A method for quality of perception driven cooperative scheduling in wireless rechargeable sensor networks

Abstract

The application discloses a kind of wireless chargeable sensor network in perception quality driven cooperative scheduling method, including the following steps: obtaining sensor, charger and interest point set, establish network model;Establish charging model;According to the sensing characteristics of directional sensor, establish perception model;Formalization maximization problem of sensing utility under the constraint of charger opening cost;Call sensing scheduling algorithm, determine the sensing angle and sensing duration of sensor;Call opening scheduling algorithm, determine the opening duration of charger, the application provides a method for determining the charger opening scheme and sensor sensing scheme for the chargeable sensor with directional sensing, to maximize the sensing utility of network under the constraint of charger opening cost.

Description

Technical Field

[0001] This invention relates to the field of wireless rechargeable sensor networks, and more particularly to a cooperative scheduling method driven by sensing quality in wireless rechargeable sensor networks. Background Technology

[0002] Wireless sensor networks have been developing for decades; however, the limited battery capacity of sensors results in a short lifespan, making extending sensor lifespan a critical issue. Wireless power transfer technology, which can stably and continuously replenish devices without contact, has attracted widespread attention from academia and industry. In wireless rechargeable sensor networks, sensor nodes can be repeatedly charged via wireless power transfer technology, maintaining long-term operation and significantly reducing costs. This technology holds broad application prospects in smart cities, wearable devices, and environmental monitoring.

[0003] Currently, numerous research efforts have emerged regarding wireless rechargeable sensor networks, focusing on minimizing charging latency, optimizing charger placement, and minimizing the number of chargers. Most of these studies isolate the charging problem, concentrating solely on the charging process itself. While some researchers have investigated charging issues involving sensing tasks, they have neglected to address the problem that current wireless rechargeable sensor networks fail to maximize network sensing utility due to insufficient sensing quality. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a sensing quality-driven cooperative scheduling method in wireless rechargeable sensor networks to solve the problem of maximizing the sensing utility of the network under the constraint of charger activation cost.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution, including:

[0008] Acquire a set of sensors, chargers, and points of interest, and build a network model;

[0009] Establish a charging model;

[0010] Based on the sensing characteristics of directional sensors, a sensing model is established;

[0011] The problem of maximizing perceived utility under the constraint of charging cost in a formalized charger setup;

[0012] The sensing scheduling algorithm is invoked to determine the sensing angle and sensing duration of the sensor;

[0013] Invoke the start-up scheduling algorithm to determine the charger's start-up duration.

[0014] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, the establishment of the charging model includes the following steps:

[0015] A1: Sensors i From charger c j Received charging power P(s) i c j )for:

[0016]

[0017] A2: The charger's on-time is calculated in time slices, and the charger on-time scheme is defined as follows: c j The number of time slices used, when the activation scheme is H, for sensor s i The energy after charging is:

[0018]

[0019] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, wherein: the sensor s i From charger c j Received charging power P(s) i c j Where α and β are constants related to hardware and environment, D represents the maximum charging distance of the charger, ||s i c j || indicates s i With c j The Euclidean distance between them.

[0020] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, wherein: the sensor s i In the energy after charging, τ represents the size of the time slice. s i The remaining energy, E cap This indicates the sensor's battery capacity.

[0021] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, the step of establishing a sensing model based on the sensing points of the directed sensors includes the following steps:

[0022] B1: Definition For s i The perceived direction vector, when Angle θ i At that time, s i Point of interest o k The perceived quality is:

[0023]

[0024] Where w k The weights of the points of interest are represented by a and b, which are constants related to the sensor hardware and the environment. ||s i o k || indicates s i and o k European distance between express and The angle between them, R represents the sensing radius of the sensor, and A represents the sensing angle of the sensor;

[0025] B2: Define the sensor's sensing scheme as T = (T1, T2, ..., T...). m The entire network acquires points of interest under scheme T. k Its utility is:

[0026]

[0027] in s i The perception scheme, s i At angle The duration of perception is Indicates point of interest o k The upper limit of utility, s i Perception o k The utility obtained.

[0028] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, the formal problem of maximizing sensing utility under the constraint of charger activation cost includes the following steps:

[0029] Let the activation scheme be H and the sensing scheme be T. The total sensing utility corresponding to the joint scheduling scheme (H, T) is expressed as: The problem of maximizing perceived utility under the constraint of charger activation cost is formalized as follows:

[0030]

[0031]

[0032]

[0033] Where B represents the budget for the number of time slices, e represents the energy consumed by the sensor per unit of time, constraint (5) means that the total number of time slices allocated to the charger does not exceed the budget B, and constraint (6) means that the total energy consumption of the sensor cannot exceed its own energy.

[0034] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, the step of invoking the sensing scheduling algorithm to determine the sensing angle and sensing duration of the sensor includes the following steps:

[0035] C1: Assume the charger's activation scheme H is given, denoted as... The original problem now takes the form of:

[0036]

[0037]

[0038] C2: For s i ∈S, construct the interest point cover set Optimal Angle Set

[0039] C3: Initialize s i The perception scheme is

[0040] C4: Select make The sum of the corresponding perceived qualities is maximized, and this is taken as the current perceived direction to calculate the perceived time. Update perception scheme Update the sensor's remaining energy in o k The residual utility;

[0041] C5: According to renew The residual utility of the points of interest;

[0042] C6: Repeat steps C4 to C5 until... For O or Φ i for

[0043] C7: Select the next unvisited sensor in S and repeat C2 to C6;

[0044] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, wherein: C2 includes the following steps:

[0045] C21: Initialize s i Optimal angle set Interest Point Coverage Set Angle Interval Set

[0046] C22:s i Rotate counterclockwise, and when the first point of interest enters the perception area, let the angle at that moment be... And initialize x = 1;

[0047] C23:s i Continue rotating, and record the direction when the point of interest just enters or leaves the sensory area. in

[0048] C25: Update Φ i Ω i Ψ i :

[0049] C26: If If the angle is greater than or equal to 2π, the process terminates; otherwise, it proceeds to C23.

[0050] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, wherein: C5 includes the following steps:

[0051] C51: For any Update o k Residual utility:

[0052] C52: If The value is 0, check Ω i Each element in like Then o k from Delete;

[0053] C53: If o is deleted k back Not for Then recalculate Corresponding optimal perception angle Otherwise delete

[0054] As a preferred embodiment of the sensing quality-driven cooperative scheduling method in the wireless rechargeable sensor network described in this invention, the step of invoking the activation scheduling algorithm to determine the activation duration of the charger includes the following steps:

[0055] D1: Let T′ be the sensing scheme used to determine the sensing angle and sensing duration of the sensor by calling the sensing scheduling algorithm. The original problem then becomes:

[0056]

[0057]

[0058] D2: Initialize the charger activation scheme H = (h1, h2, ..., h...) n )←(0, 0, ..., 0);

[0059] D3: Each time, allocate a time slice to a charger cj to maximize its marginal perceived utility, i.e.: j ← arg max j＝1，2，...，n U(H+I j ,T′)-U(H,T′), where Ij is a unit vector, and the j-th component is 1 while all other components are 0;

[0060] D4: Update H and B: H = H + I j B = B-1;

[0061] D5: Repeat D3 to D4 until B is 0.

[0062] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention considers the influence of sensor sensing angle on sensing quality and proposes a problem for maximizing sensing utility; it designs a charger activation scheme and a sensor sensing scheme to address this problem, with an overall approximation ratio of... The aforementioned perceptual scheduling algorithm has an approximation ratio of: That is, in the worst case, its performance is at least the optimal solution. The aforementioned startup scheduling algorithm is approximately equal to... That is, in the worst case, its performance is at least the optimal solution. When both the perceptual scheduling algorithm and the enabled scheduling algorithm are used simultaneously, the resulting approximate ratio is: To maximize the network's sensing utility while keeping the charging startup cost a constraint. Attached Figure Description

[0063] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0064] Figure 1 This is a flowchart of the sensing scheme and charging scheme of a sensing quality-driven cooperative scheduling method in a wireless rechargeable sensor network according to an embodiment of the present invention.

[0065] Figure 2 This is a schematic diagram of a network model for a quality-driven cooperative scheduling method in a wireless rechargeable sensor network according to an embodiment of the present invention.

[0066] Figure 3 This is a flowchart of the perception scheduling algorithm for a perception quality-driven cooperative scheduling method in a wireless rechargeable sensor network, according to an embodiment of the present invention.

[0067] Figure 4 This is a flowchart illustrating the initialization of the optimal sensor angle set and interest point coverage set in a sensing quality-driven cooperative scheduling method for a wireless rechargeable sensor network, as described in one embodiment of the present invention.

[0068] Figure 5 This is a flowchart illustrating the update of residual utility of interest points in a sensing quality-driven cooperative scheduling method in a wireless rechargeable sensor network, according to an embodiment of the present invention.

[0069] Figure 6 This is a flowchart of a charger scheduling algorithm for a quality-driven cooperative scheduling method in a wireless rechargeable sensor network, as described in one embodiment of the present invention. Detailed Implementation

[0070] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0071] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0072] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0073] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0074] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0075] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0076] Example 1

[0077] Reference Figure 1-6 As an embodiment of the present invention, a cooperative scheduling method driven by sensing quality in a wireless rechargeable sensor network is provided, comprising:

[0078] Let S = {s1, s2, ..., s} lie on the two-dimensional plane Ω. m Let C = {c1, c2, ..., c3} represent the set of rechargeable sensors. n Let O represent the set of chargers, O = {o1, o2, ..., o...} l} represents a set of points of interest.

[0079] Establish a charging model;

[0080] Based on the sensing characteristics of directional sensors, a sensing model is established;

[0081] The problem of maximizing perceived utility under the constraint of charging cost in a formalized charger setup;

[0082] The sensing scheduling algorithm is invoked to determine the sensing angle and sensing duration of the sensor;

[0083] Invoke the start-up scheduling algorithm to determine the charger's start-up duration.

[0084] Establishing a charging model includes the following steps:

[0085] Sensors i From charger c j Received charging power P(s) i c j )for:

[0086]

[0087] Where α and β are constants related to hardware and environment, and D represents the maximum charging distance of the charger, ||s i c j || represents s i With c j The Euclidean distance between them.

[0088] A2: The charger's on-time is calculated in time slices, and the charger on-time scheme is defined as follows: c j The number of time slices used.

[0089] When the activation scheme is H, sensor s i The energy after charging is:

[0090]

[0091] Where τ is the size of the time slice, s i The remaining energy, E cap This indicates the sensor's battery capacity.

[0092] Based on the sensing characteristics of directed sensors, a sensing model is established, including the following steps:

[0093] B1: Definition For s i The perceived direction vector, when Angle θ iAt that time, s i Point of interest o k The perceived quality is:

[0094]

[0095] Where w k The weights of the points of interest are represented by a and b, which are constants related to the sensor hardware and the environment. ||s i o k || represents s i and o k European distance between express and The angle between them, R represents the sensing radius of the sensor, and A represents the sensing angle of the sensor;

[0096] B2: Define the sensor's sensing scheme as T = (T1, T2, ..., T...). m The entire network acquires points of interest (POIs) under scheme T. k Its utility is:

[0097]

[0098] in s i The perception scheme, s i At angle The duration of perception is Indicates point of interest o k The upper limit of utility, s i Perception o k The utility obtained.

[0099] The formalized problem of maximizing perceived utility under the constraint of charger activation cost includes the following steps: Let the activation scheme be H and the perception scheme be T. The total perceived utility corresponding to the joint scheduling scheme (H, T) is expressed as... The problem of maximizing perceived utility under the constraint of charger activation cost is formalized as follows:

[0100]

[0101]

[0102]

[0103] Where B represents the budget for the number of time slices, e represents the energy consumed by the sensor per unit of time, constraint (5) means that the total number of time slices allocated to the charger does not exceed the budget B, and constraint (6) means that the total energy consumption of the sensor cannot exceed its own energy.

[0104] The sensing scheduling algorithm is invoked to determine the sensor's sensing angle and sensing duration. The process is as follows: Figure 3 As shown, it includes the following steps:

[0105] C1: Assume the charger's activation scheme H is given, denoted as... The original problem now takes the form of:

[0106]

[0107]

[0108] C3: Initialize s i The perception scheme is

[0109] C4: Select make The sum of the corresponding perceived qualities is maximized, and this is taken as the current perceived direction to calculate the perceived time. Update perception scheme Update the sensor's remaining energy in o k The residual utility;

[0110] C5: According to renew The residual utility of the points of interest;

[0111] C6: Repeat C4 to C5 until... 0 or Φ i for

[0112] C7: Select the next unvisited sensor in S, and repeat C2 to C6;

[0113] Furthermore, C2 includes the following steps:

[0114] C21: Initialize s i Optimal angle set Interest Point Coverage Set Angle Interval Set

[0115] C22:s i Rotate counterclockwise, and when the first point of interest enters the perception area, let the angle at that moment be... And initialize x = 1;

[0116] C23:s i Continue rotating, and record the direction when the point of interest just enters or leaves the sensory area. in

[0117] C25: Update Φ i Ω i Ψ i :

[0118] C26: If If the angle is greater than or equal to 2π, the process terminates; otherwise, proceed to C23.

[0119] Furthermore, C5 includes the following steps:

[0120] C51: For any Update o k Residual utility:

[0121] C52: If The value is 0, check Ω i Each element in like Then o k from Delete;

[0122] C53: If o is deleted k back Not for Then recalculate Corresponding optimal perception angle Otherwise delete

[0123] Furthermore, the perception scheduling algorithm is invoked to determine the sensor's sensing angle and sensing duration, with an approximate ratio of... That is, in the worst case, its performance is at least the optimal solution.

[0124] When both the sensing scheme and the activation scheme are known, Perception o k The utility gained is expressed as: Then the total perceived utility obtained by X is: Next, let's assume that the known activation scheme is... Let the sensing scheme generated by the sensing scheduling algorithm be T′. When scheme T′ is adopted, the sensor set is represented as: S′={s′1,s′2,...,s′ m The corresponding perceived utility is} Let the optimal strategy be T. * Plan T was adopted. * At that time, the sensor set is represented as: The corresponding optimal perceived utility is Note that s i and This refers to the same sensor, the only difference being the sensing strategy employed, s′ i Using scheme T′ i , Usage Plan

[0125] The inequality can be derived as: U(S) * )≤U(S′∪S * )≤2u(S′), therefore

[0126] The startup scheduling algorithm is invoked to determine the charger's startup duration. The process is as follows: Figure 6 As shown, it includes the following steps:

[0127] D1: Let T′ be the sensing scheme used to determine the sensing angle and sensing duration of the sensor by calling the sensing scheduling algorithm. The original problem then becomes:

[0128]

[0129]

[0130] D2: Initialize the charger activation scheme H = (h1, h2, ..., h...) n )←(0, 0, ..., 0);

[0131] D3: Allocate a time slice to a charger cj each time to maximize its marginal perceived utility, i.e.: j ← arg max j＝1，2，...，n U(H+I j ,T′)-U(H,T′), where I j It is a unit vector, and the j-th component is 1 while all other components are 0;

[0132] D4: Update H and B: H = H + I j B = B-1;

[0133] D5: Repeat D3 to D4 until B is 0.

[0134] The power-on scheduling algorithm is invoked to determine the charger's power-on duration, with an approximate ratio of... That is, in the worst case, its performance is at least the optimal solution.

[0135] Suppose the perception scheduling scheme adopts the output T′ of the perception scheduling algorithm. In this case, the objective function can be expressed as: The original problem can be reformulated as:

[0136] max U(H, T′)

[0137]

[0138] Z1∪Z2∪...∪Z n The charging activation scheme can be represented in the form of Y, and the conversion between Y and H is as follows:

[0139] H→Y:

[0140] Y→H: H={|Y∩Z1|,...,|Y∩Z n |}.

[0141] For the objective function, H can also be replaced by Y:

[0142]

[0143] To simplify the symbolic representation, let The problem is now equivalently represented as:

[0144]

[0145]

[0146] The problem described above is a problem of maximizing monotonic submodular functions based on basis constraints. The solution to this problem is to allocate a time slice to a charger in each iteration to maximize its marginal perceived utility. It can be proven that this greedy selection strategy is feasible. The approximate ratio.

[0147] When both the perceptual scheduling algorithm and the enabled scheduling algorithm are used simultaneously, the resulting approximate ratio is:

[0148] Suppose we call the perceptual scheduling algorithm and then call the start scheduling algorithm; the corresponding solution is:<H′,T′> The optimal solution to the original problem is <H * T * Given that the charger's activation strategy is H′, let the optimal sensing scheme be... at this time:

[0149]

[0150] When the sensor's sensing strategy is known to be T * Let the corresponding optimal activation scheme be: at this time

[0151]

[0152] because so

[0153]

[0154] And because so

[0155]

[0156] Combining equations ③ and ④, we can obtain...

[0157] Therefore, the overall approximation ratio of this invention is:

[0158] Example 2

[0159] Referring to Table 1, an embodiment of the present invention provides a cooperative scheduling method driven by sensing quality in a wireless rechargeable sensor network. To verify its beneficial effects, a comparison of two schemes is provided.

[0160] On the two-dimensional plane Ω, let S = {s1, s2, s3, s4} represent the set of rechargeable sensors, C = {c1, c2, c3} represent the set of chargers, and O = {o1, o2, o3, o4, o5, o6} represent the set of points of interest.

[0161] Table 1 Entity Coordinates

[0162] <![CDATA[s1]]> (0，10) <![CDATA[s2]]> (20，0) <![CDATA[s3]]> (20，15) <![CDATA[s4]]> (20，25) <![CDATA[c1]]> (10，10) <![CDATA[c2]]> (20，10) <![CDATA[c3]]> (20，20) <![CDATA[o1]]> (5，10) <![CDATA[o2]]> (5，10) <![CDATA[o3]]> (15，0) <![CDATA[o4]]> (15，-5) <![CDATA[o5]]> (25，0) <![CDATA[o6]]> (30，15)

[0163] The charging parameters are set as follows: α = 50, β = 10, D = 10, τ = 10, E cap =15, B=4, The perception-related parameters are set as follows: a = 15, b = 5, R = 10, A = π / 2, e = 1, w1 = 1, w2 = 2, w3 = 4, w4 = 4, w5 = w6 = 1.

[0164] C1: Assume the charger's activation scheme H is given, denoted as... The original problem is now formalized as follows:

[0165]

[0166]

[0167] C2: Select s1, construct the interest point coverage set Ω1, and the optimal angle set Φ1:

[0168] C21: Initialize the optimal angle set of s1 Interest Point Coverage Set Angle Interval Set

[0169] C22: s1 rotates counterclockwise. When o1 enters the sensing area, let the angle at this time be... And initialize x = 1;

[0170] C23: s1 continues to rotate. When o1 just leaves the sensing area, record the direction vector at this moment. Angle and the set of points of interest within the perception area before o1 leaves

[0171] C24: Calculate the coverage of points of interest. The optimal angle of perception for time:

[0172] C25: Update Φ1, Ω1, Ψ1: Ω1 = {{o1, o2}}, x = 2; C26: Continue rotating until The operation will terminate at that time.

[0173] Therefore, Ω1 = {{o1, o2}},

[0174] C3: The initialization scheme for s1 is as follows

[0175] C4: Select As the current sensing direction of s1, calculate the sensing time. min{1, min{1, 2}} = 1, update the perception scheme. Update the sensor's remaining energy

[0176] C5: According to renew The residual utility of a point of interest includes the following steps:

[0177] C51: For o1, update the remaining utility of o1:

[0178] C52: If the value is 0, check each element in Ω1. like Then o1 from Delete;

[0179] C53: After deleting o1 Not for Then recalculate Corresponding optimal perception angle

[0180] The same steps from C51 to C53 are used to process o2:

[0181] C6: Due to Jump to C7;

[0182] C7: Select the next unvisited sensor in S, and repeat C2 to C6;

[0183]

[0184] D1: Let T′ be the sensing scheme used to determine the sensing angle and sensing duration of the sensor by calling the sensing scheduling algorithm. The original problem then becomes:

[0185]

[0186]

[0187] D2: Initialize the charger startup scheme H = (h1, h2, h3) ← (0, 0, 0);

[0188] D3: Allocate a time slice to a specific charger c each time. j To maximize its perceived marginal utility:

[0189] For the first time slice, if it is allocated to c1, the marginal utility is 0.3; if it is allocated to c2, the marginal utility is 1.097; and if it is allocated to c3, the marginal utility is 0.149. Obviously, the first time slice will be allocated to c2. The calculation of marginal utility requires calling the perceptual scheduling algorithm.

[0190] D4: Update H and B: H = (0, 1, 0), B = 3;

[0191] D5: Repeat D3 to D4 until B is 0.

[0192] Similarly, the second time slice is allocated to c2, the third time slice is allocated to c2, and the fourth time slice is allocated to c1. Ultimately, the charger's activation scheme is (1, 3, 0), and the sensor's sensing scheme is... The corresponding total perceived utility is 4.609.

[0193] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A cooperative scheduling method driven by sensing quality in a wireless rechargeable sensor network, characterized in that: Includes the following steps: Acquire a set of sensors, chargers, and points of interest, and build a network model; Establish a charging model; Based on the sensing characteristics of directional sensors, a sensing model is established; The problem of maximizing perceived utility under the constraint of charging cost in a formalized charger setup; The sensing scheduling algorithm is invoked to determine the sensing angle and sensing duration of the sensor; Invoke the start-up scheduling algorithm to determine the charger's start-up duration; The process of establishing a perception model based on the sensing points of the directed sensor includes the following steps: B1: Definition for The perceived direction vector, when Angle is hour, Points of interest The perceived quality is: （3） in The weights representing points of interest , These are constants related to the sensor hardware and the environment. express and European distance between express and The angle between them This indicates the sensor's sensing radius. Indicates the size of the sensor's sensing angle; B2: Define the sensor's sensing scheme as follows The entire network in the solution Get points of interest Its utility is: （4） in express The perception scheme, express At angle The duration of perception is , , Indicate points of interest The upper limit of utility, express Perception The utility obtained; The formalized problem of maximizing perceived utility under the constraint of charger activation cost includes the following steps: Let the opening scheme be The perception scheme is At that time, the joint scheduling scheme will be implemented. The corresponding total perceived utility is expressed as The problem of maximizing perceived utility under the constraint of charger activation cost is formalized as follows: （5） ， （6） in The budget representing the number of time slices, This represents the energy consumed by the sensor per unit time, and constraint (5) represents the total number of time slices allocated to the charger not exceeding the budget. Constraint (6) indicates that the total energy consumption of the sensor cannot exceed its own energy. The invocation of the perception scheduling algorithm to determine the sensor's sensing angle and sensing duration includes the following steps: C1: Assume the charger's activation scheme It is given, denoted as The original problem now takes the form of: （7） C2: For Construct the interest point coverage set Optimal angle set ; C3: Initialization The perception scheme is ; C4: Select ,make The sum of the corresponding perceived qualities is maximized, and this is taken as the current perceived direction to calculate the perceived time. Update the perception scheme Update the sensor's remaining energy ,in express The residual utility; C5: According to ,renew The residual utility of the points of interest; C6: Repeat steps C4 to C5 until... 0 or for ; C7: Select For the next unvisited sensor, repeat steps C2 through C6; The invocation of the scheduling algorithm to determine the charger's activation duration includes the following steps: D1: Suppose that the sensing scheme, which determines the sensing angle and sensing duration of the sensor by calling the sensing scheduling algorithm, is as follows: The original problem is now formalized as: （8） D2: Initialize charger power-on scheme ; D3: Allocate a time slice to a specific charger each time. To maximize its marginal perceived utility, that is: ,in It is a unit vector, and the first... One component is 1 and all other components are 0; D4: Update , : , ; D5: Repeat steps D3 to D4 until... It is 0.

2. The cooperative scheduling method driven by sensing quality in a wireless rechargeable sensor network according to claim 1, characterized in that: The establishment of the charging model includes the following steps: A1: Sensor From the charger Received charging power for: （1） A2: The charger's on-time is calculated in time slices, and the charger on-time scheme is defined as follows: , express The number of time slices used, when the scheme is enabled. At that time, the sensor The energy after charging is: （2） in, and These are constants related to hardware and environment. Indicates the charger's maximum charging distance. express and European distance between The size of the time slice, express The remaining energy, This indicates the sensor's battery capacity.

3. The cooperative scheduling method driven by sensing quality in a wireless rechargeable sensor network according to claim 2, characterized in that: The C2 includes the following steps: C21: Initialization Optimal angle set Interest point coverage set , set of angle intervals ; C22: Rotate counterclockwise, and when the first point of interest enters the perception area, let the angle at that moment be... and initialize ; C23: Continue rotating, and when the point of interest just enters or leaves the perception area, record the direction vector at that moment. Angle And the set of points of interest within the perceived area before the point of interest enters or leaves. C24: Calculate the coverage of points of interest. The optimal angle of perception for time: ,in ; C25: Update , , : , { }, ; C26: If Angle greater than or equal to If it fails, the process terminates; otherwise, it proceeds to C23.

4. The cooperative scheduling method driven by sensing quality in a wireless rechargeable sensor network according to claim 3, characterized in that: The C5 includes the following steps: C51: For any ,renew Residual utility: ; C52: If The value is 0, check Each element in ,like Then from Delete; C53: If deleted back Not for Then recalculate. Corresponding optimal perception angle Otherwise delete , .

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