WSN node throwing type deployment method based on pre-solution set diversity ant colony algorithm

Abstract

The invention provides a WSN node throwing type deployment method based on a pre-solution set diversity ant colony algorithm, and mainly solves the problem of high deployment cost of wireless sensor network nodes. According to the method, a WSN node deterministic deployment scheme is combined with an aircraft or an unmanned aerial vehicle, an optimal route and a deployment strategy are obtained according to a determined ground advantageous deployment position, the throwing deployment operation is performed according to the optimal route and the deployment strategy, and automatic aerial throwing deployment of the WSN nodes is realized. Compared with a commonly-used uniform high-density deployment throwing type deployment scheme, under the same terrain condition and under the same coverage condition, the number of needed nodes can be reduced by 70% or above.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless sensor network deployment, and mainly relates to a WSN node scattering deployment method based on a pre-resolution set diversity ant colony algorithm. Background Art

[0002] A wireless sensor network (WSN) is a distributed sensor network, often called the "nerve endings" of the Internet of Things (IoT). It is a crucial component of the IoT and primarily consists of wireless sensor nodes capable of sensing various types of information. Each sensor node possesses sensing, communication, and computing capabilities. Numerous nodes form a self-organizing network system through single or multi-hop connections. This network system offers real-time sensing, information collection, fusion, and transmission capabilities, and is widely used in military exploration, environmental monitoring, emergency communications, and other fields.

[0003] In a hostile environment, due to the uncontrollable deployment environment, personnel are inaccessible during ground deployment, making it impossible to deploy and configure nodes. In post-disaster emergency communication scenarios, the safety of the deployment area cannot be guaranteed, which may cause casualties during ground deployment and increase unnecessary costs. Therefore, there is a practical need to deploy detection nodes in harsh environments using a scattering method. With the continuous development of the aviation industry, small aircraft are widely used in various fields due to their flexible maneuverability. In existing research, high-density node scattering deployment strategies are usually relied upon to improve network coverage capabilities. However, this solution not only significantly increases network deployment costs, but also leads to data redundancy due to overlapping node sensing areas, which in turn increases network communication load. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies and reduce the deployment cost of wireless sensor network nodes, the present invention provides a WSN node scattering deployment method based on a pre-solved set diversity ant colony algorithm. This method combines the WSN node deployment solution with aircraft or drones, autonomously planning operations according to planned paths and preset deployment strategies, and achieving automated aerial scattering deployment of WSN nodes.

[0005] A WSN node scattering deployment method based on pre-solved set diversity ant colony algorithm includes the following steps: Step 1: Build a grid terrain model based on the digital elevation model (DEM) of the target deployment area , determine the map accuracy , the map accuracy is expressed as the length of each unit in the terrain model of the deployment area rice; Step 2: The ground advantageous deployment location of wireless sensor network nodes is , , is the number of wireless sensor network nodes; Indicates the The horizontal coordinate of the ground advantage deployment position, Indicates the The vertical coordinate of the ground advantage deployment position, Indicates the The height of each ground advantage deployment position; Step 3: Construct speed decision domain; The speed decision domain is constructed based on the equal-mode vector; the speed decision domain includes Speed ​​Decision Strategy , Each speed decision strategy includes a speed vector and a speed vector direction angle; the module value of the speed vector of each speed decision strategy is the same; the speed vector direction angle of each speed decision strategy is different; The speed decision strategy is constructed by: setting the speed vector direction angle in Uniform discretization is performed within the range; that is, For the The direction angle of the velocity vector, , is the discrete interval of the velocity vector direction angle; ,when When continuously covering the entire unit circle; Step 4: Determine the drop point position corresponding to each ground advantage deployment position, and construct a pre-solution set using the drop point position; Step 5: Construct a subset of the pre-solution set; Step 6: Use the ant colony algorithm to perform path planning on the pre-solution set and the sub-set to obtain the optimal route; Step 7: According to the location of each waypoint in the optimal route , determine the first A speed decision strategy is used as the The optimal speed decision strategy for the optimal ground deployment position; Step 8: At the Waypoint The wireless sensor network nodes are A speed decision strategy, the landing position That is The actual deployment position corresponding to the optimal ground deployment position.

[0006] Furthermore, the steps of determining the throwing point position corresponding to each ground advantageous deployment position and constructing a pre-solution set using the throwing point position are as follows: Step 4-1: According to Calculation of falling displacement of wireless sensor network nodes The downtime of wireless sensor network nodes ; For the first A ground advantage deployment position, Falling displacement of wireless sensor network nodes for: (1) in, For the throwing height, For the The height of the ground advantageous deployment position of the wireless sensor network node; calculate the The downtime of wireless sensor network nodes for: (2) in, is the mass of the node, is the air friction coefficient of the node, is the Lambert W function, is the acceleration due to gravity; Step 4-2: According to The downtime of wireless sensor network nodes Get the first Motion time series of wireless sensor network nodes ; Set time discrete intervals , will The downtime of wireless sensor network nodes Discretize according to the following formula to obtain The first node of the wireless sensor network Sports moments for: (3) in, , , Indicates floor operation; All movement moments of wireless sensor network nodes constitute a time series ; is a discrete time interval; Step 4-3: Calculate the first The wireless sensor network node Under the speed decision strategy, the first The horizontal displacement sequence of the movement moments is obtained by The axis components and The weight of the axis; Substitute the motion time series obtained in step 4-2 into the following formula to obtain The wireless sensor network node Under the speed decision strategy, the first Horizontal displacement at each moment of motion for: (4) in, is the wind speed vector, For the A speed decision strategy; The horizontal displacements at all moments of the falling process constitute the horizontal displacement sequence ; In formula (4), when the wind speed vector is The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; When the wind speed vector is the wind speed vector in The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; Step 4-4: Calculate the first The horizontal position of the throwing point , according to The horizontal position of the throwing point Get the first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at each moment of movement; The value of the last moment of the horizontal displacement sequence obtained in step 4-3, that is, Substituting into formula (5), we get The horizontal position of the throwing point : (5) Further, according to formula (6), we can get The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment : (6) in, and They are exist Axis and Axial component; Falling location Indicates the The wireless sensor network node Under the speed decision strategy, the first Horizontal position at each moment of movement; when hour, , which is the horizontal position corresponding to the throwing point ,Right now ; when hour, , which is the horizontal position of the corresponding landing point, and The horizontal position of a ground advantage deployment position Approximately, that is ;like Small enough, then ; Step 4-5: Get the first The first wireless sensor network node falls during The vertical displacement sequence of each movement moment; then the first During the falling process of wireless sensor network nodes, The vertical position of the fall at each moment of movement; Substitute the motion time series obtained in step 4-2 into equation (7) to obtain The first wireless sensor network node falls during The vertical displacement sequence of the movement moments : (7) The vertical displacements at all moments of the fall constitute the vertical displacement sequence ; According to formula (8), we can get During the falling process of wireless sensor network nodes, The vertical position of the fall at each moment of movement : (8) Falling vertical position point Indicates the The wireless sensor network node The vertical position at each moment of movement; hour, , which is the vertical position of the corresponding throwing point, that is, the throwing height ,then ;when hour, , which is the vertical position of the corresponding landing point, is close to the height of the advantageous deployment position on the ground, that is, ;like Small enough, then ; Step 4-6: Combine the horizontal position point of the fall with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at the moment of movement are obtained, thereby obtaining the The throwing point position and landing point position corresponding to the advantageous deployment position; The first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at the first moment of movement is combined with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at each movement moment ; when When it is 0, ; For the The throwing point position corresponding to the advantageous deployment position; when for hour, For the The landing position corresponding to the advantageous deployment position; Step 4-7: Surface model based on the fall level location point and deployment area , get the corresponding ground projection height ; For the The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment and deploying regional surface models , the corresponding ground projection height is calculated using bilinear interpolation ; Step 4-8: Construct a pre-solution set based on the coordinates of the falling position; First, set the pre-solution set to an empty set; for If both conditions A and B are met, the throwing point position corresponding to the falling position coordinates will be included in the pre-solution set; if both conditions A and B are not met, the throwing point position corresponding to the falling position coordinates will be considered as an invalid position and will not be included in the pre-solution set; The condition A is: like Within the deployment area boundaries, that is: ,and , in , Respectively represent the maximum and minimum values ​​of the deployment area in the x-axis direction, , Respectively represent the maximum and minimum values ​​of the deployment area in the y-axis direction; The condition B is: Falling location coordinates Corresponding ground projection height and The difference is greater than the safety distance ,Right now .

[0007] Furthermore, the steps of dividing the pre-set into multiple groups are: At all throwing points In the classification, according to the ground advantage deployment position, the corner mark The throwing point positions with the same value are divided into one category, and we get categories, The categories are episodes; each episode contains A throwing point position.

[0008] Furthermore, the ant colony algorithm is used to perform path planning on the pre-solution set and the sub-set. The steps to obtain the optimal route are as follows: Step 6-1: Calculate the pheromone concentration at each casting point; the initial value of the pheromone concentration at each casting point is 1; initialize the minimum route distance ;The minimum route distance is ; Step 6-2: Construct a route based on pheromone concentration; According to the pheromone concentration at each casting point, Select the first Throwing point position As the first Waypoints , , will All the throwing point positions in the set are added to the taboo table, and the A throwing point position, The drop point positions form the route in sequence; Step 6-3: Calculate route distance based on route ; Route distance for: (9) like , then let ; and record this time The location of the waypoint , the order in which the routes are formed and their position in the collection ;in Indicates the Waypoints are selected from The first Throwing point position; Use the ant colony pheromone update algorithm to update the pheromone concentration at each casting point; Determine whether the current number of iterations has reached the preset maximum number of iterations. If the current number of iterations is greater than or equal to the maximum number of iterations, proceed to step 6-4. If the current number of iterations is less than the maximum number of iterations, clear the taboo table and return to step 6-2 to construct a route based on the updated pheromone concentration. Step 6-4: The route corresponding to the minimum route distance is the optimal route; at this time Minimum, recorded The location of the waypoint The formed route is the optimal route.

[0009] Furthermore, the ant colony pheromone update algorithm is an ant ring algorithm.

[0010] The present invention combines a deterministic WSN node deployment scheme with aircraft or drones, deriving an optimal route and deployment strategy based on a defined advantageous ground deployment location. This strategy then performs a drop-and-dump deployment operation, achieving automated aerial drop-and-dump deployment of WSN nodes. Compared to the commonly used, uniform, high-density drop-and-dump deployment scheme, this method can reduce the number of nodes required by over 70% to achieve equivalent coverage under the same terrain conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a flow chart of the present invention; Figure 2 It is the restored topographic map of the deployment area; Figure 3 This is a schematic diagram of the speed decision domain division.

[0012] Figure 4 It is aimed at Figure 2 Diagram of the deployment results for the deployment area shown. DETAILED DESCRIPTION

[0013] The technical solution adopted by the present invention to solve the technical problem is a WSN node scattering deployment method based on the pre-solved set diversity ant colony algorithm, comprising the following steps: Step 1: Build a grid terrain model based on the digital elevation model (DEM) of the target deployment area , determine the map accuracy , the map accuracy is expressed as the length of each unit in the terrain model of the deployment area rice; Step 2: The ground advantageous deployment location of wireless sensor network nodes is , , is the number of wireless sensor network nodes; Indicates the The horizontal coordinate of the ground advantage deployment position, Indicates the The vertical coordinate of the ground advantage deployment position, Indicates the The height of each ground advantage deployment position; Step 3: Construct speed decision domain; The speed decision domain is constructed based on the equal-mode vector; the speed decision domain includes Speed ​​Decision Strategy , Each speed decision strategy includes a speed vector and a speed vector direction angle; the module value of the speed vector of each speed decision strategy is the same; the speed vector direction angle of each speed decision strategy is different; The speed decision strategy is constructed by: setting the speed vector direction angle in Uniform discretization is performed within the range; that is, For the The direction angle of the velocity vector, , is the discrete interval of the velocity vector direction angle; ,when When continuously covering the entire unit circle; Step 4: Determine the drop point position corresponding to each ground advantage deployment position, and construct a pre-solution set using the drop point position; Step 4-1: According to Calculation of falling displacement of wireless sensor network nodes The downtime of wireless sensor network nodes ; For the first A ground advantage deployment position, Falling displacement of wireless sensor network nodes for: (1) in, For the throwing height, For the The height of the ground advantageous deployment position of the wireless sensor network node; calculate the The downtime of wireless sensor network nodes for: (2) in, is the mass of the node, is the air friction coefficient of the node, is the Lambert W function, is the acceleration due to gravity; Step 4-2: According to The downtime of wireless sensor network nodes Get the first Motion time series of wireless sensor network nodes ; Set time discrete intervals , will The downtime of wireless sensor network nodes Discretize according to the following formula to obtain The first node of the wireless sensor network Sports moments for: (3) in, , , Indicates floor operation; All movement moments of wireless sensor network nodes constitute a time series ; Step 4-3: Calculate the first The wireless sensor network node Under the speed decision strategy, the first The horizontal displacement sequence of the movement moments is obtained by The axis components and The weight of the axis; Substitute the motion time series obtained in step 4-2 into the following formula to obtain The wireless sensor network node Under the speed decision strategy, the first Horizontal displacement at each moment of motion for: (4) in, is the wind speed vector, For the A speed decision strategy; The horizontal displacements at all moments of the falling process constitute the horizontal displacement sequence ; In formula (4), when the wind speed vector is The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; When the wind speed vector is the wind speed vector in The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; Step 4-4: Calculate the first The horizontal position of the throwing point , according to The horizontal position of the throwing point Get the first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at each moment of movement; The value of the last moment of the horizontal displacement sequence obtained in step 4-3, that is, Substituting into formula (5), we get The horizontal position of the throwing point : (5) Further, according to formula (6), we can get The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment : (6) in, and They are exist Axis and Axial component; Falling location Indicates the The wireless sensor network node Under the speed decision strategy, the first Horizontal position at each moment of movement; when hour, , which is the horizontal position corresponding to the throwing point ,Right now ; when hour, , which is the horizontal position of the corresponding landing point, and The horizontal position of a ground advantage deployment position Approximately, that is ;like Small enough, then ; Step 4-5: Get the first The first wireless sensor network node falls during The vertical displacement sequence of each movement moment; then the first During the falling process of wireless sensor network nodes, The vertical position of the fall at each moment of movement; Substitute the motion time series obtained in step 4-2 into equation (7) to obtain The first wireless sensor network node falls during The vertical displacement sequence of the movement moments : (7) The vertical displacements at all moments of the fall constitute the vertical displacement sequence ; According to formula (8), we can get During the falling process of wireless sensor network nodes, The vertical position of the fall at each moment of movement : (8) Falling vertical position point Indicates the The wireless sensor network node The vertical position at each moment of movement; hour, , which is the vertical position of the corresponding throwing point, that is, the throwing height ,then ;when hour, , which is the vertical position of the corresponding landing point, is close to the height of the advantageous deployment position on the ground, that is, ;like Small enough, then ; Step 4-6: Combine the horizontal position point of the fall with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at the moment of movement are obtained, thereby obtaining the The throwing point position and landing point position corresponding to the advantageous deployment position; The first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at the first moment of movement is combined with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at each movement moment ; when When it is 0, ; For the The throwing point position corresponding to the advantageous deployment position; when for hour, For the The landing position corresponding to the advantageous deployment position; Step 4-7: Surface model based on the fall level location point and deployment area , get the corresponding ground projection height ; For the The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment and deploying regional surface models , the corresponding ground projection height is calculated using bilinear interpolation ; Step 4-8: Construct a pre-solution set based on the coordinates of the falling position; First, set the pre-solution set to an empty set; for If both conditions A and B are met, the throwing point position corresponding to the falling position coordinates will be included in the pre-solution set; if both conditions A and B are not met, the throwing point position corresponding to the falling position coordinates will be considered as an invalid position and will not be included in the pre-solution set; The condition A is: like Within the deployment area boundaries, that is: ,and , in , Respectively represent the maximum and minimum values ​​of the deployment area in the x-axis direction, , Respectively represent the maximum and minimum values ​​of the deployment area in the y-axis direction; The condition B is: Falling location coordinates Corresponding ground projection height and The difference is greater than the safety distance ,Right now ; Step 5: Construct a subset of the pre-solution set; At all throwing points In the classification, according to the ground advantage deployment position, the corner mark The throwing point positions with the same value are divided into one category, and we get categories, The categories are episodes; each episode contains Throwing point position; Step 6: Use the ant colony algorithm to perform path planning on the pre-solution set and the sub-set to obtain the optimal route; Step 6-1: Calculate the pheromone concentration at each casting point; the initial value of the pheromone concentration at each casting point is 1; initialize the minimum route distance ;The minimum route distance is ; Step 6-2: Construct a route based on pheromone concentration; According to the pheromone concentration at each casting point, Select the first Throwing point position As the first Waypoints , , will All the throwing point positions in the set are added to the taboo table, and the A throwing point position, The drop point positions form the route in sequence; Step 6-3: Calculate route distance based on route ; Route distance for: (9) like , then let ; and record this time The location of the waypoint , the order in which the routes are formed and their position in the collection ;in Indicates the Waypoints are selected from The first Throwing point position; Use the ant colony pheromone update algorithm to update the pheromone concentration at each casting point; Determine whether the current number of iterations has reached the preset maximum number of iterations. If the current number of iterations is greater than or equal to the maximum number of iterations, proceed to step 6-4. If the current number of iterations is less than the maximum number of iterations, clear the taboo table and return to step 6-2 to construct a route based on the updated pheromone concentration. Step 6-4: The route corresponding to the minimum route distance is the optimal route; at this time Minimum, recorded The location of the waypoint The route formed is the optimal route; Step 7: According to the location of each waypoint in the optimal route , determine the first A speed decision strategy is used as the The optimal speed decision strategy for the optimal ground deployment position; Step 8: At the Waypoint The wireless sensor network nodes are A speed decision strategy, the landing position That is The actual deployment position corresponding to the optimal ground deployment position.

[0014] Ant colony pheromone update algorithms include ant ring algorithm, ant quantity algorithm and ant density algorithm; The ant ring algorithm is used to update the pheromone concentration at the throwing point position. Global information is used. In each iteration, the best path is selected from multiple paths as the optimal path for this iteration. Under the same number of iterations, the path is optimal; under the condition of obtaining the optimal path, the number of iterations is the least.

[0015] The present invention will be further described below with reference to the accompanying drawings and examples.

[0016] by Figure 2 Taking the deployment environment shown as an example, the technical solution in the embodiment of the present invention is described.

[0017] Step 1: Build a grid terrain model based on the digital elevation model (DEM) of the target deployment area ,like Figure 2 As shown, the horizontal accuracy of the map , that is, each horizontal unit length in the deployment area terrain model represents ; There is no scaling in the vertical direction, that is, the vertical unit length is expressed ; Step 2: The ground advantageous deployment location of wireless sensor network nodes is , , For the number of wireless sensor network nodes, set 5 ground advantage deployment locations, namely ; Indicates the The horizontal coordinate of the ground advantage deployment position, Indicates the The vertical coordinate of the ground advantage deployment position, Indicates the The height of each ground advantage deployment position; Step 3: Construct speed decision domain; The speed decision domain is constructed based on the equal-mode vector; the speed decision domain includes Speed ​​Decision Strategy , Each speed decision strategy includes a speed vector; the module value of the speed vector of each speed decision strategy is the same; the direction angle of the speed vector of each speed decision strategy is different; Set the discrete interval of the velocity vector direction angle ,at this time ; The speed decision strategy is constructed by: setting the speed vector direction angle in Uniform discretization is performed within the range, which is the speed decision strategy; , For the The direction angle of the velocity vector; The speed vectors corresponding to all speed decision strategies in the speed decision domain are described using graphical representation as follows: Figure 3 As shown, all velocity vector moduli are ; Step 4: Determine the throwing point position corresponding to each advantageous deployment position to form a pre-solution set; Step 4-1: A ground advantage deployment position, Falling displacement of wireless sensor network nodes for: (1) in, For the throwing height, set , For the The height of the ground advantageous deployment location of the wireless sensor network node, for The maximum value among the heights of the ground advantage deployment positions; calculate the The downtime of wireless sensor network nodes : (2) in, is the mass of the node, is the air friction coefficient of the node, is the Lambert W function, is the acceleration due to gravity; set , , ; Step 4-2: The downtime of wireless sensor network nodes Discretize according to the following formula to obtain Motion time series of wireless sensor network nodes : (3) in, , , Indicates rounding down operation, setting time discrete interval ; Indicates the The first node of the wireless sensor network A sports moment; Step 4-3: Substitute the fall time series obtained in step 4-2 into the following formula to obtain The wireless sensor network node Under the speed decision strategy, the first The horizontal displacement sequence of the movement moment : (4) in, is the wind speed vector, For the A speed decision strategy; set the wind speed vector modulus to , the direction is the positive direction of the x-axis; In formula (4), when the wind speed vector is The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; When the wind speed vector is the wind speed vector in The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; Step 4-4: Calculate the first The horizontal position of the throwing point , and then according to The horizontal position of the throwing point Get the first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at each moment of movement; The value of the last moment of the horizontal displacement sequence obtained in step 4-3, that is, Substituting into the following formula, we get No. The wireless sensor network node The horizontal position of the corresponding throwing point under the speed decision strategy : (5) in, and They are exist Axis and Axial component, is the horizontal accuracy of the map; Further, the following formula is used to calculate the The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment : (6) in, and They are exist Axis and Axial component; Indicates the The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each moment of movement; hour, , which is the horizontal position of the corresponding throwing point ,Right now ;when hour, , which is the horizontal position of the corresponding landing point, and The horizontal position of a ground advantage deployment position Approximately, that is ;like Small enough, then ; Step 4-5: Substitute the fall time series obtained in step 4-2 into the following formula to obtain The first wireless sensor network node falls during The vertical displacement sequence of the movement moments : (7) Substitute into the following formula to get During the falling process of wireless sensor network nodes, The vertical position of the fall at each moment of movement : (8) Indicates the The wireless sensor network node The vertical position at each moment of movement; hour, , which is the vertical position of the corresponding throwing point, that is, the throwing height ,then ;when hour, , which is the vertical position of the corresponding landing point, is close to the height of the advantageous deployment position on the ground, that is, ;like Small enough, then ; Step 4-6: Combine the horizontal position point of the fall with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at the moment of movement are obtained, thereby obtaining the The throwing point position and landing point position corresponding to the advantageous deployment position; The first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at the first moment of movement is combined with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at each movement moment ; when When it is 0, ; For the The throwing point position corresponding to the advantageous deployment position; when for hour, For the The landing position corresponding to the advantageous deployment position; Step 4-7: Surface model based on the fall level location point and deployment area , get the corresponding ground projection height ; For the The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment and deploying regional surface models , the corresponding ground projection height is calculated using bilinear interpolation ; Step 4-8: Construct a pre-solution set based on the coordinates of the falling position; First, set the pre-solution set to an empty set; for If both conditions A and B are met, the throwing point position corresponding to the falling position coordinates will be included in the pre-solution set; otherwise, if both conditions A and B are not met, the throwing point position corresponding to the falling position coordinates will be considered as an invalid position and will not be included in the pre-solution set; The condition A is: like Within the deployment area boundaries, that is: ,and , in , Respectively represent the maximum and minimum values ​​of the deployment area in the x-axis direction, , Respectively represent the maximum and minimum values ​​of the deployment area in the y-axis direction; The condition B is: Falling location coordinates Corresponding ground projection height and The difference is greater than the safety distance ,Right now ; Set safe distance ,Right now ; Step 5: Pre-decode and divide the data into groups; At all throwing points In the classification, according to the ground advantage deployment position, the corner mark The throwing point positions with the same value are divided into one category, and we get categories, The categories are episodes; each episode contains at most Throwing point position; Step 6: Use the ant colony algorithm to perform path planning on the pre-solution set and the sub-set to obtain the optimal route; Step 6-1: Calculate the pheromone concentration at each casting point; the initial value of the pheromone concentration at each casting point is 1; initialize the initial route distance ;The value of the initial route distance is ; Step 6-2: Construct a route based on pheromone concentration; According to the pheromone concentration at each casting point, Select the first Throwing point position As the first Waypoints , , will All the throwing point positions in the set are added to the taboo table, and the A throwing point position, The drop point positions form the route in sequence; Step 6-3: Calculate route distance : (9) like , then let ; and record this time The location of the waypoint , the order in which the routes are formed and their position in the collection ;in Indicates the Waypoints are selected from The first Throwing point position; Use the ant colony pheromone update algorithm to update the pheromone concentration at each casting point; Determine whether the current number of iterations has reached the preset maximum number of iterations. If the current number of iterations is less than the maximum number of iterations, clear the taboo table and return to step 6-2 to construct a route based on the updated pheromone concentration. Step 6-4: At this time Minimum, recorded The location of the waypoint The route formed is the optimal route; Step 7: According to the location of each waypoint in the optimal route , determine the first A speed decision strategy is used as the The optimal speed decision strategy for the optimal ground deployment position; Step 8: At the Waypoint The wireless sensor network nodes are A speed decision strategy, the landing position That is The actual deployment position corresponding to the optimal ground deployment position.

[0018] The final actual deployment situation is as follows Figure 4 As shown in the figure, the expected deployment position is the ground advantage deployment position, and the actual deployment position is the deployment position obtained by adopting the optimal speed decision strategy at the predetermined waypoint.

Claims

1. A WSN node scattering deployment method based on pre-solution set diversity ant colony algorithm, characterized in that: The steps include: Step 1: Build a grid terrain model based on the digital elevation model (DEM) of the target deployment area , determine the map accuracy; Step 2: The ground advantageous deployment location of wireless sensor network nodes is , , is the number of wireless sensor network nodes; Indicates the The horizontal coordinate of the ground advantage deployment position, Indicates the The vertical coordinate of the ground advantage deployment position, Indicates the The height of each ground advantage deployment position; Step 3: Construct speed decision domain; The speed decision domain is constructed based on the equal-mode vector; the speed decision domain includes Speed ​​Decision Strategy , ; Each speed decision strategy includes a speed vector and a speed vector direction angle; the module value of the speed vector of each speed decision strategy is the same; the speed vector direction angle of each speed decision strategy is different; The speed decision strategy is constructed by: setting the speed vector direction angle in Uniform discretization is performed within the range; that is, For the The direction angle of the velocity vector, , is the discrete interval of the velocity vector direction angle; ,when When continuously covering the entire unit circle; Step 4: Determine the drop point position corresponding to each ground advantage deployment position, and construct a pre-solution set using the drop point position; Step 5: Construct a subset of the pre-solution set; Step 6: Use the ant colony algorithm to plan the path of the pre-solution set and the sub-set to obtain the optimal route and the location of the waypoints in the optimal route in the sub-set. ;in Indicates the Waypoints are selected from The first Throwing point position; Step 7: According to the location of each waypoint in the optimal route , determine the first A speed decision strategy is used as the The optimal speed decision strategy for the optimal ground deployment position; Step 8: Use the first The landing point obtained by the first speed decision strategy is the The actual deployment position corresponding to the optimal ground deployment position.

2. The WSN node scattering deployment method based on the pre-solution set diversity ant colony algorithm according to claim 1 is characterized in that: The steps of determining the throwing point position corresponding to each ground advantageous deployment position and constructing a pre-solution set using the throwing point position are as follows: Step 4-1: According to Calculation of falling displacement of wireless sensor network nodes The downtime of wireless sensor network nodes ; For the first A ground advantage deployment position, Falling displacement of wireless sensor network nodes for: (1) in, For the throwing height, For the The height of the ground advantageous deployment position of the wireless sensor network node; calculate the The downtime of wireless sensor network nodes for: (2) in, is the mass of the node, is the air friction coefficient of the node, is the Lambert W function, is the acceleration due to gravity; Step 4-2: According to The downtime of wireless sensor network nodes Get the first Motion time series of wireless sensor network nodes ; Set time discrete intervals , will The downtime of wireless sensor network nodes Discretize according to the following formula to obtain The first node of the wireless sensor network Sports moments for: (3) in, , , Indicates floor operation; All movement moments of wireless sensor network nodes constitute a time series ; Step 4-3: Calculate the first The wireless sensor network node Under the speed decision strategy, the first The horizontal displacement sequence of the movement moments is obtained by The axis components and The weight of the axis; Substitute the motion time series obtained in step 4-2 into the following formula to obtain The wireless sensor network node Under the speed decision strategy, the first Horizontal displacement at each moment of motion for: (4) in, is the wind speed vector, For the A speed decision strategy; The horizontal displacements at all moments of the falling process constitute the horizontal displacement sequence ; In formula (4), when the wind speed vector is The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; When the wind speed vector is the wind speed vector in The speed decision strategy is the speed decision strategy in When the axis components are exist Axis component ; Step 4-4: Calculate the first The horizontal position of the throwing point , according to The horizontal position of the throwing point Get the first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at each moment of movement; The value of the last moment of the horizontal displacement sequence obtained in step 4-3, that is, Substituting into formula (5), we get The horizontal position of the throwing point : (5) Further, according to formula (6), we can get The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment : (6) in, and They are exist Axis and Axial component; Falling location Indicates the The wireless sensor network node Under the speed decision strategy, the first Horizontal position at each moment of movement; when hour, , which is the horizontal position corresponding to the throwing point ,Right now ; when hour, , which is the horizontal position of the corresponding landing point, and The horizontal position of a ground advantage deployment position Approximately, that is ;like Small enough, then ; Step 4-5: Get the first The first wireless sensor network node falls during The vertical displacement sequence of each movement moment; then the first During the falling process of wireless sensor network nodes, The vertical position of the fall at each moment of movement; Substitute the motion time series obtained in step 4-2 into equation (7) to obtain The first wireless sensor network node falls during The vertical displacement sequence of the movement moments : (7) The vertical displacements at all moments of the fall constitute the vertical displacement sequence ; According to formula (8), we can get During the falling process of wireless sensor network nodes, The vertical position of the fall at each moment of movement : (8) Falling vertical position point Indicates the The wireless sensor network node The vertical position at each moment of movement; hour, , which is the vertical position of the corresponding throwing point, that is, the throwing height ,then ;when hour, , which is the vertical position of the corresponding landing point, is close to the height of the advantageous deployment position on the ground, that is, ;like Small enough, then ; Step 4-6: Combine the horizontal position point of the fall with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at the moment of movement are obtained, thereby obtaining the The throwing point position and landing point position corresponding to the advantageous deployment position; The first The wireless sensor network node Under the speed decision strategy, the first The horizontal position point of the fall at the first moment of movement is combined with the vertical position point of the fall to obtain the The wireless sensor network node Under the speed decision strategy, the first The coordinates of the falling position at each movement moment ; when When it is 0, ; For the The throwing point position corresponding to the advantageous deployment position; when for hour, For the The landing position corresponding to the advantageous deployment position; Step 4-7: Surface model based on the fall level location point and deployment area , get the corresponding ground projection height ; For the The wireless sensor network node Under the speed decision strategy, the first The horizontal position of the fall at each movement moment and deploying regional surface models , the corresponding ground projection height is calculated using bilinear interpolation ; Step 4-8: Construct a pre-solution set based on the coordinates of the falling position; First, set the pre-solution set to an empty set; for If both conditions A and B are met, the throwing point position corresponding to the falling position coordinates will be included in the pre-solution set; if both conditions A and B are not met, the throwing point position corresponding to the falling position coordinates will be considered as an invalid position and will not be included in the pre-solution set; The condition A is: like Within the deployment area boundaries, that is: ,and , in , Respectively represent the maximum and minimum values ​​of the deployment area in the x-axis direction, , Respectively represent the maximum and minimum values ​​of the deployment area in the y-axis direction; The condition B is: Falling location coordinates Corresponding ground projection height and The difference is greater than the safety distance ,Right now .

3. The WSN node scattering deployment method based on the pre-solution set diversity ant colony algorithm according to claim 1 is characterized in that: The steps of the pre-set division are: At all throwing points In the classification, according to the ground advantage deployment position, the corner mark The throwing point positions with the same value are divided into one category, and we get categories, The categories are episodes; each episode contains A throwing point position.

4. The WSN node scattering deployment method based on the pre-solution set diversity ant colony algorithm according to claim 1 is characterized in that: Using the ant colony algorithm, the path planning is performed on the pre-solution set and the sub-solution set. The steps to obtain the optimal route are as follows: Step 6-1: Calculate the pheromone concentration at each casting point; the initial value of the pheromone concentration at each casting point is 1; initialize the minimum route distance ; The minimum route distance is ; Step 6-2: Construct a route based on pheromone concentration; According to the pheromone concentration at each casting point, Select the first Throwing point position As the first Waypoints , , will All the throwing point positions in the set are added to the taboo table, and the A throwing point position, The drop point positions form the route in sequence; Step 6-3: Calculate route distance based on route ; Route distance for: (9) like , then let ; and record this time The location of the waypoint , the order in which the routes are formed and their position in the collection ;in Indicates the Waypoints are selected from The first Throwing point position; Use the ant colony pheromone update algorithm to update the pheromone concentration at each casting point; Determine whether the current number of iterations has reached the preset maximum number of iterations. If the current number of iterations is greater than or equal to the maximum number of iterations, proceed to step 6-4. If the current number of iterations is less than the maximum number of iterations, clear the taboo table and return to step 6-2 to construct a route based on the updated pheromone concentration. Step 6-4: The route corresponding to the minimum route distance is the optimal route; at this time Minimum, recorded The location of the waypoint The formed route is the optimal route.

5. The WSN node scattering deployment method based on the pre-solution set diversity ant colony algorithm according to claim 4 is characterized in that: The ant colony pheromone update algorithm is the ant ring algorithm.

6. A computer-readable storage medium storing a computer program; wherein: When the computer program is executed by a processor, a WSN node scattering deployment method based on a pre-solution set diversity ant colony algorithm according to any one of claims 1 to 5 is implemented.

7. A terminal device comprising a processor, a memory, and a computer program stored in the memory; characterized in that: When the processor executes the computer program, the WSN node scattering deployment method based on the pre-solution set diversity ant colony algorithm according to any one of claims 1 to 5 is implemented.

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