Network parameter configuration method, system, electronic device and application program

Abstract

The present application provides a network parameter configuration method, system, electronic device and application, which relates to the field of wireless communication technology. The method is applied to the network distribution equipment in the MESH network, and the MESH network also includes a master node device and a slave node device. The method includes: obtaining the network status data in the MESH network in the last detection cycle uploaded by the master node device; calculating the lifetime data of the data packet to be configured in the MESH network based on the network status data; sending the calculated lifetime data to the master node device to configure the lifetime data of the data packet in the master node device, so that the master node device broadcasts the lifetime data to the slave node device to configure the lifetime data of the data packet in the slave node device. The present application can adaptively adjust the lifetime data of the data packet according to the network status data, reduce the risk of network congestion, and improve the transmission efficiency of the data packet.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a network parameter configuration method, system, electronic device and application program. Background Art

[0002] MESH network is a wireless communication network architecture, which is widely used in the interconnection of IoT devices. In order to control the propagation range of data packets in the network, MESH network adopts the Time-To-Live (TTL) mechanism. The TTL mechanism means that when a data packet starts to propagate from the source node device, the TTL data will decrease when passing through the node device until it drops to zero, at which point the data packet will stop propagating. Therefore, the TTL data is crucial to the transmission of data packets.

[0003] Therefore, how to adjust the survival time data in real time has become a technical problem that needs to be solved urgently in the industry. Summary of the invention

[0004] The embodiments of the present application provide a network parameter configuration method, system, electronic device and application program, which can adjust the lifetime data according to the network status, improve the utilization rate of network resources, and at least partially solve the above-mentioned technical problems.

[0005] In a first aspect, an embodiment of the present application provides a network parameter configuration method, which is applied to a network distribution device in a MESH network, wherein the MESH network further includes a master node device and a slave node device, and the method includes:

[0006] Obtaining network status data in the MESH network during the last detection cycle uploaded by the master node device;

[0007] Calculate the survival time data of the data packet to be configured in the MESH network based on the network status data;

[0008] The calculated lifetime data is sent to the master node device to configure the lifetime data of the data packet in the master node device, so that the master node device broadcasts the lifetime data to the slave node device to configure the lifetime data of the data packet in the slave node device.

[0009] In a second aspect, an embodiment of the present application further provides a network parameter configuration method, which is applied to a slave node device in a MESH network, wherein the MESH network further includes a master node device and a distribution network device; the method includes:

[0010] Receiving lifetime data of a data packet to be configured in the MESH network broadcasted by the master node device or other slave node devices in the MESH network;

[0011] Based on the lifetime data of the data packet to be configured in the MESH network, the lifetime data of the data packet in the slave node device is configured;

[0012] The survival time data is calculated by the network distribution device based on the network status data in the MESH network in the last detection cycle uploaded by the master node device.

[0013] In a third aspect, the present application provides a network parameter configuration system, including a network distribution device, a master node device, and a slave node device in a MESH network;

[0014] The network configuration device is used to receive the network status data in the MESH network in the last detection cycle uploaded by the master node device, calculate the survival time data of the data packet to be configured in the MESH network based on the network status data, and send the calculated survival time data to the master node device;

[0015] The master node device is used to send the network status data to the network distribution device, and configure the lifetime data of the data packet in the master node device based on the lifetime data of the data packet to be configured in the MESH network sent by the network distribution device;

[0016] The slave node device is used to configure the lifetime data of the data packet in the slave node device based on the lifetime data of the data packet to be configured in the MESH network sent by the master node device.

[0017] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to implement the above method when executing the program through the computer program.

[0018] In a fifth aspect, an embodiment of the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned method when executed by a processor.

[0019] In a sixth aspect, an embodiment of the present application provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0020] In a seventh aspect, an embodiment of the present application provides an application program, which, when executed by a processor, implements the method in which the execution subject is a distribution network device.

[0021] Beneficial effects of the embodiments of the present application:

[0022] In an embodiment of the present application, the lifetime data of the data packet to be configured in the MESH network is calculated by using the network status data in the MESH network in the previous detection cycle, and the lifetime data of the data packet in the master node device and the slave node device are configured according to the calculated lifetime data of the data packet, so that the lifetime data of the data packet can be adaptively adjusted according to the network status data of the MESH network, so that the lifetime data of the data packet can effectively adapt to the changes in the network environment of the MESH network, reduce the risk of network congestion, and improve the transmission efficiency of the data packet and the utilization efficiency of network resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is one of the flowcharts of the network parameter configuration method provided in the embodiment of the present application;

[0025] Figure 2 This is one of the structural diagrams of the network parameter configuration system provided in the embodiment of the present application;

[0026] Figure 3 This is the second flow chart of the network parameter configuration method provided in the embodiment of the present application;

[0027] Figure 4 This is the third flow chart of the network parameter configuration method provided in the embodiment of the present application;

[0028] Figure 5 This is the second structural diagram of the network parameter configuration system provided in the embodiment of the present application;

[0029] Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0031] It should be noted that the terms "first", "second" etc. in the present application are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, method, system, product or equipment comprising a series of steps or modules need not be limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or equipment.

[0032] It should be noted that in the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of the information involved are in compliance with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and do not violate public order and good morals.

[0033] Figure 1 This is one of the flow charts of the network parameter configuration method provided in the embodiment of the present application, such as Figure 1 As shown, the method includes step 110, step 120 and step 130. The steps of the method flow are only a possible implementation of the present application.

[0034] Step 110: Obtain network status data in the MESH network during the previous detection cycle uploaded by the master node device.

[0035] Specifically, the network parameter configuration method provided in the embodiment of the present application is applied to the network distribution equipment in the MESH network. The network distribution equipment can be various electronic devices with display screens and supporting web browsing, including but not limited to servers, smart phones, tablet computers, laptops, and desktop computers.

[0036] The network distribution device in the embodiment of the present application is communicatively connected with the master node device in the MESH network.

[0037] A MESH network is a wireless communication network architecture used in the interconnection of Internet of Things (IoT) devices. A MESH network can be a wireless local area network consisting of a Bluetooth wireless mesh or a wireless local area network consisting of a WiFi wireless mesh.

[0038] The application scenario of the present application can be a lighting control scenario or a recording scenario, which is not limited here. For example, when the application scenario is a lighting control scenario, the MESH network is composed of multiple smart devices in the lighting control scenario, and the master node device is a smart device in the lighting control scenario.

[0039] Lighting control scene refers to the environment formed by controlling and managing the lighting effects of smart devices. Smart devices refer to hardware devices that integrate Bluetooth wireless mesh or WiFi wireless mesh wireless modules. Smart devices have networking functions and can exchange data. In the lighting control scene, smart devices can include smart lights, smart switches, smart sensors, and smart audio devices.

[0040] Each node device in the MESH network, such as each smart device, can send and receive data packets and can serve as a relay station between other node devices. Therefore, each node device can serve as a master node device or a slave node device. The master node device is a node device connected to the distribution network device, and the slave node device communicates with the distribution network device through the master node device. The distribution network device can switch the master node device at any time, or automatically determine a master node device from other slave node devices when a problem occurs in the master node device, and switch to connect to the master node device.

[0041] In order to control the propagation range of data packets in the network, the MESH network adopts a survival time mechanism. The survival time data indicates the maximum number of hops that a data packet can transmit in the MESH network. When a data packet starts to propagate from the master node device, the survival time data will decrease each time it passes through a node device until it drops to zero. After it drops to zero, the data packet will stop propagating.

[0042] Network status data refers to various information and statistics transmitted through the MESH network. For example, network status data may include the number of node devices in the MESH network, the data packet flow of the master node device, and / or the packet loss rate of the data packets sent by the distribution network device to the MESH network.

[0043] Step 120: Calculate the lifetime data of the data packet to be configured in the MESH network based on the network status data.

[0044] Specifically, a detection cycle can be set to calculate the survival time data of the data packet to be configured in the MESH network according to the network status data in the MESH network in each previous detection cycle. The detection cycle can be dynamically set according to actual conditions.

[0045] A relationship formula between network status data and survival time data can be constructed to calculate the survival time data through the formula; a prediction model can also be constructed, and the prediction model can be a neural network model. The network status data in the MESH network in the previous detection cycle is input into the prediction model to obtain the survival time data output by the prediction model.

[0046] Step 130, sending the calculated lifetime data to the master node device to configure the lifetime data of the data packet in the master node device, so that the master node device broadcasts the lifetime data to the slave node device to configure the lifetime data of the data packet in the slave node device.

[0047] Specifically, after calculating the lifetime data, the network configuration device sends the lifetime data to each node device in the MESH network through a network configuration protocol (such as the Bluetooth Mesh configuration protocol) to achieve automatic configuration update of the lifetime data.

[0048] For example, the network distribution device sends the calculated lifetime data of the data packet to be configured in the MESH network to the master node device, and then broadcasts the lifetime data to each slave node device through the master node device. After receiving the lifetime data, the master node device and the slave node device will configure and update the lifetime data of the data packet stored locally to ensure that the lifetime data of the data packet stored in the master node device and the slave node device are configured to the lifetime data of the data packet to be configured in the MESH network.

[0049] When the data packet is transmitted to the master node device, the lifetime data stored in the master node device is recorded in the data packet, and then the data packet with the lifetime data recorded is broadcasted to the slave node device. The lifetime data will decrease each time it passes through the slave node device until it drops to zero. After it drops to zero, the data packet will stop propagating.

[0050] The network parameter configuration method provided in the embodiment of the present application calculates the lifetime data of the data packet to be configured in the MESH network through the network status data in the MESH network in the previous detection cycle, and configures the lifetime data of the data packet in the master node device and the slave node device according to the calculated lifetime data of the data packet, so that the lifetime data of the data packet can be adaptively adjusted according to the network status data of the MESH network, so that the lifetime data of the data packet can effectively adapt to the changes in the network environment of the MESH network, reduce the risk of network congestion, and improve the transmission efficiency of the data packet and the utilization efficiency of network resources.

[0051] It should be noted that each implementation method of the present application can be freely combined, the order can be changed, or it can be executed separately, and does not need to rely on or depend on a fixed execution order.

[0052] In some embodiments, the network status data includes the number of node devices in the MESH network, the data packet flow of the master node device and / or the packet loss rate of the data packets sent by the distribution network device in the MESH network; obtaining the network status data in the MESH network in the previous detection cycle uploaded by the master node device includes:

[0053] Determine the quantity data based on the number of node devices corresponding to the heartbeat packets received in the previous detection cycle and the maximum number of node devices supported by the MESH network;

[0054] Determine the data packet flow based on the number of data packets received and sent by the master node device in the last detection cycle and the cycle time of the last detection cycle;

[0055] Determine the packet loss rate based on the number of data packet responses received by the distribution network device and the number of data packets sent;

[0056] Network status data is obtained based on volume data, packet flow and / or packet loss rate.

[0057] Specifically, a heartbeat packet is a network status data packet sent periodically to detect the status and stability of a network connection. It is usually sent periodically by network devices (such as smart routers or gateways) to ensure that other devices are still online and responding.

[0058] Get the number of heartbeat packets received in the last detection cycle to determine the number of node devices currently connected to the MESH network, that is, determine the number of online node devices. According to the design specifications or configuration of the MESH network, determine the maximum number of node devices supported by the network, for example, the maximum number of node devices is 255. The value of the number of node devices = the number of online node devices ÷ the maximum number of node devices.

[0059] Get the number of all data packets received and sent by the master node device in the last detection cycle. Determine the specific duration of the last detection cycle. The total number of data packets received and sent by the master node device per unit time in the last detection cycle = (the number of data packets received by the master node device + the number of data packets sent by the master node device) ÷ the specific duration of the last detection cycle. Data packet flow = the total number of data packets received and sent by the master node device per unit time in the last detection cycle ÷ the total number of data packets that the master node device can receive and send at most per unit time. The total number of data packets that the master node device can receive and send at most per unit time is the maximum processing capacity of the master node device for data packets per unit time.

[0060] Get the number of data packet responses received by the network configuration device and the number of data packets sent by the network configuration device in the previous detection cycle. Packet loss rate = 1-number of data packet responses ÷ number of data packets sent.

[0061] The network status data may include the number of node devices, data packet flow, and packet loss rate.

[0062] The network parameter configuration method provided in the embodiment of the present application can accurately identify the network status of the MESH network through network status data such as the number of node devices, data packet flow and packet loss rate.

[0063] In some embodiments, calculating the network congestion parameter in the MESH network in the last detection period according to the network status data includes:

[0064] Obtaining a first weight for quantity data, a second weight for packet flow, and a third weight for packet loss rate;

[0065] Determining a network congestion parameter based on the first weight, the quantity data, the second weight, the packet flow, the third weight, and the packet loss rate;

[0066] The sum of the first weight, the second weight and the third weight is equal to 1.

[0067] Specifically, the network congestion parameter is a parameter used to characterize the network status of the MESH network. The survival time data can be adjusted in real time through the specific network congestion parameter of the MESH network.

[0068] The number of node devices, data packet flow, and packet loss rate may have different impacts on the network status of the MESH network, so more accurate network congestion parameters can be obtained by setting weights. The greater the impact of the data on the network status, the greater the corresponding weight of the data.

[0069] The weight of the number of node devices is called the first weight, the weight of the data packet flow is called the second weight, and the weight of the packet loss rate is called the third weight. The first weight, the second weight, and the third weight can be set according to the historical data and actual scenarios of the MESH network.

[0070] Network congestion parameters C The specific calculation formula is as follows:

[0071]

[0072] Among them, 0< C <1, N The number of node devices corresponding to the heartbeat packets received by the network configuration device in the previous detection cycle; N max The maximum number of node devices supported by the MESH network; max The maximum processing capacity of the master node device for data packets per unit time (the total number of data packets received and sent per unit time, packets / second). λ The total number of data packets received and sent by the master node device per unit time in the previous detection cycle (packets / second); α is the first weight, β is the second weight, γ is the third weight, α+β+γ =1; R lossis the packet loss rate of the network configuration device in the previous detection cycle, 0< R loss <1.

[0073] For example, the network configuration device is a mobile phone, and each step of the network parameter configuration method is executed through an application installed on the mobile phone. The master node device is lamp 1, and the slave node device is lamp 2. Figure 2 is one of the structural diagrams of the network parameter configuration system provided in the embodiment of the present application, Figure 3 This is a second flow chart of the network parameter configuration method provided in the embodiment of the present application, such as Figure 2 and Figure 3 As shown, the monitoring module is used to collect network status data in real time. Analysis module: used to regularly process and analyze network status data, generate corresponding network congestion parameters and adjusted lifetime data of data packets to be configured in the MESH network. Control module: used as the source of MESH network status data, and sends the lifetime data of data packets to be configured in the MESH network to each node device through the MESH network protocol. Execution module: used to periodically report the data of the node device to the monitoring module, execute the lifetime data sent by the control module to configure the lifetime data of each node device, and configure and execute the data forwarding mechanism in the MESH network according to the lifetime data.

[0074] The application on the mobile phone initiates the lifetime data configuration as the configurator of the MESH network, sets the default lifetime data (for example, the lifetime data is 5), and completes the lifetime data configuration of lamps 1 and 2.

[0075] After the configuration is completed, lamps 1 and 2 regularly report their online status through heartbeat packets, and the master node device (lamp 1) reports the received and sent data packet traffic statistics within the previous detection cycle t λ to the application.

[0076] The monitoring module in the application saves the data reported by the node equipment and the online status of the node equipment in real time.

[0077] The analysis module in the application regularly queries the data saved by the detection module according to the detection cycle, and determines the number of node devices in the MESH network, the data packet flow of the main node device, and the packet loss rate of the data packets sent by the distribution network device to the MESH network according to the data transmitted by the monitoring module. The network congestion parameter is calculated based on the first weight, the second weight, the third weight and the network status data.

[0078] The network parameter configuration method provided in the embodiment of the present application determines network congestion parameters by setting weights, thereby improving the accuracy of the determined network congestion parameters and improving the accuracy of the network parameter configuration.

[0079] In some embodiments, step 120 includes:

[0080] Calculate the network congestion parameters in the MESH network during the previous detection cycle based on the network status data;

[0081] Obtain the congestion coefficient threshold and historical survival time data in the previous detection cycle;

[0082] The survival time data is obtained based on the network congestion parameter, the congestion coefficient threshold and the historical survival time data.

[0083] The survival time data is obtained based on the network congestion parameters, congestion coefficient threshold and historical survival time data, including:

[0084] Determine the adjustment direction and adjustment range of the historical survival time data based on the network congestion parameter, the congestion coefficient threshold and the historical survival time data;

[0085] Based on the adjustment range and direction, the historical survival time is adjusted to obtain the survival time data.

[0086] The adjustment direction and adjustment range of the historical survival time data are determined based on the network congestion parameter, the congestion parameter threshold, and the historical survival time data, including:

[0087] Determine the adjustment direction of the historical survival time data based on the network congestion parameter, the congestion parameter threshold and the historical survival time data;

[0088] The adjustment range of the historical survival time data is determined based on the adjustment direction, the network congestion parameter and the congestion parameter threshold.

[0089] The congestion parameter threshold includes a first congestion parameter threshold and a second congestion parameter threshold; determining the adjustment direction of the historical survival time data based on the network congestion parameter, the congestion parameter threshold and the historical survival time data includes:

[0090] When the network congestion parameter is less than or equal to the first congestion parameter threshold and the historical survival time data is greater than or equal to the time data threshold, determining that the adjustment direction is to increase the survival time;

[0091] When the network congestion parameter is greater than or equal to the second congestion parameter threshold, determining the adjustment direction is to reduce the survival time;

[0092] When the network congestion parameter is greater than the first congestion parameter threshold and less than the second congestion parameter threshold, the adjustment direction is determined to be no adjustment.

[0093] The adjustment range of the historical survival time data is determined based on the adjustment direction, network congestion parameter, and congestion parameter threshold, including:

[0094] If the adjustment direction is to increase the survival time, determining a first amplitude value of the adjustment amplitude based on a difference level of a difference between the network congestion parameter and the first congestion parameter threshold;

[0095] If the adjustment direction is to reduce the survival time, determining a second amplitude value of the adjustment amplitude based on a difference level of a difference between the network congestion parameter and a second congestion parameter threshold;

[0096] If the adjustment direction is no adjustment, the adjustment range is determined to be zero.

[0097] Specifically, the congestion parameter threshold includes a first congestion parameter threshold and a second congestion parameter threshold. The first congestion parameter threshold is the congestion parameter threshold when the network is extremely good; the second congestion parameter threshold is the congestion parameter threshold when the network is relatively congested. The specific values ​​of the first congestion parameter threshold and the second congestion parameter threshold can be dynamically adjusted according to actual conditions. The network status of the MESH network is divided into the following levels according to the network congestion parameter and the congestion parameter threshold:

[0098] Excellent: Network congestion parameter ≤ first congestion parameter threshold.

[0099] Normal: The first congestion parameter threshold < network congestion parameter < second congestion parameter threshold.

[0100] Congestion: The network congestion parameter ≥ the second congestion parameter threshold.

[0101] The lifetime data is dynamically adjusted according to the network congestion level. The detection cycle can be set, for example, the network congestion parameters are determined every time t. The historical lifetime data is the latest lifetime data stored in the master node device during the previous detection cycle.

[0102] When the network status is excellent (network congestion parameter ≤ first congestion parameter threshold), the MESH network has no network congestion and the network performance has certain redundancy. If the adjustment direction is confirmed to increase the survival time, the historical survival time data in the previous detection cycle can be added to obtain the survival time data, for example, adding 1 to the historical survival time data to improve the data packet coverage; but if the historical survival time data ≥ the time data threshold, it will not be increased. The time data threshold can be determined according to the configuration of the MESH network, for example, the time data threshold can be 127.

[0103] When the network status is normal (the first congestion parameter threshold < network congestion parameter < the second congestion parameter threshold), the network performance and data packet coverage of the MESH network are both ideal, which can not only meet the communication stability requirements but also cover a larger range. Therefore, the adjustment direction is confirmed to be no adjustment, and the historical survival time data can be directly used as the survival time data, that is, the survival time data is not updated.

[0104] When the network status is congested (network congestion parameter ≥ second congestion parameter threshold), the MESH network is congested and the network performance cannot meet the communication stability. If the adjustment direction is confirmed to reduce the survival time, the historical survival time data in the previous detection cycle can be reduced to obtain the survival time data, for example, subtract 1 from the historical survival time data to reduce network congestion. However, if the historical survival time data is ≤1, it will no longer be reduced.

[0105] The first amplitude value and the second amplitude value of the adjustment amplitude of the increase or decrease of the historical survival time data can be determined according to the difference level between the network congestion parameter and the network parameter. The greater the difference between the network congestion parameter and the network parameter, the greater the difference level, and the greater the amplitude value of the adjustment amplitude.

[0106] After calculating the lifetime data of the data packet to be configured in the MESH network, the control module in the application sends the lifetime data to the master node device through the network configuration protocol to configure the lifetime data of the data packet in the master node device, and the master node device forwards the lifetime data to the slave node device, thereby realizing the automatic configuration update of the lifetime data of the data packet in the MESH network. When the network status changes and the network status is not in a normal state, the lifetime data is configured and updated again to ensure that the lifetime data is adjusted to a better value in real time with the network status.

[0107] The network parameter configuration method provided in the embodiment of the present application can adjust the lifetime data in real time through network congestion parameters and congestion parameter thresholds, so that the network status of the MESH network can reach a better state, thereby improving the network stability of the MESH network and the transmission efficiency of data packets.

[0108] In some embodiments, a survival time prediction model can also be obtained, and the survival time data can be predicted by generating the time prediction model. Specifically, the network status data in the MESH network in the previous detection cycle and the historical generation time data in the MESH network in the previous detection cycle are obtained, and the network status data and the historical generation time data are input into the survival time prediction model for processing to obtain the survival time data of the data packet in the MESH network. The survival time prediction model can quickly and accurately predict the survival time data.

[0109] In some embodiments, step 120 includes:

[0110] Obtain historical survival time data in the MESH network during the previous detection cycle;

[0111] The network status data is input into the first feature extraction network of the survival time prediction model for feature extraction processing to obtain the MESH network features;

[0112] Inputting the historical survival time data into the second feature extraction network of the survival time prediction model for feature extraction processing to obtain survival time features;

[0113] The MESH network features and the survival time features are fused to obtain the network time fusion features;

[0114] The network time fusion features are input into the time decision maker of the survival time prediction model to obtain the survival time data.

[0115] Specifically, the survival time prediction model is a neural network model used to predict the survival time data of a data packet to be configured in the MESH network.

[0116] The survival time prediction model can be constructed using convolutional neural network models, fully connected neural network models, recurrent neural network models, and long short-term memory neural network models.

[0117] The first feature extraction network is a part of the survival time prediction model and is used to extract useful features from the raw network status data.

[0118] The network status data is input into the first feature extraction network of the survival time prediction model. The first feature extraction network automatically learns and extracts feature vectors that can represent the network status and behavior from the input network status data through various algorithms and techniques (such as convolutional neural networks in deep learning) to obtain MESH network features.

[0119] The second feature extraction network is also part of the survival time prediction model and is used to extract useful features from historical survival time data.

[0120] The historical survival time data is input into the second feature extraction network of the survival time prediction model. The second feature extraction network automatically learns and extracts feature vectors that can represent the historical survival time data from the input historical survival time data through various algorithms and techniques to obtain survival time features.

[0121] The network time fusion feature is obtained by combining the MESH network feature and the survival time feature. The network time fusion feature includes comprehensive information about the network status and historical survival time, providing a more comprehensive and accurate basis for subsequent time decisions.

[0122] The time decider is the core part of the survival time prediction model, which is used to make decisions based on the input network time fusion features. The time decider can be a classifier, regressor, or other types of machine learning models. The time decider analyzes the fused feature vector and predicts the survival time data of the data packet to be configured in the MESH network.

[0123] The survival time prediction model can be obtained by training in advance. For example, a data set to be trained and an initial survival time model are obtained, wherein the data set to be trained includes network state data samples in the MESH network, historical survival time data samples corresponding to the network state data samples, and survival time data samples corresponding to the network state data samples; the network state data samples and the historical survival time data samples corresponding to the network state data samples are input into the initial survival time model, the initial first feature extraction network of the initial survival time model extracts the MESH network features of the network state data samples, and the initial second feature extraction network of the initial survival time model extracts the survival time features of the historical survival time data samples corresponding to the network state data samples, and the MESH network features and the survival time features are fused to obtain network time fusion features; the network time fusion features are input into the initial time decision maker of the initial survival time prediction model to obtain predicted survival time data, the predicted survival time data are compared with the survival time data samples corresponding to the network state data samples to obtain loss data, the model parameters of the initial survival time model are adjusted according to the loss data, and the initial survival time model is further trained according to the data set to be trained until the initial survival time model can accurately predict the survival time data.

[0124] The network parameter configuration method provided in the embodiment of the present application predicts the survival time data in real time through the survival time prediction model to adapt to the ever-changing network environment, thereby improving the data packet transmission efficiency of the MESH network.

[0125] The executor of the network parameter configuration method described above is a network distribution device. The following describes a network parameter configuration method in which the executor provided in an embodiment of the present application is a slave node device. The network parameter configuration method in which the executor described below is a slave node device and the network parameter configuration method in which the executor is a network distribution device can be referenced to each other.

[0126] Figure 4 This is a flowchart of the network parameter configuration method provided in the embodiment of the present application. Figure 4 As shown, the method includes step 410 and step 420. The steps of the method flow are only a possible implementation of the present application.

[0127] Step 410: Receive the lifetime data of the data packet to be configured in the MESH network broadcasted by the master node device or other slave node devices in the MESH network.

[0128] Step 420: configure the lifetime data of the data packet in the slave node device based on the lifetime data of the data packet to be configured in the MESH network; wherein the lifetime data is calculated by the distribution network device based on the network status data in the MESH network in the previous detection cycle uploaded by the master node device.

[0129] Specifically, after the distribution network device calculates the lifetime data of the data packet to be configured in the MESH network based on the network status data in the MESH network in the previous detection cycle, it will send the lifetime data to the master node device, and the master node device will then broadcast the lifetime data to the slave node devices.

[0130] The slave node device will receive the lifetime data broadcasted by the master node device or other slave node devices, and configure the lifetime data of the locally recorded data packet through the lifetime data.

[0131] The network parameter configuration method provided in the embodiment of the present application calculates the lifetime data of the data packet to be configured in the MESH network through the network status data in the MESH network in the previous detection cycle, and configures the lifetime data of the data packet in the master node device and the slave node device according to the calculated lifetime data of the data packet, so that the lifetime data of the data packet can be adaptively adjusted according to the network status data of the MESH network, so that the lifetime data of the data packet can effectively adapt to the changes in the network environment of the MESH network, reduce the risk of network congestion, and improve the transmission efficiency of the data packet and the utilization efficiency of network resources.

[0132] In some embodiments, after step 420, the process further includes:

[0133] Compare the remaining survival time data carried in the received data packet with the survival time data;

[0134] In a case where the remaining survival time data is greater than the survival time data, the remaining survival time data is configured based on the survival time data.

[0135] Specifically, the remaining lifetime data is the maximum number of hops that a data packet received from a node device can still propagate.

[0136] When a data packet is transmitted to a slave node device, the lifetime data carried by the data packet in the master node device may be different from the lifetime data currently stored in the slave node device due to reasons such as the propagation rate and the detection cycle. Therefore, the remaining lifetime data carried in the current data packet can be compared with the lifetime data of the slave node device, and the remaining lifetime data can be adjusted based on the comparison results.

[0137] For example, the remaining lifetime data carried in the data packet received from the node device and the lifetime data of the data packet recorded in the node device are checked.

[0138] If the remaining lifetime data is greater than the lifetime data, the remaining lifetime data of the data packet is configured as the lifetime data.

[0139] The network parameter configuration method provided in the embodiment of the present application can reduce network congestion of the MESH network and improve the transmission efficiency of the data packet by configuring the remaining lifetime data carried in the received data packet from the lifetime data of the data packet recorded in the node device.

[0140] The network parameter configuration system provided in an embodiment of the present application is described below. The network parameter configuration system described below and the network parameter configuration method described above can be referenced to each other.

[0141] Figure 5 This is the second structural diagram of the network parameter configuration system provided in the embodiment of the present application, such as Figure 5 As shown, the system includes a distribution network device 510, a master node device 520 and a slave node device 530 in a MESH network;

[0142] The network configuration device 510 is used to receive the network status data in the MESH network in the last detection cycle uploaded by the master node device 520, calculate the survival time data of the data packet to be configured in the MESH network based on the network status data, and send the calculated survival time data to the master node device 520;

[0143] The master node device 520 is used to send network status data to the network distribution device 510, and configure the lifetime data of the data packet in the master node device 520 based on the lifetime data of the data packet to be configured in the MESH network sent by the network distribution device 510;

[0144] The slave node device 530 is used to configure the lifetime data of the data packet in the slave node device 530 based on the lifetime data of the data packet to be configured in the MESH network sent by the master node device 520.

[0145] The number of network distribution devices 510, master node devices 520 and slave node devices 530 can be set according to actual conditions.

[0146] It should be noted here that the network parameter configuration system provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned network parameter configuration method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0147] Figure 6 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Figure 6As shown, the electronic device may include: a processor (Processor) 610, a communication interface (Communication Interface) 620, a memory (Memory) 630 and a communication bus 640, wherein the processor 610, the communication interface 620, and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call a computer program in the memory 630 to execute the above method, for example, including:

[0148] Obtain the network status data in the MESH network during the last detection cycle uploaded by the master node device;

[0149] Calculate the survival time data of the data packet to be configured in the MESH network based on the network status data;

[0150] The calculated lifetime data is sent to the master node device to configure the lifetime data of the data packet in the master node device, so that the master node device broadcasts the lifetime data to the slave node device to configure the lifetime data of the data packet in the slave node device.

[0151] It also includes: receiving the survival time data of the data packet to be configured in the MESH network broadcasted by the master node device or other slave node devices in the MESH network;

[0152] Based on the lifetime data of the data packet to be configured in the MESH network, the lifetime data of the data packet in the slave node device is configured;

[0153] The survival time data is calculated by the distribution network device based on the network status data in the MESH network during the previous detection cycle uploaded by the master node device.

[0154] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software function modules and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., and other media that can store program codes.

[0155] On the other hand, an embodiment of the present application also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the methods provided in the above embodiments.

[0156] On the other hand, an embodiment of the present application further provides a processor-readable storage medium, which stores a computer program, and the computer program is used to enable the processor to execute the methods provided in the above embodiments.

[0157] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO)), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drives (SSDs)), etc.

[0158] On the other hand, an embodiment of the present application further provides an application program, which, when executed by a processor, implements the above-mentioned method in which the execution subject is a distribution network device.

[0159] The embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement the present invention without paying creative labor.

[0160] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0161] The embodiments of the present application are introduced in detail above. Specific examples are used in the present application to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A network parameter configuration method, characterized in that: A network distribution device applied to a MESH network, wherein the MESH network further includes a master node device and a slave node device, and the method includes: Obtaining network status data in the MESH network during the last detection cycle uploaded by the master node device; Calculate the survival time data of the data packet to be configured in the MESH network based on the network status data; Sending the calculated survival time data to the master node device to configure the survival time data of the data packet in the master node device, so that the master node device broadcasts the survival time data to the slave node device to configure the survival time data of the data packet in the slave node device; The step of calculating the survival time data of the data packet to be configured in the MESH network based on the network status data includes: Calculating a network congestion parameter in the MESH network in the previous detection period according to the network status data; Obtaining a congestion parameter threshold and historical survival time data within the previous detection cycle; The survival time data is obtained based on the network congestion parameter, the congestion parameter threshold and the historical survival time data.

2. The network parameter configuration method according to claim 1, characterized in that: The obtaining the survival time data based on the network congestion parameter, the congestion parameter threshold and the historical survival time data includes: Determining an adjustment direction and an adjustment range of the historical survival time data based on the network congestion parameter, the congestion parameter threshold, and the historical survival time data; Based on the adjustment range and adjustment direction, the historical survival time is adjusted to obtain the survival time data.

3. The network parameter configuration method according to claim 2, characterized in that: The determining the adjustment direction and adjustment range of the historical survival time data based on the network congestion parameter, the congestion parameter threshold and the historical survival time data includes: Determining an adjustment direction of the historical survival time data based on the network congestion parameter, the congestion parameter threshold, and the historical survival time data; An adjustment range of the historical survival time data is determined based on the adjustment direction, the network congestion parameter and the congestion parameter threshold.

4. The network parameter configuration method according to claim 3, characterized in that: The congestion parameter threshold includes a first congestion parameter threshold and a second congestion parameter threshold; and determining the adjustment direction of the historical survival time data based on the network congestion parameter, the congestion parameter threshold and the historical survival time data includes: When the network congestion parameter is less than or equal to the first congestion parameter threshold and the historical survival time data is greater than or equal to the time data threshold, determining that the adjustment direction is to increase the survival time; When the network congestion parameter is greater than or equal to the second congestion parameter threshold, determining that the adjustment direction is to reduce the survival time; When the network congestion parameter is greater than the first congestion parameter threshold and less than the second congestion parameter threshold, the adjustment direction is determined to be no adjustment.

5. The network parameter configuration method according to claim 3, characterized in that: The congestion parameter threshold includes a first congestion parameter threshold and a second congestion parameter threshold; and determining the adjustment range of the historical survival time data based on the adjustment direction, the network congestion parameter and the congestion parameter threshold includes: If the adjustment direction is to increase the survival time, determining a first amplitude value of the adjustment amplitude based on a difference level of a difference between the network congestion parameter and the first congestion parameter threshold; If the adjustment direction is to reduce the survival time, determining a second amplitude value of the adjustment amplitude based on a difference level of a difference between the network congestion parameter and the second congestion parameter threshold; If the adjustment direction is no adjustment, the adjustment amplitude is determined to be zero.

6. The network parameter configuration method according to claim 1, characterized in that: The network status data includes the number of node devices in the MESH network, the data packet flow of the master node device and / or the packet loss rate of the data packets sent by the distribution network device in the MESH network; The obtaining of the network status data in the MESH network in the last detection cycle uploaded by the master node device includes: Determine the quantity data based on the number of node devices corresponding to the heartbeat packets received in the previous detection cycle and the maximum number of node devices supported by the MESH network; Determine the data packet flow based on the number of data packets received and sent by the master node device in the previous detection cycle and the cycle time of the previous detection cycle; Determining the packet loss rate based on the number of data packet responses received and the number of data packets sent by the network distribution device; The network status data is obtained based on the quantity data, the data packet flow and / or the packet loss rate.

7. The network parameter configuration method according to claim 6, characterized in that: The calculating, according to the network status data, a network congestion parameter in the MESH network in the previous detection cycle includes: Obtaining a first weight of the quantity data, a second weight of the data packet flow, and a third weight of the packet loss rate; determining the network congestion parameter based on the first weight, the quantity data, the second weight, the data packet flow, the third weight, and the packet loss rate; The sum of the first weight, the second weight and the third weight is equal to 1.

8. The network parameter configuration method according to claim 1 or 6, characterized in that: The calculating the survival time data of the data packet to be configured in the MESH network based on the network status data includes: Obtaining historical survival time data in the MESH network during the previous detection cycle; The network status data is input into the first feature extraction network of the survival time prediction model for feature extraction processing to obtain MESH network features; Inputting the historical survival time data into the second feature extraction network of the survival time prediction model for feature extraction processing to obtain survival time features; The MESH network feature and the survival time feature are fused to obtain a network time fusion feature; The network time fusion feature is input into the time decision maker of the survival time prediction model to obtain the survival time data.

9. A network parameter configuration method, characterized in that: A slave node device applied to a MESH network, wherein the MESH network further includes a master node device and a network distribution device; the method includes: Receiving lifetime data of a data packet to be configured in the MESH network broadcasted by the master node device or other slave node devices in the MESH network; configuring the lifetime data of the data packet in the slave node device based on the lifetime data of the data packet to be configured in the MESH network; Among them, the survival time data is calculated by the distribution network device based on the network status data in the MESH network in the previous detection cycle uploaded by the master node device; the distribution network device calculates the network congestion parameters in the MESH network in the previous detection cycle according to the network status data; obtains the congestion parameter threshold and the historical survival time data in the previous detection cycle; and obtains the survival time data based on the network congestion parameter, the congestion parameter threshold and the historical survival time data.

10. The network parameter configuration method according to claim 9, characterized in that: After configuring the lifetime data of the data packet in the slave node device based on the lifetime data of the data packet to be configured in the MESH network, the method further includes: Comparing the remaining lifetime data carried in the received data packet with the lifetime data; In a case where the remaining survival time data is greater than the survival time data, the remaining survival time data is configured based on the survival time data.

11. A network parameter configuration system, characterized in that: Including distribution equipment, master node equipment and slave node equipment in the MESH network; The network configuration device is used to receive the network status data in the MESH network in the last detection cycle uploaded by the master node device, calculate the survival time data of the data packet to be configured in the MESH network based on the network status data, and send the calculated survival time data to the master node device; The master node device is used to send the network status data to the network distribution device, and configure the lifetime data of the data packet in the master node device based on the lifetime data of the data packet to be configured in the MESH network sent by the network distribution device; The slave node device is used to configure the survival time data of the data packet in the slave node device based on the survival time data of the data packet to be configured in the MESH network sent by the master node device; The step of calculating the survival time data of the data packet to be configured in the MESH network based on the network status data includes: Calculating a network congestion parameter in the MESH network in the previous detection period according to the network status data; Obtaining a congestion parameter threshold and historical survival time data within the previous detection cycle; The survival time data is obtained based on the network congestion parameter, the congestion parameter threshold and the historical survival time data.

12. An electronic device comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor is configured to execute the network parameter configuration method according to any one of claims 1 to 10 through the computer program.

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