Safe, efficient and dynamic UANETs data transmission method

Abstract

The invention discloses a safe, efficient and dynamic UANETs data transmission method, and relates to the technical field of data transmission. The method comprises the following steps: firstly, acquiring and analyzing state information of each communication node of an unmanned aerial vehicle in a UANETs network so as to evaluate the stability of the communication node; thirdly, clustering the unmanned aerial vehicle based on the state stability evaluation value, selecting a cluster head, and further distributing a broadcast frequency; and finally, the data transmission process of each unmanned aerial vehicle cluster is monitored and analyzed, clustering is dynamically adjusted according to an evaluation result, and flexible adjustment of clustering and optimal selection of cluster heads are realized, so that the data transmission efficiency and safety are effectively improved, the data transmission process is continuously monitored and analyzed, the stability and reliability of the UANETs network are enhanced, and the data transmission efficiency is improved. Therefore, the efficiency and quality of data transmission are improved, and powerful support is provided for autonomous management and intelligent optimization of an unmanned aerial vehicle network.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, in particular to a safe, efficient and dynamic UANETs data transmission method. Background Art

[0002] With the increasing popularity of distributed systems and microservice architectures, we combine data collection on non-trusted ends with the efficiency and reliability of the NATS messaging system, and implement strict encryption technology, authentication and authorization mechanisms, as well as dynamic configuration and expansion capabilities to achieve secure, efficient, and dynamic data transmission in complex network environments, in order to meet the high requirements of data transmission performance and security in different application scenarios.

[0003] For example, the invention patent with announcement number CN108307448B announces a data transmission method and device, which includes: when the air interface supports multiple connections, a mapping relationship is established between the uplink and downlink PDU flows and one or more air interface RB bearers, and in the downlink direction, the main base station can dynamically select the transmission path of the data packet of the downlink PDU flow; in the uplink direction, the UE can dynamically select the air interface RB bearer for transmitting the data packet of the uplink PDU flow, and the main base station can control certain PDU flows to be transmitted only through the air interface RB bearer of a specific main base station or secondary base station, thereby solving the QoS and user plane data transmission in the case of 5G multiple connections.

[0004] For example, the invention patent with announcement number CN102316516B announces a method for constructing an LTE uplink data transmission structure, which adds a PDCP SDU cache at the packet data convergence protocol layer to store PDCP SDU IP packet pointers transmitted from higher layers that have not yet been converted into PDCP PDUs; at the radio link control layer, the RLC SDU cache is deleted and only the RLC PDU cache is retained. The RLC PDU cache stores RLC PDUs to be confirmed, and the data assembled into the RLC PDU is obtained from the PDCP PDU cache.

[0005] Based on the above findings, the existing technical solutions may have the problem of unstable status of each communication node of the drone, which may lead to the leakage of privacy data, data destruction, communication interference and failure of drone mission execution. Summary of the invention

[0006] In view of the deficiencies of the prior art, the present invention provides a safe, efficient and dynamic UANETs data transmission method, which solves the problems designed in the above-mentioned background technology.

[0007] To achieve the above object, the present invention is realized through the following technical solutions: A secure, efficient and dynamic UANETs data transmission method, including obtaining the status information of each communication node of the drones in the UANETs network, and analyzing the status information of each communication node of the drones to obtain the status stability evaluation value of each communication node of the drones.

[0008] According to the status stability evaluation value of each communication node of the drones, cluster each communication node of the drones in the UANETs network to obtain each drone cluster of the UANETs network, and screen the cluster heads of each drone cluster of the UANETs network, and adjust the broadcast frequency of the drones in the UANETs network.

[0009] Monitor and analyze the data transmission process of the cluster heads of each drone cluster of the UANETs network and each communication node of the drones to obtain the data transmission evaluation value of each drone cluster of the UANETs network, and adjust the clustering of each communication node of the drones in the UANETs network according to the data transmission evaluation value of each drone cluster of the UANETs network.

[0010] Further, the status information of each communication node of the drones includes: the signal strength of each communication node, the number of times of role change of each communication node, the packet loss rate of each communication node, and the interference power of each communication node.

[0011] Further, extract the interference power, the signal strength, the number of times of role change, and the packet loss rate of each communication node of the drones, and process to obtain the status stability evaluation value of each communication node of the drones, and the status stability evaluation value of each communication node of the drones is used to evaluate the communication stability of the drones.

[0012] Extract the status stability evaluation value of each communication node of the drones and compare it with the status stability evaluation value threshold of the communication nodes in the database. If the status stability evaluation value of a certain communication node of the drones is higher than or equal to the status stability evaluation value threshold of the communication nodes in the database, continuously monitor the status information of each communication node of the drones; if the status stability evaluation value of a certain communication node of the drones is lower than the status stability evaluation value threshold of the communication nodes in the database, adjust the communication frequency of the communication node of the drones.

[0013] Further, extract the status stability evaluation value of each communication node of the drones, and compare it with the status stability evaluation threshold of each communication node of the drones stored in the database. If the status stability evaluation value of a certain communication node of the drones is higher than or equal to the status stability evaluation threshold of each communication node of the drones, mark the communication node of the drones as a candidate cluster head, and thus obtain each candidate cluster head, and divide each drone cluster according to the preset number limit of drones within the cluster.

[0014] Furthermore, the cluster head information of each candidate cluster head is broadcast to each neighboring node, and each neighboring node receives and analyzes the cluster head information of each candidate cluster head, wherein the cluster head information of each candidate cluster head includes the remaining total energy, communication delay, and bandwidth, and is combined with the state stability evaluation value of each candidate cluster head of the UAV, and the state evaluation value of each candidate cluster head of each neighboring node is obtained by processing, and the state evaluation values ​​of each candidate cluster head of each neighboring node are sorted, and the candidate cluster head node ranked first in each UAV cluster is selected as the cluster head of each neighboring node, thereby obtaining the cluster head of each UAV cluster in the UANETs network.

[0015] Furthermore, each monitoring time period is preset, and the number of drones in each drone cluster is counted during each monitoring time period, and the energy efficiency and moving distance of each drone are monitored. The moving distance of each drone in each drone cluster and the energy efficiency of each drone are averaged respectively to obtain the average moving distance of the drones in each drone cluster and the average energy efficiency of the drones. Combined with the number of drones in each drone cluster, the broadcast stability value of each drone cluster of the UANETs network in each monitoring time period is obtained.

[0016] The broadcast stability value of each drone cluster in the UANETs network in each monitoring time period is compared with the broadcast stability threshold stored in the database. If the broadcast stability value of a drone cluster in a certain monitoring time period is higher than or equal to the broadcast stability threshold stored in the database, it means that the broadcast frequency of the drone cluster does not need to be adjusted. If the broadcast stability value of a drone cluster in a certain monitoring time period is lower than the broadcast stability threshold stored in the database, the broadcast frequency of the drone cluster is adjusted and allocated.

[0017] Furthermore, during each monitoring time period, the data transmission process of each communication node in each drone cluster of the UANETs network is monitored and analyzed to obtain the communication data of each communication node in each drone cluster of the UANETs network. The communication data of each communication node in each drone cluster of the UANETs network includes: data transmission rate and retransmission rate.

[0018] Furthermore, the data transmission rate and retransmission rate of each communication node of each drone cluster of the UANETs network are extracted, and the broadcast stability value of each drone cluster of the UANETs network in each monitoring time period and the state evaluation value of each communication node in each drone cluster are combined to obtain the data transmission evaluation value of each drone cluster of the UANETs network. The data transmission evaluation value of each drone cluster of the UANETs network is used to evaluate the network stability of each drone cluster.

[0019] Furthermore, the data transmission evaluation value of each drone cluster of the UANETs network is extracted and matched with the network stability of the drone cluster corresponding to each interval of the data transmission evaluation value stored in the database to obtain the network stability of each drone cluster, and the network stability of the drone cluster includes: highly stable, moderately stable, and generally stable.

[0020] The network stability of each drone cluster in the UANETs network is extracted. When the network stability of a drone cluster is highly stable, the data transmission process of the communication nodes in the drone cluster is continuously monitored and analyzed.

[0021] When the network stability of a certain drone cluster is moderately stable or generally stable, the number of communication nodes in the drone cluster is adjusted and the cluster head is re-elected.

[0022] Furthermore, the data transmission evaluation value of each drone cluster in the UANETs network is analyzed as follows: ; In the formula, represents the data transmission evaluation value of the i-th UAV cluster in the UANETs network, represents the broadcast stability value of the ith drone cluster in the qth monitoring period, Indicates the xth candidate cluster head status evaluation value of the sth neighbor node represents the data transmission rate of the jth communication node of the i-th UAV cluster represents the retransmission rate of the jth communication node of the i-th UAV cluster, Indicates the reference value of the data transmission rate of the communication node to be set. It represents the maximum permissible value of the retransmission rate of the communication node, e is a natural constant, Indicates the weight factor corresponding to the broadcast stability value of the set drone cluster, Indicates the weight factor corresponding to the set data transmission rate Indicates the weight factor corresponding to the set retransmission rate, represents the weight factor corresponding to the set candidate cluster head state evaluation value, i represents the number of each drone cluster, , m represents the total number of drone clusters, j represents the number of each communication node, , n represents the total number of communication nodes, q represents the number of each monitoring time period, , r represents the total number of monitoring time periods, s represents the number of each neighbor node, , p represents the total number of neighbor nodes, x represents the number of each candidate cluster head, , y represents the total number of candidate cluster heads.

[0023] The present invention has the following beneficial effects: (1) The present invention obtains and analyzes the status information of each communication node of the UAV in the UANETs network to evaluate its stability; then, the UAVs are clustered and the cluster heads are selected based on the status stability evaluation value, and then the broadcast frequency is allocated; finally, the data transmission process of each UAV cluster is monitored and analyzed, and the clustering is dynamically adjusted according to the evaluation results. By realizing the flexible adjustment of clustering and the optimal selection of cluster heads, the efficiency and security of data transmission are effectively improved. The continuous monitoring and analysis of the data transmission process is helpful to enhance the stability and reliability of the UANETs network, thereby improving the efficiency and quality of data transmission, and also provides strong support for the autonomous management and intelligent optimization of the UAV network; (2) The present invention obtains the state stability evaluation value of each communication node of the drone by extracting and processing the interference power, signal strength, number of role changes and packet loss rate of each communication node of the drone, evaluates its state stability, and compares it with the threshold in the database to adjust the communication frequency of the unstable node; at the same time, the candidate cluster head is selected according to the state stability evaluation value, and the drone nodes are organized to form a cluster network; (3) The present invention receives and analyzes the remaining total energy, communication delay, and bandwidth of candidate cluster heads through each neighbor node, evaluates and sorts the candidate cluster heads in combination with the state stability evaluation value, selects the best one as the cluster head, and forms a UAV cluster structure of the UANETs network. By dynamically selecting the best node as the cluster head, the reliability and efficiency of data transmission are significantly improved, and resource allocation is optimized, ensuring the security, efficiency, and dynamic adaptability of the UANETs data transmission network; (4) The present invention presets each monitoring time period, counts the number of drones in the drone cluster, monitors the energy efficiency and moving distance in each cluster, calculates the average moving distance, combines the number of drones and the energy efficiency to obtain the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period, and compares it with the broadcast stability threshold value, and adjusts the broadcast frequency adjustment allocation of the drone cluster according to the result; (5) The present invention monitors the data transmission process of the communication nodes of each drone cluster in the UANETs network, combines the data transmission rate and retransmission rate of each communication node, and combines the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period with the status evaluation value of each communication node in each drone cluster, obtains the data transmission evaluation value of each drone cluster in the UANETs network to evaluate the network stability, and takes corresponding monitoring or adjustment measures according to the network stability.

[0024] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 This is the average moving distance of the drone of the present invention-the broadcast stability value change curve of the drone cluster of the UANETs network. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inside", "all around" and the like indicating orientation or positional relationship are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0028] See also Figure 1 The embodiment of the present invention provides a technical solution: a safe, efficient and dynamic UANETs data transmission method, comprising obtaining the status information of each communication node of a UAV in the UANETs network, and analyzing the status information of each communication node of the UAV to obtain a status stability evaluation value of each communication node of the UAV.

[0029] According to the status stability evaluation value of each drone communication node, the drone communication nodes in the UANETs network are clustered to obtain the drone clusters of the UANETs network, and the cluster heads of each drone cluster of the UANETs network are screened to adjust the broadcast frequency of the drones in the UANETs network.

[0030] The data transmission process of the cluster head of each UAV cluster and each communication node of the UAV in the UANETs network is monitored and analyzed to obtain the data transmission evaluation value of each UAV cluster in the UANETs network. According to the data transmission evaluation value of each UAV cluster in the UANETs network, the clustering of each communication node of the UAV in the UANETs network is adjusted.

[0031] It should be noted that the status information of each communication node of the UAV in the UANETs (Unmanned Aircraft Networked and Autonomous Tactical System) network is obtained and analyzed to evaluate its stability; then, the UAVs are clustered and the cluster heads are selected based on the state stability evaluation value, and then the broadcast frequency is allocated; finally, the data transmission process of each UAV cluster is monitored and analyzed, and the clustering is dynamically adjusted according to the evaluation results. By realizing the flexible adjustment of clustering and the optimal selection of cluster heads, the efficiency and security of data transmission are effectively improved, which provides strong support for the autonomous management and intelligent optimization of the UAV network.

[0032] Specifically, the status information of each communication node of the drone includes: the signal strength of each communication node, the number of role changes of each communication node, the packet loss rate of each communication node, and the interference power of each communication node.

[0033] It should be noted that a wireless signal detector is used to detect the signal strength of each communication node of the drone; the number of role changes of each communication node refers to the number of times the role of each communication node changes during the execution of the task in the UANETs network, and the number of role status changes of the communication node is recorded through the status log of the drone communication node; network testing tools (such as ping, traceroute, etc.) can be used to detect the loss of data packets during transmission, so as to obtain the packet loss rate; a power meter is used to measure the power of the received interference signal.

[0034] Specifically, the interference power of each communication node of the drone, the signal strength of each communication node, the number of role changes of each communication node, and the packet loss rate of each communication node are extracted, and the state stability evaluation value of each communication node of the drone is obtained by processing. The state stability evaluation value of each communication node of the drone is used to evaluate the communication stability of the drone.

[0035] The state stability evaluation value of each communication node of the UAV is extracted and compared with the state stability evaluation value threshold of the communication node in the database. If the state stability evaluation value of a communication node of the UAV is higher than or equal to the state stability evaluation value threshold of the communication node in the database, the state information of each communication node of the UAV is continuously monitored; if the state stability evaluation value of a communication node of the UAV is lower than the state stability evaluation value threshold of the communication node in the database, the communication frequency of the communication node of the UAV is adjusted.

[0036] It should be noted that the specific analysis process of the state stability evaluation value of each communication node of the drone is as follows: ; In the formula, represents the state stability evaluation value of the jth communication node of the UAV, represents the interference power of the jth communication node of the UAV, represents the signal strength of the jth communication node of the UAV, represents the number of times the jth communication node role of the drone changes, represents the packet loss rate of the jth communication node of the drone, Indicates the interference power reference value of the set communication node, Indicates the signal strength reference value of the set communication node, Indicates the reference value of the number of communication node role changes. Indicates the reference value of the packet loss rate of the set communication node. Indicates the correction factor corresponding to the interference power of the set communication node, Indicates the correction factor corresponding to the signal strength of the set communication node, Indicates the correction factor corresponding to the number of communication node role changes. represents the correction factor corresponding to the packet loss rate of the set communication node, j represents the number of each communication node, , n represents the total number of communication nodes.

[0037] It should be noted that there is a correlation between the interference power of each communication node of the drone, the signal strength of each communication node, the number of role changes of each communication node, and the packet loss rate of each communication node. The greater the interference power, the stronger the signal interference to the drone communication node, resulting in reduced signal strength; frequent role changes will cause a burden on the communication node, thereby affecting the stability of its signal strength; larger interference power may cause the communication link between communication nodes to be unstable, requiring nodes to change roles frequently, resulting in an increase in the number of node role changes; an increase in interference power will lead to instability of the communication link, thereby increasing the packet loss rate. It can be seen that the state stability evaluation value of each communication node of the drone is obtained by jointly processing the interference power of each communication node of the drone, the signal strength of each communication node, the number of role changes of each communication node, and the packet loss rate of each communication node; It is the correction factor corresponding to the interference power of the communication node preset in the database, which represents the numerical value of the influence of the interference power of the communication node on the state stability evaluation value of each communication node of the UAV. When used, the correction factor corresponding to the interference power of the communication node can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the interference power of the communication node and the correction factor corresponding to the interference power of the communication node preset in the database form a mapping set, and the real-time interference power of the communication node is input into the mapping set to obtain the correction factor corresponding to the interference power of the communication node. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; It is the correction factor corresponding to the signal strength of the communication node preset in the database, which represents the numerical value of the influence of the signal strength of the communication node on the state stability evaluation value of each communication node of the drone. When used, the correction factor corresponding to the signal strength of the communication node can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the signal strength of the communication node and the correction factor corresponding to the signal strength of the communication node preset in the database form a mapping set, and the real-time signal strength of the communication node is input into the mapping set to obtain the correction factor corresponding to the signal strength of the communication node. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; It is the correction factor corresponding to the number of communication node role changes preset in the database, which represents the numerical value of the influence of the number of communication node role changes on the state stability evaluation value of each communication node of the drone. When used, the correction factor corresponding to the number of communication node role changes can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the number of communication node role changes and the correction factor corresponding to the number of communication node role changes preset in the database form a mapping set, and the real-time number of communication node role changes is input into the mapping set to obtain the correction factor corresponding to the number of communication node role changes. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; It is the correction factor corresponding to the packet loss rate of the communication node preset in the database, which represents the numerical value of the influence of the packet loss rate of the communication node on the state stability evaluation value of each communication node of the drone. When used, the correction factor corresponding to the packet loss rate of the communication node can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the packet loss rate of the communication node and the correction factor corresponding to the packet loss rate of the communication node preset in the database form a mapping set, and the real-time packet loss rate of the communication node is input into the mapping set to obtain the correction factor corresponding to the packet loss rate of the communication node, wherein the mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1].

[0038] It should be noted that by extracting the interference power, signal strength, number of role changes and packet loss rate of each communication node of the drone, the state stability evaluation value of each communication node of the drone is processed. If the state stability evaluation value of a communication node of the drone is higher than or equal to the state stability evaluation value threshold of the communication node in the database, the state information of each communication node of the drone is continuously monitored, and there is no need to adjust the communication frequency; if the state stability evaluation value of a communication node of the drone is lower than the state stability evaluation value threshold of the communication node in the database, the communication frequency of the communication node of the drone is adjusted, including extracting the current communication frequency of the node, reducing it according to the set communication frequency adjustment range, and recalculating the state information of the communication node of the drone after each reduction. The state stability evaluation value is calculated until the state stability evaluation value of the communication node of the drone is higher than or equal to the state stability evaluation value threshold of the communication node in the database. For example, assuming that the set communication frequency adjustment range is 10%, when the state stability evaluation value of a communication node of the drone is lower than the state stability evaluation value threshold of the communication node in the database, the communication frequency of the communication node is reduced by 10%. After the adjustment, the state stability evaluation value of the communication node of the drone is recalculated. If it is higher than or equal to the state stability evaluation value threshold of the communication node, the adjustment is terminated. If it is lower than the state stability evaluation value threshold of the communication node, the adjustment is continued until the state stability evaluation value of the communication node of the drone is higher than or equal to the state stability evaluation value threshold of the communication node in the database.

[0039] It should be noted that the state stability of the drone communication nodes is evaluated and the communication frequency is dynamically adjusted to cope with unstable situations, thereby ensuring the security and efficiency of data transmission. At the same time, this method can continuously monitor the state information of the communication nodes, providing a strong guarantee for the stable operation of the drone and effectively improving the overall performance and reliability of the drone communication network system.

[0040] Specifically, the state stability evaluation value of each communication node of the drone is extracted and compared with the state stability evaluation threshold of each communication node of the drone stored in the database. If the state stability evaluation value of a communication node of the drone is higher than or equal to the state stability evaluation threshold of each communication node of the drone, the communication node of the drone is marked as a candidate cluster head. Thus, the candidate cluster heads are obtained, and the drone clusters are divided according to the preset limit on the number of drones in the cluster.

[0041] The cluster head information of each candidate cluster head is broadcast to each neighboring node. Each neighboring node receives and analyzes the cluster head information of each candidate cluster head. The cluster head information of each candidate cluster head includes the remaining total energy, communication delay, and bandwidth. The state stability evaluation value of each candidate cluster head of each neighboring node is combined to obtain the state evaluation value of each candidate cluster head of each neighboring node. The state evaluation values ​​of each candidate cluster head of each neighboring node are sorted, and the candidate cluster head node ranked first in each drone cluster is selected as the cluster head of each neighboring node, thereby obtaining the cluster head of each drone cluster in the UANETs network.

[0042] It should be noted that the specific steps for dividing each drone cluster are to extract the state stability evaluation value of each drone communication node, and compare it with the stored state stability evaluation threshold of each drone communication node, and mark the drone communication nodes whose state stability evaluation value of each drone communication node is higher than or equal to the state stability evaluation threshold of each drone communication node as candidate cluster heads. Each candidate cluster head broadcasts its signal strength and position coordinates to other ordinary nodes around it, and each ordinary node selects the cluster head with the strongest signal and the closest distance as the cluster head of the cluster to be joined. If the cluster heads with the strongest signal and the closest distance point to different candidate cluster heads respectively, the candidate cluster head with the strongest signal is selected as the cluster head of the cluster to be joined. If the signal strengths are equal, If the number of drones in the cluster has reached the preset limit, the cluster head confirms the joining request of the ordinary node, adds the node to its own cluster member list, and sends a confirmation message to the ordinary node to notify it that it has successfully joined the cluster; if the number of drones in the cluster has reached the preset limit, the joining request of the ordinary node is rejected. After receiving the rejection command sent by the cluster head, the ordinary node marks the cluster head and resends the joining request to other cluster heads until it is rejected by all cluster heads or successfully joins the cluster.

[0043] It should be noted that each neighbor node refers to other nodes that can directly communicate within the communication range of the candidate cluster head. In the cluster head selection process, the neighbor node decides whether to join a cluster based on the information broadcast by the candidate cluster head.

[0044] It should be noted that the remaining total energy refers to the total energy that can be released by the battery in the current state, which can be obtained by monitoring the remaining power of the battery. UAVs are usually equipped with a battery management system (BMS), which can monitor the current state of the battery in real time. The remaining power of each candidate cluster head is the remaining total energy of the candidate cluster head; using network performance monitoring tools (such as PingPlotter), the communication delay of communication nodes can be monitored; using bandwidth measurement tools (such as iperf, Speedtest), the bandwidth of communication nodes can be measured.

[0045] It should be noted that the specific analysis process of the evaluation value of each candidate cluster head state of each neighboring node is as follows: ; In the formula, represents the xth candidate cluster head status evaluation value of the sth neighbor node, represents the state stability evaluation value of the x-th candidate cluster head of the UAV, represents the remaining total energy of the xth candidate cluster head of the sth neighbor node, represents the communication delay of the xth candidate cluster head of the sth neighbor node, The bandwidth of the xth candidate cluster head of the sth neighbor node, represents the reference value of the energy of the candidate cluster head. Indicates the maximum permissible value of the communication delay of the communication node. It represents the bandwidth reference value of the communication node, e is a natural constant, Indicates the weight factor corresponding to the set state stability evaluation value of the communication node, Indicates the weight factor corresponding to the remaining total energy of the set candidate cluster head, Indicates the weight factor corresponding to the communication delay of the set communication node, It represents the weight factor corresponding to the bandwidth of the communication node, s represents the number of each neighbor node, , p represents the total number of neighbor nodes, x represents the number of each candidate cluster head, , y represents the total number of candidate cluster heads; The weight factor corresponding to the state stability evaluation value of the communication node preset in the database represents the numerical value of the influence of the state stability evaluation value of the communication node on the state evaluation value of each candidate cluster head of each neighboring node. When used, the weight factor corresponding to the state stability evaluation value of the communication node can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the state stability evaluation value of the communication node and the weight factor corresponding to the state stability evaluation value of the communication node preset in the database form a mapping set, and the real-time state stability evaluation value of the communication node is input into the mapping set to obtain the weight factor corresponding to the state stability evaluation value of the communication node. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0,1]; The weight factor corresponding to the residual total energy of the candidate cluster head preset in the database represents the numerical value of the influence of the residual total energy of the candidate cluster head on the state evaluation value of each candidate cluster head of each neighboring node. When used, the weight factor corresponding to the residual total energy of the candidate cluster head can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the residual total energy of the candidate cluster head and the weight factor corresponding to the residual total energy of the candidate cluster head preset in the database form a mapping set, and the residual total energy of the real-time candidate cluster head is input into the mapping set to obtain the weight factor corresponding to the residual total energy of the candidate cluster head. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; The weight factor corresponding to the communication delay of the communication node preset in the database represents the numerical value of the influence of the communication delay of the communication node on the state evaluation value of each candidate cluster head of each neighboring node. When used, the weight factor corresponding to the communication delay of the communication node can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the communication delay of the communication node and the weight factor corresponding to the communication delay of the communication node preset in the database form a mapping set, and the communication delay of the real-time communication node is input into the mapping set to obtain the weight factor corresponding to the communication delay of the communication node. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; It is the weight factor corresponding to the bandwidth of the preset communication node in the database, which represents the degree of influence of the bandwidth of the communication node on the evaluation values of the candidate cluster head states of each neighbor node. When in use, the weight factor corresponding to the bandwidth of the communication node can be directly obtained from the database, and its corresponding relationship can be a preset mapping relationship. For example, the bandwidth of the communication node and the weight factor corresponding to the bandwidth of the preset communication node in the database form a mapping set. Inputting the real-time bandwidth of the communication node into the mapping set to obtain the weight factor corresponding to the bandwidth of the communication node, and the mapping relationship therein can be a one-to-one or many-to-one relationship. In this example, its value range is [0,1].

[0046] It should be noted that by monitoring the cluster head information of each candidate cluster head, including the remaining total energy, communication delay and bandwidth, and combining with the state stability evaluation value of the candidate cluster head, the evaluation value of the candidate cluster head state of each neighbor node is obtained. Sorting the evaluation values of the candidate cluster head states of each neighbor node in descending order and selecting the candidate cluster head ranked first in each drone cluster as the cluster head helps to ensure that the drone cluster can maintain efficient and stable communication under various conditions.

[0047] Specifically, preset each monitoring time period. During each monitoring time period, count the number of drones in each drone cluster and monitor the energy efficiency and moving distance of each drone. Take the average value of the moving distance and energy efficiency of each drone in each drone cluster respectively to obtain the average moving distance of the drones in each drone cluster and the average energy efficiency of the drones. Combine the number of drones in each drone cluster and process to obtain the broadcast stability value of each drone cluster of the UANETs network in each monitoring time period.

[0048] Compare the broadcast stability value of each drone cluster of the UANETs network in each monitoring time period with the broadcast stability threshold stored in the database. If the broadcast stability value of a certain drone cluster in a certain monitoring time period is higher than or equal to the broadcast stability threshold stored in the database, it means that the broadcast frequency of this drone cluster does not need to be adjusted. If the broadcast stability value of a certain drone cluster in a certain monitoring time period is lower than the broadcast stability threshold stored in the database, then adjust and allocate the broadcast frequency of this drone cluster.

[0049] It should be noted that through the drone cluster management system, the composition and changes of each drone cluster are tracked and recorded in real time to obtain the number of drones in each drone cluster; through the GPS positioning system, the flight trajectory and position information of the drones are recorded to obtain the moving distance of the drones in each monitoring time period; the energy efficiency is the ratio of the output power to the input power of the drone. Use a power meter to directly measure the input power and output power of the drone, and divide the output power by the input power to obtain the energy efficiency of the drone.

[0050] It should be noted that the broadcast stability value of each drone cluster in the UANETs network in each monitoring period is analyzed as follows: ; In the formula, represents the broadcast stability value of the i-th drone cluster in the UANETs network during the q-th monitoring period, represents the number of drones in the ith drone cluster during the qth monitoring period, represents the number of drones in the ith drone cluster in the q-1th monitoring period, represents the energy efficiency of the ith UAV cluster in the qth monitoring period, represents the average moving distance of the drones in the i-th drone cluster during the q-th monitoring period, Indicates the allowed value of the number of drones in the set drone cluster. Represents the energy efficiency reference value of the set UAV cluster, Indicates the maximum allowable average moving distance of drones within a set drone cluster. Indicates the correction factor corresponding to the set number of drones, Represents the correction factor corresponding to the energy efficiency of the set drone cluster, It represents the correction factor corresponding to the average moving distance of the drones in the set drone cluster, i represents the number of each drone cluster, , m represents the total number of drone clusters, q represents the number of each monitoring time period, , r represents the total number of monitoring time periods.

[0051] It should be noted that there is a correlation between the average moving distance of drones in each drone cluster, the number of drones in each drone cluster and the energy efficiency of each drone in each monitoring time period. The shorter the distance a drone moves, the less energy it consumes and the higher the energy efficiency. The average moving distance of drones and the number of drones often affect each other. For example, when monitoring a large area, it may be necessary to increase the number of drones to improve coverage. It can be seen that the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period is determined by the average moving distance of drones in each drone cluster, the number of drones in each drone cluster and the energy efficiency of each drone in each monitoring time period. It is the correction factor corresponding to the number of drones preset in the database, which indicates the numerical value of the influence of the number of drones on the broadcast stability value of each drone cluster of the UANETs network in each monitoring time period. When used, the correction factor corresponding to the number of drones can be directly obtained from the database, and its corresponding relationship can be a pre-set mapping relationship. For example, the number of drones and the correction factors corresponding to the number of drones preset in the database form a mapping set, and the real-time number of drones is input into the mapping set to obtain the correction factor corresponding to the number of drones. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; It is the correction factor corresponding to the energy efficiency of the drone cluster preset in the database, which represents the numerical value of the influence of the energy efficiency of the drone cluster on the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period. When used, the correction factor corresponding to the energy efficiency of the drone cluster can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the energy efficiency of the drone cluster and the correction factor corresponding to the energy efficiency of the drone cluster preset in the database form a mapping set, and the real-time energy efficiency of the drone cluster is input into the mapping set to obtain the correction factor corresponding to the energy efficiency of the drone cluster. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; It is the correction factor corresponding to the average moving distance of drones in the drone cluster preset in the database, which indicates the numerical value of the influence of the average moving distance of drones in the drone cluster on the broadcast stability value of each drone cluster of the UANETs network in each monitoring time period. When used, the correction factor corresponding to the average moving distance of drones in the drone cluster can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the average moving distance of drones in the drone cluster and the correction factor corresponding to the average moving distance of drones in the drone cluster preset in the database form a mapping set. The real-time average moving distance of drones in the drone cluster is input into the mapping set to obtain the correction factor corresponding to the average moving distance of drones in the drone cluster. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1].

[0052] like Figure 2 As shown, Figure 2The broadcast stability value curve of the drone cluster in the UANETs network represents the average moving distance of the drone, where the x-axis represents the average moving distance of the drones in the i-th drone cluster in the q-th monitoring period, and the y-axis represents the broadcast stability value of the i-th drone cluster in the UANETs network in the q-th monitoring period. Three different sets of example parameters are defined in the figure, corresponding to different situations of the three curves, represented by solid lines, dashed lines and dot-dash lines, respectively, and the corresponding curve labels are a, b, and c, respectively. Assume that the number of drones in the i-th drone cluster in the q-th monitoring period is = 6 (number), the number of drones in the ith drone cluster in the q-1th monitoring period =3 (units), the allowed value of the number of drones in the set drone cluster =2 (units), energy efficiency reference value of the set drone cluster =1.0 (W), the maximum permissible average moving distance of drones in the set drone cluster =10 (meters), the correction factor corresponding to the set number of drones =0.3, the correction factor corresponding to the energy efficiency of the set UAV cluster =0.5, the correction factor corresponding to the average moving distance of the drones in the set drone cluster =0.2, when the energy efficiency of the i-th UAV cluster in the q-th monitoring time period is 0.6, the schematic diagram of the broadcast stability value of the i-th UAV cluster in the UANETs network in the q-th monitoring time period is shown in curve a, when the energy efficiency of the i-th UAV cluster in the q-th monitoring time period is 0.8, the schematic diagram of the broadcast stability value of the i-th UAV cluster in the q-th monitoring time period is shown in curve b, when the energy efficiency of the i-th UAV cluster in the q-th monitoring time period is 1.0, the schematic diagram of the broadcast stability value of the i-th UAV cluster in the q-th monitoring time period is shown in curve c.

[0053] As shown in Table 1, Table 1 is sample data of the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period, which lists the broadcast stability value of each drone cluster in the UANETs network and the average moving distance of the drone.

[0054] Table 1 Example data of broadcast stability values ​​of each drone cluster in UANETs network:

[0055] As shown in Table 1, in a specific embodiment, assuming that the number of drones in the i-th drone cluster in the q-th monitoring time period is = 6 (number), the number of drones in the ith drone cluster in the q-1th monitoring period =3 (units), the allowed value of the number of drones in the set drone cluster =2 (units), energy efficiency reference value of the set drone cluster =1.0 (W), the maximum permissible average moving distance of drones in the set drone cluster =10 (meters), the correction factor corresponding to the set number of drones =0.3, the correction factor corresponding to the energy efficiency of the set UAV cluster =0.5, the correction factor corresponding to the average moving distance of the drones in the set drone cluster =0.2.

[0056] It should be noted that the adjustment and allocation of the broadcast frequency of the drone cluster includes comparing the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period with the preset broadcast stability threshold. When the broadcast stability value of a drone cluster in a certain monitoring time period is lower than the broadcast stability threshold stored in the database, the spectrum analyzer is used to identify the frequency band with less interference, and the drone cluster is allocated to the frequency band with less frequency interference to reduce frequency interference.

[0057] Specifically, during each monitoring time period, the data transmission process of each communication node in each drone cluster of the UANETs network is monitored and analyzed to obtain the communication data of each communication node in each drone cluster of the UANETs network. The communication data of each communication node in each drone cluster of the UANETs network includes: data transmission rate and retransmission rate.

[0058] The data transmission rate and retransmission rate of each communication node of each drone cluster in the UANETs network are extracted, and the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period and the state evaluation value of each communication node in each drone cluster are combined to obtain the data transmission evaluation value of each drone cluster in the UANETs network. The data transmission evaluation value of each drone cluster in the UANETs network is used to evaluate the network stability of each drone cluster.

[0059] The data transmission evaluation value of each drone cluster of the UANETs network is extracted and matched with the network stability of the drone cluster corresponding to each interval of the data transmission evaluation value stored in the database to obtain the network stability of each drone cluster. The network stability of the drone cluster includes: highly stable, moderately stable, and generally stable.

[0060] The network stability of each drone cluster in the UANETs network is extracted. When the network stability of a drone cluster is highly stable, the data transmission process of the communication nodes in the drone cluster is continuously monitored and analyzed.

[0061] When the network stability of a certain drone cluster is moderately stable or generally stable, the number of communication nodes in the drone cluster is adjusted and the cluster head is re-elected.

[0062] It should be noted that a network tester is used to connect to the communication link of the drone to monitor the data transmission rate in real time to obtain the data transmission rate of the communication nodes in the drone cluster; the number of sent data packets and retransmitted data packets are recorded through special testing software (such as iperf, netperf), and the retransmission rate is obtained by dividing the number of retransmitted data packets by the number of sent data packets.

[0063] It should be noted that the data transmission evaluation value of each drone cluster of the UANETs network is extracted and matched with the network stability of the drone cluster corresponding to each interval of the data transmission evaluation value stored in the database. The network stability of each drone cluster is preset in the database. When used, the network stability of each drone cluster can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the data transmission evaluation value of each drone cluster and the network stability of the drone cluster in the database form a mapping set, and the real-time data transmission evaluation value of each drone cluster is input into the mapping set to obtain the network stability of each drone cluster. The mapping relationship can be a one-to-one relationship. The network stability of the drone cluster includes: high stability, medium stability, and general stability. By evaluating the network stability of the drone cluster, reliable data support is provided for subsequent adjustments and optimizations.

[0064] It should be noted that adjusting the number of communication nodes in the drone cluster and re-electing the cluster head includes: the communication nodes in each drone cluster extract their own position parameters and the position parameters of the cluster head to obtain the distance between the communication node and the cluster head, and compare the distance between the communication node and the cluster head with the distance threshold set in the database. If the distance between the communication node and the cluster head is greater than the distance threshold stored in the database, the communication node exits the drone cluster, accepts the position information of each cluster head, joins the nearest drone cluster, and re-monitors and collects the status information of the communication nodes in each adjusted drone cluster, processes to obtain the status stability evaluation value of each communication node of the drone, and re-elects a new candidate cluster head, re-obtains the status evaluation value of each candidate cluster head of each neighboring node and sorts them, and elects a new cluster head.

[0065] Specifically, the data transmission evaluation value of each drone cluster in the UANETs network is analyzed as follows: ; In the formula, represents the data transmission evaluation value of the i-th UAV cluster in the UANETs network, represents the broadcast stability value of the ith drone cluster in the qth monitoring period, Indicates the xth candidate cluster head status evaluation value of the sth neighbor node represents the data transmission rate of the jth communication node of the i-th UAV cluster represents the retransmission rate of the jth communication node of the i-th UAV cluster, Indicates the reference value of the data transmission rate of the communication node to be set. It represents the maximum permissible value of the retransmission rate of the communication node, e is a natural constant, Indicates the weight factor corresponding to the broadcast stability value of the set drone cluster, Indicates the weight factor corresponding to the set data transmission rate Indicates the weight factor corresponding to the set retransmission rate, represents the weight factor corresponding to the set candidate cluster head state evaluation value, and i represents the number of each drone cluster , m represents the total number of drone clusters, j represents the number of each communication node, , n represents the total number of communication nodes, q represents the number of each monitoring time period, , r represents the total number of monitoring time periods, s represents the number of each neighbor node, , p represents the total number of neighbor nodes, x represents the number of each candidate cluster head, , y represents the total number of candidate cluster heads.

[0066] It should be noted that there is a correlation between the data transmission rate and the retransmission rate. When the retransmission rate is higher, the retransmission of data packets will occupy the bandwidth originally used to transmit new data, resulting in lower data transmission efficiency; The weight factor corresponding to the broadcast stability value of the drone cluster set in the database represents the numerical value of the influence of the broadcast stability value of the drone cluster on the data transmission evaluation value of each drone cluster in the UANETs network. When used, the weight factor corresponding to the broadcast stability value of the drone cluster can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the broadcast stability value of the drone cluster and the weight factor corresponding to the broadcast stability value of the drone cluster preset in the database form a mapping set. The real-time broadcast stability value of the drone cluster is input into the mapping set to obtain the weight factor corresponding to the broadcast stability value of the drone cluster. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; The weight factor corresponding to the data transmission rate set in the database represents the numerical value of the influence of the data transmission rate on the data transmission evaluation value of each drone cluster in the UANETs network. When used, the weight factor corresponding to the data transmission rate can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the data transmission rate and the weight factor corresponding to the data transmission rate preset in the database form a mapping set, and the real-time data transmission rate is input into the mapping set to obtain the weight factor corresponding to the data transmission rate. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; The weight factor corresponding to the retransmission rate set in the database represents the numerical value of the influence of the retransmission rate on the data transmission evaluation value of each drone cluster in the UANETs network. When used, the weight factor corresponding to the retransmission rate can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the retransmission rate and the weight factor corresponding to the retransmission rate preset in the database form a mapping set, and the real-time retransmission rate is input into the mapping set to obtain the weight factor corresponding to the retransmission rate. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1]; The weight factor corresponding to the candidate cluster head state evaluation value set in the database represents the numerical value of the influence of the candidate cluster head state evaluation value on the data transmission evaluation value of each drone cluster of the UANETs network. When used, the weight factor corresponding to the candidate cluster head state evaluation value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the candidate cluster head state evaluation value and the weight factor corresponding to the candidate cluster head state evaluation value preset in the database form a mapping set, and the real-time candidate cluster head state evaluation value is input into the mapping set to obtain the weight factor corresponding to the candidate cluster head state evaluation value. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0,1].

[0067] It should be noted that a safe, efficient and dynamic UANETs data transmission method also includes a database for storing and managing the status information of each communication node of the drone. In this embodiment, the database is used to store a set reference value of interference power of the communication node, a set reference value of signal strength of the communication node, a set reference value of the number of role changes of the communication node, a set reference value of the packet loss rate of the communication node, a correction factor corresponding to the interference power of the communication node, a correction factor corresponding to the signal strength of the communication node, a correction factor corresponding to the number of role changes of the communication node, a correction factor corresponding to the packet loss rate of the communication node, a state stability assessment value threshold of the communication node, a state stability assessment threshold of each communication node of the drone, a set communication frequency adjustment amplitude, a set reference value of the energy of the candidate cluster head, a set maximum allowable value of the communication delay of the communication node, a set reference value of the bandwidth of the communication node, and a set state stability assessment value of the communication node. The corresponding weight factor, the set weight factor corresponding to the remaining total energy of the candidate cluster head, the set weight factor corresponding to the communication delay of the communication node, the set weight factor corresponding to the bandwidth of the communication node, the set allowable value of the change in the number of drones in the drone cluster, the set reference value of the energy efficiency of the drone cluster, the set maximum allowable value of the average moving distance of the drones in the drone cluster, the correction factor corresponding to the set number of drones, the set correction factor corresponding to the energy efficiency of the drone cluster, the set correction factor corresponding to the average moving distance of the drones in the drone cluster, the preset broadcast stability threshold, the network stability of the drone cluster, the set distance threshold, the set reference value of the data transmission rate of the communication node, the set maximum allowable value of the retransmission rate of the communication node, the set weight factor corresponding to the broadcast stability value of the drone cluster, the set weight factor corresponding to the data transmission rate, the set weight factor corresponding to the retransmission rate, the preset limit on the number of drones in the cluster, etc.

[0068] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0069] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A secure, efficient and dynamic UANETs data transmission method, characterized in that: include: Obtain the status information of each communication node of the UAV in the UANETs network, analyze the status information of each communication node of the UAV, and obtain the status stability evaluation value of each communication node of the UAV; According to the status stability evaluation value of each drone communication node, the drone communication nodes in the UANETs network are clustered to obtain the drone clusters of the UANETs network, and the cluster heads of each drone cluster of the UANETs network are screened to adjust the broadcast frequency of the drones in the UANETs network; The data transmission process of the cluster head of each UAV cluster and each communication node of the UAV in the UANETs network is monitored and analyzed to obtain the data transmission evaluation value of each UAV cluster in the UANETs network. According to the data transmission evaluation value of each UAV cluster in the UANETs network, the clustering of each communication node of the UAV in the UANETs network is adjusted.

2. According to claim 1, a secure, efficient and dynamic UANETs data transmission method is characterized by: The status information of each communication node of the drone includes: the signal strength of each communication node, the number of role changes of each communication node, the packet loss rate of each communication node, and the interference power of each communication node.

3. A secure, efficient and dynamic UANETs data transmission method according to claim 2, characterized in that: The state information of each communication node of the UAV is analyzed to obtain the state stability evaluation value of each communication node of the UAV. The specific analysis is as follows: Extract the interference power of each communication node of the drone, the signal strength of each communication node, the number of role changes of each communication node, and the packet loss rate of each communication node, and process them to obtain the state stability evaluation value of each communication node of the drone, which is used to evaluate the communication stability of the drone; The state stability evaluation value of each communication node of the UAV is extracted and compared with the state stability evaluation value threshold of the communication node in the database. If the state stability evaluation value of a communication node of the UAV is higher than or equal to the state stability evaluation value threshold of the communication node in the database, the state information of each communication node of the UAV is continuously monitored; if the state stability evaluation value of a communication node of the UAV is lower than the state stability evaluation value threshold of the communication node in the database, the communication frequency of the communication node of the UAV is adjusted.

4. A secure, efficient and dynamic UANETs data transmission method according to claim 1, characterized in that: According to the state stability evaluation value of each communication node of the drone, each communication node of the drone in the UANETs network is clustered, and the specific analysis is as follows: The state stability evaluation value of each communication node of the drone is extracted and compared with the state stability evaluation threshold of each communication node of the drone stored in the database. If the state stability evaluation value of a communication node of the drone is higher than or equal to the state stability evaluation threshold of each communication node of the drone, the communication node of the drone is marked as a candidate cluster head. Thus, the candidate cluster heads are obtained and the drone clusters are divided according to the preset limit on the number of drones in the cluster.

5. A secure, efficient and dynamic UANETs data transmission method according to claim 4, characterized in that: The cluster heads of each drone cluster in the screening UANETs network are specifically analyzed as follows: The cluster head information of each candidate cluster head is broadcast to each neighboring node. Each neighboring node receives and analyzes the cluster head information of each candidate cluster head. The cluster head information of each candidate cluster head includes the remaining total energy, communication delay, and bandwidth. The state stability evaluation value of each candidate cluster head of each neighboring node is combined to obtain the state evaluation value of each candidate cluster head of each neighboring node. The state evaluation values ​​of each candidate cluster head of each neighboring node are sorted, and the candidate cluster head node ranked first in each drone cluster is selected as the cluster head of each neighboring node, thereby obtaining the cluster head of each drone cluster in the UANETs network.

6. A secure, efficient and dynamic UANETs data transmission method according to claim 1, characterized in that: The above adjustment of the broadcast frequency of drones in the UANETs network is specifically analyzed as follows: Preset each monitoring time period, count the number of drones in each drone cluster in each monitoring time period, monitor the energy efficiency of each drone and the moving distance of each drone, take the average of the moving distance of each drone in each drone cluster and the energy efficiency of each drone, and obtain the average moving distance of drones in each drone cluster and the average energy efficiency of drones. Combined with the number of drones in each drone cluster, the broadcast stability value of each drone cluster of UANETs network in each monitoring time period is obtained; The broadcast stability value of each drone cluster in the UANETs network in each monitoring time period is compared with the broadcast stability threshold stored in the database. If the broadcast stability value of a drone cluster in a certain monitoring time period is higher than or equal to the broadcast stability threshold stored in the database, it means that the broadcast frequency of the drone cluster does not need to be adjusted. If the broadcast stability value of a drone cluster in a certain monitoring time period is lower than the broadcast stability threshold stored in the database, the broadcast frequency of the drone cluster is adjusted and allocated.

7. A secure, efficient and dynamic UANETs data transmission method according to claim 1, characterized in that: The data transmission process of the cluster heads of each drone cluster and each communication node of the drone in the UANETs network is monitored and analyzed, and the specific analysis is as follows: During each monitoring time period, the data transmission process of each communication node in each drone cluster of the UANETs network is monitored and analyzed to obtain the communication data of each communication node in each drone cluster of the UANETs network. The communication data of each communication node in each drone cluster of the UANETs network includes: data transmission rate and retransmission rate.

8. A secure, efficient and dynamic UANETs data transmission method according to claim 7, characterized in that: The data transmission evaluation value of each drone cluster in the UANETs network is specifically analyzed as follows: The data transmission rate and retransmission rate of each communication node of each drone cluster in the UANETs network are extracted, and the broadcast stability value of each drone cluster in the UANETs network in each monitoring time period and the state evaluation value of each communication node in each drone cluster are combined to obtain the data transmission evaluation value of each drone cluster in the UANETs network. The data transmission evaluation value of each drone cluster in the UANETs network is used to evaluate the network stability of each drone cluster.

9. A secure, efficient and dynamic UANETs data transmission method according to claim 8, characterized in that: The clustering of each communication node of the UAV in the UANETs network is adjusted, and the specific analysis is as follows: Extract the data transmission evaluation value of each drone cluster of the UANETs network and match it with the network stability of the drone cluster corresponding to each interval of the data transmission evaluation value stored in the database to obtain the network stability of each drone cluster, where the network stability of the drone cluster includes: highly stable, moderately stable, and generally stable; Extract the network stability of each drone cluster in the UANETs network. When the network stability of a drone cluster is highly stable, continuously monitor and analyze the data transmission process of the communication nodes in the drone cluster. When the network stability of a certain drone cluster is moderately stable or generally stable, the number of communication nodes in the drone cluster is adjusted and the cluster head is re-elected.

10. A secure, efficient and dynamic UANETs data transmission method according to claim 8, characterized in that: The data transmission evaluation value of each drone cluster in the UANETs network is analyzed in detail as follows: ； In the formula, represents the data transmission evaluation value of the i-th UAV cluster in the UANETs network, represents the broadcast stability value of the ith drone cluster in the qth monitoring period, Indicates the xth candidate cluster head status evaluation value of the sth neighbor node represents the data transmission rate of the jth communication node of the i-th UAV cluster represents the retransmission rate of the jth communication node of the i-th UAV cluster, Indicates the reference value of the data transmission rate of the communication node to be set. It represents the maximum permissible value of the retransmission rate of the communication node, e is a natural constant, Indicates the weight factor corresponding to the broadcast stability value of the set drone cluster, Indicates the weight factor corresponding to the set data transmission rate Indicates the weight factor corresponding to the set retransmission rate, represents the weight factor corresponding to the set candidate cluster head state evaluation value, and i represents the number of each drone cluster , m represents the total number of drone clusters, j represents the number of each communication node, , n represents the total number of communication nodes, q represents the number of each monitoring time period, , r represents the total number of monitoring time periods, s represents the number of each neighbor node, , p represents the total number of neighbor nodes, x represents the number of each candidate cluster head, , y represents the total number of candidate cluster heads.

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