A signal-free zone ad hoc network communication system

Abstract

The application discloses a kind of signal-free area ad hoc communication system, specifically relates to wireless communication technical field, for solving the problem that connectivity critical state caused by node density or mobility change in low-density network is not fully considered in existing dynamic routing protocol;By real-time acquisition node position coordinate and communication radius, the connectivity critical state of network is predicted in combination with average node spacing and mobile direction dispersion;In critical state, high-priority detection nodes are screened based on obstacle avoidance collaborative angle variance and virtual pheromone concentration, and the sending frequency of detection message is adaptively adjusted according to node moving speed;By fusing link survival time, node residual energy and signal strength fluctuation rate to construct path stability evaluation model, high stability path is dynamically selected as main transmission link, and the rest is backup link;Real-time monitoring of main link signal fluctuation characteristics, in abnormal state, quickly switch to the path with optimal comprehensive stability in backup link.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, and more particularly, to a self-organizing network communication system in a signal-free area. BACKGROUND

[0002] In emergency communication in a signal-free area (such as a remote mountainous area or a disaster site), self-organizing network technology relies on equipment self-organizing network to realize information transmission, and its core relies on a dynamic routing protocol (such as AODV or OLSR) to maintain the connectivity of the network topology in a changing environment. The existing technology usually establishes and maintains a routing table based on a neighbor discovery and shortest path selection mechanism through periodic broadcast of a beacon or on-demand routing request. However, in a scenario in which nodes are sparsely distributed and highly dynamic (such as a wide-area search and rescue or field monitoring), the network topology often presents an intermittent connectivity characteristic. The traditional method needs to frequently send probe messages to find potential paths, thereby causing a dramatic increase in control overhead and a reduction in energy efficiency, and it is difficult to guarantee the continuity and stability of end-to-end communication.

[0003] The current dynamic routing protocol does not fully consider the connectivity critical state problem caused by changes in node density or mobility in a low-density network. When the number of available paths approaches the threshold of the phase transition of network connectivity, the traditional routing strategy may cause sudden path interruption, data flooding retransmission, and energy waste. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present application provide a self-organizing network communication system in a signal-free area to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0006] A self-organizing network communication system in a signal-free area, comprising:

[0007] a node parameter acquisition module: periodically acquiring node parameters of network nodes, the node parameters including position coordinates and a communication radius;

[0008] a connectivity criticality determination module: calculating an average node spacing and a mobility direction dispersion based on the node parameters to determine whether the network is in a connectivity critical state;

[0009] a probe node screening module: screening high-priority probe nodes in the connectivity critical state;

[0010] a dynamic probe control module: adjusting the sending frequency of probe messages based on the moving speed of the high-priority probe nodes;

[0011] The multi-path generation module calculates the stability weight of each path according to the detection result, selects a path with a stability weight higher than a preset weight threshold as a main transmission link, and selects the remaining paths as backup links;

[0012] The data shunting execution module switches to a path with the highest stability weight in the backup links when the signal strength of the main transmission link fluctuates abnormally.

[0013] In a preferred embodiment, the high-priority detection node is specifically screened as follows:

[0014] The node with a low obstacle avoidance coordination angle variance and a virtual information concentration higher than the group average is selected as the high-priority detection node.

[0015] The group average is the arithmetic average of the virtual information concentrations of all nodes.

[0016] In a preferred embodiment, the node parameters of the network node are periodically collected, including:

[0017] The active collection period is triggered according to a preset time interval, the position coordinates are obtained through the beacon interaction between nodes in the active collection period, and the communication radius is inversely calculated through the signal strength.

[0018] When the instantaneous change rate of the node receiving signal strength exceeds a preset change threshold, the event-driven collection period is triggered, the position coordinates are updated through multi-hop cooperative positioning in the event-driven collection period, and the communication radius is dynamically calibrated according to the maximum effective communication distance of the adjacent node.

[0019] In a preferred embodiment, the average node spacing and the moving direction dispersion are calculated according to the node parameters to determine whether the network is in a connectivity critical state, including:

[0020] The position coordinates of all nodes are traversed, the Euclidean distance between each pair of nodes is calculated, the node pairs with a Euclidean distance greater than the communication radius are removed, and the arithmetic average of the distances of the remaining node pairs is taken as the average node spacing.

[0021] The position coordinate change amount of each node in adjacent two collection periods is extracted to generate a moving direction vector, and the moving direction dispersion of the node group is calculated based on the azimuth angle of the moving direction vector.

[0022] If the average node spacing exceeds a preset multiple of the communication radius and the moving direction dispersion is higher than a preset dispersion threshold, it is determined that the network is in a connectivity critical state.

[0023] In a preferred embodiment, the obstacle avoidance coordination angle variance is obtained by:

[0024] Based on the generated moving direction vector, all adjacent nodes within the corresponding communication radius are selected for each node;

[0025] The geometric angle between the moving direction vector of the node and each adjacent node is calculated, and the geometric angle is converted into an angle value through the vector dot product formula;

[0026] The geometric angle values of all adjacent node pairs are counted, and the variance of the geometric angle values is calculated as the obstacle avoidance coordination angle variance.

[0027] In a preferred embodiment, the method for obtaining the virtual pheromone concentration is:

[0028] The number of successfully forwarded probe packets by the node within a preset period is counted, and each successful forwarding increases the virtual pheromone concentration by a preset increment value;

[0029] The virtual pheromone concentration is weighted according to the link survival time maintained by the node, and the link with a survival time exceeding a preset stability threshold is additionally increased in concentration value by an overtime proportion;

[0030] At the end of each collection period, a preset decay rate is applied to the virtual pheromone concentration to generate an updated virtual pheromone concentration.

[0031] In a preferred embodiment, the sending frequency of the probe packet is adjusted according to the moving speed of the high-priority probe node, including:

[0032] The moving speed of the high-priority probe node is extracted, and when the moving speed exceeds a preset speed threshold, the sending frequency of the probe packet is increased to a first preset multiple of the reference frequency;

[0033] The moving direction dispersion of the high-priority probe node is extracted, and when the moving direction dispersion exceeds a preset dispersion threshold, the sending frequency of the probe packet is increased to a second preset multiple of the reference frequency;

[0034] If the moving speed exceeds the preset speed threshold and the moving direction dispersion exceeds the preset dispersion threshold, the first preset multiple and the second preset multiple are added to adjust the sending frequency of the probe packet;

[0035] If the moving speed does not exceed the preset speed threshold and the moving direction dispersion does not exceed the preset dispersion threshold, the sending frequency of the probe packet is restored to the reference frequency.

[0036] In a preferred embodiment, the stability weight of each path is calculated according to the probe result, and the path with a stability weight higher than a preset weight threshold is selected as the main transmission link, and the rest is selected as the standby link, including:

[0037] The link survival duration of the statistical path is the duration from the establishment to the interruption or deletion of the path, and is normalized according to the proportion of the survival duration in the total detection duration;

[0038] The residual energy of all nodes in the path is acquired, and the average value of the residual energy of the nodes is calculated;

[0039] The signal strength fluctuation rate of the path is extracted, and the signal strength fluctuation rate is the ratio of the standard deviation to the average of the received signal strength in the transmission process of the path;

[0040] The link survival duration proportion, the average value of the residual energy of the nodes and the signal strength fluctuation rate are multiplied by the weighted product to generate the stability weight of the path;

[0041] The path with the stability weight higher than the preset weight threshold is selected as the main transmission link, and the remaining paths are used as backup links.

[0042] In a preferred embodiment, when the signal strength fluctuation of the main transmission link is abnormal, the path with the highest stability weight in the backup link is switched to, comprising:

[0043] The signal strength fluctuation rate of the main transmission link is continuously monitored, and when the signal strength fluctuation rate exceeds the preset fluctuation threshold, it is determined to be abnormal;

[0044] The stability weight of all paths in the backup link list is acquired, and the path with the highest stability weight is selected as the target switching path;

[0045] It is verified whether the current signal strength fluctuation rate of the target switching path is lower than that of the main transmission link, and if it is satisfied, the switching is performed;

[0046] After the switching is completed, the original main transmission link is downgraded to the backup link and the stability weight is updated.

[0047] Compared with the prior art, the present application has the following beneficial effects:

[0048] 1. The application effectively solves the problem of excessive control overhead and insufficient communication reliability caused by unstable path of traditional routing protocol in low-density dynamic network scenario by introducing connectivity critical state prediction mechanism and multi-dimensional collaborative screening strategy. First, based on dynamic perception of node density distribution and group movement trend, the system can identify the network connectivity critical state in advance, significantly reduce the sending amount of redundant detection packets by optimizing the selection logic of detection nodes and the adaptive regulation of detection frequency, compared with the fixed period or random detection mechanism in traditional method, the application quantifies the node motion coordination by avoiding obstacle collaborative angle variance, and realizes the precise selection and resource allocation of detection nodes in high dynamic scene by combining the virtual pheromone concentration representing the node path maintenance contribution, which not only avoids the risk of path failure caused by node motion conflict, but also reduces the energy waste caused by inefficient detection, so as to improve the overall energy efficiency ratio while ensuring network connectivity;

[0049] 2. The application breaks through the limitation of traditional routing protocol relying on single link or static path selection by dynamic evaluation of multi-path stability weight and master-slave link switching mechanism, based on multi-dimensional parameter fusion calculation of link survival time, node energy state and signal fluctuation, the system can select the transmission path with optimal comprehensive stability in real time, and realize the rapid response of link switching through fluctuation rate threshold trigger mechanism; Compared with the defect of passive retransmission after path breakage in the prior art, the application greatly improves the continuity and anti-interference ability of data transmission through predictive path maintenance and dynamic shunting execution, especially in the scene of sparse node distribution and frequent topology change, it can effectively suppress the data flooding phenomenon, reduce the communication delay and energy consumption fluctuation caused by repeated path reconstruction, and provides high-robustness communication guarantee for emergency rescue, field monitoring and other scenes. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 It is a structural schematic diagram of a signal-free area ad hoc network communication system of the application;

[0051] Figure 2 It is a flowchart of the obstacle avoidance collaborative angle variance acquisition method in the application;

[0052] Figure 3 It is a flowchart of the virtual pheromone concentration acquisition method in the application. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the application will be described clearly and completely in the embodiments of the application combined with the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0054] Embodiment 1 Figure 1 A structural schematic diagram of a signal-free area ad hoc network communication system is given, a signal-free area ad hoc network communication system comprising:

[0055] A node parameter acquisition module: periodically acquiring node parameters of network nodes, the node parameters including position coordinates and communication radius;

[0056] A connectivity criticality determination module: calculating average node spacing and moving direction dispersion according to the node parameters to determine whether the network is in a connectivity critical state;

[0057] A probe node screening module: screening high-priority probe nodes under the connectivity critical state;

[0058] A dynamic probe control module: adjusting the probe message sending frequency according to the moving speed of the high-priority probe nodes;

[0059] A multi-path generation module: calculating the stability weight of each path according to the probe results, and selecting the path with a stability weight higher than a preset weight threshold as the main transmission link, and the rest as backup links;

[0060] A data shunting execution module: switching to the path with the highest stability weight in the backup links when the signal strength of the main transmission link fluctuates abnormally.

[0061] Periodically acquiring node parameters of network nodes, including:

[0062] In the signal-free area ad hoc network communication, the specific implementation process of periodically acquiring node parameters of network nodes is as follows:

[0063] The preset time interval of periodic acquisition is set to any value between 5 seconds and 30 seconds, and the setting basis of the time interval is the ratio of the average moving speed of the network nodes to the communication radius. When the average moving speed of the network nodes increases, the preset time interval is shortened to increase the acquisition frequency. In the active acquisition period triggered by the preset time interval, each node periodically broadcasts a beacon data packet containing its own position coordinates, and the adjacent nodes receive the beacon data packet and extract the position coordinates of the sending node. At the same time, the communication radius of the sending node is inversely calculated according to the received signal strength indicator value, wherein the calculation method of the received signal strength indicator value for inversely calculating the communication radius is as follows: Where R is the communication radius, P t is the sending power, P r is the receiving power, and L is the environmental attenuation factor, which is obtained by fitting historical communication data.

[0064] When any node detects that the instantaneous change rate of the received signal strength indication value exceeds the preset change threshold (for example, the change rate exceeds 20%) in two consecutive sampling periods, an event-driven collection period is triggered.

[0065] In the event-driven collection period, the node sends a cooperative positioning request to the neighboring nodes, and the neighboring nodes update the position coordinates of the node based on the multi-hop cooperative positioning method. Specifically, the node calculates its own position by trilateration, selects the position coordinates of more than three neighboring nodes as reference points, and corrects its own position coordinates according to the joint solution results of the time difference of arrival and the received signal strength indication value; at the same time, the communication radius of the node is dynamically calibrated according to the maximum effective communication distance of the neighboring nodes, and the maximum effective communication distance is obtained by: counting the farthest distance of all neighboring nodes in the historical communication that successfully established a link, and taking the moving average of the farthest distance as the calibration reference.

[0066] After completing the active collection period or the event-driven collection period, the node stores the collected position coordinates and communication radius into the local routing table, and periodically broadcasts the update information through the routing table.

[0067] According to the node parameters, the average node spacing and the moving direction dispersion are calculated to determine whether the network is in a connectivity critical state, including:

[0068] The position coordinates of all nodes in the network are traversed, and the Euclidean distance between each pair of nodes is calculated. The calculation method of the Euclidean distance is: according to the horizontal and vertical coordinate values of node A and the horizontal and vertical coordinate values of node B, the sum of the square of the horizontal coordinate difference and the square of the vertical coordinate difference is calculated, and the straight-line distance between the two nodes is obtained by taking the square root of the sum of squares.

[0069] If the calculated Euclidean distance is greater than the communication radius of the node, the node pair is removed, and only the node pairs with a Euclidean distance less than or equal to the communication radius are retained; the arithmetic mean of the Euclidean distances of all retained node pairs is taken to obtain the average node spacing.

[0070] For example, when the network contains nodes 1 to 5, the distances between node 1 and node 2, node 1 and node 3, node 1 and node 4, node 1 and node 5, node 2 and node 3, etc. are calculated, and after removing the node pairs with a distance greater than the communication radius, the distances of the remaining effective node pairs are added and divided by the number of effective node pairs to finally obtain the average node spacing.

[0071] For each node, the position coordinate change amount in the adjacent two collection periods is extracted, which is obtained by subtracting the position coordinate value recorded in the previous collection period from the position coordinate value recorded in the current collection period.

[0072] The moving direction vector is generated according to the position coordinate change amount, and the direction of the moving direction vector is determined by the ratio of the horizontal direction change amount and the vertical direction change amount, and is converted into an azimuth value by an inverse tangent function.

[0073] For example, the node has a position coordinate of (10 meters, 20 meters) in the last period and a position coordinate of (15 meters, 25 meters) in the current period, the horizontal direction change amount is 5 meters, the vertical direction change amount is 5 meters, and the azimuth of the moving direction vector is 45 degrees.

[0074] The azimuth values of all nodes are counted, and the standard deviation of the azimuth values is calculated as the moving direction dispersion.

[0075] The standard deviation of the azimuth value is calculated in the following manner: first, the arithmetic mean of all azimuth values is calculated, then the square of the difference between each azimuth value and the arithmetic mean is calculated, and then the square of all the difference values is averaged to obtain the standard deviation of the azimuth value.

[0076] The average node distance is compared with the preset multiple of the communication radius, and the moving direction dispersion is compared with the preset dispersion threshold value; if the average node distance exceeds the preset multiple of the communication radius and the moving direction dispersion is higher than the preset dispersion threshold value, it is determined that the network is in a connectivity critical state.

[0077] The preset multiple of the communication radius is set according to the wireless signal attenuation model, for example: in the free space propagation model, when the communication distance is expanded to 1.5 times the original communication radius, the received signal strength will be attenuated to the minimum sensitivity threshold of the receiving device, at this time the preset multiple is set to 1.5 times; the preset dispersion threshold value is set by historical data statistics, for example: in the historical running data of the network, when the moving direction dispersion of the node group exceeds 30 degrees, the probability of network connectivity rupture is more than 90%, therefore the preset dispersion threshold value is set to 30 degrees.

[0078] In a specific implementation, if the network nodes are deployed in a field search and rescue scene, the initial communication radius of the nodes is 100 meters, when the calculated average node distance is 160 meters (more than 1.5 times of 100 meters) and the moving direction dispersion is 35 degrees (more than the 30-degree threshold), it is determined that the network enters a connectivity critical state, triggering the subsequent path maintenance mechanism. If the node group moves dispersedly in the disaster site, the moving direction dispersion of the nodes rapidly rises to 40 degrees, and the average node distance reaches 1.6 times the communication radius, then it is also determined as a critical state.

[0079] Figure 2 A flowchart of the obstacle avoidance cooperative angle variance acquisition method in the application is given, and the obstacle avoidance cooperative angle variance acquisition method is as follows:

[0080] Based on the generated moving direction vector, all adjacent nodes within the communication radius of each node are selected.

[0081] The communication radius is obtained by periodically collecting the communication radius value through the node parameter acquisition module. If the node has completed dynamic calibration of the communication radius within the event-driven acquisition period, the calibrated communication radius value is preferentially used.

[0082] For example, the communication radius of node A is 100 meters, and all nodes with a straight-line distance of less than or equal to 100 meters from node A are selected as adjacent nodes. The position coordinates of the adjacent nodes are obtained through the node parameter acquisition module.

[0083] The geometric angle between the moving direction vector of the node and each adjacent node is calculated.

[0084] The moving direction vector is generated from the position coordinate change of two adjacent acquisition periods. Specifically, the horizontal direction change and the vertical direction change are obtained by subtracting the position coordinates of the previous acquisition period from the position coordinates of the current acquisition period, and the horizontal direction change and the vertical direction change together constitute the moving direction vector.

[0085] For example, the position coordinates of node B in the previous period are east longitude 10 meters and north latitude 20 meters, and the position coordinates in the current period are east longitude 15 meters and north latitude 25 meters. The horizontal direction change is 5 meters in the east direction, and the vertical direction change is 5 meters in the north direction. The moving direction vector is represented as moving in the east-north 45-degree direction.

[0086] The calculation process of the geometric angle is as follows: for the current node and a certain adjacent node, the moving direction vectors of the two nodes are obtained, the dot product of the two vectors is calculated, and the dot product is equal to the product of the horizontal direction change of the current node and the horizontal direction change of the adjacent node, plus the product of the vertical direction change of the current node and the vertical direction change of the adjacent node.

[0087] The modulus of the moving direction vector of the current node is calculated, which is the square root of the sum of the square of the horizontal direction change and the square of the vertical direction change. The modulus of the moving direction vector of the adjacent node is calculated in the same way as the current node. The dot product is divided by the product of the modulus of the current node and the modulus of the adjacent node to obtain the cosine value. The cosine value is converted to an angle value through the inverse cosine function to obtain the geometric angle between the two moving direction vectors.

[0088] The geometric included angle values of all adjacent node pairs are counted, and the variance of the angle values is calculated as the obstacle avoidance coordination angle variance.

[0089] If the nodes are randomly dispersed and moved, the geometric included angle difference is significant, and the variance increases.

[0090] For example, if the node group moves in the same direction in a wide-area search and rescue task, the geometric included angle between the movement direction vectors of each node is generally less than 10 degrees, and the variance is less than 5, indicating that the group motion is highly coordinated, and is suitable for being a high-priority detection node; if the node group is dispersed for operation in field monitoring, the geometric included angle difference can be more than 60 degrees, and the variance is more than 50, indicating that the group motion is disordered, and the detection priority needs to be reduced to avoid resource waste.

[0091] Figure 3 A flowchart of the virtual pheromone concentration acquisition method in the application is given, and the virtual pheromone concentration acquisition method is:

[0092] Each node counts the number of successfully forwarded detection packets in a preset period; the preset period is set according to network dynamics, for example, when the average node moving speed is 2 meters per second, the preset period is set to 30 seconds; when the average node moving speed is 5 meters per second, the preset period is shortened to 10 seconds.

[0093] The number of successfully forwarded detection packets is counted in the following way: after receiving a detection packet, if the node forwards it to the next hop node within a preset timeout time (for example, 500 milliseconds) and no packet loss occurs, it is counted as a successful forwarding.

[0094] The virtual pheromone concentration is increased by a preset increment value for each successful forwarding of a detection packet. The preset increment value is set according to the network load balancing requirement, for example, 0.1 in a low-load scenario and 0.05 in a high-load scenario, to avoid overloading of the detection task caused by too high concentration value of a single node.

[0095] The link survival duration is counted in the following way: the duration from the link establishment time to the link interruption or timeout deletion time. If the link survival duration exceeds a preset stable threshold (for example, 30 seconds), the virtual pheromone concentration is additionally increased by a timeout proportion.

[0096] The timeout ratio is calculated as follows: the link survival time is reduced by the preset stable threshold, and then divided by the preset stable threshold to obtain a timeout ratio coefficient. For example, the preset stable threshold is 30 seconds, and the survival time of a certain link is 50 seconds, so the timeout ratio coefficient is (50-30) / 30≈0.67, and the additional concentration value is 0.67×preset increment value. If the link survival time is less than 30 seconds, no additional weighting is triggered.

[0097] At the end of each collection period, a preset decay rate is applied to the virtual pheromone concentration to generate an updated virtual pheromone concentration. The preset decay rate is set according to the network topology change frequency, for example, in a scenario where the average node moving speed is 2 meters per second, the decay rate is set to 5%; in a high dynamic scenario where the average node moving speed is 5 meters per second, the decay rate is increased to 10%.

[0098] The decay calculation method is: the current virtual pheromone concentration is multiplied by (1-decay rate) to obtain the updated concentration value. For example, the current concentration of node A is 3.0, and the decay rate is 5%, so the updated concentration is 3.0×0.95=2.85.

[0099] In a specific implementation scenario, if node B successfully forwards the probe packet 20 times within a preset period of 30 seconds, and the preset increment value is 0.1, then the basic concentration increment is 20×0.1=2.0; if the survival time of a link maintained by it is 50 seconds (more than the preset stable threshold of 30 seconds), the timeout ratio coefficient is (50-30) / 30≈0.67, and the additional concentration increment is 0.67×0.1=0.067, and the total increment is 2.0+0.067=2.067; if the decay rate is 5%, then the updated concentration is 2.067×0.95≈1.96.

[0100] If node C successfully forwards the probe packet 15 times within the same period and the link survival time is 25 seconds (not more than the preset stable threshold), then the basic concentration increment is 15×0.1=1.5, and there is no additional increment, and the updated concentration is 1.5×0.95=1.425.

[0101] For example, in a disaster rescue scenario, if a group of nodes stably forward probe packets in a cooperative search and rescue task and maintain long-lived links, their virtual pheromone concentration remains above the threshold, and they are suitable as high-priority probe nodes; if the nodes frequently move in the field monitoring, causing link interruption, and the virtual pheromone concentration is below the threshold due to the decay rate and low forwarding quantity, then their probe priority is reduced.

[0102] It is worth noting that the virtual pheromone concentration here is a quantitative index generated by simulating the ant colony pheromone diffusion mechanism, which represents the contribution and stability of the node in path maintenance by calculating the weighted cumulative value of the number of successfully forwarded probe packets and the link survival time, and its value increases dynamically with the forwarding behavior and decreases periodically according to the preset decay rate.

[0103] The high-priority probe node is screened under the connectivity critical state, which is specifically:

[0104] The virtual pheromone concentration of all nodes in the current network is calculated to generate a virtual pheromone concentration set, which contains the virtual pheromone concentration of each node.

[0105] The group mean of the virtual pheromone concentration set is calculated, which is the arithmetic mean of the virtual pheromone concentrations of all nodes. The calculation method is to add all the values in the concentration set and divide by the total number of nodes.

[0106] For example, there are 10 nodes in the network, and the total virtual pheromone concentration is 25.0, so the group mean is 25.0 / 10 = 2.5. If the virtual pheromone concentration of node D is 3.0 (higher than the mean 2.5), and the virtual pheromone concentration of node E is 2.0 (lower than the mean 2.5), then node D meets the concentration screening condition, and node E does not meet it.

[0107] At the same time, the obstacle avoidance coordination angle variance of each node is obtained.

[0108] Finally, the nodes that meet the following two conditions are screened as high-priority probe nodes:

[0109] The obstacle avoidance coordination angle variance is lower than the preset coordination threshold: indicating that the node movement direction is consistent with the group coordination;

[0110] The virtual pheromone concentration is higher than the group mean: indicating that the node's contribution in historical path maintenance is higher than the average level.

[0111] The setting basis of the preset coordination threshold is: in the historical running data of the network, when the obstacle avoidance coordination angle variance is lower than a certain threshold, the path breaking probability of the node group is significantly reduced. By statistical analysis of the variance distribution of network splitting events, combined with the node density and mobility characteristics, the threshold is dynamically adjusted to ensure that the screening condition adapts to the group coordination needs of different scenarios.

[0112] For example, in the historical running data of the network, when the obstacle avoidance coordination angle variance is lower than 20 degrees, the path breaking probability of the node group is reduced by 60% compared to the scenario where the variance is higher than 20 degrees. Therefore, by statistical analysis of the variance distribution data of at least 100 network splitting events, the threshold is set to 20 degrees, and the threshold is dynamically adjusted according to the number of nodes per square kilometer in different node density scenarios.

[0113] For example, in disaster rescue scenarios, node H has an obstacle avoidance coordination angle variance of 18 (lower than 20) and a virtual pheromone concentration of 3.2 (higher than the group average of 2.5), so it is marked as a high-priority detection node; node I has a variance of 22 (higher than 20) and a concentration of 3.0 (higher than the average), so it is excluded. In the field monitoring scenario, node J has a variance of 15 (lower than 20) but a concentration of 2.3 (lower than the average of 2.5), so it is also not a high-priority node.

[0114] Adjusting the detection message sending frequency according to the moving speed of the high-priority detection node, comprising:

[0115] Extracting the moving speed of the high-priority detection node. The moving speed is calculated by the change in position coordinates of the node in the adjacent two collection periods, specifically: the difference between the position coordinates of the current period and the position coordinates of the previous period is divided by the time interval of the collection period. For example, node A moves 50 meters in two periods of 10 seconds, so the moving speed is 50 meters / 10 seconds = 5 meters / second.

[0116] The preset speed threshold is set according to the network dynamics, for example, in a scenario where the average moving speed of nodes is 3 meters / second, the preset speed threshold is set to 4 meters / second, and when the moving speed of a node exceeds 4 meters / second, it is determined to be in a high-speed moving state.

[0117] When the moving speed of the high-priority detection node exceeds the preset speed threshold, the detection message sending frequency is increased to the first preset multiple of the reference frequency. The reference frequency is the message sending frequency set by the initial detection task, for example, 1 per second; the first preset multiple is set according to the speed exceeding ratio, for example, 1.5 times when the speed exceeds the threshold by 20%, and 2 times when the speed exceeds the threshold by 50%.

[0118] For example, the moving speed of node B is 6 meters / second (exceeding the threshold of 4 meters / second), the reference frequency is 1 per second, and the first preset multiple is 2, so the adjusted frequency is 2 per second.

[0119] At the same time, the moving direction dispersion of the high-priority detection node is extracted. The moving direction dispersion is calculated by the azimuth variance of the moving direction vector of the node group, specifically: the azimuth of the moving direction of all nodes is calculated, and the square of the standard deviation is calculated. The preset dispersion threshold is set according to the group coordination demand, for example, it is set to 20 degrees in the cooperative search and rescue scenario, and when the dispersion exceeds 20 degrees, it is determined that the moving direction of the node group is dispersed. For example, the moving direction dispersion of the node group is 25 degrees (exceeding the threshold of 20 degrees), so the frequency adjustment is triggered.

[0120] When the moving direction dispersion exceeds the preset dispersion threshold, the probe message sending frequency is increased to a second preset multiple of the reference frequency. The second preset multiple is set according to the dispersion exceeding ratio, for example, when the dispersion exceeds the threshold of 10 degrees, the multiple is 1.2 times, and when the dispersion exceeds 20 degrees, the multiple is 1.5 times. For example, the dispersion of the node group is 30 degrees (exceeding the threshold of 20 degrees), the reference frequency is 1 per second, and the second preset multiple is 1.5 times. Therefore, the adjusted frequency is 1.5 per second.

[0121] If the high-priority probe node simultaneously satisfies the moving speed exceeding the preset speed threshold and the moving direction dispersion exceeding the preset dispersion threshold, the first preset multiple and the second preset multiple are added to adjust the probe message sending frequency. For example, the moving speed of node C triggers the first multiple of 2 times, and the dispersion triggers the second multiple of 1.5 times, and the total multiple is 3 times after adding. When the reference frequency is 1 per second, it is adjusted to 3 per second.

[0122] When the moving speed does not exceed the preset speed threshold and the moving direction dispersion does not exceed the preset dispersion threshold, the probe message sending frequency is restored to the reference frequency. For example, the moving speed of node D is 3 meters per second (not exceeding the threshold of 4 meters per second), and the dispersion is 15 degrees (not exceeding the threshold of 20 degrees). Therefore, the reference frequency of 1 per second is maintained.

[0123] According to the probe results, the stability weight of each path is calculated, and the path with a stability weight higher than a preset weight threshold is selected as the main transmission link, and the rest are used as backup links, including:

[0124] First, the link survival duration of the path is counted. The link survival duration is the duration from the establishment time to the interruption or deletion time of the path, which is normalized according to the proportion of the survival duration to the total probe duration. The total probe duration is the cumulative duration of all probe tasks within a preset period, for example, in a 30-minute period, if the survival duration of a certain link is 15 minutes, the survival duration proportion is 15 / 30=0.5. If the path is deleted due to node movement or signal interruption, the survival duration stops counting.

[0125] Secondly, the residual energy of all nodes in the path is obtained. The residual energy is periodically collected by the built-in energy sensor of the node, and the arithmetic mean of the residual energy of all nodes in the path is taken. For example, a certain path includes node A (residual energy 80%), node B (residual energy 70%), and node C (residual energy 60%), and the arithmetic mean is (80+70+60) / 3=70%. If the node energy is lower than the critical value (for example, 20%), a low-energy warning is triggered, but it still participates in the average value calculation.

[0126] Next, the signal strength fluctuation rate of the path is extracted. The signal strength fluctuation rate is calculated by continuously collecting received signal strength values during the path's survival period and calculating the ratio of the standard deviation to the mean of these strength values. For example, if the mean of the received signal strength of a certain path during the survival period is -75 dBm and the standard deviation is 5 dBm, then the fluctuation rate is 5 / 75 ≈ 0.067. If the path signal strength fluctuates violently (e.g., the standard deviation exceeds 30% of the mean), the fluctuation rate is marked as 0.3.

[0127] After dimensionless processing of the link survival duration ratio, the average of the node residual energy, and the signal strength fluctuation rate, a weighted product is generated to generate the stability weight of the path. The calculation method of the weighted product is: W = L α × E β × (1-S) γ ; where W represents the stability weight of the path; L represents the link survival duration ratio, with a value range of 0 to 1; E represents the average of the node residual energy, expressed in percentage (e.g., 70% is converted to 0.7); S represents the signal strength fluctuation rate, with a value range of 0 to 1; α, β, and γ are the weight indices of the link survival duration ratio, the average of the node residual energy, and the signal strength fluctuation rate, respectively.

[0128] The setting of the weight indices (α, β, and γ) is based on network operation requirements and historical path stability data, and the primary and secondary relationships are assigned by analyzing the influence of different parameters on the path breakage probability: the link survival duration ratio reflects the time stability of the path, giving it a higher weight; the average of the node residual energy represents energy sustainability, giving it a medium weight; the signal strength fluctuation rate measures signal reliability, giving it a lower weight. The specific index values are determined by simulating the correlation between each parameter and the path survival rate, and are periodically optimized and adjusted according to the dynamic characteristics of the network.

[0129] Finally, paths with a stability weight higher than a preset weight threshold are selected as the main transmission link. The preset weight threshold is set according to the historical path success rate, for example, when the weight threshold is set to 0.6, the path with a weight of 0.80 is selected as the main link, and the path with a weight of 0.46 is downgraded to a backup link.

[0130] For example, in a field monitoring scenario, if a path has a weight of 0.55 (slightly lower than the threshold of 0.6) due to frequent node movement, it is still used as a backup link and only activated when the main link is interrupted.

[0131] When the signal strength fluctuation of the main transmission link is abnormal, switch to the path with the highest stability weight in the backup link, including:

[0132] Continuously monitor the signal strength fluctuation rate of the main transmission link. If the signal strength fluctuation rate of the main transmission link exceeds the preset fluctuation threshold for 3 consecutive sampling periods, the switching mechanism is triggered.

[0133] The preset fluctuation threshold is set according to historical communication quality data, for example, when the fluctuation rate exceeds 0.1, it is determined to be abnormal.

[0134] The stability weight of all paths in the backup link list is obtained, for example, the backup link list contains path X (stability weight 0.85), path Y (0.72), and path Z (0.68), and path X is selected as the target switching path. If the weights of multiple paths are the same, the path with a higher average residual energy of nodes is selected.

[0135] It is verified whether the current signal strength fluctuation rate of the target switching path is lower than that of the main transmission link, and the verification process includes: at the moment of switching decision, the received signal strength value of the target switching path is collected in real time, and the current signal strength fluctuation rate is calculated. For example, the signal strength fluctuation rate of the main transmission link is 0.12 (exceeding the threshold 0.1), and the current signal strength fluctuation rate of the target switching path X is 0.08 (lower than 0.1 and lower than the main link 0.12), which meets the switching condition. If the current signal strength fluctuation rate of the target switching path is abnormal (such as reaching 0.15), the path is skipped and the path Y with the second highest weight is selected for re-verification.

[0136] When the switching is performed, the data stream is migrated from the main transmission link to the target switching path, and the transmission task of the original main link is interrupted. For example, in a disaster rescue scene, the main transmission link is caused by the rapid movement of nodes to rise to 0.13, and after switching to the backup link X, the data stream continues to be transmitted through path X.

[0137] After the switching is completed, the original main transmission link is downgraded to a backup link, and its stability weight is updated. The updating method is: the weight is recalculated according to the survival time length of the downgraded link, the residual energy of the nodes and the latest signal strength fluctuation rate.

[0138] In a field monitoring scene, if the main transmission link is caused by environmental interference to rise to 0.11 (exceeding the threshold 0.1), and the stability weight of the backup link Y is 0.75 and the current fluctuation rate is 0.09, then switch to link Y. If the fluctuation rate of link Y rises to 0.12 in the next period after switching, the switching mechanism is triggered again, and the path Z with the highest weight in the remaining backup link is selected for verification.

[0139] The setting basis of the preset fluctuation threshold is: in the historical running data of the network, when the signal strength fluctuation rate exceeds 0.1, the data packet loss rate in the scene with a fluctuation rate lower than 0.1 increases by 50%, therefore by counting at least 100 communication interruption events, the threshold is set to 0.1. The updating frequency of the stability weight is synchronized with the detection period, which ensures that the backup link list reflects the path state in real time.

[0140] It is worth noting that in specific implementation, if the node group in the cooperative search and rescue task causes the main link fluctuation rate to be abnormal due to sudden obstacles, the system quickly switches to the standby link to ensure continuous transmission of the rescue command. If the node group is dispersed and moved in the field, causing the fluctuation rates of multiple standby links to exceed the standard, the path reconstruction mechanism is started instead of forced switching.

[0141] The above formulas are dimensionless numerical calculations, and the formulas are obtained by software simulation of a large amount of data to obtain a formula closest to the actual situation. The preset parameters and threshold values in the formula are set by a person skilled in the art according to the actual situation.

[0142] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center and the like containing one or more available medium sets. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0143] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and module described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0144] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the division of the above-described device embodiment is merely an example, and there can be other division manners. For example, the modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, devices or modules, and can be in electrical, mechanical or other forms.

[0145] The modules illustrated as separated components can or can not be physically separated, and the components illustrated as modules can or can not be physical modules, and can be located in one place, or can be distributed on a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0146] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can be physically present alone, or two or more modules can be integrated into one module.

[0147] If the functions are realized in the form of software function modules and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part of the prior art that contributes to the technical solutions or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program codes that can be stored in the medium.

[0148] The above description is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0149] Finally: the above only for the preferred embodiments of the present application, and not for limiting the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application, should be included in the scope of protection of the present application.

Claims

1. A dead zone self-organizing network communication system, characterized by, Comprise: Node parameter acquisition module: periodically acquire node parameters of network nodes, node parameters including position coordinates and communication radius; Connectivity criticality determination module: calculate average node spacing and moving direction dispersion based on node parameters to determine whether the network is in connectivity critical state; Probe node screening module: screen high-priority probe nodes under connectivity critical state; Dynamic probe control module: adjust probe message sending frequency according to moving speed of high-priority probe nodes; Multi-path generation module: calculate stability weight of each path according to probe results, select paths with stability weight higher than preset weight threshold as main transmission links, and the rest as backup links, including: Statistical path link survival time, link survival time is the duration from path establishment to interruption or deletion, and is normalized according to the proportion of survival time in total probe time; Obtain the average value of node residual energy of all nodes in the path; Extract the signal strength fluctuation rate of the path, which is the ratio of the standard deviation to the mean of the received signal strength during path transmission; Weighted product of link survival time proportion, node residual energy average value and signal strength fluctuation rate to generate path stability weight; Select paths with stability weight higher than preset weight threshold as main transmission links, and the rest as backup links; Data shunting execution module: switch to the path with the highest stability weight in the backup link when the signal strength fluctuation of the main transmission link is abnormal.

2. The system of claim 1, wherein, The specific method for screening high-priority probe nodes is: Nodes with obstacle avoidance coordination angle variance below preset coordination threshold and virtual pheromone concentration higher than group average are selected as high-priority probe nodes; Wherein, the group average is the arithmetic average of the virtual pheromone concentrations of all nodes.

3. The system of claim 1, wherein Periodically acquire node parameters of network nodes, including: Trigger active acquisition period according to preset time interval, obtain position coordinates through beacon interaction between nodes in active acquisition period, and inversely calculate communication radius through signal strength; When the instantaneous change rate of node received signal strength exceeds the preset change threshold, trigger event-driven acquisition period, update position coordinates through multi-hop cooperative positioning in event-driven acquisition period, and dynamically calibrate communication radius according to the maximum effective communication distance of adjacent nodes.

4. The system of claim 1, wherein, Calculate average node spacing and moving direction dispersion based on node parameters to determine whether the network is in connectivity critical state, including: Traverse the position coordinates of all nodes, calculate the Euclidean distance between each pair of nodes, remove the node pairs with Euclidean distance greater than communication radius, and take the arithmetic average of the distance of the remaining node pairs as the average node spacing; Extract the position coordinate change of each node in adjacent two acquisition periods to generate a moving direction vector, and calculate the moving direction dispersion of the node group based on the azimuth of the moving direction vector; If the average node spacing exceeds the preset multiple of the communication radius and the moving direction dispersion is higher than the preset dispersion threshold, it is determined that the network is in connectivity critical state.

5. The system of claim 2, wherein, The method for obtaining obstacle avoidance coordination angle variance is: Based on the generated moving direction vector, select all adjacent nodes within the corresponding communication radius for each node; The geometric included angle between the computing node and the moving direction vector of each adjacent node is converted into an angle value by a vector dot product formula; The geometric included angle of all adjacent node pairs is counted, and the variance of the geometric included angle is calculated as the obstacle avoidance coordination angle variance.

6. The system of claim 2, wherein, The method for obtaining the virtual pheromone concentration is: Count the number of successfully forwarded probe packets by the node within a preset period, and increase the virtual pheromone concentration by a preset increment value for each successful forwarding; According to the link survival time maintained by the node, the virtual pheromone concentration is weighted, and the link with a survival time exceeding a preset stable threshold is additionally increased in concentration value by an overtime proportion; At the end of each collection period, a preset decay rate is applied to the virtual pheromone concentration to generate an updated virtual pheromone concentration.

7. The system of claim 1, wherein Adjust the probe packet sending frequency according to the moving speed of the high-priority probe node, including: Extract the moving speed of the high-priority probe node, and when the moving speed exceeds a preset speed threshold, increase the probe packet sending frequency to a first preset multiple of the reference frequency; Extract the moving direction dispersion of the high-priority probe node, and when the moving direction dispersion exceeds a preset dispersion threshold, increase the probe packet sending frequency to a second preset multiple of the reference frequency; If the moving speed exceeds the preset speed threshold and the moving direction dispersion exceeds the preset dispersion threshold, add the first preset multiple and the second preset multiple to adjust the probe packet sending frequency; If the moving speed does not exceed the preset speed threshold and the moving direction dispersion does not exceed the preset dispersion threshold, restore the probe packet sending frequency to the reference frequency.

8. The system of claim 1, wherein, When the signal strength of the main transmission link fluctuates abnormally, switch to the path with the highest stability weight in the standby link, including: Continuously monitor the signal strength fluctuation rate of the main transmission link, and determine it as abnormal when the signal strength fluctuation rate exceeds a preset fluctuation threshold; Obtain the stability weight of all paths in the standby link list, and select the path with the highest stability weight as the target switching path; Verify whether the current signal strength fluctuation rate of the target switching path is lower than that of the main transmission link, and if so, perform switching; After switching, downgrade the original main transmission link to a standby link and update the stability weight.

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