devices in the networking adjustment scheme and the ideal networking template is consistent among all devices; If the two devices are in the same subnet in the networking adjustment scheme and the ideal networking template, the combination of the two devices is judged to be a true example TP; If the two devices are not in the same subnet in the networking adjustment scheme and the ideal networking template, the combination of the two devices is judged to be a true counterexample TN; If two devices are in the same subnet in the networking adjustment scheme, but not in the same subnet in the ideal networking template, the combination of the two devices is judged as a false positive FP; If two devices are not in the same subnet in the networking adjustment scheme, but are in the same subnet in the ideal networking template, the combination of the two devices is judged to be a false counterexample FN; The Rand coefficient of the network adjustment solution is calculated based on the number of true positive examples TP, true negative examples TN, false positive examples FP, and false negative examples FN: Among them, RI represents the Rand coefficient.

3. The device networking adjustment method based on the Rand coefficient according to claim 1 is characterized in that: The step of evaluating whether the networking solution meets the system requirements according to 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 solution meets resource configuration requirements based on the networking model; If the Rand coefficient is lower than the set threshold and the networking solution meets the resource configuration requirements, then the networking solution meets the system requirements; If the Rand coefficient is not lower than the set threshold or the networking solution does not meet the resource configuration requirements, then the networking solution does not meet the system requirements.

4. The device networking adjustment method based on the Rand coefficient according to claim 3 is characterized in that: Optimizing the networking solution according to the Rand coefficient and the networking model specifically includes: Optimizing the overall topology and global resource configuration of the networking solution according to the networking model; Optimizing the collaboration and communication efficiency of each subnet in the networking solution according to the networking model; Optimizing the roles and resource configuration of devices according to the networking model; The subnet division of the networking solution is optimized according to the Rand coefficient.

5. The device networking adjustment method based on the Rand coefficient according to claim 4 is characterized in that: Optimizing the overall topology structure and global resource configuration of the networking solution according to the networking model specifically includes: Analyze high-latency nodes, overloaded nodes, and isolated devices in the networking solution according to the networking model; Performing an optimization action of reconfiguring a connection path or adding a relay node for each of the high-latency nodes; Performing an optimization action of role setting or task decomposition on each of the overloaded nodes; An optimization action of classifying each of the isolated devices into a subnet is performed.

6. The device networking adjustment method based on the Rand coefficient according to claim 5 is characterized in that: The optimization action of classifying each of the isolated devices into a subnet further includes: If the high-latency nodes, overloaded nodes and isolated devices exceed the set number, network reconstruction is performed.

7. The device networking adjustment method based on the Rand coefficient according to claim 4 is characterized in that: Optimizing the collaboration and communication efficiency of each subnet in the networking solution according to the networking model specifically includes: Analyze the communication frequency and data exchange volume between any two devices in the subnet according to the networking model to obtain analysis results; The communication path of the subnet is optimized according to the analysis result.

8. A device networking adjustment system based on Rand coefficient, characterized in that: The equipment networking adjustment system based on the Rand coefficient includes: A preliminary evaluation module, used to obtain a networking solution and an ideal networking template, and calculate a Rand coefficient of the networking solution according to the ideal networking template and the networking solution; An evaluation and optimization module obtains a networking model, and evaluates whether the networking solution meets the system requirements according to the Rand coefficient and the networking model; if the networking solution does not meet the system requirements, the networking solution is optimized according to the Rand coefficient and the networking model; The feedback output module re-evaluates whether the optimized networking solution meets the system requirements according to the Rand coefficient and the networking model. If the networking solution does not meet the system requirements, the module returns to the evaluation and optimization module. If the networking solution meets the system requirements, the module outputs the networking solution.

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

10. A readable storage medium, characterized in that: The readable storage medium stores a device networking adjustment program based on a Rand coefficient, and when the device networking adjustment program based on a Rand coefficient is executed by a processor, the steps of the device networking adjustment method based on a Rand coefficient as described in any one of claims 1 to 7 are implemented.

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