Unmanned aerial vehicle position and sensor power joint optimization method and device, and storage medium

Abstract

The invention discloses an unmanned aerial vehicle position and sensor power joint optimization method and device and a storage medium, and the method comprises the steps: building an energy efficiency optimal mathematical optimization model considering the constraints of data safety, maximum power, flight height and the like through defining the confidential transmission energy utilization efficiency of data collection; meanwhile, a problem solving process is given; therefore, joint optimization of the real-time position of the unmanned aerial vehicle and the sending power of the sensor is realized. Through joint optimization of the real-time position of the unmanned aerial vehicle and the sending power of the sensor, the safety of sensor data acquisition is ensured, and the energy utilization efficiency of the sensor is improved as much as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed wireless sensor network data acquisition based on unmanned aerial vehicles, and in particular to a method, device and storage medium for joint optimization of unmanned aerial vehicle position and sensor power. Background Art

[0002] Drones have the advantages of strong mobility, good controllability, flexible deployment, and low cost of use. They have great application prospects in the field of distributed wireless sensor network data collection. However, there are two problems in using drones to collect sensor data. One is the security of data transmission, especially the perception data of some sensitive services may be eavesdropped, tampered or destroyed by potential illegal users. The other is the limited energy of sensors. Since sensors are generally powered by batteries with limited energy, they are usually in low power or dormant states. The perception data is stored in their own memory and is only activated to send data when data is collected. How to make sensors send more data under limited energy is a problem that needs to be considered and solved.

[0003] Generally, wireless sensor network data security mostly adopts traditional encryption technology based on cryptographic theory, which has problems such as high complexity of key generation and management and large amount of calculation. For the problem of limited sensor energy, the traditional method is to send data with the lowest possible power to save energy, but the data transmission rate will also be very low. This transmission strategy is not suitable for drone-based data collection, because drone data collection has mission time requirements. Summary of the invention

[0004] The present invention proposes a method, device and storage medium for jointly optimizing the position and sensor power of a drone, which can solve at least one of the technical problems in the background technology.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for jointly optimizing the position and sensor power of a UAV includes defining the energy utilization efficiency of confidential transmission of data acquisition, establishing a mathematical optimization model for optimal energy efficiency that takes into account constraints such as data security, maximum power and flight altitude, and providing a solution process for the problem. This method further realizes the joint optimization of the real-time position of the UAV and the transmission power of the sensor.

[0007] Furthermore, by defining the energy utilization efficiency of confidential transmission of data acquisition, a mathematical optimization model for optimal energy efficiency considering constraints such as data security, maximum power and flight altitude was established, including:

[0008] Assume that the three-dimensional coordinates of the drone and the eavesdropper are (x, y, z) and (x e ,y e ,ze ); There are I sensors in total, and the position coordinates of the i-th sensor are expressed as (u i ,v i ,0), i=1,2,…,I; In practical applications, the UAV locates the sensor and the eavesdropper to obtain their positions; The distances from the i-th sensor to the UAV and the eavesdropper are expressed as:

[0009]

[0010] Based on physical layer security technology, considering sensor power constraints and flight altitude constraints, the optimization problem with the goal of maximizing sensor energy efficiency is established as follows:

[0011]

[0012] where d i and l i It has been given in equations (1) and (2); p i represents the transmission power of the i-th sensor; β0=α0 / σ 2 , α0 represents the channel power gain at a reference distance of 1 meter; σ 2 represents the variance of Gaussian white noise; p max represents the maximum power constraint of the sensor; z min and z max Indicates the minimum and maximum flight altitudes allowed by the drone; for convenience, X and P represent the position vector of the drone and the power vector of the sensor, respectively. X and P are optimization variables.

[0013] Furthermore, the problem-solving process specifically includes:

[0014] ① By introducing an auxiliary variable Γ and giving an initial value Γ (0) , the optimal solution X of problem (3) * and P * Solve the following problem through loop iteration:

[0015]

[0016] The superscript (j) indicates the number of iterations. The optimal solution to problem (4) is represented by X (j) and P (j) Indicates that it will be used for the next iteration during the loop;

[0017] ②Problem (4) Equivalent transformation; introduction of slack variables and B=(b1,b2,…,b I ), problem (4) is equivalently transformed into the following optimization problem:

[0018]

[0019] By solving problem (5), we can get the optimal solution to problem (4);

[0020] ③ Solve problem (5) iteratively; for a set of given values ​​corresponding to the optimization variables X, P, A, B Problem (5) can be approximated as the following problem:

[0021]

[0022] Wherein, the superscript (n) indicates the number of iterations;

[0023]

[0024] Given a set of initial values ​​corresponding to the optimization variables X, P, A, B By solving problem (6) iteratively, we can obtain the optimal solution to problem (5); In fact, the optimal solution of problem (6) obtained in the nth iteration will be used in the next iteration. The optimal solution of problem (6) is expressed as In this way, the optimal solution to problem (5) is obtained by iteratively solving problem (6) until convergence.

[0025] Furthermore, the specific implementation steps of the problem solving process are as follows:

[0026] S1, input the three-dimensional position coordinates of the eavesdropper and sensor (x e ,y e ,z e ) and (u i ,v i ,0),i=1,2,…,I;

[0027] S2. Given the initial value Γ of the auxiliary variable Γ (0) , j:=0;

[0028] S3, j:=j+1;

[0029] S4. Given a set of initial values ​​corresponding to the optimization variables X, P, A, B n:=0;

[0030] S5, n:=n+1;

[0031] S6. For a given Γ (j-1) and Solve problem (6) to get its optimal

[0032]

[0033] S7, determine whether the increment of the objective function value of problem (4) meets the convergence condition, if so, continue to the next step, otherwise go to step S5 and iterate until the solution of problem (4) converges;

[0034] S8, Utilizing X (j) and P (j) Find the objective function value of the original problem (3);

[0035] S9. Determine whether the increment of the objective function value of problem (3) satisfies the convergence condition. If so, return the optimal solution X of problem (3). * :=X (j) , P * :=P (j) , otherwise go to step S3 and iterate until the solution to problem (3) converges.

[0036] On the other hand, the present invention further discloses a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the above method.

[0037] On the other hand, the present invention further discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above method.

[0038] It can be seen from the above technical solutions that the method for jointly optimizing the position and sensor power of the drone of the present invention ensures the security of sensor data collection by jointly optimizing the real-time position of the drone and the sensor transmission power, while maximizing the energy utilization efficiency of the sensor. Specifically, the present invention is based on physical layer security technology, comprehensively considers the security issues and energy limitation issues of sensor data collection, and achieves the purpose of ensuring data transmission security and maximizing the energy utilization efficiency of the sensor by jointly optimizing the real-time position of the drone and the sensor transmission power.

[0039] The key points of the present invention are: by defining the energy utilization efficiency of confidential transmission of data collection, a mathematical optimization problem of optimal energy efficiency considering constraints such as data security, maximum power and flight altitude is established; the problem-solving process is given; and a joint optimization algorithm for the real-time position of the drone and the sensor transmission power is proposed.

[0040] The advantages of the present invention are as follows: based on the physical layer technology, a joint solution to data security and energy limitation problems is proposed, and the energy utilization efficiency of the sensor is maximized while ensuring the security of data transmission through joint optimization of the real-time position of the drone and the sensor transmission power. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flowchart of the present invention;

[0042] Figure 2 This is a wireless sensor network data collection scenario in which an eavesdropper exists in an embodiment of the present invention;

[0043] Figure 3 is the horizontal position corresponding to all terminals when the position of the eavesdropper in the embodiment of the present invention changes;

[0044] Figure 4 The energy efficiency of confidentiality transmission corresponding to the sensor when the position of the eavesdropper changes in the embodiment of the present invention;

[0045] Figure 5 is the confidentiality rate throughput corresponding to the sensor when the position of the eavesdropper changes in the embodiment of the present invention;

[0046] Figure 6 It is the total power corresponding to the sensor when the position of the eavesdropper changes in the embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0048] like Figure 1 As shown, a method for jointly optimizing the position and sensor power of a UAV according to an embodiment of the present invention includes defining the energy utilization efficiency of confidential transmission of data acquisition, establishing a mathematical optimization model for optimal energy efficiency that takes into account constraints such as data security, maximum power and flight altitude; and providing a problem-solving process; thereby achieving joint optimization of the real-time position of the UAV and the transmission power of the sensor.

[0049] Specifically, the embodiments of the present invention consider the actual scenario of using drones to collect distributed wireless sensor data, such as Figure 2 As shown in the figure, as the eavesdropper moves, by jointly optimizing the spatial position of the drone and the sensor transmission power, the utilization efficiency of the limited energy of the sensor can be maximized while ensuring data security.

[0050] exist Figure 2 In the process of collecting sensor data, illegal users may eavesdrop on the data. The three-dimensional position coordinates of the drone and the eavesdropper are represented as (x, y, z) and (x e ,y e ,z e There are I sensors in total, and the position coordinates of the i-th sensor are expressed as (u i ,v i,0), i=1,2,…,I. In practical applications, drones locate sensors and eavesdroppers to obtain their positions. The distances from the i-th sensor to the drone and the eavesdropper can be expressed as:

[0051]

[0052] (1) Modeling of energy efficiency optimization based on physical layer security

[0053] Based on physical layer security technology, considering sensor power constraints and flight altitude constraints, the optimization problem with the goal of maximizing sensor energy efficiency is established as follows:

[0054]

[0055] where d i and l i It has been given in equations (1) and (2); p i represents the transmission power of the i-th sensor; β0=α0 / σ 2 , α0 represents the channel power gain at a reference distance of 1 meter; σ 2 represents the variance of Gaussian white noise; p max represents the maximum power constraint of the sensor; z min and z max Indicates the minimum and maximum flight altitudes allowed by the drone; for convenience, X and P represent the position vector of the drone and the power vector of the sensor, respectively. X and P are optimization variables.

[0056] (2) Methods for solving energy efficiency optimization problems

[0057] ① By introducing an auxiliary variable Γ and giving an initial value Γ (0) , the optimal solution X of problem (3) * and P * The following problem can be solved by loop iteration:

[0058]

[0059] The superscript (j) indicates the number of iterations. The optimal solution to problem (4) is represented by X (j) and P (j) Indicates that it will be used in the next iteration during the loop.

[0060] ② Problem (4) Equivalent transformation. Introduce slack variables and B=(b1,b2,…,b I ), problem (4) is equivalently transformed into the following optimization problem:

[0061]

[0062] By solving problem (5), we can get the optimal solution to problem (4).

[0063] ③ Solve problem (5) iteratively. For a set of given values ​​corresponding to the optimization variables X, P, A, and B Problem (5) can be approximated as the following problem

[0064]

[0065] Wherein, the superscript (n) indicates the number of iterations;

[0066]

[0067] Given a set of initial values ​​corresponding to the optimization variables X, P, A, B By iteratively solving problem (6), we can obtain the optimal solution to problem (5). In fact, the optimal solution of problem (6) obtained in the nth iteration will be used in the next iteration. The optimal solution of problem (6) is expressed as In this way, the optimal solution to problem (5) can be obtained by iteratively solving problem (6) until convergence.

[0068] The specific steps of the original problem (3) are shown in Algorithm 1:

[0069] Algorithm 1: Joint optimization algorithm for drone real-time position and sensor transmission power

[0070]

[0071]

[0072] In summary, the present invention is based on physical layer security technology, comprehensively considers the security issues and energy limitation issues of sensor data acquisition, and jointly optimizes the real-time position of the drone and the sensor transmission power to ensure the security of data transmission and maximize the energy utilization efficiency of the sensor.

[0073] In order to verify the performance of the algorithm in the present invention, the proposed joint optimization algorithm of the real-time position of the UAV and the sensor transmission power is compared with the fixed power maximum distance difference minimization algorithm. The basic idea of ​​the latter algorithm is to optimize the position of the UAV so that it can cover more sensors, and then activate the sensors with positive confidentiality transmission rate to send data at maximum power. Consider 1000×1000m 2 In order to more comprehensively measure certain data in the area, the sensors are distributed in a regular grid. In order to better eavesdrop on the data, the eavesdropper's movement trajectory is a curve. Its flight altitude is fixed at 70m. It should be noted that the algorithm proposed in the present invention is applicable to any sensor distribution mode and eavesdropper movement position. The simulation parameters are shown in Table 1 below.

[0074] Table 1 Simulation parameters

[0075]

[0076]

[0077] As the eavesdropper's position changes, the position of each communication terminal changes as follows: Figure 3 As shown in the figure. The simulation results show that when the eavesdropper's position changes, the drone always maintains the lowest allowed altitude. In order to clearly observe the position change, the three-dimensional positions of the drone and the eavesdropper are projected onto the horizontal plane. From the simulation results, it can be seen that as the eavesdropper's position changes, in order to ensure the security of the data, the drone positions obtained by the two algorithms are adaptively adjusted as the eavesdropper's position changes.

[0078] Figure 4 The energy efficiency of the two algorithms is compared when the eavesdropper's position changes. The horizontal coordinate reflects the change of the eavesdropper's position. Figure 4 It can be seen that the energy efficiency of the joint optimization algorithm proposed in the present invention is significantly higher than that of the maximum distance difference minimization algorithm. At the two ends of the energy efficiency curve, the energy efficiency of the confidentiality transmission obtained by the joint optimization algorithm is higher. It is worth noting that the confidentiality rate throughput of the joint optimization is also higher than that of the maximum distance difference minimization algorithm, as shown in Figure 5 However,

[0079] However, the total power consumed by the joint optimization is not always greater than the total power consumed by the maximum distance difference minimization algorithm. Figure 6 As shown in the total power curve, at the two ends of the curve, the joint optimization algorithm consumes less power but achieves higher confidentiality rate throughput and confidentiality transmission energy efficiency.

[0080] exist Figure 6 In the simulation, the power curve obtained by the maximum distance difference minimization algorithm fluctuates greatly. This is because sometimes only a part of the sensors are selected for data transmission, and the remaining sensors remain in a dormant state to save energy. However, from the perspective of confidential transmission energy efficiency, this simple sensor energy-saving selection strategy is not optimal. Due to the global optimization of the drone position and sensor power, the joint optimization algorithm can achieve higher confidential transmission energy efficiency. It is worth noting that the joint optimization algorithm also has an implicit function of sensor selection. The simulation results show that if the channel quality of the sensor is too poor to support the data confidentiality transmission requirements, no power will be allocated to it, that is, the sensor will not be activated and will remain in a dormant state.

[0081] On the other hand, the present invention further discloses a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the above method.

[0082] On the other hand, the present invention further discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above method.

[0083] In another embodiment provided in the present application, a computer program product comprising instructions is also provided, which, when executed on a computer, enables the computer to execute any one of the methods for jointly optimizing the position and sensor power of a drone in the above-mentioned embodiments.

[0084] It is understandable that the system, device and storage medium provided in the embodiments of the present invention correspond to the method provided in the embodiments of the present invention, and the explanation, examples and beneficial effects of the relevant contents can refer to the corresponding parts in the above methods.

[0085] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive Solid State Disk (SSD)), etc.

[0086] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0087] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0088] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for joint optimization of drone position and sensor power, characterized in that: This includes defining the energy utilization efficiency of confidential transmission of data collection, establishing a mathematical optimization model for optimal energy efficiency that takes into account constraints such as data security, maximum power, and flight altitude; at the same time, giving the problem-solving process; and thus achieving the joint optimization of the real-time position of the drone and the sensor transmission power.

2. The method for joint optimization of drone position and sensor power according to claim 1, characterized in that: By defining the energy utilization efficiency of confidential transmission of data acquisition, a mathematical optimization model for energy efficiency optimization considering constraints such as data security, maximum power and flight altitude was established, including: Assume that the three-dimensional coordinates of the drone and the eavesdropper are (x, y, z) and (x e ,y e ,z e ); There are I sensors in total, and the position coordinates of the i-th sensor are expressed as (u i ,v i ,0), i=1,2,…,I; In practical applications, the UAV locates the sensor and the eavesdropper to obtain their positions; The distances from the i-th sensor to the UAV and the eavesdropper are expressed as: Based on physical layer security technology, considering sensor power constraints and flight altitude constraints, the optimization problem with the goal of maximizing sensor energy efficiency is established as follows: where d i and l i It has been given in equations (1) and (2); p i represents the transmission power of the i-th sensor; β0=α0 / σ 2 , α0 represents the channel power gain at a reference distance of 1 meter; σ 2 represents the variance of Gaussian white noise; p max represents the maximum power constraint of the sensor; z min and z max Indicates the minimum and maximum flight altitudes allowed by the drone; for convenience, X and P represent the position vector of the drone and the power vector of the sensor, respectively. X and P are optimization variables.

3. The method for joint optimization of drone position and sensor power according to claim 2, characterized in that: The problem-solving process includes: ① By introducing an auxiliary variable Γ and giving an initial value Γ (0) , the optimal solution X of problem (3) * and P * Solve the following problem through loop iteration: The superscript (j) indicates the number of iterations. The optimal solution to problem (4) is represented by X (j) and P (j) Indicates that it will be used for the next iteration during the loop; ②Problem (4) Equivalent transformation; introduction of slack variables and B=(b1,b2,…,b I ), problem (4) is equivalently transformed into the following optimization problem: By solving problem (5), we can get the optimal solution to problem (4); ③ Solve problem (5) iteratively; for a set of given values ​​corresponding to the optimization variables X, P, A, B Problem (5) can be approximated as the following problem: Wherein, the superscript (n) indicates the number of iterations; Given a set of initial values ​​corresponding to the optimization variables X, P, A, B By solving problem (6) iteratively, we can obtain the optimal solution to problem (5); In fact, the optimal solution of problem (6) obtained in the nth iteration will be used in the next iteration. The optimal solution of problem (6) is expressed as In this way, the optimal solution to problem (5) is obtained by iteratively solving problem (6) until convergence.

4. The method for joint optimization of drone position and sensor power according to claim 3, characterized in that: The specific steps of problem solving are as follows: S1, input the three-dimensional position coordinates of the eavesdropper and sensor (x e ,y e ,z e ) and (u i ,v i ,0),i=1,2,…,I; S2. Given the initial value Γ of the auxiliary variable Γ (0) , j:=0; S3, j:=j+1; S4. Given a set of initial values ​​corresponding to the optimization variables X, P, A, B S5, n:=n+1; S6. For a given Γ (j-1) and Solve problem (6) to get its optimal S7, determine whether the increment of the objective function value of problem (4) meets the convergence condition, if so, continue to the next step, otherwise go to step S5 and iterate until the solution of problem (4) converges; S8, Utilizing X (j) and P (j) Find the objective function value of the original problem (3); S9. Determine whether the increment of the objective function value of problem (3) satisfies the convergence condition. If so, return the optimal solution X of problem (3). * :=X (j) , P * :=P (j) , otherwise go to step S3 and iterate until the solution to problem (3) converges.

5. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 4.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 4.

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