Intelligent routing control method, system and medium based on dual-mode communication terminal

Abstract

The application provides a smart routing control method, system and medium based on a dual-mode communication terminal. The method comprises the following steps: acquiring an ad hoc network state flag bit of the dual-mode communication terminal, comparing the ad hoc network state flag bit with a preset ad hoc network state flag bit setting value, if the comparison is consistent, obtaining a link state evaluation index according to communication quality monitoring data and node load data of each communication link of the ad hoc network, and determining a target link for service data transmission, if the comparison of the ad hoc network state flag bit is inconsistent, acquiring channel monitoring data corresponding to each channel of a low-orbit satellite, determining a target channel, and further processing and generating traffic prediction data, performing traffic allocation on the target channel according to the traffic prediction data, and performing service data transmission; thereby realizing smart routing control of the dual-mode communication terminal.

Description

Technical Field

[0001] This application relates to the fields of big data and intelligent routing control technology, and more specifically, to intelligent routing control methods, systems and media based on dual-mode communication terminals. Background Technology

[0002] A dual-mode communication terminal is a terminal device that integrates satellite communication and terrestrial wireless ad hoc network communication functions. Its main feature is the ability to acquire trunking routing information in real time and achieve autonomous, seamless switching between satellite channels and terrestrial ad hoc network channels to meet diverse communication needs. Because dual-mode communication terminals involve switching and cooperating between two different communication modes, traditional routing control methods cannot effectively manage their communication paths. In a dual-mode communication environment, data needs to select an appropriate transmission path based on factors such as network conditions and communication quality. However, currently, there is a lack of technology that enables dual-mode communication terminals to autonomously switch modes and select communication paths and allocate traffic based on factors such as communication quality, node load, and network status.

[0003] Effective technical solutions are urgently needed to address the above problems. Summary of the Invention

[0004] The purpose of this application is to provide an intelligent routing control method, system, and medium based on a dual-mode communication terminal. The method selects the communication mode based on the self-organizing network status flag, and then evaluates the communication link based on communication quality and node load in the self-organizing network communication mode to obtain the optimal link in the self-organizing network mode. In the low-Earth orbit satellite communication mode, the method selects the target channel based on the channel monitoring data of the low-Earth orbit satellite and allocates traffic to the target channel, so as to realize the technology of autonomous communication mode switching, intelligent path selection, and traffic allocation of the dual-mode communication terminal.

[0005] This application also provides an intelligent routing control method based on a dual-mode communication terminal, including the following steps:

[0006] Obtain the self-organizing network status flag bit of the dual-mode communication terminal and compare the self-organizing network status flag bit with the preset self-organizing network status flag bit setting value;

[0007] If the self-organizing network status flags match, then obtain the communication quality monitoring data and node load data of each communication link in the self-organizing network, and process the node load data to obtain the node load impact factor.

[0008] Based on the communication quality monitoring data and the node load impact factor processing, a link status evaluation index is obtained, and a target link is determined for service data transmission.

[0009] If the self-organizing network status flags are inconsistent, then obtain the channel monitoring data corresponding to each channel of the low-Earth orbit satellite and determine the target channel;

[0010] The acquired real-time monitoring data of dual-mode communication terminals and real-time network congestion data of the target channel are input into the trained traffic prediction model to generate traffic prediction data. Based on the traffic prediction data, traffic is allocated to the target channel and service data is transmitted.

[0011] Optionally, in the intelligent routing control method based on dual-mode communication terminals described in this application, if the self-organizing network status flag bits are consistent, then acquiring the communication quality monitoring data and node load data of each communication link in the self-organizing network, and processing the node load data to obtain the node load influence factor, includes:

[0012] The communication quality monitoring data includes transmission rate, packet loss rate, communication latency, and bandwidth utilization.

[0013] The node load data includes data transmission volume, CPU utilization, and memory usage.

[0014] The node load impact factor is obtained by processing the data transfer volume, CPU utilization, and memory usage.

[0015] Optionally, in the intelligent routing control method based on a dual-mode communication terminal described in this application, the step of obtaining a link state evaluation index based on the communication quality monitoring data and the node load impact factor, and determining the target link for service data transmission, includes:

[0016] The link status evaluation index is obtained by processing the transmission rate, packet loss rate, communication latency, bandwidth utilization, and node load impact factor.

[0017] The link status evaluation index corresponding to each link is sorted, and the link with the largest link status evaluation index is selected as the target link.

[0018] The dual-mode communication terminal sends service data to the target communication terminal through the target link.

[0019] Optionally, in the intelligent routing control method based on a dual-mode communication terminal described in this application, the step of obtaining channel monitoring data corresponding to each channel of the low-Earth orbit satellite and determining the target channel if the self-organizing network status flags are inconsistent includes:

[0020] If the self-organizing network status flags are inconsistent, then obtain the channel monitoring data corresponding to each channel of the low-Earth orbit satellite;

[0021] The channel monitoring data includes signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate;

[0022] The channel state evaluation index corresponding to each channel is obtained by processing the signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate.

[0023] The channel state evaluation index is compared with a preset channel state evaluation index threshold, and the channel corresponding to the channel state evaluation index that meets the preset threshold comparison requirements is taken as the target channel.

[0024] Optionally, in the intelligent routing control method based on a dual-mode communication terminal described in this application, the step of inputting the acquired real-time monitoring data of the dual-mode communication terminal and the real-time network congestion data of the target channel into a trained traffic prediction model to generate traffic prediction data, allocating traffic to the target channel according to the traffic prediction data, and transmitting service data includes:

[0025] Acquire historical traffic data of the target channel, along with its corresponding terminal communication behavior data and historical network congestion data;

[0026] The historical network congestion data includes historical transmission rate, historical signal strength data, historical network congestion time data, and historical network congestion degree data; the terminal communication behavior data includes access type data, access time data, and terminal location data.

[0027] A traffic prediction model is generated by training a model based on the historical traffic data, combined with the historical transmission rate, historical signal strength data, historical network congestion time data, historical network congestion degree data, as well as the access type data, access time data, and terminal location data.

[0028] The system acquires real-time monitoring data of dual-mode communication terminals and real-time network congestion data of the target channel. The real-time monitoring data of dual-mode communication terminals includes real-time access type data, real-time access time data, and real-time terminal location data. The real-time network congestion data of the target channel includes real-time signal strength data, real-time transmission rate data, real-time network congestion time data, and real-time network congestion degree data.

[0029] The real-time access type data, real-time access time data, terminal real-time location data, real-time signal strength data, real-time transmission rate data, real-time network congestion time data, and real-time network congestion degree data are input into the traffic prediction model for processing to obtain traffic prediction data.

[0030] Traffic is allocated to the target channel based on the traffic prediction data, and service data is sent to the target communication terminal.

[0031] Optionally, the intelligent routing control method based on a dual-mode communication terminal described in this application further includes:

[0032] The link failure assessment index is obtained by processing the link status assessment index of each communication link in the self-organizing network.

[0033] The channel fault assessment index is obtained by processing the channel state assessment index of each channel of the low-Earth orbit satellite.

[0034] Optionally, the intelligent routing control method based on a dual-mode communication terminal described in this application further includes:

[0035] The link failure assessment index is compared with a preset link failure assessment index threshold to obtain a link failure assessment threshold comparison result. The channel failure assessment index is compared with a preset channel failure assessment index threshold to obtain a channel failure assessment threshold comparison result.

[0036] If the comparison result of the link failure assessment threshold or the channel failure assessment threshold does not meet the requirements of the preset threshold comparison result, the self-organizing network status flag bit will be compared with the preset self-organizing network status flag bit setting value, and the self-organizing network status flag bit update will be determined based on the comparison result.

[0037] If neither the link fault assessment threshold comparison result nor the channel fault assessment threshold comparison result meets the preset threshold comparison result requirements, a fault alarm will be issued.

[0038] Secondly, this application provides an intelligent routing control system based on a dual-mode communication terminal. The system includes a memory and a processor. The memory stores a program for an intelligent routing control method based on a dual-mode communication terminal. When the program for the intelligent routing control method based on the dual-mode communication terminal is executed by the processor, it performs the following steps:

[0039] Obtain the self-organizing network status flag bit of the dual-mode communication terminal and compare the self-organizing network status flag bit with the preset self-organizing network status flag bit setting value;

[0040] If the self-organizing network status flags match, then obtain the communication quality monitoring data and node load data of each communication link in the self-organizing network, and process the node load data to obtain the node load impact factor.

[0041] Based on the communication quality monitoring data and the node load impact factor processing, a link status evaluation index is obtained, and a target link is determined for service data transmission.

[0042] If the self-organizing network status flags are inconsistent, then obtain the channel monitoring data corresponding to each channel of the low-Earth orbit satellite and determine the target channel;

[0043] The acquired real-time monitoring data of dual-mode communication terminals and real-time network congestion data of the target channel are input into the trained traffic prediction model to generate traffic prediction data. Based on the traffic prediction data, traffic is allocated to the target channel and service data is transmitted.

[0044] Optionally, in the intelligent routing control system based on a dual-mode communication terminal described in this application, if the self-organizing network status flag bits are consistent, then acquiring the communication quality monitoring data and node load data of each communication link in the self-organizing network, and processing the node load data to obtain the node load influence factor, includes:

[0045] The communication quality monitoring data includes transmission rate, packet loss rate, communication latency, and bandwidth utilization.

[0046] The node load data includes data transmission volume, CPU utilization, and memory usage.

[0047] The node load impact factor is obtained by processing the data transfer volume, CPU utilization, and memory usage.

[0048] Thirdly, this application also provides a computer-readable storage medium storing a program for an intelligent routing control method based on a dual-mode communication terminal. When the program for the intelligent routing control method based on a dual-mode communication terminal is executed by a processor, it implements the steps of the intelligent routing control method based on a dual-mode communication terminal as described in any of the preceding claims.

[0049] As can be seen from the above, the intelligent routing control method, system and medium based on dual-mode communication terminals provided in this application select the communication mode according to the self-organizing network status flag bit, and then evaluate the communication link according to the communication quality and node load in the self-organizing network communication mode to obtain the optimal link in the self-organizing network mode. In the low-orbit satellite communication mode, the target channel is selected according to the channel monitoring data of the low-orbit satellite and traffic is allocated to the target channel, so as to realize the technology of autonomous communication mode switching, intelligent path selection and traffic allocation of dual-mode communication terminals.

[0050] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing embodiments of this application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart illustrating the intelligent routing control method based on a dual-mode communication terminal provided in this application embodiment;

[0053] Figure 2 A flowchart illustrating the determination of the target link in the intelligent routing control method based on a dual-mode communication terminal provided in this application embodiment;

[0054] Figure 3 A flowchart illustrating the determination of the target channel in the intelligent routing control method based on a dual-mode communication terminal provided in this application embodiment;

[0055] Figure 4 This is a flowchart illustrating the generation of traffic prediction data in the intelligent routing control method based on a dual-mode communication terminal provided in this application embodiment. Detailed Implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0057] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0058] Please refer to Figure 1 , Figure 1This is a flowchart of an intelligent routing control method based on a dual-mode communication terminal according to some embodiments of this application. This intelligent routing control method based on a dual-mode communication terminal is used in terminal devices, such as computers and mobile phones. The intelligent routing control method based on a dual-mode communication terminal includes the following steps:

[0059] S11. Obtain the self-organizing network status flag bit of the dual-mode communication terminal, and compare the self-organizing network status flag bit with the preset self-organizing network status flag bit setting value.

[0060] S12. If the self-organizing network status flags are consistent, then obtain the communication quality monitoring data and node load data of each communication link in the self-organizing network, and obtain the node load impact factor based on the node load data.

[0061] S13. Obtain the link status evaluation index based on the communication quality monitoring data and the node load impact factor, and determine the target link for service data transmission;

[0062] S14. If the self-organizing network status flags are inconsistent, obtain the channel monitoring data corresponding to each channel of the low-orbit satellite and determine the target channel.

[0063] S15. Input the acquired real-time monitoring data of the dual-mode communication terminal and the real-time network congestion data of the target channel into the trained traffic prediction model to generate traffic prediction data. Based on the traffic prediction data, allocate traffic to the target channel and transmit service data.

[0064] It should be noted that, firstly, the communication mode is selected based on the self-organizing network status flag. The self-organizing network status flag indicates the network connection status between the dual-mode communication terminal and the self-organizing network. If the self-organizing network status flag does not match the set value, it means that the dual-mode communication terminal has left the self-organizing network and is using low-Earth orbit satellite communication. If the flag matches, it means that the dual-mode communication terminal is within the self-organizing network and can use self-organizing network communication. In the self-organizing network communication mode, the communication link is evaluated based on communication quality and node load to obtain the optimal link in the self-organizing network mode. In the low-Earth orbit satellite communication mode, the target channel is selected based on the channel monitoring data of the low-Earth orbit satellite and traffic is allocated to the target channel to realize the technology of autonomous communication mode switching, intelligent path selection and traffic allocation of the dual-mode communication terminal.

[0065] According to an embodiment of the present invention, if the self-organizing network status flag bits are consistent, then the communication quality monitoring data and node load data of each communication link in the self-organizing network are obtained, and the node load impact factor is obtained by processing the node load data, including:

[0066] The communication quality monitoring data includes transmission rate, packet loss rate, communication latency, and bandwidth utilization.

[0067] The node load data includes data transmission volume, CPU utilization, and memory usage.

[0068] The node load impact factor is obtained by processing the data transfer volume, CPU utilization, and memory usage.

[0069] It should be noted that in this embodiment, if the self-organizing network status flag bit matches the preset self-organizing network status flag bit setting value, it indicates that the dual-mode communication terminal is located within the self-organizing network and can utilize the self-organizing network for communication. In order to evaluate the communication link based on the link communication quality and node load of the self-organizing network, it is necessary to obtain communication quality monitoring data and node load data, and process the node load impact factor based on data transmission volume, CPU utilization, and memory usage.

[0070] The formula for calculating the node load impact factor is as follows:

[0071]

[0072] Where, r s y is the node load impact factor. p u r and c q These represent data transmission volume, CPU utilization, and memory usage, respectively. α, β1, and β2 are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0073] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating the determination of a target link in an intelligent routing control method based on a dual-mode communication terminal, as described in some embodiments of this application. According to an embodiment of the present invention, the step of obtaining a link status evaluation index based on the communication quality monitoring data and the node load impact factor, and determining the target link for service data transmission, includes:

[0074] S21. Process the data based on the transmission rate, packet loss rate, communication delay time, bandwidth utilization, and node load impact factor to obtain the link status evaluation index.

[0075] S22. Sort the link status evaluation index corresponding to each link and select the link with the largest link status evaluation index as the target link.

[0076] S23. The dual-mode communication terminal sends service data to the target communication terminal through the target link.

[0077] It should be noted that the link status is evaluated based on communication quality monitoring data to obtain the link status evaluation index;

[0078] The formula for calculating the link state assessment index is as follows:

[0079]

[0080] Among them, w h v is the link state assessment index. a l t t h b h and r s These are transmission rate, packet loss rate, communication latency, bandwidth utilization, and node load impact factors, respectively. χ, δ, λ1, λ2, and λ3 are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0081] Please refer to Figure 3 , Figure 3 This is a flowchart illustrating the determination of a target channel in an intelligent routing control method based on a dual-mode communication terminal, as described in some embodiments of this application. According to an embodiment of the present invention, the step of obtaining channel monitoring data corresponding to each channel of a low-Earth orbit satellite and determining the target channel if the self-organizing network status flag comparison is inconsistent includes:

[0082] S31. If the self-organizing network status flags are inconsistent, obtain the channel monitoring data corresponding to each channel of the low-orbit satellite.

[0083] S32, The channel monitoring data includes signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate;

[0084] S33. Based on the signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate, obtain the channel state evaluation index corresponding to each channel;

[0085] S34. Compare the channel state evaluation index with a preset channel state evaluation index threshold, and take the channel corresponding to the channel state evaluation index that meets the preset threshold comparison requirements as the target channel.

[0086] It should be noted that in this embodiment, if the self-organizing network status flag bit does not match the preset self-organizing network status flag bit setting value, it indicates that the dual-mode communication terminal is outside the self-organizing network range and needs to utilize low-Earth orbit satellite communication. Channel status assessment is performed based on signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate. Channel occupancy rate refers to the ratio of the amount of data transmitted in the channel to the total channel capacity. The formula for calculating the channel status assessment index is:

[0087]

[0088] Among them, w x s is the channel state assessment index. h n r de and p r These are signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate, respectively. ε1 and ε2 are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0089] Please refer to Figure 4 , Figure 4 This is a flowchart illustrating the generation of traffic prediction data in an intelligent routing control method based on a dual-mode communication terminal, as described in some embodiments of this application. According to embodiments of the present invention, the step of inputting acquired real-time monitoring data of the dual-mode communication terminal and real-time network congestion data of the target channel into a trained traffic prediction model for processing to generate traffic prediction data, allocating traffic to the target channel based on the traffic prediction data, and transmitting service data includes:

[0090] S41. Obtain historical traffic data of the target channel and its corresponding terminal communication behavior data and historical network congestion data;

[0091] S42. The historical network congestion data includes historical transmission rate, historical signal strength data, historical network congestion time data, and historical network congestion degree data; the terminal communication behavior data includes access type data, access time data, and terminal location data.

[0092] S43. Based on the historical traffic data, combined with the historical transmission rate, historical signal strength data, historical network congestion time data, historical network congestion degree data, as well as the access type data, access time data, and terminal location data, a model is trained to generate a traffic prediction model.

[0093] S44. Obtain real-time monitoring data of the dual-mode communication terminal and real-time network congestion data of the target channel. The real-time monitoring data of the dual-mode communication terminal includes real-time access type data, real-time access time data and real-time terminal location data. The real-time network congestion data of the target channel includes real-time signal strength data, real-time transmission rate data, real-time network congestion time data and real-time network congestion degree data.

[0094] S45. Input the real-time access type data, real-time access time data, terminal real-time location data, real-time signal strength data, real-time transmission rate data, real-time network congestion time data, and real-time network congestion degree data into the traffic prediction model for processing to obtain traffic prediction data.

[0095] S46. Allocate traffic to the target channel based on the traffic prediction data, and send the service data to the target communication terminal.

[0096] It should be noted that, in order to allocate resources reasonably to the target channel, a traffic prediction model is trained and generated based on the historical traffic data of the target channel, its corresponding terminal communication behavior data, and historical network congestion data, and traffic prediction is performed based on the traffic prediction model.

[0097] According to an embodiment of the present invention, it further includes:

[0098] The link failure assessment index is obtained by processing the link status assessment index of each communication link in the self-organizing network.

[0099] The channel fault assessment index is obtained by processing the channel state assessment index of each channel of the low-Earth orbit satellite.

[0100] It should be noted that the link failure assessment index is obtained by processing the link status assessment index of each communication link in the ad hoc network.

[0101] The formula for calculating the link failure assessment index is as follows:

[0102]

[0103] Where, k v The link failure assessment index is i = 1, ..., n, where n represents the number of communication links, and w hi Let ξ be the link state evaluation index corresponding to the i-th communication link. i These are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform);

[0104] The channel fault assessment index is obtained by processing the channel state assessment index of each channel of the low-orbit satellite.

[0105]

[0106] Where, k s The channel fault assessment index is denoted as j = 1, ..., m, where m represents the number of low-Earth orbit satellite channels, and w xj Let ψ be the channel state evaluation index corresponding to the j-th channel. j These are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0107] According to an embodiment of the present invention, it further includes:

[0108] The link failure assessment index is compared with a preset link failure assessment index threshold to obtain a link failure assessment threshold comparison result. The channel failure assessment index is compared with a preset channel failure assessment index threshold to obtain a channel failure assessment threshold comparison result.

[0109] If the comparison result of the link failure assessment threshold or the channel failure assessment threshold does not meet the requirements of the preset threshold comparison result, the self-organizing network status flag bit will be compared with the preset self-organizing network status flag bit setting value, and the self-organizing network status flag bit update will be determined based on the comparison result.

[0110] If neither the link fault assessment threshold comparison result nor the channel fault assessment threshold comparison result meets the preset threshold comparison result requirements, a fault alarm will be issued.

[0111] It should be noted that in this embodiment, if the link failure assessment threshold comparison result does not meet the preset threshold comparison result requirement, but the channel failure assessment threshold comparison result does meet the preset threshold comparison result requirement, it indicates that the ad hoc network has experienced a communication failure. In this case, the ad hoc network status flag is compared with the preset ad hoc network status flag value. If the comparison is consistent, it indicates that the ad hoc network is currently in a communication state and the ad hoc network status flag needs to be updated, using low-Earth orbit satellite communication. If the channel failure assessment threshold comparison result does not meet the preset threshold comparison result requirement, but the link failure assessment threshold comparison result does meet the preset threshold comparison result requirement, it indicates that the low-Earth orbit satellite has experienced a communication failure. In this case, the ad hoc network status flag is compared with the preset ad hoc network status flag value. If the comparison is inconsistent, it indicates that the ad hoc network is currently in a low-Earth orbit satellite communication state and the ad hoc network status flag is updated. The specific implementation is as follows:

[0112] If the comparison result of the link failure assessment threshold does not meet the requirements of the preset threshold comparison result, but the comparison result of the channel failure assessment threshold meets the requirements of the preset threshold comparison result, then the self-organizing network status flag bit is compared with the preset self-organizing network status flag bit setting value. If the comparison is consistent, the self-organizing network status flag bit is updated; if the comparison is inconsistent, no action is taken.

[0113] If the comparison result of the channel fault assessment threshold does not meet the requirements of the preset threshold comparison result, but the comparison result of the link fault assessment threshold meets the requirements of the preset threshold comparison result, then the self-organizing network status flag bit is compared with the preset self-organizing network status flag bit setting value. If the comparison is inconsistent, the self-organizing network status flag bit is updated; if the comparison is consistent, no action is taken.

[0114] It is worth mentioning that, according to embodiments of the present invention, it further includes:

[0115] The dual-mode communication terminal was subjected to performance testing to obtain performance test data, including dual-mode switching time data, dual-mode switching success rate data, environmental adaptability data, and communication security data.

[0116] The performance evaluation index is obtained by processing the dual-mode switching time data, dual-mode switching success rate data, environmental adaptability data, and communication security data.

[0117] The performance evaluation index is compared with a preset performance evaluation index threshold. If the threshold comparison result does not meet the preset threshold comparison result requirements, a performance anomaly alert is issued to the dual-mode communication terminal.

[0118] It should be noted that performance abnormalities in dual-mode communication terminals can affect the control effect of intelligent routers. Therefore, by processing data related to dual-mode switching, environmental adaptability, and communication security, a performance evaluation index is obtained. Among them, environmental adaptability data refers to the data used to measure the terminal's ability to work normally in various physical environments and usage scenarios, while communication security data is used to evaluate the security of data transmission in the two communication modes.

[0119] The formula for calculating the performance evaluation index is as follows:

[0120]

[0121] Where, σ v g is a performance evaluation index. u i w a k t s These are data on dual-mode handover success rate, environmental adaptability, communication security, and dual-mode handover time, respectively, μ1, μ2, μ3, and... These are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0122] This invention also discloses an intelligent routing control system based on a dual-mode communication terminal, including a memory and a processor. The memory stores a program for an intelligent routing control method based on the dual-mode communication terminal. When the processor executes the program for the intelligent routing control method based on the dual-mode communication terminal, it performs the following steps:

[0123] Obtain the self-organizing network status flag bit of the dual-mode communication terminal and compare the self-organizing network status flag bit with the preset self-organizing network status flag bit setting value;

[0124] If the self-organizing network status flags match, then obtain the communication quality monitoring data and node load data of each communication link in the self-organizing network, and process the node load data to obtain the node load impact factor.

[0125] Based on the communication quality monitoring data and the node load impact factor processing, a link status evaluation index is obtained, and a target link is determined for service data transmission.

[0126] If the self-organizing network status flags are inconsistent, then obtain the channel monitoring data corresponding to each channel of the low-Earth orbit satellite and determine the target channel;

[0127] The acquired real-time monitoring data of dual-mode communication terminals and real-time network congestion data of the target channel are input into the trained traffic prediction model to generate traffic prediction data. Based on the traffic prediction data, traffic is allocated to the target channel and service data is transmitted.

[0128] It should be noted that, firstly, the communication mode is selected based on the self-organizing network status flag. The self-organizing network status flag indicates the network connection status between the dual-mode communication terminal and the self-organizing network. If the self-organizing network status flag does not match the set value, it means that the dual-mode communication terminal has left the self-organizing network and is using low-Earth orbit satellite communication. If the flag matches, it means that the dual-mode communication terminal is within the self-organizing network and can use self-organizing network communication. In the self-organizing network communication mode, the communication link is evaluated based on communication quality and node load to obtain the optimal link in the self-organizing network mode. In the low-Earth orbit satellite communication mode, the target channel is selected based on the channel monitoring data of the low-Earth orbit satellite and traffic is allocated to the target channel to realize the technology of autonomous communication mode switching, intelligent path selection and traffic allocation of the dual-mode communication terminal.

[0129] According to an embodiment of the present invention, if the self-organizing network status flag bits are consistent, then the communication quality monitoring data and node load data of each communication link in the self-organizing network are obtained, and the node load impact factor is obtained by processing the node load data, including:

[0130] The communication quality monitoring data includes transmission rate, packet loss rate, communication latency, and bandwidth utilization.

[0131] The node load data includes data transmission volume, CPU utilization, and memory usage.

[0132] The node load impact factor is obtained by processing the data transfer volume, CPU utilization, and memory usage.

[0133] It should be noted that in this embodiment, if the self-organizing network status flag bit matches the preset self-organizing network status flag bit setting value, it indicates that the dual-mode communication terminal is located within the self-organizing network and can utilize the self-organizing network for communication. In order to evaluate the communication link based on the link communication quality and node load of the self-organizing network, it is necessary to obtain communication quality monitoring data and node load data, and process the node load impact factor based on data transmission volume, CPU utilization, and memory usage.

[0134] The formula for calculating the node load impact factor is as follows:

[0135]

[0136] Where, r s y is the node load impact factor. p u r and c qThese represent data transmission volume, CPU utilization, and memory usage, respectively. α, β1, and β2 are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0137] According to an embodiment of the present invention, the step of obtaining a link state assessment index based on the communication quality monitoring data and the node load impact factor, and determining the target link for service data transmission, includes:

[0138] The link status evaluation index is obtained by processing the transmission rate, packet loss rate, communication latency, bandwidth utilization, and node load impact factor.

[0139] The link status evaluation index corresponding to each link is sorted, and the link with the largest link status evaluation index is selected as the target link.

[0140] The dual-mode communication terminal sends service data to the target communication terminal through the target link.

[0141] It should be noted that the link status is evaluated based on communication quality monitoring data to obtain the link status evaluation index;

[0142] The formula for calculating the link state assessment index is as follows:

[0143]

[0144] Among them, w h v is the link state assessment index. a l t t h b h and r s These are transmission rate, packet loss rate, communication latency, bandwidth utilization, and node load impact factors, respectively. χ, δ, λ1, λ2, and λ3 are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0145] According to an embodiment of the present invention, if the self-organizing network status flags are inconsistent, then obtaining the channel monitoring data corresponding to each channel of the low-Earth orbit satellite and determining the target channel includes:

[0146] If the self-organizing network status flags are inconsistent, then obtain the channel monitoring data corresponding to each channel of the low-Earth orbit satellite;

[0147] The channel monitoring data includes signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate;

[0148] The channel state evaluation index corresponding to each channel is obtained by processing the signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate.

[0149] The channel state evaluation index is compared with a preset channel state evaluation index threshold, and the channel corresponding to the channel state evaluation index that meets the preset threshold comparison requirements is taken as the target channel.

[0150] It should be noted that in this embodiment, if the self-organizing network status flag bit does not match the preset self-organizing network status flag bit setting value, it indicates that the dual-mode communication terminal is outside the self-organizing network range and needs to utilize low-Earth orbit satellite communication. Channel status assessment is performed based on signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate. Channel occupancy rate refers to the ratio of the amount of data transmitted in the channel to the total channel capacity. The formula for calculating the channel status assessment index is:

[0151]

[0152] Among them, w x s is the channel state assessment index. h n r d e and p r These are signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate, respectively. ε1 and ε2 are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0153] According to an embodiment of the present invention, the step of inputting the acquired real-time monitoring data of the dual-mode communication terminal and the real-time network congestion data of the target channel into a trained traffic prediction model to generate traffic prediction data, allocating traffic to the target channel based on the traffic prediction data, and transmitting service data includes:

[0154] Acquire historical traffic data of the target channel, along with its corresponding terminal communication behavior data and historical network congestion data;

[0155] The historical network congestion data includes historical transmission rate, historical signal strength data, historical network congestion time data, and historical network congestion degree data; the terminal communication behavior data includes access type data, access time data, and terminal location data.

[0156] A traffic prediction model is generated by training a model based on the historical traffic data, combined with the historical transmission rate, historical signal strength data, historical network congestion time data, historical network congestion degree data, as well as the access type data, access time data, and terminal location data.

[0157] The system acquires real-time monitoring data of dual-mode communication terminals and real-time network congestion data of the target channel. The real-time monitoring data of dual-mode communication terminals includes real-time access type data, real-time access time data, and real-time terminal location data. The real-time network congestion data of the target channel includes real-time signal strength data, real-time transmission rate data, real-time network congestion time data, and real-time network congestion degree data.

[0158] The real-time access type data, real-time access time data, terminal real-time location data, real-time signal strength data, real-time transmission rate data, real-time network congestion time data, and real-time network congestion degree data are input into the traffic prediction model for processing to obtain traffic prediction data.

[0159] Traffic is allocated to the target channel based on the traffic prediction data, and service data is sent to the target communication terminal.

[0160] It should be noted that, in order to allocate resources reasonably to the target channel, a traffic prediction model is trained and generated based on the historical traffic data of the target channel, its corresponding terminal communication behavior data, and historical network congestion data, and traffic prediction is performed based on the traffic prediction model.

[0161] According to an embodiment of the present invention, it further includes:

[0162] The link failure assessment index is obtained by processing the link status assessment index of each communication link in the self-organizing network.

[0163] The channel fault assessment index is obtained by processing the channel state assessment index of each channel of the low-Earth orbit satellite.

[0164] It should be noted that the link failure assessment index is obtained by processing the link status assessment index of each communication link in the ad hoc network.

[0165] The formula for calculating the link failure assessment index is as follows:

[0166]

[0167] Where, k v The link failure assessment index is i = 1, ..., n, where n represents the number of communication links, and w hi Let ξ be the link state evaluation index corresponding to the i-th communication link. i These are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform);

[0168] The channel fault assessment index is obtained by processing the channel state assessment index of each channel of the low-orbit satellite.

[0169]

[0170] Where, k s The channel fault assessment index is denoted as j = 1, ..., m, where m represents the number of low-Earth orbit satellite channels, and w xj Let ψ be the channel state evaluation index corresponding to the j-th channel. j These are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0171] According to an embodiment of the present invention, it further includes:

[0172] The link failure assessment index is compared with a preset link failure assessment index threshold to obtain a link failure assessment threshold comparison result. The channel failure assessment index is compared with a preset channel failure assessment index threshold to obtain a channel failure assessment threshold comparison result.

[0173] If the comparison result of the link failure assessment threshold or the channel failure assessment threshold does not meet the requirements of the preset threshold comparison result, the self-organizing network status flag bit will be compared with the preset self-organizing network status flag bit setting value, and the self-organizing network status flag bit update will be determined based on the comparison result.

[0174] If neither the link fault assessment threshold comparison result nor the channel fault assessment threshold comparison result meets the preset threshold comparison result requirements, a fault alarm will be issued.

[0175] It should be noted that in this embodiment, if the link failure assessment threshold comparison result does not meet the preset threshold comparison result requirement, but the channel failure assessment threshold comparison result does meet the preset threshold comparison result requirement, it indicates that the ad hoc network has experienced a communication failure. In this case, the ad hoc network status flag is compared with the preset ad hoc network status flag value. If the comparison is consistent, it indicates that the ad hoc network is currently in a communication state and the ad hoc network status flag needs to be updated, using low-Earth orbit satellite communication. If the channel failure assessment threshold comparison result does not meet the preset threshold comparison result requirement, but the link failure assessment threshold comparison result does meet the preset threshold comparison result requirement, it indicates that the low-Earth orbit satellite has experienced a communication failure. In this case, the ad hoc network status flag is compared with the preset ad hoc network status flag value. If the comparison is inconsistent, it indicates that the ad hoc network is currently in a low-Earth orbit satellite communication state and the ad hoc network status flag is updated. The specific implementation is as follows:

[0176] If the comparison result of the link failure assessment threshold does not meet the requirements of the preset threshold comparison result, but the comparison result of the channel failure assessment threshold meets the requirements of the preset threshold comparison result, then the self-organizing network status flag bit is compared with the preset self-organizing network status flag bit setting value. If the comparison is consistent, the self-organizing network status flag bit is updated; if the comparison is inconsistent, no action is taken.

[0177] If the comparison result of the channel fault assessment threshold does not meet the requirements of the preset threshold comparison result, but the comparison result of the link fault assessment threshold meets the requirements of the preset threshold comparison result, then the self-organizing network status flag bit is compared with the preset self-organizing network status flag bit setting value. If the comparison is inconsistent, the self-organizing network status flag bit is updated; if the comparison is consistent, no action is taken.

[0178] If neither the link fault assessment threshold comparison result nor the channel fault assessment threshold comparison result meets the preset threshold comparison result requirements, a fault alarm will be issued.

[0179] If both the link fault assessment threshold comparison result and the channel fault assessment threshold comparison result meet the preset threshold comparison result requirements, no processing is required.

[0180] It is worth mentioning that, according to embodiments of the present invention, it further includes:

[0181] The dual-mode communication terminal was subjected to performance testing to obtain performance test data, including dual-mode switching time data, dual-mode switching success rate data, environmental adaptability data, and communication security data.

[0182] The performance evaluation index is obtained by processing the dual-mode switching time data, dual-mode switching success rate data, environmental adaptability data, and communication security data.

[0183] The performance evaluation index is compared with a preset performance evaluation index threshold. If the threshold comparison result does not meet the preset threshold comparison result requirements, a performance anomaly alert is issued to the dual-mode communication terminal.

[0184] It should be noted that performance abnormalities in dual-mode communication terminals can affect the control effect of intelligent routers. Therefore, by processing data related to dual-mode switching, environmental adaptability, and communication security, a performance evaluation index is obtained. Among them, environmental adaptability data refers to the data used to measure the terminal's ability to work normally in various physical environments and usage scenarios, while communication security data is used to evaluate the security of data transmission in the two communication modes.

[0185] The formula for calculating the performance evaluation index is as follows:

[0186]

[0187] Where, σ v g is a performance evaluation index. u i w a k t s These are data on dual-mode handover success rate, environmental adaptability, communication security, and dual-mode handover time, respectively, μ1, μ2, μ3, and... These are preset characteristic coefficients (which can be obtained by querying the database of the preset dual-mode communication terminal intelligent routing control platform).

[0188] A third aspect of the present invention provides a readable storage medium storing a program for an intelligent routing control method based on a dual-mode communication terminal. When the program for the intelligent routing control method based on a dual-mode communication terminal is executed by a processor, it implements the steps of the intelligent routing control method based on a dual-mode communication terminal as described in any of the preceding claims.

[0189] The present invention discloses an intelligent routing control method, system, and medium based on a dual-mode communication terminal. The method selects the communication mode according to the self-organizing network status flag, and then evaluates the communication link according to the communication quality and node load in the self-organizing network communication mode to obtain the optimal link in the self-organizing network mode. In the low-Earth orbit satellite communication mode, the method selects the target channel according to the channel monitoring data of the low-Earth orbit satellite and allocates traffic to the target channel, so as to realize the technology of autonomous communication mode switching, intelligent path selection and traffic allocation of the dual-mode communication terminal.

[0190] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0191] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0192] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0193] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0194] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. An intelligent routing control method based on a dual-mode communication terminal, characterized in that, Includes the following steps: Obtain the self-organizing network status flag bit of the dual-mode communication terminal and compare the self-organizing network status flag bit with the preset self-organizing network status flag bit setting value; If the self-organizing network status flags match, then obtain the communication quality monitoring data and node load data of each communication link in the self-organizing network, and process the node load data to obtain the node load impact factor. Based on the communication quality monitoring data and the node load impact factor processing, a link status evaluation index is obtained, and a target link is determined for service data transmission. If the self-organizing network status flags are inconsistent, then the channel monitoring data corresponding to each channel of the low-Earth orbit satellite is obtained and the target channel is determined. Specifically, this includes: if the self-organizing network status flags are inconsistent, then the channel monitoring data corresponding to each channel of the low-Earth orbit satellite is obtained; the channel monitoring data includes signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate; based on the signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate, the channel state assessment index corresponding to each channel is obtained; the calculation formula for the channel state assessment index is: ； in, It is a channel state assessment index. , , and These are signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate, respectively. , , and These are the preset characteristic coefficients; The channel state evaluation index is compared with a preset channel state evaluation index threshold, and the channel corresponding to the channel state evaluation index that meets the preset threshold comparison requirements is taken as the target channel. The acquired real-time monitoring data of the dual-mode communication terminal and the real-time network congestion data of the target channel are input into the trained traffic prediction model to generate traffic prediction data. Based on the traffic prediction data, traffic is allocated to the target channel and service data is transmitted. The real-time monitoring data of the dual-mode communication terminal includes real-time access type data, real-time access time data and real-time terminal location data. The real-time network congestion data of the target channel includes real-time signal strength data, real-time transmission rate data, real-time network congestion time data and real-time network congestion degree data.

2. The intelligent routing control method based on a dual-mode communication terminal according to claim 1, characterized in that, If the self-organizing network status flags match, then the communication quality monitoring data and node load data of each communication link in the self-organizing network are obtained. The node load impact factor is obtained by processing the node load data, including: The communication quality monitoring data includes transmission rate, packet loss rate, communication latency, and bandwidth utilization. The node load data includes data transmission volume, CPU utilization, and memory usage. The node load impact factor is obtained by processing the data transfer volume, CPU utilization, and memory usage.

3. The intelligent routing control method based on a dual-mode communication terminal according to claim 2, characterized in that, The step of obtaining a link status assessment index based on the communication quality monitoring data and the node load impact factor, and determining the target link for service data transmission, includes: The link status evaluation index is obtained by processing the transmission rate, packet loss rate, communication latency, bandwidth utilization, and node load impact factor. The link status evaluation index corresponding to each link is sorted, and the link with the largest link status evaluation index is selected as the target link. The dual-mode communication terminal sends service data to the target communication terminal through the target link.

4. The intelligent routing control method based on a dual-mode communication terminal according to claim 3, characterized in that, The process of inputting the acquired real-time monitoring data of the dual-mode communication terminal and the real-time network congestion data of the target channel into the trained traffic prediction model to generate traffic prediction data, allocating traffic to the target channel based on the traffic prediction data, and transmitting service data includes: Acquire historical traffic data of the target channel, along with its corresponding terminal communication behavior data and historical network congestion data; The historical network congestion data includes historical transmission rate, historical signal strength data, historical network congestion time data, and historical network congestion degree data; the terminal communication behavior data includes access type data, access time data, and terminal location data. A traffic prediction model is generated by training a model based on the historical traffic data, combined with the historical transmission rate, historical signal strength data, historical network congestion time data, historical network congestion degree data, as well as the access type data, access time data, and terminal location data. The system acquires real-time monitoring data of dual-mode communication terminals and real-time network congestion data of the target channel. The real-time monitoring data of dual-mode communication terminals includes real-time access type data, real-time access time data, and real-time terminal location data. The real-time network congestion data of the target channel includes real-time signal strength data, real-time transmission rate data, real-time network congestion time data, and real-time network congestion degree data. The real-time access type data, real-time access time data, terminal real-time location data, real-time signal strength data, real-time transmission rate data, real-time network congestion time data, and real-time network congestion degree data are input into the traffic prediction model for processing to obtain traffic prediction data. Traffic is allocated to the target channel based on the traffic prediction data, and service data is sent to the target communication terminal.

5. The intelligent routing control method based on a dual-mode communication terminal according to claim 4, characterized in that, Also includes: The link failure assessment index is obtained by processing the link status assessment index of each communication link in the self-organizing network. The channel fault assessment index is obtained by processing the channel state assessment index of each channel of the low-Earth orbit satellite.

6. The intelligent routing control method based on a dual-mode communication terminal according to claim 5, characterized in that, Also includes: The link failure assessment index is compared with a preset link failure assessment index threshold to obtain a link failure assessment threshold comparison result. The channel failure assessment index is compared with a preset channel failure assessment index threshold to obtain a channel failure assessment threshold comparison result. If the comparison result of the link failure assessment threshold or the channel failure assessment threshold does not meet the requirements of the preset threshold comparison result, the self-organizing network status flag bit will be compared with the preset self-organizing network status flag bit setting value, and the self-organizing network status flag bit update will be determined based on the comparison result. If neither the link fault assessment threshold comparison result nor the channel fault assessment threshold comparison result meets the preset threshold comparison result requirements, a fault alarm will be issued.

7. An intelligent routing control system based on a dual-mode communication terminal, characterized in that, The system includes a memory and a processor. The memory stores a program for an intelligent routing control method based on a dual-mode communication terminal. When the processor executes the program for the intelligent routing control method based on the dual-mode communication terminal, it performs the following steps: Obtain the self-organizing network status flag bit of the dual-mode communication terminal and compare the self-organizing network status flag bit with the preset self-organizing network status flag bit setting value; If the self-organizing network status flags match, then obtain the communication quality monitoring data and node load data of each communication link in the self-organizing network, and process the node load data to obtain the node load impact factor. Based on the communication quality monitoring data and the node load impact factor processing, a link status evaluation index is obtained, and a target link is determined for service data transmission. If the self-organizing network status flags are inconsistent, then the channel monitoring data corresponding to each channel of the low-Earth orbit satellite is obtained and the target channel is determined. Specifically, this includes: if the self-organizing network status flags are inconsistent, then the channel monitoring data corresponding to each channel of the low-Earth orbit satellite is obtained; the channel monitoring data includes signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate; based on the signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate, the channel state assessment index corresponding to each channel is obtained; the calculation formula for the channel state assessment index is: ； in, It is a channel state assessment index. , , and These are signal strength data, signal-to-noise ratio data, bit error rate, and channel occupancy rate, respectively. , and These are the preset characteristic coefficients; The channel state evaluation index is compared with a preset channel state evaluation index threshold, and the channel corresponding to the channel state evaluation index that meets the preset threshold comparison requirements is taken as the target channel. The acquired real-time monitoring data of the dual-mode communication terminal and the real-time network congestion data of the target channel are input into the trained traffic prediction model to generate traffic prediction data. Based on the traffic prediction data, traffic is allocated to the target channel and service data is transmitted. The real-time monitoring data of the dual-mode communication terminal includes real-time access type data, real-time access time data and real-time terminal location data. The real-time network congestion data of the target channel includes real-time signal strength data, real-time transmission rate data, real-time network congestion time data and real-time network congestion degree data.

8. The intelligent routing control system based on a dual-mode communication terminal according to claim 7, characterized in that, If the self-organizing network status flags match, then the communication quality monitoring data and node load data of each communication link in the self-organizing network are obtained. The node load impact factor is obtained by processing the node load data, including: The communication quality monitoring data includes transmission rate, packet loss rate, communication latency, and bandwidth utilization. The node load data includes data transmission volume, CPU utilization, and memory usage. The node load impact factor is obtained by processing the data transfer volume, CPU utilization, and memory usage.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an intelligent routing control program based on a dual-mode communication terminal. When the intelligent routing control program based on the dual-mode communication terminal is executed by a processor, it implements the steps of the intelligent routing control method based on a dual-mode communication terminal as described in any one of claims 1 to 6.

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