Unmanned aerial vehicle charging scheduling method based on uneven clustering and related system

Abstract

The application discloses a kind of unmanned aerial vehicle charging scheduling method and related system based on uneven clustering, carries out ring to wireless sensor network, determines the cluster radius of outermost ring and the number of clusters according to the maximum communication radius between nodes;Cluster head selection is carried out, nodes upload data to cluster head, and sequentially uploaded to base station by cluster head;The flight height of unmanned aerial vehicle in the ring is obtained by cluster radius;After node sends charging request, unmanned aerial vehicle calculates charging time in each ring, and charges each cluster according to certain order.The application can improve the charging efficiency of unmanned aerial vehicle for wireless sensor network, prolong the life cycle of wireless sensor network, and alleviate energy hole problem.

Description

TECHNICAL FIELD

[0001] The application relates to a non-uniform clustering-based unmanned aerial vehicle charging scheduling method and a related system based on a wireless sensor network, and belongs to the technical field of wireless sensor network charging. BACKGROUND

[0002] Wireless sensor networks, as a promising technology, are widely used in intelligent transportation, biological medicine, agricultural monitoring, manufacturing, etc. These applications require the network to have a long life cycle to achieve long-term monitoring and data collection.

[0003] However, sensor nodes are generally small in size and have very limited battery capacity, so energy limitation has become a bottleneck problem restricting the development of wireless sensor networks. It is difficult to maintain long-term work of nodes by replacing batteries due to the large number of node deployments and wide distribution range, and how to supply energy to nodes and prolong the life cycle of the network has become a research focus.

[0004] In the wireless sensor network, nodes collect data and then transmit the data to the sink node through multi-hop forwarding. Some nodes need to collect data and also undertake the task of forwarding, and the closer to the sink node, the heavier the task, which may lead to the energy hole problem. The energy hole problem can be alleviated by non-uniform clustering of nodes.

[0005] With the development of wireless energy transmission technology, there are currently two ways of wireless charging vehicles (WCV) and unmanned aerial vehicles (UAV) to supply energy to sensor nodes. Compared with wireless charging vehicles, unmanned aerial vehicles can move in three-dimensional free space and can realize one-to-many charging. SUMMARY

[0006] The application aims to prolong the life cycle of the wireless sensor network, and provides a non-uniform clustering-based unmanned aerial vehicle charging scheduling method, which prolongs the life cycle of the network by non-uniform clustering of the network and unmanned aerial vehicle charging scheduling.

[0007] Technical scheme: In order to achieve the above purpose, the technical scheme adopted by the application is:

[0008] A kind of unmanned aerial vehicle charging scheduling method based on uneven clustering, the wireless sensor network is divided into ring, and the node in wireless sensor network is clustered;The node closest to the cluster center in each cluster is selected as the cluster head node, and the node uploads data to the cluster head node, and the cluster head node is sequentially uploaded to the base station;The cluster radius of the outermost ring and the number of clusters are determined according to the maximum communication radius between nodes;The flight height of the unmanned aerial vehicle in the ring is obtained by the cluster radius;According to the relationship between the cluster radius of adjacent two rings, the cluster radius of adjacent inner ring is obtained from the cluster radius of outer ring, and the number of corresponding clusters and the flight height of unmanned aerial vehicle are obtained;After the node sends a charging request, the unmanned aerial vehicle calculates the charging time in each ring, and charges each cluster in a certain order. Specifically, it includes the following steps:

[0009] Step 1, the wireless sensor network is divided into K circular rings with different widths, the nodes in each circular ring form a plurality of tangent circular clusters, and each cluster is tangent to the inner and outer edges of the circular ring. The number of clusters in each layer of circular ring and the cluster radius of each layer of circular ring are determined according to the maximum communication radius between nodes and the radius of the unmanned aerial vehicle projection area.

[0010] Step 2, the flight height of the unmanned aerial vehicle corresponding to each layer of circular ring is obtained according to the cluster radius of each layer of circular ring.

[0011] Step 3, the node closest to the cluster center in each cluster is selected as the cluster head, the nodes in each cluster transmit data to the cluster head through single hop, the cluster head selects the cluster head in the adjacent inner ring of the ring where it is located as the next hop, and sends data to the cluster head through single hop, and finally transmits to the base station.

[0012] Step 4, when the residual energy of a cluster head in the first ring is lower than , send a charging request to the unmanned aerial vehicle, the battery capacity of the node E. After receiving the request, the unmanned aerial vehicle starts the first cycle of charging from the base station, charges the cluster according to the flight height corresponding to the cluster radius during charging, and returns to the base station after the first cycle of charging is completed.

[0013] Step 5, the unmanned aerial vehicle returns to the base station and starts the next cycle of charging.

[0014] Preferably, the method for determining the number of clusters in each layer of circular ring and the cluster radius of each layer of circular ring according to the maximum communication radius between nodes and the radius of the unmanned aerial vehicle projection area in step 1 is as follows:

[0015] Step 11, according to the cluster radius in the outermost ring and the maximum communication radius r t between nodes, the number of clusters n K of the Kth layer is obtained, and then the cluster radius r K of the Kth layer is obtained, if the number of clusters n KIf not, take the value of its upward rounding, and recalculate the cluster radius r in the outermost ring K .

[0016] Step 12, from the K-1 ring, according to the cluster radius of the adjacent outer ring, the cluster radius and the number of clusters in each ring except the outermost ring are calculated in turn, until the obtained cluster radius is less than The ring where the cluster with the cluster radius less than is taken as the first ring. The ring width of the i-th ring is 2r i , at this time the network is divided into K circular rings.

[0017] Preferred: the method of calculating the cluster radius and the number of clusters in each ring except the outermost ring in step 12 according to the cluster radius of the adjacent outer ring: let j=0, for the K-j ring and the K-j-1 ring, according to the cluster radius r K-j of the K-j ring, the cluster radius r K-j-1 of the K-j-1 ring is calculated, and according to r K-j-1 , the flight height h K-j-1 of the UAV in the K-j-1 ring and the number of clusters n K-j-1 are calculated, if n K-j-1 is not an integer, take the value of its upward rounding, and calculate r K-j-1 , then let the value of j increase by 1, continue to repeat the above calculation steps, until the obtained cluster radius is less than The ring where the cluster with the cluster radius less than is taken as the first ring, and the value of K is j+2.

[0018] The relationship between the cluster radius r K-j of the K-j ring and the cluster radius r K-j-1 of the K-j-1 ring is:

[0019]

[0020] Wherein, r K-j represents the cluster radius of the K-j ring, r K-j-1 represents the cluster radius of the K-j-1 ring, K is the number of circular rings, r i is the cluster radius of the i-th ring, i=K-j, K-j+1, K-j+2, …, K, R i is the outer radius of the i-th ring, and p is the density.

[0021] Preferred: the method of step 3 is that a vertical ray is made from the center of the wireless sensor network upwards, and intersects with the inner and outer circumferences of each ring at two points. For the i-th circular ring, the midpoint between the two points is taken as the center, and r iDraw a circle with the radius, forming the first cluster in the i-th ring. In the clockwise direction, form the tangential cluster in turn. Select the node closest to the cluster center in each cluster as the cluster head. The nodes in each cluster transmit data to the cluster head through single hop. The cluster head selects the cluster head in the adjacent inner ring of the ring it is in as the next hop, and sends data to the cluster head through single hop. Finally, the data is transmitted to the base station.

[0022] Preferably, the method of step 4 is:

[0023] When the residual energy of a cluster head in the first ring is lower than , send a charging request to the UAV, and the battery capacity of the node. After receiving the request, the UAV starts charging in the first cycle from the base station. The UAV selects the cluster in which the cluster head with the lowest residual energy in the first ring as the first cluster to be charged, and then charges each cluster in the clockwise direction in turn. The hovering time of the UAV at the hovering point above each cluster in the same ring is the same. After charging the last cluster in the ring, select the cluster in which the cluster head in the adjacent outer ring is closest to the cluster head of the cluster as the starting point of charging in the ring, and select the direction closer to the cluster with the lowest residual energy of the cluster head in the ring as the flight direction of the UAV. If the cluster with the lowest residual energy of the cluster head in the current ring is the starting point of the UAV, the UAV flies in the clockwise direction. The UAV charges the nodes in each layer from the inside out in turn until the last cluster in the outermost layer is charged, and returns to the base station along a straight line. The first charging cycle is completed. The hovering time of the UAV at the hovering point above each cluster in the i-th circular ring is t i , and the first charging cycle is T1.

[0024] Preferably, the method of step 5 is:

[0025] The UAV returns to the base station and starts charging in the next cycle. For the second and subsequent cycles, the hovering time of the UAV at the hovering point above each cluster in the i-th circular ring is t i ′ , the charging cycle is T, and the energy consumption rate of the cluster head in the i-th ring is P i , the charging amount of the UAV for the cluster head in the i-th ring is P i T, if it is greater than the battery capacity of the cluster head, the cluster head will be charged to full capacity.

[0026] Preferably, the wireless sensor network is a network formed by N homogeneous nodes randomly and uniformly distributed in a plane area without obstacles with a density of p. The wireless sensor network is fixed in position, and its nodes have sensing, communication and computing capabilities, and are equipped with wireless charging coils based on magnetic coupling resonance for receiving wireless energy supply from the UAV. The maximum communication radius between nodes is r t, the radius of the network is R, and a base station is located at the center of the network, collects the sensing data of all nodes in the network, and supplements the energy of the unmanned aerial vehicle.

[0027] Another object of the present application is to provide an unmanned aerial vehicle charging scheduling system based on uneven clustering of a wireless sensor network, comprising a circular ring cluster division unit, a flight height determination unit, a circular ring cluster encoding unit, a first cycle scheduling execution unit, and a next cycle scheduling execution unit.

[0028] The circular ring cluster division unit is used to divide the wireless sensor network into K circular rings with different widths, and the nodes in each circular ring form a plurality of tangent circular clusters, each cluster being tangent to the inner and outer edges of the circular ring. The number of circular ring clusters in each layer and the cluster radius of each layer are determined according to the maximum communication radius between nodes and the radius of the unmanned aerial vehicle projection area.

[0029] The flight height determination unit is used to obtain the flight height of the unmanned aerial vehicle corresponding to each layer of circular ring according to the cluster radius of each layer of circular ring.

[0030] The circular ring cluster encoding unit is used to select the node closest to the cluster center in each cluster as the cluster head, and each node in the cluster transmits data to the cluster head through single hop, the cluster head selects the cluster head in the adjacent inner ring of the ring it is located as the next hop, and sends data to the cluster head through single hop, and finally transmits to the base station.

[0031] The first cycle scheduling execution unit is used to send a charging request to the unmanned aerial vehicle when the residual energy of a cluster head in the first ring is lower than When the unmanned aerial vehicle receives the request, it starts the first cycle of charging from the base station, charges the cluster according to the flight height corresponding to the cluster radius during charging, and returns to the base station after the first cycle of charging is completed.

[0032] The next cycle scheduling execution unit is used to start the next cycle of charging after the unmanned aerial vehicle returns to the base station.

[0033] Another object of the present application is to provide an electronic device, comprising at least one processor, at least one memory and a communication interface. The processor, memory and communication interface communicate with each other. The memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the unmanned aerial vehicle charging scheduling method based on uneven clustering.

[0034] Compared with the prior art, the present application has the following beneficial effects:

[0035] By dividing the network into rings and unevenly clustering nodes according to the energy consumption of the cluster head in each ring, the energy hole problem is effectively alleviated, the nodes can successfully forward data, and the network energy utilization rate is improved. Meanwhile, one-to-many charging is carried out by using a UAV, the UAV is dispatched to supplement the energy of the nodes, the energy demand of the nodes is maximally met, and the network life cycle is prolonged. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 Fig. 1 is a schematic diagram of the network structure of the present application. For emphasis, only part of the sensing nodes in the network are symbolically shown in the figure;

[0037] Figure 2 Fig. 2 is a schematic diagram of the formation of clusters in the outermost ring of the network of the present application;

[0038] Figure 3 Fig. 3 is a schematic diagram of the charging scheduling route of the UAV of the present application;

[0039] Figure 4 Fig. 4 is a flowchart of the clustering calculation method of the present application. DETAILED DESCRIPTION

[0040] The present application will be further illustrated below in conjunction with the drawings and specific examples, which should be understood as merely illustrating the present application and not limiting the scope of the present application. After reading the present application, those skilled in the art can make various modifications to the equivalent forms of the present application, which all fall within the scope defined by the appended claims of the present application.

[0041] EMBODIMENT

[0042] A UAV charging scheduling method based on uneven clustering, as shown in Fig. 1, comprises the following steps: Figures 1-4

[0043] Step 1: divide the wireless sensor network into K circular rings with different widths, form several tangent circular clusters in each circular ring, and each cluster is tangent to the inner and outer edges of the circular ring. Determine the number of clusters in each circular ring and the cluster radius of each circular ring according to the maximum communication radius between nodes and the radius of the UAV projection area.

[0044] In another embodiment, the wireless sensor network (hereinafter referred to as "network") is a network formed by randomly and uniformly distributing N isomorphic sensing nodes (hereinafter referred to as "nodes") with a density of p in a plane area without obstacles. The wireless sensor network is fixed in position, its nodes have sensing, communication and computing capabilities, and are equipped with a wireless charging coil based on magnetic coupling resonance for receiving wireless energy supply from the UAV. The maximum communication radius between nodes is r t , the radius of the network is R, and a base station is located at the center of the network to collect sensing data of nodes in the entire network and supplement energy for the UAV. ​

[0045] In another embodiment, the network is divided into K annular rings with different widths, the outermost ring is the Kth ring, the nodes in each annular ring form a number of tangent circular clusters, each cluster is tangent to both the inner and outer edges of the annular ring. The outer radius of the ith ring is denoted as R i , the cluster radius in the ring is denoted as r i , and the number of clusters is denoted as n i (i∈[1,K]).

[0046] In another embodiment, the method for determining the number of clusters in each annular ring and the cluster radius of each annular ring according to the maximum communication radius between nodes and the radius of the UAV projection area in step 1 is as follows:

[0047] Step 11, according to the cluster radius in the outermost ring and the maximum communication radius between nodes r t , the number of clusters in the Kth layer n K is obtained, and then the cluster radius r K of the Kth layer is obtained. If the number of clusters in the Kth layer n K is not an integer, take its upward integer value, and recalculate the value of the cluster radius r K in the outermost ring.

[0048] The UAV flies in the network at a fixed speed v, the charging expansion angle is fixed as α, the flight height of the UAV in the ith ring is denoted as h i , the UAV charges each cluster when hovering, the hovering point is located above the center of the cluster, and the radius of the UAV projection area is the cluster radius. Let the cluster radius r K in the outermost ring be r t , and thus the number of clusters in the Kth layer n K is calculated. If n K is not an integer, take its upward integer value, and recalculate the value of r K , and the flight height h K of the UAV in the outermost ring is obtained from r K .

[0049] Step 12, starting from the K-1th ring, the cluster radius and the number of clusters in each ring except the outermost ring are sequentially calculated according to the cluster radius of the adjacent outer ring, until the obtained cluster radius is less than The ring in which the cluster with a cluster radius less than is located is regarded as the first ring. The ring width of the ith ring is 2r i , and thus the network is divided into K annular rings.

[0050] Step 2, according to the cluster radius of each annular ring, the flight height of the UAV in each annular ring is obtained.

[0051] In another embodiment, the method for determining the cluster radius and number of clusters in each ring except the outermost ring is based on the cluster radius of the ring immediately adjacent to the outermost ring: Let j = 0, for the Kj-th ring and the Kj-1-th ring, based on the cluster radius r of the Kj-th ring... K-j Calculate the cluster radius r of the (Kj-1)th ring. K-j-1 And according to r K-j-1 Calculate the flight altitude h of the UAV in the Kj-1 ring. K-j-1 And the number of clusters n K-j-1 Similarly, if n K-j-1 If the value is not an integer, take its floor value and calculate r. K-j-1 Then increment the value of j by 1 and repeat the above calculation steps until the obtained cluster radius is less than 1. The cluster radius will be smaller than The ring containing the cluster is taken as the first ring, and the value of K is j+2.

[0052] The outer radius R of the Kjth ring K-j The value of is given by the following formula:

[0053]

[0054] In the formula, R K-j Let r represent the radius of the outer circle of the Kj-th ring, and R represent the radius of the wireless sensor network. K-i Let represent the cluster radius of the Ki-th ring, and j-1 represent the ring number from the K-th ring to the (K-j+1)-th ring.

[0055] The number of clusters in the Kj-th ring, n K-j The value of is given by the following formula:

[0056]

[0057] In the formula, R K-j Let r represent the outer radius of the Kj-th ring. K-j Let n represent the cluster radius of the Kj-th ring. K-j This represents the number of clusters in the Kj-th ring.

[0058] The flight altitude h corresponding to the cluster radius of the Kjth ring. K-j The value of is given by the following formula:

[0059]

[0060] In the formula, h K-j r represents the flight altitude of the UAV in the Kj ring. K-j Let Kj represent the cluster radius of the Kj-th ring, and α represent the UAV charging expansion angle.

[0061] The flight altitude h of the drone in the Kj ringK-j The relationship between the flight height h of the K-j-1 ring and the K-j ring is given by the following formula: K-j-1

[0062]

[0063] The above formula can ensure that the unmanned aerial vehicle flies at a lower height in the ring with greater cluster head energy consumption, thereby obtaining greater energy transmission efficiency. Wherein, h K-j represents the flight height of the unmanned aerial vehicle in the K-j ring, h K-j-1 represents the flight height of the unmanned aerial vehicle in the K-j-1 ring, E K-j is the total energy consumption of the cluster head in the K-j ring, and E K-j-1 is the total energy consumption of the cluster head in the K-j-1 ring.

[0064] The total energy consumption E K-j of the cluster head in the K-j ring is given by the following formula:

[0065]

[0066] Wherein, E K-j is the total energy consumption of the cluster head in the K-j ring, l is the data amount generated by the node in one period, K is the number of circular rings, r i is the cluster radius of the i ring, i = K-j, K-j+1, K-j+2, …, K, R i is the outer circle radius of the i ring, p is the density, e r is the energy consumption of the node receiving 1 bit of data, and e t is the energy consumption of the node sending 1 bit of data.

[0067] Thus, the relationship between the cluster radius r K-j of the K-j ring and the cluster radius r K-j-1 of the K-j-1 ring is:

[0068]

[0069] According to this formula, the cluster radius of each ring adjacent to the outermost ring can be sequentially obtained. Wherein, r K-j represents the cluster radius of the K-j ring, r K-j-1 represents the cluster radius of the K-j-1 ring, K is the number of circular rings, r i is the cluster radius of the i ring, i = K-j, K-j+1, K-j+2, …, K, R i is the outer circle radius of the i ring, and p is the density.

[0070] ​Step 3: Select the node closest to the cluster center in each cluster as the cluster head. Nodes in each cluster transmit data to the cluster head via a single hop. The cluster head selects the nearest cluster head in the adjacent inner ring of its ring as the next hop, and sends the data to that cluster head via a single hop, and finally transmits it to the base station.

[0071] In another embodiment, the method in step 3 is as follows: draw a vertical ray upward from the center of the wireless sensor network, intersecting the inner and outer circumferences of each ring at two points. For the i-th ring, with the midpoint between the two points as the center, r... i Draw a circle with radius i to form the first cluster in the i-th ring. Continue forming tangent clusters in a clockwise direction. Select the node closest to the cluster center in each cluster as the cluster head. Nodes within each cluster transmit data to the cluster head via a single hop. The cluster head selects the nearest cluster head in its adjacent inner ring as the next hop and sends the data to that cluster head via a single hop, finally transmitting it to the base station. The entire network is then clustered.

[0072] Step 4, when the remaining energy of a cluster head in the first ring is lower than At that time, a charging request is sent to the drone, specifying the battery capacity of node E. Upon receiving the request, the drone departs from the base station and begins the first charging cycle. During charging, the cluster is charged according to the flight altitude corresponding to the cluster radius. The first charging cycle is completed, and the drone returns to the base station.

[0073] In another embodiment, the method in step 4 is as follows:

[0074] When the remaining energy of a cluster head in the first ring is lower than At that time, a charging request is sent to the drone, specifying the battery capacity of node E. Upon receiving the request, the drone departs from the base station and begins the first charging cycle. The drone selects the cluster with the lowest remaining energy in the first ring as the first cluster to charge, and then charges each cluster sequentially in a clockwise direction. The drone's hovering time above each cluster in the same ring is the same. After charging the last cluster in the current ring, it selects the cluster with the closest remaining energy in the adjacent outer ring as the starting point for charging that ring, and chooses the direction closest to the cluster with the lowest remaining energy in that ring as its flight direction. If the cluster with the lowest remaining energy in the current ring is the drone's flight starting point, the drone flies clockwise. The drone charges the nodes of each layer sequentially from the inside out until it has completed charging the last cluster in the outermost layer, then returns to the base station in a straight line, completing the first charging cycle. The hovering time of the drone above each cluster in the i-th ring is t. i The duration of the first cycle is T1.

[0075] The hovering duration t of the drone at each cluster above the i-th ring. iis given by the following formula:

[0076]

[0077] wherein, t i is the hovering time of the UAV at the hovering point above each cluster of the i-th ring, E is the battery capacity of the node, P i is the energy consumption rate of the cluster head of the i-th ring, n i is the number of clusters of the i-th ring, R i is the outer radius of the i-th ring, r i is the cluster radius of the i-th ring, and v is the flight speed of the UAV.

[0078] The value of the first cycle time T1 is given by the following formula:

[0079]

[0080] wherein, T1 is the first cycle time, K is the number of rings, t i is the hovering time of the UAV at the hovering point above each cluster of the i-th ring, n i is the number of clusters of the i-th ring, and v is the flight speed of the UAV, and d is the path charging of the UAV to complete a cycle charging.

[0081] The value of the path charging d of the UAV to complete a cycle charging is given by the following formula:

[0082]

[0083] wherein, d is the path charging of the UAV to complete a cycle charging, K is the number of rings, R i is the outer radius of the i-th ring, r i is the cluster radius of the i-th ring, r k is the cluster radius of the k-th ring, n i is the number of clusters of the i-th ring, and R represents the radius of the wireless sensor network.

[0084] Step 5, after the UAV returns to the base station, the next cycle of charging is started.

[0085] In another embodiment, the method of starting the next cycle of charging after the UAV returns to the base station in step 5 is:

[0086] The second cycle of charging is started immediately after the UAV returns to the base station. For the second and subsequent cycles, the hovering time of the UAV at the hovering point above each cluster of the i-th ring is t i ′ , the charging cycle is T, the energy consumption rate of the cluster head of the i-th ring is P i , and the charging amount of the UAV for the cluster head of the i-th ring is P iT, if greater than the cluster head battery capacity, the cluster head to full charge.

[0087] The value of the charging period T is given by the following formula:

[0088]

[0089] Where T is the charging period, d is the path charging of the UAV to complete a cycle, v is the flight speed of the UAV, P i is the energy consumption rate of the i-th ring cluster head, P S is the energy transmission rate of the UAV, η i is the energy transmission efficiency of the UAV at the i-th layer cluster node.

[0090] The value of the energy transmission efficiency η i of the UAV at the i-th layer cluster node is given by the following formula:

[0091]

[0092] Where η i is the energy transmission efficiency of the UAV at the i-th layer cluster node, h i is the flight height of the UAV at the i-th ring, a, b, c are constant parameters.

[0093] The value of the hovering time t i ′ of the UAV at the hovering point above each cluster of the i-th ring is given by the following formula:

[0094]

[0095] Where t i ′ is the hovering time of the UAV at the hovering point above each cluster of the i-th ring, P i is the energy consumption rate of the i-th ring cluster head, T is the charging period, η i is the energy transmission efficiency of the UAV at the i-th layer cluster node, P S is the energy transmission rate of the UAV.

[0096] Simulation example

[0097] N isomorphic perception nodes (hereinafter referred to as "nodes") are randomly and uniformly distributed in a circular plane area (hereinafter referred to as "network") without obstacles with a density p, the position is fixed, the nodes have perception, communication and calculation ability, and are equipped with wireless charging coils based on magnetic coupling resonance, which are used to receive wireless energy supply from the UAV, the maximum communication radius between nodes is r t , and the radius of the network is R. In this example, r tThe value of is set to 50m, the value of R is set to 500m, and the value of ρ is set to 0.1. A base station is located at the center of the network, collecting sensing data from all nodes in the network and replenishing energy for the drones.

[0098] The network is divided into K rings of varying widths, with the outermost ring being the Kth ring. Nodes within each ring form several tangent circular clusters, each cluster being tangent to both the inner and outer edges of the ring. The drone charges one cluster each time it hovers, with the hovering point located above the cluster's center. The radius of the drone's projected area is the cluster radius. Let r be the cluster radius within the outermost ring. K =r t =50m, n is calculated using formula (2) K The value is approximately 28.21, and n K Round up to get n K =29. r is recalculated using formula (2). K The value is 48.8m. In this example, the UAV expansion angle α is set to 30°, and the flight altitude h of the UAV in the Kth ring is calculated by formula (3). K The value is 84.5m.

[0099] Let j = 0, and calculate the cluster radius of the (Kj-1)th ring using formula (6). Calculate the outer ring radius of the (Kj-1)th ring using formula (1). Similarly, calculate n using formula (2). K-j-1 The value of n. If n K-j-1 If the value is not an integer, take its floor value and recalculate r using formula (2). K-j-1 The value of j is calculated using formula (3) to determine the flight altitude of the UAV at the Kj-1th altitude, and the value of j is incremented by 1.

[0100] Repeat the above steps until the resulting cluster radius is smaller than 1. Let the ring containing these clusters be the first ring, and the width of the i-th ring be 2r. i At this point, the network can be divided into K rings, where K is j+2. In this example... The value of is 25m, and the value of K is 4, such as Figure 1 As shown.

[0101] Draw a perpendicular ray upwards from the center of the network, intersecting the inner and outer circles of each ring at two points. For the i-th ring, with the midpoint between the two points as the center, r... i Draw a circle with radius i to form the first cluster in the i-th ring. Continue forming tangent clusters in a clockwise direction, as follows: Figure 2 The shaded area is shown. The node closest to the cluster center in each cluster is selected as the cluster head node (hereinafter referred to as "cluster head"). Nodes within each cluster transmit data to the cluster head via a single hop. The cluster head selects the nearest cluster head in the adjacent outer ring of its ring and sends the data to that cluster head via a single hop, finally transmitting it to the base station, as shown below.Figure 1 The whole network is clustered as shown in the data uploading path.

[0102] The battery capacity of the node is E, when the residual energy of a cluster head in the first ring is lower than the request to the unmanned aerial vehicle. After receiving the request, the unmanned aerial vehicle starts charging in the first cycle. The unmanned aerial vehicle selects the cluster in which the cluster head with the lowest residual energy in the first ring is located as the cluster to be charged first, and then charges each cluster in the clockwise direction. The hovering time of the unmanned aerial vehicle at the hovering point above each cluster in the same ring is the same. After charging the last cluster in the ring, the cluster head in the adjacent outer ring closest to the cluster head of the cluster is selected as the starting point of charging in the ring, and the direction closer to the cluster with the lowest residual energy of the cluster head in the ring is selected as the flight direction of the unmanned aerial vehicle. If the cluster with the lowest residual energy of the cluster head in the current ring is the starting point of the unmanned aerial vehicle, the unmanned aerial vehicle flies in the clockwise direction. As shown in Figure 3 , the unmanned aerial vehicle charges each cluster in the second ring in the counterclockwise direction, and selects c as the starting point of the third ring after reaching point b. The unmanned aerial vehicle charges the nodes in each layer from the inside to the outside until the last cluster in the outermost layer is charged, and then returns to the base station along a straight line. The hovering time of the unmanned aerial vehicle in each cluster of the ith circular ring is t i , and the first charging cycle lasts for T1. In this example, the battery capacity E of the node is 2KJ, and the flight speed v of the unmanned aerial vehicle is 4m / s. t i is calculated by formula (7), and T1 is calculated by formula (8).

[0103] After the unmanned aerial vehicle returns to the base station, it starts charging in the second cycle. For the second and subsequent cycles, the hovering time of the unmanned aerial vehicle in each cluster of the ith circular ring is t i ′ , the charging cycle is T, the energy consumption rate of the cluster head in the ith ring is P i , and the charging amount of the unmanned aerial vehicle for the cluster head in the ith ring is P i T. If it is greater than the battery capacity of the cluster head, the cluster head will be charged to full power. t i ′ and T are calculated by formula (10) and formula (12) respectively.

[0104] As can be seen from the above, the present application can improve the charging efficiency of the unmanned aerial vehicle for the wireless sensor network, prolong the life cycle of the wireless sensor network, and alleviate the energy hole problem.

[0105] The above merely describes the preferred embodiments of the present application, and it should be pointed out that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, and these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A method for charging scheduling of unmanned aerial vehicles (UAVs) based on uneven clustering, characterized in that, The method comprises the following steps: Step 1, the wireless sensor network is divided into a plurality of annular rings with different widths K Each node in each annular ring forms a plurality of tangent circular clusters, and each cluster is tangent to both the inner and outer edges of the annular ring; the number of clusters in each annular ring and the cluster radius of each annular ring are determined according to the maximum communication radius between nodes and the radius of the unmanned aerial vehicle projection area; Step 2: Obtain the flight height of the UAV corresponding to each circular ring according to the cluster radius of each circular ring; Step 3: Select the node closest to the cluster center in each cluster as the cluster head, and transmit data from each node in the cluster to the cluster head through single hop, select the cluster head closest to the cluster head in the adjacent inner ring of the ring as the next hop, and transmit data to the cluster head through single hop, and finally transmit the data to the base station; Step 4, when the residual energy of a certain cluster head in the first ring is lower than a charging request is sent to the unmanned aerial vehicle, E the battery capacity of the node; after receiving the request, the unmanned aerial vehicle departs from the base station and starts charging in the first cycle, and charges the cluster at the flight height corresponding to the cluster radius during charging. After the first cycle of charging is completed, the unmanned aerial vehicle returns to the base station; Step 5: After the UAV returns to the base station, start charging in the next period.

2. The method of claim 1, wherein: The method for determining the number of clusters of each circular ring and the cluster radius of each circular ring according to the maximum communication radius between nodes and the radius of the UAV projection area in step 1 is as follows: Step 11, according to the cluster radius in the outermost ring and the maximum communication radius between nodes the number of clusters in the first layer is obtained K the number of clusters in the first layer is obtained the number of clusters in the first layer is obtained K the cluster radius of the first layer is obtained the number of clusters in the first layer is obtained K the number of clusters in the first layer is obtained the number of clusters in the first layer is obtained the cluster radius in the outermost ring is obtained Step 12, from the first K -1 ring, the cluster radius of each ring except the outermost ring and the number of clusters are sequentially calculated according to the cluster radius of the ring next to the outer ring, until the obtained cluster radius is less than , the ring where the cluster with the cluster radius less than is located is taken as the first ring; the i ring has a ring width of 2 , at this time the network is divided into K annular rings.

3. The method of claim 2, wherein: The cluster radius of each ring except the outermost ring and the number of clusters in each ring are sequentially calculated according to the cluster radius of the ring immediately outside in step 12: let j =0, for the first K - j ring, the cluster radius of the first K - j- ring is calculated according to the cluster radius of the second K - j ring , the flight height of the UAV in the first K - j- ring is calculated according to , and the number of clusters K j- is calculated according to , if is not an integer, the value is rounded up, and is calculated, then the value of j is increased by 1, and the above calculation steps are repeated until the obtained cluster radius is less than , the ring in which the cluster with the cluster radius less than is located is taken as the first ring, K , and the value of j+ is 2;​​ The first K - j The cluster radius of the ring The first K - j- 1The cluster radius of the ring is: wherein, represents the first K - j cluster radius of the ring, represents the first K - j- cluster radius of the ring, K is the number of tori, is the first i cluster radius of the ring, i=K - j , K - j+ 1, K - j+ 2,..., K , is the outer radius of the first i ring, is the density.

4. The method of claim 3, wherein: The first K - j The outer radius of the circle is given by the formula: ； wherein denotes the number of rings of the first K - j the outer radius of the ring, R denotes the radius of the wireless sensor network, denotes the number of rings of the first K - i the cluster radius of the ring, denotes the number of rings of the first K ring to the first K - j+ 1 the number of rings of the first The number of clusters of rings K - j The number of clusters of rings is given by the following equation: ； wherein represents the first K - j outer radius of the ring, represents the first K - j cluster radius of the ring, represents the first K - j number of clusters of the ring; The first K - j The cluster radius of the ring corresponds to the flight altitude is given by the following formula: ； wherein represents the flight height of the drone at the K - j ring, represents the cluster radius of the K - j ring, α represents the drone charging expansion angle; The UAV flies at a height of K - j the height of the first relationship to the height of the first K - j the height of the first is given by the following equation: wherein, represents the flight height of the UAV in the K - j ring, represents the flight height of the UAV in the K - j -1 ring, is the total energy consumption of the cluster head in the K - j ring, is the total energy consumption of the cluster head in the K - j -1 ring; The total energy consumption of the cluster head of the ring K - j The value of the total energy consumption of the cluster head of the ring is given by the following formula: wherein, is the first K - j total energy consumption of the cluster head of the ring, l is the data amount generated by the node in a cycle, K is the number of rings, is the first i radius of the ring, i=K - j , K - j+ 1, K - j+ 2, …, K , is the outer radius of the first i ring, is the density, is the energy consumption of the node to receive 1-bit data, is the energy consumption of the node to send 1-bit data.

5. The method of claim 4, wherein: Step 3 is as follows: Draw a vertical ray upward from the center of the wireless sensor network, intersecting the inner and outer circles of each ring at two points; for the first... i A ring, with the midpoint between two points as its center. Draw a circle with radius 1 to form the first circle. i The first cluster in the ring; tangent clusters are formed sequentially in a clockwise direction; the node closest to the cluster center in each cluster is selected as the cluster head, and the nodes in each cluster transmit data to the cluster head through a single hop. The cluster head selects the nearest cluster head in the adjacent inner ring of its ring as the next hop, and sends the data to that cluster head through a single hop, and finally transmits it to the base station.

6. The method of claim 5, wherein: The method of step 4 is as follows: When the residual energy of a certain cluster head in the first ring is lower than a charging request is sent to the UAV, E the battery capacity of the node; the UAV departs from the base station after receiving the request and starts charging in the first cycle; The unmanned aerial vehicle selects a cluster with the lowest residual energy of the cluster head in the first ring as the first charged cluster, and then charges each cluster in turn in the clockwise direction. The hovering time of the unmanned aerial vehicle at the hovering point above each cluster in the same ring is the same. After charging the last cluster in the ring, the cluster head of the cluster with the closest distance to the cluster head in the adjacent outer ring is selected as the starting point of charging in the ring, and the direction closer to the cluster with the lowest residual energy of the cluster head in the ring is selected as the flight direction of the unmanned aerial vehicle. If the cluster with the lowest residual energy of the cluster head in the current ring is the starting point of the unmanned aerial vehicle, the unmanned aerial vehicle flies in the clockwise direction. The unmanned aerial vehicle charges each layer of nodes in turn from the inside to the outside until the last cluster in the outermost layer is charged, returns to the base station along the straight line, and the charging of the first period is completed. i The hovering time of the unmanned aerial vehicle at the hovering point above each cluster in the first ring is , and the first period is . The hovering duration of the UAV at the hovering point above each cluster of the first circular ring i is given by the following equation: ​ ； In the formula, For drones in the i The hovering duration of the hovering point above each cluster of the rings. E The battery capacity of the node. For the first i Energy consumption rate of the ring cluster head For the first i The number of clusters in a ring, For the first i The outer radius of the ring, For the first i Cluster radius of the ring, v The flight speed of the drone; the first period length is given by the following equation: ； In the formula, is the first cycle length, K is the number of circular rings, is the hovering time of the hovering point of the unmanned aerial vehicle above each cluster of the i th circular ring, is the number of clusters of the i th circular ring, v is the flight speed of the unmanned aerial vehicle, d is the path charging of the unmanned aerial vehicle completing one cycle charging; The unmanned aerial vehicle completes a period of charging along a charging path d The value of the ratio is given by the following equation: ； In the formula, d The path for the drone to complete one charging cycle. K The number of rings. For the first i The outer radius of the ring, For the first i Cluster radius of the ring, For the first k Cluster radius of the ring, For the first i The number of clusters in a ring, R This indicates the radius of the wireless sensor network.

7. The method of claim 6, wherein, The method of step 5 is as follows: The drone begins its second charging cycle immediately upon returning to the base station; for the second and subsequent cycles, the drone... i The hovering time of the hovering point above each cluster of the rings is: The charging cycle is T , No. i The energy consumption rate of the ring cluster head is The drone is the first i The charge of the ring's cluster head is T If the charge is greater than the battery capacity of the cluster head, then charge the cluster head to full capacity. charging period T The value of t is given by the equation: ； wherein, T is the charging period, d is the path charging of the UAV to complete a cycle of charging, v is the flight speed of the UAV, is the first i energy consumption rate of the cluster head, is the energy transmission rate of the UAV, is the energy transmission efficiency of the UAV in the first i layer cluster head node; The unmanned aerial vehicle is in the first i Energy transmission efficiency of layer cluster head node The value of the transmission efficiency of the layer cluster head node is given by the following formula: ； Wherein, is the energy transmission efficiency of the cluster head node in the first layer, i is the energy transmission efficiency of the cluster head node in the first layer, is the energy transmission efficiency of the cluster head node in the first layer, i is the flight height of the ring, a , b , c is a constant parameter; The UAV hovers over each cluster of the first i annular ring for a hovering duration given by the following equation: ； wherein, is the hovering time length of the unmanned aerial vehicle at the hovering point above each cluster of the i th circular ring, is the energy consumption rate of the cluster head of the i th circular ring, T is the charging period, is the energy transmission efficiency of the unmanned aerial vehicle at the cluster head node of the i th layer, is the energy transmission rate of the unmanned aerial vehicle.

8. The method of claim 7, wherein: The wireless sensor network is N isomorphic nodes at density A network is formed by randomly and uniformly distributing nodes within an unobstructed planar area. The wireless sensor network is fixed in location, with nodes possessing sensing, communication, and computing capabilities. It is equipped with a wireless charging coil based on magnetic coupling resonance to receive wireless energy replenishment from a drone. The maximum communication radius between nodes is [missing information]. The radius of the network is R A base station is located at the center of the network, collecting perception data from all nodes in the network and replenishing energy for drones. 9.A UAV charging scheduling system based on uneven clustering of a wireless sensor network, characterized in that: The method of step 5 is as follows: The circular ring cluster division unit is used for dividing the wireless sensor network into circular rings with different widths K The nodes in each circular ring form a plurality of tangent circular clusters, each cluster being tangent to both the inner and outer edges of the circular ring; the number of circular cluster layers and the cluster radius of each circular ring layer are determined according to the maximum communication radius between nodes and the radius of the unmanned aerial vehicle projection area. The method of step 5 is as follows: The method of step 5 is as follows: The first periodic scheduling execution unit is used when the remaining energy of a cluster head in the first ring is lower than... At that time, a charging request is sent to the drone. E The battery capacity of the node; after receiving the request, the drone departs from the base station and begins the first charging cycle. During charging, the cluster is charged according to the flight altitude corresponding to the cluster radius. After the first charging cycle is completed, the drone returns to the base station. The flight height determination unit is configured to obtain the flight height of the UAV corresponding to each circular ring according to the cluster radius of each circular ring; 10. An electronic device, comprising: The cluster coding unit is configured to select the node closest to the cluster center in each cluster as the cluster head, and transmit data from each node in the cluster to the cluster head through single hop, select the cluster head closest to the cluster head in the adjacent inner ring of the ring as the next hop, and transmit data to the cluster head through single hop, and finally transmit the data to the base station; The next period scheduling execution unit is configured to start charging in the next period after the UAV returns to the base station. The method comprises: At least one processor, at least one memory and a communication interface; The processor, memory and communication interface communicate with each other; The memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the method for scheduling charging of the UAV based on uneven clustering according to any one of claims 1-8.

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