A robust utility directional wireless charger placement method

Abstract

The present invention discloses a method for placing a robust utility directed wireless charger, including: defining a set of rechargeable sensors, a set of directed wireless chargers, and the charging utility of the rechargeable sensors; formalizing the problem of placing a robust utility directed wireless charger; using a region discretization method to obtain a discretized finite sub-region set and a candidate covering sensor set; calling a charger placement strategy discretization algorithm to obtain a finite charger placement strategy space; transforming the problem of placing a robust utility directed wireless charger; calling a robust utility directed wireless charger placement algorithm to calculate the position and charging direction of the wireless charger. The present invention provides a method for placing a robust utility directed wireless charger, which distributes charging energy to each sensor as evenly as possible, so that normal sensors can take on the work tasks of failed sensors, and the algorithm used can save a lot of time while ensuring accuracy, and greatly improves sensor utility.

Description

Technical Field

[0001] The invention relates to the technical field of wireless rechargeable sensor networks, and in particular to a robust utility directional wireless charger placement method. Background Art

[0002] Wireless sensor networks have been widely used. As an important part of wireless sensor networks, sensors are usually charged through physical connections. However, physical connections may cause problems such as leakage due to aging wires, which may lead to safety issues in sensor networks. Wireless chargers transfer electricity to sensors through electromagnetic waves to complete the charging of sensors. Currently, sensors mainly receive charging power by installing directional antennas. Their electronic components are more sophisticated and complex and more easily damaged. Therefore, the robustness of the wireless charging system needs to be considered to extend the working life of wireless sensor networks.

[0003] However, there are few studies on the robust placement of wireless chargers. Only a few scholars have studied the robustness of transmission energy fluctuations and electromagnetic radiation fluctuations caused by electromagnetic jitter, but have not considered the robustness caused by system failures. Since rechargeable sensors are precision electronic instruments with a large number of electronic components, these components may have various failures, such as packaging failures, contact failures, printed circuit board failures, relay failures, etc. In addition, the external environment may also cause directional wireless chargers to fail. For example, lightning can generate electromagnetic pulses and damage directional wireless chargers by generating overvoltage and surges. Dust may also affect the reliability of printed circuit board assembly. At the same time, vibration, aging, corrosion, humidity, cold and heat can cause human and non-human failures. Therefore, the study of robust charger placement methods for sensor failures is of practical significance and an urgent problem to be solved. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] Therefore, the technical problem solved by the present invention is: for possible sensor failures, such as packaging failure, contact failure, printed circuit board failure, relay failure, etc., the charging energy cannot be evenly distributed to each sensor, and the normal sensor cannot take on the working tasks of the failed sensor.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a robust utility directional wireless charger placement method, comprising: defining a set of chargeable sensors, a set of directional wireless chargers, and charging utilities of the chargeable sensors;

[0007] Formalize the robust utility directed wireless charger placement problem;

[0008] A discretized finite sub-region set and a candidate coverage sensor set are obtained by using a region discretization method;

[0009] Call the charger placement strategy discretization algorithm to obtain a limited charger placement strategy space;

[0010] Transforming the robust utility directed wireless charger placement problem;

[0011] The robust utility directional wireless charger placement algorithm is called to calculate the position and charging direction of the wireless charger.

[0012] As a preferred solution of the robust utility directional wireless charger placement method of the present invention, wherein: the rechargeable sensor set is: set S = {s1, n2, ..., s n}, the set of directional wireless chargers is O, the charging area Ω is a two-dimensional plane, and the charger is placed in the charging area Ω.

[0013] As a preferred solution of the robust utility directional wireless charger placement method of the present invention, wherein: the charging utility of the rechargeable sensor includes:

[0014] Rechargeable Sensors i From directional wireless charger o j The charging power obtained is:

[0015]

[0016] Among them, the directional wireless charger and the rechargeable sensor have charging angles A and s and receiving angle A o , α and β are two constants determined by the magnetic field environment and hardware parameters of the charger and the rechargeable device, D is the maximum charging distance, d(s i ,o j ) is a directional wireless charger o j With rechargeable sensors i The distance between Directed wireless charger j The charging direction vector, For rechargeable sensors i The receiving direction vector, when d(s i ,o j)≤D, and When , the rechargeable sensor always obtains positive power;

[0017] Formalize the rechargeable sensors i When the deployed placement strategy set is The charging effect is:

[0018]

[0019] in, Represents the set of deployed placement strategies, To place the strategy space, For sensors i The maximum charging power that can be received, and is a known positive real number;

[0020] Defines the minimum charging utility of all rechargeable sensors for:

[0021]

[0022] As a preferred solution of the robust utility directed wireless charger placement method of the present invention, the formalized robust utility directed wireless charger placement problem includes:

[0023] Establishing constraints Ensure that the number of deployed chargers is less than the upper limit m, where is the number of deployed chargers;

[0024] Establishing constraints Ensure that the deployment strategy of the sensor is reasonable, that is, the charger is located in the charging area, and the charging direction is between 0 and 360 degrees. For the convenience of expression, the present invention reuses the symbol o j For charger o j The deployment position, θ j For charger o j Charging direction;

[0025] Taking maximizing the minimum sensor charging utility as the optimization goal, a unified formalized robust utility directed wireless charger placement problem is obtained:

[0026]

[0027]

[0028]

[0029] As a preferred solution of the robust utility directional wireless charger placement method described in the present invention, the region discretization method includes:

[0030] A1: Defining approximate power

[0031]

[0032] Where d is the charging distance, l(k) = β((1+∈) k / 2 -1) is the discretized charging distance, l(0) = 0, l(K) = D, D is the maximum charging distance, ∈ is the discretization constant, K is the number of segments, P(0) is the charging power when the charging distance is 0, and P(D) is the charging power when the charging distance is D;

[0033] A2: For each rechargeable sensor i , taking its position as the center, receiving direction Receiving Angle A o , concentric sectors with radius l(1), l(2), …, l(K) are drawn. The receiving area of ​​each rechargeable sensor is divided into K partitions, and the partitions of different sensors overlap each other to form new discrete sub-areas;

[0034] A3: For each of the new discrete sub-regions, let F i , define sub-region F i The rechargeable sensor set that can cover the sub-area is the candidate coverage sensor set

[0035] As a preferred solution of the robust utility directional wireless charger placement method described in the present invention, the calling of the charger placement strategy discretization algorithm includes:

[0036] B1: Select a sub-region F that has not been calculated i ;

[0037] B2: Select the sub-area F i The candidate coverage sensor set Any pair of rechargeable sensors in , set as s1 and s2;

[0038] B3: Execute projection partitioning algorithm;

[0039] B4: Execute translation partitioning algorithm;

[0040] B5: Repeat steps B2 to B4 until Each pair of rechargeable sensors has been selected;

[0041] B6: Execute the rotation partitioning algorithm in the sub-area F i A point is randomly selected from the boundary as the deployment position of the directional wireless charger, and its charging direction is rotated counterclockwise from 0 degrees to 360 degrees to cover the rechargeable sensors one by one. First, the direction of the directional wireless charger is initialized to 0 degrees. During the rotation process, if some covered rechargeable sensor nodes will be uncovered, the current charging direction is marked as the dominant direction; then the rotation is continued. If some covered rechargeable sensors will be uncovered after the new sensor nodes are covered, the current direction is marked as the dominant direction; during the rotation process, if the rotation angle is greater than 360 degrees, the rotation is terminated, and all the dominant directions obtained are combined with the current directional wireless charger deployment position into a charger placement strategy, and the charger placement strategy is incorporated into the limited charger placement strategy space.

[0042] B7: The limited charger placement strategy space Delete the charger placement strategies that are subsets of other charger placement strategies;

[0043] B8: Repeat steps B1 to B7 until all sub-areas F i The strategies have been calculated;

[0044] B9: Return the limited charger placement strategy space

[0045] As a preferred solution of the robust utility directional wireless charger placement method described in the present invention, the execution of the projection partitioning algorithm is as follows: draw a straight line passing through s1 and s2, and extend the straight line to intersect with the sub-area boundary; place the charger at these intersections, and adjust its direction so that s1 and s2 are exactly located on the clockwise boundary of the charger coverage area, obtain the current charger placement strategy, and incorporate it into the limited charger placement strategy space

[0046] As a preferred solution of the robust utility directional wireless charger placement method of the present invention, the execution of the translation partitioning algorithm is: draw two arcs passing through s1 and s2, and form an angle A with them. s Then, the intersection points of the trajectory and the partition boundary are calculated, and the chargers are placed at these intersection points, so that s1 and s2 are exactly located on the two boundaries of the charger coverage area, respectively, to obtain the current charger placement strategy and incorporate it into the limited charger placement strategy space

[0047] As a preferred solution of the robust utility directional wireless charger placement method of the present invention, wherein: transforming the robust utility directional wireless charger placement problem includes:

[0048] C1: Based on the approximate power Substituting the actual charging power P(d), we can obtain the rechargeable sensor s i Approximate charging efficiency and minimum approximate charging utility

[0049]

[0050]

[0051] C2: Rewrite P1 as:

[0052]

[0053]

[0054] C3: Introduce a positive real number k and rewrite P2 into the equivalent P3:

[0055] (P3)max k (12)

[0056]

[0057] C4: Introduce formula Define P4:

[0058]

[0059]

[0060] As a preferred solution of the robust utility directional wireless charger placement method of the present invention, the robust utility directional wireless charger placement algorithm includes:

[0061] D1: Initialize the binary search lower bound k min =0, binary search upper bound

[0062] D2: Perform a binary search, let

[0063] D3: Initialize the temporary deployed placement strategy set to an empty set, that is,

[0064] D4: From the set of deployment strategies that have not yet been selected Find the right The deployment strategy with the largest marginal value (oj ,θ j ), that is:

[0065] D5: Change the strategy (o j ,θ j ) joins the temporary deployed placement strategy set, i.e.

[0066] D6: Repeat steps D4 to D5 until the total charging utility is greater than or equal to k or All charger placement strategies in have been selected;

[0067] D7: If the number of strategies in the temporarily deployed placement strategy set Greater than m, that is Then let k max = k; otherwise, let k min = k,

[0068] D8: Repeat steps D2 to D7 until (k max -k min )<γ, where γ is the search accuracy and γ is a known constant;

[0069] D9: Returns the set of deployed placement strategies

[0070] Beneficial effects of the invention: The invention provides a robust and effective directional wireless charger placement method, which distributes the charging energy to each sensor as evenly as possible, so that normal sensors can take on the work tasks of failed sensors. The algorithm used can ensure accuracy while saving a lot of time, and the sensor utility is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0072] Figure 1 A schematic diagram of sensor placement for a robust utility directional wireless charger placement method provided by an embodiment of the present invention;

[0073] Figure 2 A flowchart of a robust utility directional wireless charger placement method provided by one embodiment of the present invention;

[0074] Figure 3A charging model diagram of a directional wireless charger and a sensor in a method for placing a directional wireless charger with robust utility provided by an embodiment of the present invention;

[0075] Figure 4 A schematic diagram of power discretization of a directional wireless charger in a method for placing a directional wireless charger with robust utility provided by an embodiment of the present invention;

[0076] Figure 5 A schematic diagram of sub-regions after region discretization in a robust utility directional wireless charger placement method provided by an embodiment of the present invention;

[0077] Figure 6 A flowchart of a charger placement strategy discretization algorithm in a robust utility directional wireless charger placement method provided by one embodiment of the present invention;

[0078] Figure 7 A schematic diagram of projection partitioning in a method for placing a robust utility directional wireless charger provided by an embodiment of the present invention;

[0079] Figure 8 A schematic diagram of translation partitioning in a robust utility directional wireless charger placement method provided by an embodiment of the present invention;

[0080] Fig. 9 A schematic diagram of rotation division in a robust utility directional wireless charger placement method provided by an embodiment of the present invention;

[0081] Fig.10 A flowchart of a robust utility placement algorithm for a directed wireless charger in a robust utility directed wireless charger placement method provided by a third embodiment of the present invention;

[0082] Fig.11 A directed charger placement scheme outputted from a method for placing a robust utility directed wireless charger provided by an embodiment of the present invention;

[0083] Fig.12 A comparison diagram of the effects of a robust utility directional wireless charger placement method provided by the third embodiment of the present invention;

[0084] Fig.13 A physical experiment diagram of a robust utility directional wireless charger placement method provided in the fourth embodiment of the present invention;

[0085] Fig.14 A comparison diagram of the effectiveness of sensors in a physical experiment in a robust utility directional wireless charger placement method provided in the fourth embodiment of the present invention. DETAILED DESCRIPTION

[0086] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0087] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0088] 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 term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0089] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0090] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0091] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0092] Example 1

[0093] Reference Figure 2 , 610. In one embodiment of the present invention, a robust utility directional wireless charger placement method is provided, comprising:

[0094] S1: define a rechargeable sensor set, a directional wireless charger set, and a rechargeable sensor charging utility;

[0095] Specifically, the rechargeable sensor set is: set S = {s1, s2, ..., s n}, the set of directed wireless chargers is O, and the charging area Ω is a two-dimensional plane, where the chargers are placed in the charging area Ω.

[0096] Specifically, the charging utilities of rechargeable sensors include:

[0097] (1) Rechargeable sensors i From directional wireless charger o j The charging power obtained is:

[0098]

[0099] Among them, the directional wireless charger and the rechargeable sensor have charging angles A and s and receiving angle A o , α and β are two constants determined by the magnetic field environment and hardware parameters of the charger and the rechargeable device, D is the maximum charging distance, d(s i ,o j ) is a directional wireless charger o j With rechargeable sensors i The distance between Directed wireless charger j The charging direction vector, For rechargeable sensors i The receiving direction vector, when d(s i ,o j )≤D, and When , the rechargeable sensor always obtains positive power;

[0100] (2) Formalization of rechargeable sensors i When the deployed placement strategy set is

[0101]

[0102] in, Represents the set of deployed placement strategies, To place the strategy space, For sensors iThe maximum charging power that can be received, and is a known positive real number;

[0103] (3) Define the minimum charging utility of all rechargeable sensors for:

[0104]

[0105] S2: Formalize the robust utility directed wireless charger placement problem;

[0106] Furthermore, the formalized robust utility directed wireless charger placement problem includes:

[0107] Establishing constraints Ensure that the number of deployed chargers is less than the upper limit m, where is the number of deployed chargers;

[0108] Establishing constraints Ensure that the deployment strategy of the sensor is reasonable, that is, the charger is located in the charging area, and the charging direction is between 0 and 360 degrees. For the convenience of expression, the present invention reuses the symbol o j For charger o j The deployment position, θ j For charger o j Charging direction;

[0109] Taking maximizing the minimum sensor charging utility as the optimization goal, a unified formalized robust utility directed wireless charger placement problem is obtained:

[0110]

[0111]

[0112]

[0113] S3: Obtain a discretized finite sub-region set and its candidate coverage sensor set using a region discretization method;

[0114] Furthermore, the regional discretization methods include:

[0115] A1: Defining approximate power

[0116]

[0117] Where d is the charging distance, l(k) = β((1+∈) k / 2 -1) is the discretized charging distance, l(0) = 0, l(K) = D, D is the maximum charging distance, ∈ is the discretization constant, K is the number of segments, P(0) is the charging power when the charging distance is 0, and P(D) is the charging power when the charging distance is D;

[0118] A2: For each rechargeable sensor i , taking its position as the center, receiving direction Receiving Angle A o , concentric sectors with radius l(1), l(2),…, l(K) are drawn. The receiving area of ​​each rechargeable sensor is divided into K partitions, and the partitions of different sensors overlap each other to form new discrete sub-areas.

[0119] A3: For each sub-region of the new discrete sub-region, let F i , define sub-region F i The rechargeable sensor set that can cover the sub-area is the candidate coverage sensor set

[0120] S4: calling the charger placement strategy discretization algorithm to obtain a limited charger placement strategy space;

[0121] Furthermore, the charger placement strategy discretization algorithm is called, including:

[0122] B1: Select a sub-region F that has not been calculated i ;

[0123] B2: Select sub-area F i The candidate coverage sensor set Any pair of rechargeable sensors in , set as s1 and s2;

[0124] B3: Execute projection partitioning algorithm;

[0125] Specifically, the projection partitioning algorithm is executed as follows: draw a straight line through s1 and s2, and extend the straight line to intersect the sub-area boundary. Place the chargers at these intersections and adjust their directions so that s1 and s2 are exactly on the clockwise boundary of the charger coverage area. Obtain the current charger placement strategy and incorporate it into the limited charger placement strategy space.

[0126] B4: Execute translation partitioning algorithm;

[0127] Specifically, the translation partitioning algorithm is executed as follows: draw two arcs passing through s1 and s2, and form an angle A with them s Then calculate the intersection points of the trajectory and the partition boundary, place the chargers at these intersections, and make s1 and s2 exactly on the two boundaries of the charger coverage area, obtain the current charger placement strategy, and incorporate it into the limited charger placement strategy space

[0128] B5: Repeat steps B2 to B4 until Each pair of rechargeable sensors has been selected;

[0129] B6: Execute the rotation partitioning algorithm, in sub-area F i A point is randomly selected from the boundary as the deployment location of the directed wireless charger, and its charging direction is rotated counterclockwise from 0 degrees to 360 degrees to cover the rechargeable sensors one by one. First, the direction of the directed wireless charger is initialized to 0 degrees. During the rotation process, if some covered rechargeable sensor nodes will be uncovered, the current charging direction is marked as the dominant direction. Then continue to rotate. If some covered rechargeable sensors will be uncovered after the new sensor nodes are covered, the current direction is marked as the dominant direction. During the rotation process, if the rotation angle is greater than 360 degrees, the rotation is terminated, and all the dominant directions obtained are combined with the current deployment location of the directed wireless charger into a charger placement strategy, and the charger placement strategy is incorporated into the limited charger placement strategy space.

[0130] B7: Charger placement strategy in limited space Delete the charger placement strategies that are subsets of other charger placement strategies;

[0131] B8: Repeat steps B1 to B7 until all sub-areas F i The strategies have been calculated;

[0132] B9: Return to the limited charger placement strategy space

[0133] It should be noted that there is limited space for charger placement strategies. The size is O(K 2 n 4 ),

[0134] The maximum number of sub-regions divided in step S3 does not exceed O(K 2 n 2 ), for each sub-region, the number of candidate dominating strategies generated by step B3 or B4 is O(n 2 ), because the number of sensor node pairs is And each pair of sensor nodes only generates O(1) candidate dominating strategies. In step B6, since there are at most n sensor nodes in the coverage set of any sub-area, there are O(n) candidate dominating strategies. Therefore, any partition has O(n 2) dominant strategies. Therefore, the size of the strategy space obtained in step S4 is O(K 2 n 4 ).

[0135] S5: Transforming the robust utility of directional wireless charger placement problem;

[0136] Furthermore, the problem of converting the robust utility to the directional wireless charger placement problem includes:

[0137] C1: Based on approximate power Substituting the actual charging power P(d), we can obtain the rechargeable sensor s i Approximate charging efficiency and minimum approximate charging utility

[0138]

[0139]

[0140] C2: Rewrite P1 as follows:

[0141]

[0142]

[0143] C3: Introduce a positive real number k and rewrite P2 into the equivalent P3:

[0144] (P3)max k (12)

[0145]

[0146] C4: Introduce formula Define P4:

[0147]

[0148]

[0149] S6: Call the robust utility directional wireless charger placement algorithm to calculate the position and charging direction of the wireless charger.

[0150] Furthermore, the robust utility directed wireless charger placement algorithm includes:

[0151] D1: Initialize the binary search lower bound k min =0, binary search upper bound

[0152] D2: Perform a binary search, let

[0153] D3: Initialize the temporary deployed placement strategy set to an empty set, that is,

[0154] D4: From the set of deployment strategies that have not yet been selected Find the right The deployment strategy with the largest marginal value (o j ,θ j ), that is:

[0155] D5: Change the strategy (o j ,θ j ) joins the temporary deployed placement strategy set, i.e.

[0156] D6: Repeat steps D4 to D5 until the total charging utility is greater than or equal to k or All charger placement strategies in have been selected;

[0157] D7: If the number of strategies in the temporarily deployed placement strategy set Greater than m, that is Then let k max = k; otherwise, let k min = k,

[0158] D8: Repeat steps D2 to D7 until (k max -k min )<γ, where γ is the search accuracy and γ is a known constant;

[0159] D9: Returns the set of deployed placement strategies

[0160] It should be noted that the robust utility scheduling algorithm for directed wireless chargers is a polynomial time algorithm. For the binary search algorithm in step D8, γ∈(0,1) is the search accuracy and the search space is The outer layer meets the requirements of search accuracy result output The time complexity of step C4 is to search for the strategy space with the largest marginal utility among all strategy spaces, and its time complexity is Step D4 to step D5 are iterated m times, so the time complexity of the robust utility scheduling algorithm for directed wireless chargers is That is, the robust utility coverage scheduling algorithm for directed wireless chargers is a polynomial time algorithm. This polynomial time algorithm can save a lot of computing time while ensuring accurate results.

[0161] Example 2

[0162] Reference Figure 1-11 , is an embodiment of the present invention, in which the sensor is placed as follows Figure 1 As shown, the placement strategy of the directional wireless charger is solved with the goal of maximizing the charging utility of the sensor with the smallest charging utility.

[0163] Depend on Figure 2 As can be seen from the flowchart, the robust utility directional wireless charger placement method of the present invention comprises the following steps:

[0164] In this embodiment S1, the set of sensors is S = {s1, s2, s3, s4, s5, s6}, the set of directional wireless chargers is O, the charging area is a two-dimensional plane Ω of 4m*4m, and the information of each sensor is shown in Table 1, where the coordinate position is based on the coordinate origin (the lower left corner of the charging area Ω is defined as the coordinate origin).

[0165] Table 1 Sensor information table

[0166]

[0167]

[0168] Specifically, the rechargeable sensor charging utility includes the following steps:

[0169] (1) Set α = 100, β = 40, maximum charging distance D = 1.5 m, and charging angle A of the directional wireless charger s =45°, the sensor receiving angle is A o =60°, when d(s i ,o j )≤D, When , the sensor can always obtain positive power. Therefore, substituting the above parameters into formula (1), we get:

[0170]

[0171] In this example, the charging model of the directional wireless charger and the sensor is as follows: Figure 3 As shown in the figure, there are rechargeable sensors s1, s2, and directional wireless charger o1 in the plane. For sensor s1, according to the receiving direction φ1 of its receiving antenna, in order to more intuitively display the concept of receiving direction, the direction vector is defined And displayed in Figure 3 In the receiving angle A o The maximum receiving radius can construct a fan-shaped receiving area. The receiving area of ​​sensor s2 is constructed in a similar way. The directional wireless charger o1 has a charging angle A according to its charging direction θ1. sand the maximum charging radius D to construct a fan-shaped charging area. i Directed wireless charger j The charging area and charger o j In sensor i When in the receiving area, the wireless charger j To sensor i Energy transfer. Figure 3 In the example, the directional wireless charger o1 can transmit energy to the sensor s2, but cannot transmit energy to the sensor s1.

[0172] (2) Formalization of sensors i The charging effect is

[0173]

[0174] in, represents the placement strategy of the deployed chargers, For all placement strategies, For sensors i The maximum charging power that can be received. For sensors i Charging effect.

[0175] (3) Define the minimum charging utility of all sensors

[0176]

[0177] S2: Formalizing the robust utility directed wireless charger placement problem includes the following steps:

[0178] Establishing constraints Ensure that the number of deployed chargers is less than the upper limit m, where is the number of deployed chargers. In this embodiment, m=8, that is, at most 8 directional wireless chargers can be deployed;

[0179] Establishing constraints Ensure that the deployment strategy of the sensor is reasonable, that is, the charger is located in the charging area, and the charging direction is between 0 and 360 degrees. For the convenience of expression, the present invention reuses the symbol o j For charger o j The deployment position, θ j For charger o j Charging direction;

[0180] Taking maximizing the minimum sensor charging utility as the optimization goal, a unified formalized robust utility directed wireless charger placement problem is obtained:

[0181]

[0182]

[0183]

[0184] S3 includes the following steps:

[0185] A1 is composed of Figure 4 As shown, the approximate power is defined

[0186]

[0187] where d is the charging distance, l(k) = β((1 + ∈) k / 2 - 1) is the discretized charging distance, l(0) = 0, l(K) = D, D is the maximum charging distance, ∈ is the discretization constant, and K is the number of segments 2. In this embodiment, ∈ = 0.2, D = 1.5m, so three discretized distances are formed: l(0) = 0, l(1) = 1.12m, l(2) = 1.5m. As Figure 4 shown, the original charging power is continuous. Now when l(0) < d ≤ l(1), when l(1) < d ≤ l(2), when d > l(2),

[0188] A2: As Figure 5 shown, for each sensor s i , with its position as the center and the receiving direction receiving angle A o , concentric sectors with radii l(1) and l(2) are drawn. In this way, the receiving area of each sensor is divided into 2 partitions, and the partitions of different sensors overlap to form new and smaller discrete sub - regions. Finally, Figure 5 6 sub - regions are obtained in

[0189] A3: For each sub - region in (42), denoted as F i , the set of sensors that the sub - region F i can cover is defined as the candidate coverage sensor set of this sub - region Taking sensors s1 and s2 as an example, in Figure 5 , sensors s1 and s2 construct the sub - regions {F1, F2, F3, F4, F5, F6}, where

[0190] Using the same method as in step S3, all sub - regions are calculated

[0191] The flowchart of the charger placement strategy discretization algorithm in step S5 is as follows: Figure 6 As shown, the following steps are included:

[0192] B1: Select a sub-region F that has not been calculated i ;

[0193] B2: Select sub-area F i The candidate coverage sensor set Any pair of sensors in is set as s1 and s2;

[0194] B3: If Figure 7 As shown, this embodiment takes the projection partitioning of s1 and s2 as an example to obtain the strategies (o1, θ1), (o2, θ1), the sensor set covered by (o1, θ1) is {s1}, and the sensor set covered by (o2, θ1) is {s1, s2}, and the strategy is incorporated into the charger placement strategy space

[0195] B4: If Figure 8 As shown, this embodiment performs translation partitioning on s4 and s5 to obtain strategies (o3, θ2) and (o4, θ3), which can cover the sensor sets {s4, s5} and {s4, s5, s6} respectively, and incorporate the strategies into the charger placement strategy space

[0196] B5: Repeat steps (52) to (54) until Each pair of sensors has been selected.

[0197] B6: Fig. 9 As shown, in sub-area F i A point o5 is randomly selected from the boundary of the charger as the deployment position of the charger, and its charging direction is rotated counterclockwise from 0 degrees to 360 degrees to cover the sensors one by one. First, the direction of the charger is initialized to 0 degrees, such as Fig. 9 As shown in (a), during the rotation process, if some covered sensor nodes will be uncovered, the current charging direction is marked as the dominant direction. Then continue to rotate. If some covered sensors will be uncovered after the new sensor nodes are covered, the current direction is marked as the dominant direction. During the rotation process, if the rotation angle is greater than 360 degrees, the rotation is terminated. Fig. 9 Three dominant directions were obtained, namely Fig. 9 (b), covering sensor {s3}, Fig. 9 (c) Covering sensors {s1,s2} Fig. 9(d) Covering sensors {s4, s5, s6}, all the dominant directions obtained are combined with the current deployment position into a charger placement strategy and incorporated into the charger placement strategy space

[0198] B7: Identify and delete some placement strategies in the strategy space. The sensor set covered by (o1, θ1) is included in the sensor set covered by (o2, θ1), so the strategy (o1, θ1) is deleted. Because the sensor set covered by (o3, θ2) is included in the sensor set covered by (o4, θ3), the strategy (o3, θ2) is deleted. Finally, the placement strategy set is obtained as shown in Table 2.

[0199] B8: Repeat steps B1 to B7 until all sub-areas F i All have been calculated;

[0200] B9: Return to the limited charger placement strategy space

[0201] Table 2 Deployment strategy set in sub-region F1

[0202]

[0203]

[0204] In this embodiment, the specific steps of step S5 are as follows:

[0205] C1: Approximate charging power obtained in step S3 Substitute the actual charging power P(d) to obtain the sensor s i Approximate charging efficiency and minimum approximate charging utility

[0206]

[0207]

[0208] C2: Rewrite the original scheduling model as

[0209]

[0210]

[0211] C3: Introduce a positive real number k and rewrite the original problem as

[0212] max k

[0213]

[0214] C4: Introduce formula Rephrase the question as

[0215]

[0216]

[0217] In this embodiment, Fig.10 It can be seen that the specific steps of step S6 are as follows:

[0218] D1: Initialize the binary search lower bound k min = 0, binary search upper bound Binary search accuracy γ = 0.001,

[0219] D2: Perform a binary search, let

[0220] D3: Initialize the temporary deployed placement strategy set to an empty set, that is,

[0221] D4: From the set of deployment strategies that have not yet been selected Find the right The deployment strategy with the largest marginal value (o j ,θ j ), that is, According to this example, the deployment strategy that can be selected is (o4,θ4), and its marginal value is 0.06;

[0222] D5: Change the strategy (o j ,θ j ) joins the temporary deployed placement strategy set, i.e.

[0223] D6: Repeat steps (74) to (75) until the total charging utility is greater than or equal to k or all charging strategies have been selected. In this embodiment, (o4, θ4), (o1, θ2), (o2, θ1), (o5, θ7), (o3, θ3), (o8, θ9) (o6, θ7), (o7, θ8) are selected in turn according to the selection method with the largest marginal value;

[0224] D7: If the number of strategies in the temporarily deployed placement strategy set Greater than 8, that is Then let k max = k; otherwise, let k min = k,

[0225] D8: Repeat steps (72) to (77) until (k max-k min )<γ;

[0226] D9: Fig.11 As shown, the deployed placement strategy collection is returned.

[0227] Since large-scale wireless rechargeable sensor networks require a very large amount of data from chargers and sensors, it is difficult to list embodiments. Therefore, this embodiment lists embodiments of a method for robust utility placement of directional wireless chargers in a small-scale wireless rechargeable sensor network, but still proves through theoretical derivation that the application of the present invention in large-scale wireless rechargeable sensor networks still has great advantages.

[0228] Example 3

[0229] Reference Fig.12 , which is another implementation case of the present invention. In order to verify and illustrate the technical effects adopted in this method, this embodiment involves two schemes for comparative testing with the method of the present invention.

[0230] (1) Optimizing the charging utility placement algorithm. The algorithm iteratively selects the placement strategy with the maximum marginal total charging utility until m chargers are placed.

[0231] (2) Maximum Worst Sensor Marginal Utility Algorithm: This algorithm iteratively selects the placement strategy that maximizes the marginal charging utility of the worst sensor node until m chargers are placed.

[0232] Parameter setting: We evenly distribute the sensor nodes in a 60m×60m square area. We set α=100, β=40, D=6m, n=90, m=100, A s =π / 2,A o =2π / 3. For each s i ∈S, its maximum charging power is We will vary the values ​​of key parameters to explore their effects on the algorithm. All simulations are run on a Windows machine with an Intel(R) Xeon(R) CPU E5-2603 v2 and 16 GB of memory. Each measurement is averaged over 100 random topologies.

[0233] like Fig.12 As shown, the robust utility directional wireless charger placement algorithm is compared with the other two algorithms in terms of the number of sensors, such as Fig.12(a), the robust utility directional wireless charger placement algorithm outperforms the optimized charging utility placement algorithm and the maximum worst sensor marginal utility algorithm by 120.11% and 54.61%, respectively. In terms of the number of chargers, Fig.12 (b), the robust utility directional wireless charger placement algorithm outperforms the optimized charging utility placement algorithm and the maximum worst sensor marginal utility algorithm by 53.25% and 32.81%, respectively. In terms of sensor receiving angle, Fig.12 (c), the robust utility directional wireless charger placement algorithm outperforms the optimized charging utility placement algorithm and the maximum worst sensor marginal utility algorithm by 23.01% and 70.23%, respectively. In terms of charging angle, Fig.12 (d), the robust utility directional wireless charger placement algorithm outperforms the optimized charging utility placement algorithm and the maximum worst sensor marginal utility algorithm by 44.73% and 37.01%, respectively. In terms of the upper limit of the sensor's receiving power, Fig.12 (e), the robust utility directional wireless charger placement algorithm outperforms the optimized charging utility placement algorithm and the maximum worst sensor marginal utility algorithm by 80.87% and 64.77%, respectively. As for the discretization constant in step (4), Fig.12 (f), the robust utility directional wireless charger placement algorithm outperforms the optimized charging utility placement algorithm and the maximum-worst sensor marginal utility algorithm by 21.15% and 58.96%, respectively.

[0234] Example 4

[0235] Reference Fig.13 , which is another implementation case of the present invention, is verified by actual experiments based on the two existing algorithms proposed in the previous embodiment. Fig.13 As shown, the experiment was conducted in a 4m×4m area, where four sensor nodes were placed at random locations in the area with coordinates of (1.32, 1.65), (1.07, 1.26), (2.89, 2.38), (1.53, 1.19), (0.97, 1.95) and (1.06, 2.91), discretization constant ∈ = 0.2, binary search accuracy γ = 0.001, number of chargers m = 8, and maximum received power The detailed strategies of the three algorithms are as follows Fig.13 and as shown in Table 3. The optimization charging utility placement algorithm is as follows Fig.13 (a) shows the maximum worst sensor marginal utility algorithm. Fig.13 As shown in (b), the robust utility directional wireless charger placement algorithm is Fig.13 (c) Fig.14 As shown, the robust utility directional wireless charger placement algorithm outperforms the optimized charging utility placement algorithm and the maximum-worst sensor marginal utility algorithm by at least 68.97% and 58.06%, respectively.

[0236] Table 3 Charger placement strategies of different algorithms

[0237]

[0238]

[0239] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A robust utility directional wireless charger placement method, characterized in that: include: defining a set of chargeable sensors, a set of directed wireless chargers, and a charging utility for the chargeable sensors; Formalize the robust utility directed wireless charger placement problem; A discretized finite sub-region set and a candidate coverage sensor set are obtained by using a region discretization method; The region discretization method comprises: A1: Defining approximate power Where d is the charging distance, l(k) = β((1+∈) k / 2 -1) is the discretized charging distance, l(0) = 0, l(K) = D, D is the maximum charging distance, ∈ is the discretization constant, K is the number of segments, P(0) is the charging power when the charging distance is 0, and P(D) is the charging power when the charging distance is D; A2: For each rechargeable sensor i , taking its position as the center, receiving direction Receiving Angle A o , concentric sectors with radius l(1), l(2), …, l(K) are drawn. The receiving area of ​​each rechargeable sensor is divided into K partitions, and the partitions of different sensors overlap each other to form new discrete sub-areas; A3: For each of the new discrete sub-regions, let F i , define sub-region F i The rechargeable sensor set that can cover the sub-area is the candidate coverage sensor set Call the charger placement strategy discretization algorithm to obtain a limited charger placement strategy space; Transforming the robust utility directed wireless charger placement problem; Call the robust utility directional wireless charger placement algorithm to calculate the position and charging direction of the wireless charger; The robust utility directed wireless charger placement algorithm includes: D1: Initialize binary search lower bound k min =0, binary search upper bound D2: Perform a binary search, let D3: Initialize the temporary deployed placement strategy set to an empty set, that is, D4: From the set of deployment strategies that have not yet been selected Find the right The deployment strategy with the largest marginal value (o j ,θ j ), that is: D5: Change the strategy (o j ,θ j ) joins the temporary deployed placement strategy set, i.e. D6: Repeat steps D4 to D5 until the total charging utility is greater than or equal to k or All charger placement strategies in have been selected; D7: If the number of strategies in the temporarily deployed placement strategy set Greater than m, that is Then let k max = k; otherwise, let k min = k, D8: Repeat steps D2 to D7 until (k max -k min )<γ, where γ is the search accuracy and γ is a known constant; D9: Returns the set of deployed placement strategies 2. The method for placing a robust utility directional wireless charger according to claim 1, wherein: The rechargeable sensor set is: set S = {s1, s2, ..., s n }, the set of directional wireless chargers is O, the charging area Ω is a two-dimensional plane, and the charger is placed in the charging area Ω.

3. The method for placing a robust utility directional wireless charger according to claim 1 or 2, characterized in that: The rechargeable sensor charging utility includes: Rechargeable Sensors i From directional wireless charger o j The charging power obtained is: Among them, the directional wireless charger and the rechargeable sensor have charging angles A and s and receiving angle A o , α and β are two constants determined by the magnetic field environment and hardware parameters of the charger and the rechargeable device, D is the maximum charging distance, d(s i ,o j ) is a directional wireless charger o j With rechargeable sensors i The distance between Directed wireless charger j The charging direction vector, For rechargeable sensors i The receiving direction vector, when d(s i ,o j )≤D, and At 0, the rechargeable sensor always obtains positive power; Formalize the rechargeable sensors i When the deployed placement strategy set is The charging effect is: in, Represents the set of deployed placement strategies, To place the strategy space, For sensors i The maximum charging power that can be received, and is a known positive real number; Defines the minimum charging utility of all rechargeable sensors for:

4. The robust utility directional wireless charger placement method as claimed in claim 3, characterized in that: The formalized robust utility directed wireless charger placement problem includes: Establishing constraints Ensure that the number of deployed chargers is less than the upper limit m, where is the number of deployed chargers; Establishing constraints Ensure that the deployment strategy of the sensor is reasonable, that is, the charger is located in the charging area, and the charging direction is between 0 and 360 degrees. For the convenience of expression, the present invention reuses the symbol o j For charger o j The deployment position, θ j For charger o j Charging direction; Taking maximizing the minimum sensor charging utility as the optimization goal, a unified formalized robust utility directed wireless charger placement problem is obtained:

5. The method for placing a robust utility directional wireless charger according to claim 4, wherein: The calling of the charger placement strategy discretization algorithm comprises: B1: Select a sub-region F that has not been calculated i ; B2: Select the sub-area F i The candidate coverage sensor set Any pair of rechargeable sensors in , set as s1 and s2; B3: Execute projection partitioning algorithm; B4: Execute translation partitioning algorithm; B5: Repeat steps B2 to B4 until Each pair of rechargeable sensors has been selected; B6: Execute the rotation partitioning algorithm in the sub-area F i A point is randomly selected from the boundary as the deployment position of the directional wireless charger, and its charging direction is rotated counterclockwise from 0 degrees to 360 degrees to cover the rechargeable sensors one by one. First, the direction of the directional wireless charger is initialized to 0 degrees. During the rotation process, if some covered rechargeable sensor nodes will be uncovered, the current charging direction is marked as the dominant direction; then the rotation is continued. If some covered rechargeable sensors will be uncovered after the new sensor nodes are covered, the current direction is marked as the dominant direction; during the rotation process, if the rotation angle is greater than 360 degrees, the rotation is terminated, and all the dominant directions obtained are combined with the current directional wireless charger deployment position into a charger placement strategy, and the charger placement strategy is incorporated into the limited charger placement strategy space. B7: The limited charger placement strategy space Delete the charger placement strategies that are subsets of other charger placement strategies; B8: Repeat steps B1 to B7 until the strategies of all sub-regions F have been calculated; B9: Return the limited charger placement strategy space 6. The method for placing a robust utility directional wireless charger according to claim 5, characterized in that: The execution of the projection partitioning algorithm is as follows: draw a straight line through s1 and s2, and extend the straight line to intersect with the sub-area boundary; place the chargers at these intersections and adjust their directions so that s1 and s2 are exactly located on the clockwise boundary of the charger coverage area, obtain the current charger placement strategy, and incorporate it into the limited charger placement strategy space 7. The robust utility directional wireless charger placement method of claim 6, wherein: The translation partitioning algorithm is as follows: draw two arcs passing through s1 and s2, and form an angle A with them. s Then, the intersection points of the trajectory and the partition boundary are calculated, and the chargers are placed at these intersection points, so that s1 and s2 are exactly located on the two boundaries of the charger coverage area, respectively, to obtain the current charger placement strategy and incorporate it into the limited charger placement strategy space 8. The method for placing a robust utility directional wireless charger according to claim 7, wherein: Transforming the robust utility directed wireless charger placement problem includes: C1: Based on the approximate power Substituting the actual charging power P(d), we can obtain the rechargeable sensor s i Approximate charging efficiency and minimum approximate charging utility C2: Rewrite P1 as: C3: Introduce a positive real number k and rewrite P2 into an equivalent P3: (P3)maxk(12) C4: Introduce formula Define P4:

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