CN113659670A - Wireless sensor network charging method based on region division - Google Patents

Wireless sensor network charging method based on region division Download PDF

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CN113659670A
CN113659670A CN202110922293.9A CN202110922293A CN113659670A CN 113659670 A CN113659670 A CN 113659670A CN 202110922293 A CN202110922293 A CN 202110922293A CN 113659670 A CN113659670 A CN 113659670A
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CN113659670B (en
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叶晓国
梅经纬
邓徐赛
江佳鹏
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Nanjing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0042—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by the mechanical construction
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
    • H02J50/10—Circuit arrangements or systems for wireless supply or distribution of electric power using inductive coupling
    • H02J50/12—Circuit arrangements or systems for wireless supply or distribution of electric power using inductive coupling of the resonant type
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
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Abstract

The invention discloses a wireless sensor network charging method based on region division, and provides a wireless sensor network charging method aiming at the defects of the background art. The method can divide the area to be monitored into a plurality of areas with isotropy, each mobile charging trolley is only responsible for charging the nodes in the specific area, so that energy waste caused by the fact that the mobile charging trolley moves to the next node to be charged too far is avoided, finally, path planning is carried out on the mobile charging trolleys according to the divided areas, an initial path is generated firstly, then, optimization is carried out according to the initial path to determine an approximate optimal path, accordingly, the charging time of the whole network is fully shortened, and the life cycle of the sensing network is prolonged.

Description

Wireless sensor network charging method based on region division
Technical Field
The invention relates to a wireless sensor network charging method based on region division, which can be used in the technical field of wireless sensing.
Background
Wireless sensor networks have been widely used in many fields, such as forest fire detection, building structure health monitoring, home automation, and so on. Since the conventional sensor nodes use limited battery energy and can only operate for a limited time, the conventional sensor nodes become one of the most critical obstacles for the long-term continuous operation of the wireless sensor network. One solution is to equip the sensor nodes with energy absorbing devices that can extract energy from the environment, solving the energy supply problem to some extent, but the energy extracted by the nodes is very unstable due to the unpredictability of the environmental energy sources.
The breakthrough progress of wireless energy transmission and rechargeable lithium battery technology provides a feasible technical foundation for energy supplement of a wireless rechargeable sensor network. Research by Kurs et al shows that high-efficiency energy transmission can be achieved wirelessly by a strongly coupled magnetic resonance technology without wires and plugs. Over a distance of two meters, a transmitter with 60W power can achieve a wireless power transfer efficiency of 40%. A typical application scenario is that a mobile charging vehicle carries a mobile charger equipped with a large-capacity battery, and starts from a mobile charging service station, a plurality of sensor nodes needing to be charged in a network are charged according to a certain scheduling policy, so that the sensor nodes are prevented from stopping working due to energy exhaustion. After one round of charging, the mobile charging vehicle returns to the charging service station for energy supply to prepare for the next round of charging. However, due to the non-uniform distribution of sensors, it may be relatively sparse or dense over a local area. In the face of the situation, the wireless charging trolley and the base station are configured for the monitoring area in different areas, so that the wireless charging trolley is guaranteed to move only within a certain range, and energy waste caused by the fact that the distance from the wireless charging trolley to the next node is too long is avoided.
Considering that the distances from the centroids to the different sides of the different shapes of the graph are different, the areas to be divided are divided by using the shapes having isotropy (the characteristic that the physical and chemical properties of the object do not change due to the difference of the directions, that is, the performance values of a certain object measured in different directions are completely the same, which is also called homogeneity), so that the mobile charger needs to be scheduled reasonably and efficiently, the charging efficiency of the mobile charger is improved, and the lifetime of the whole network is prolonged to the maximum extent. In order to improve the charging efficiency and reduce the cost of the charging trolley, a variable neighborhood search algorithm framework is provided based on an intelligent optimization algorithm, and the problem of path planning of the charging trolley is solved.
Disclosure of Invention
The invention aims to solve the problems in the prior art, and provides a wireless sensor network charging method based on region division.
The purpose of the invention is realized by the following technical scheme: a wireless sensor network charging method based on region division comprises the following steps:
s1: abstracting a wireless chargeable sensor network into a region with the length L and the width W on a two-dimensional plane, and using S ═ S1，s2，s3，...，sn}. represents the set of n chargeable sensors contained within the area;
s2: performing area division on the two-dimensional plane area in the step of S1, and dividing the two-dimensional plane area into q areas, wherein q is designated as isotropic after division;
s3: dividing a two-dimensional planar area into k2A mesh grid with equal area, wherein
Figure BDA0003206477200000021
a is an input integer representing a precision index;
s4: starting from the first small square grid at the upper left corner of the two-dimensional plane not divided into areas, moving a grids to the right, and then moving a grids downwards to form a grid containing a2Regions of the small squares having isotropy;
s5: judging whether a small squares exist in the horizontal direction of the right side of the isotropic region divided in the previous step, if so, repeating the step S4, otherwise, executing the step S6;
s6: determining a correction parameter b by aIn
Figure BDA0003206477200000022
Receiving a-b grids which are horizontally moved rightwards on the right side of an area which is not divided on a two-dimensional plane, forming an isotropic area by moving the area surrounded by the grids a downwards, adding 1 to the value of m when a conforming area is found, wherein the value of m represents the divided area number of a-b small grids with the length being a and a small grid with the width being a, and the initial value of m is 0;
s7: circularly executing the steps S4, S5 and S6 from the first square grid at the upper left corner of the divided area until a small squares are not involved in the vertical direction of the divided area;
s8: for the rest mesh-shaped small squares which are not divided, starting from the grid at the lower left corner, if m is larger than n, n represents the number of the isotropic regions taking a small squares and a + b small squares as two sides, and a adjacent small squares are adjacent to the divided isotropic regions, adding the adjacent a small squares into the adjacent divided isotropic regions, adding 1 to the value of n, and starting from the region which is not divided at the upper right corner in the same process; if m is n and the number of the divided regions is less than q-1, the first group a2Forming a homodromous area by the adjacent small squares, repeatedly executing the process, and executing the step S9 when the number of the divided areas is q-1;
s9: the number of remaining unallocated tiles must now fall within
Figure BDA0003206477200000023
In the interval between the two, the last remaining small square grids form the last area;
s10: setting a charging threshold value beta for each sensor node, wherein beta is lambda E, 0 is more than lambda and less than 1, E is the maximum electric quantity when the sensor node is fully charged, and monitoring the sensor node s with the residual energy less than beta in the networkiAs a node of the sensor to be charged, the sensor to be charged sends a charging demand to the base station, and adds the node siAdding a set T, wherein elements in the set T represent charging tasks of corresponding nodes;
s11: before the charging path is generated, a better solution is found to participate in the following iteration, with the base station s0As a starting point, all sensor nodes in the set T are planned as a bar initial solution Linit。
Preferably, in the step S2, the two-dimensional plane area is divided into seven areas by area division, and in the step S3, the accuracy index a is set to 3.
Preferably, in the step S1, for the region to be divided, it is designated to divide it into q isotropic regions, and the region to be divided is divided into k2A small grid of equal area, while each isotropic region is assigned to contain a2Small lattice of hair
Figure BDA0003206477200000031
When the determined isotropic region contains a2When the grid is small, the area is called as an ideal area, the number of the ideal areas is set and recorded, and when the square area with the side length of a cannot be divided, the corrected side length of a certain side is acceptable to be [ a-b, a + b ]]In between, i.e. each isotropic region of the division contains
Figure BDA0003206477200000032
Small squares, m and n respectively set the number of the isotropic areas with a side length of a +/-b, wherein m records the number of the areas with a side length of a-b, n records the number of the areas with a side length of a + b, ideally, the isotropic areas comprise
Figure BDA0003206477200000033
Small squares, and the ideal region generated by the method in the steps of S4, S5, S6, S7, S8 and S9 contains a2Squares of small grids, at most one square containing small grids
Figure BDA0003206477200000034
Irregular shape of the cells;
for quantitative evaluation, a size deviation ratio index ε is further defined, representing the ratio of the difference between the maximum and minimum region sizes to the mean:
Figure BDA0003206477200000035
wherein:
Figure BDA0003206477200000041
Figure BDA0003206477200000042
preferably, the step of S11 further includes the steps of:
s110: traversing all nodes in the set T to form a request path Lc；
S111: setting the system temperature t and the lower temperature limit tminSetting an iteration time as a temperature reduction index delta;
s112: exchange LcTo generate a new solution LnAnd calculating a fitness F (L)n) If F (L)n)＞F(Lc)
The optimal solution is updated, otherwise with a certain probability
Figure BDA0003206477200000043
Accepting a poor solution;
s113: gradually reducing the temperature, t ═ t × delta, if t > tminOr the iteration number does not reach the threshold value, the step S113 is repeated, otherwise, the initial solution L is obtainedinit。
Preferably, the step of S12 further includes the steps of: :
s120: setting a series of neighborhoods NkThe neighborhood action is a function by which, for the current solution s, its corresponding set of neighbor solutions is generated, defining the neighborhood action as: exchanging solution elements in solution set path at intervals of q/3 and in solution pathThe solution elements in the middle position are solution elements in the symmetric axisymmetric exchange solution path;
s121: initialization k 1, Zc＝LinitIteratively obtaining the current solution Z according to the field actioncNeighbor solution set Z ofnAnd calculate the neighbor solution ZnIs a fitness of F (Z)n)＞F(Zc) Updating the optimal solution, resetting k to 1, continuing the iteration until the iteration is finished, otherwise, setting k to k +1, continuing the iteration, and finally outputting the approximate optimal solution Zbest。
Compared with the prior art, the invention adopting the technical scheme has the following technical effects: the technical scheme provides a wireless sensor network charging method based on region division aiming at the defects of the background technology, the region to be monitored is divided by the region division method so as to avoid energy waste caused by the fact that the distance from the wireless charging trolley to the next node is too far, and finally a charging path is given based on an intelligent optimization algorithm so as to solve the problem of path planning of the charging trolley.
According to the method, the area to be monitored can be divided into a plurality of areas with isotropy, each mobile charging trolley in the method is only responsible for charging the nodes in a specific area, so that energy waste caused by the fact that the mobile charging trolley moves to the next node to be charged too far is avoided, finally, path planning is carried out on the mobile charging trolleys according to the divided areas, an initial path is generated firstly, then, optimization is carried out according to the initial path to determine an approximate optimal path, therefore, the charging time of the whole network is fully shortened, and the life cycle of the sensing network is prolonged.
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Fig. 1 is a schematic diagram illustrating an exemplary regional division of a wireless sensor network according to a method for charging a wireless sensor network based on regional division of the present invention.
Fig. 2 is a flowchart of a wireless sensor network charging method based on region division according to the present invention.
FIG. 3 is an exemplary diagram of an initial path generated by the path generation method of the present invention.
FIG. 4 is an illustration of an optimized path plan according to the present invention.
Detailed Description
Objects, advantages and features of the present invention will be illustrated and explained by the following non-limiting description of preferred embodiments. The embodiments are merely exemplary for applying the technical solutions of the present invention, and any technical solution formed by replacing or converting the equivalent thereof falls within the scope of the present invention claimed.
The invention discloses a wireless sensor network charging method based on region division.
Each part is specifically described below: a base station: the base station is a fixed point in a network center, can collect data of the whole network sensor by a multi-hop routing transmission method, comprises the collected data and the self electric quantity information, and can supplement energy for the mobile charger to make a scheduling route plan.
A sensor node: the sensor nodes are randomly deployed on some nodes on the two-dimensional space position, the sensor nodes have the functions of monitoring the surrounding environment, and data can be transmitted among the nodes through a route, so that different nodes have different energy consumption rates. The total energy of the batteries of all the sensor nodes is the same.
The mobile charger is: the device is movable, carries a large-capacity rechargeable battery and can perform energy conversion with the sensor node. All mobile chargers can carry the same amount of energy, all obtained from the base station, and are used for charging the sensors and mechanically moving the required energy, and the mobile chargers work along a scheduled route established by the base station.
Scheduling routes: the base station plans according to the position of the sensor node needing to supplement energy at a certain moment, different mobile chargers have different routes, and all the routes finally return to the base station, so that the system can be ensured to operate all the time.
The technical scheme provides a wireless sensor network charging method based on isotropic region division. In the traditional method, under the scene that the sensor nodes are distributed unevenly, the charging trolley is possibly away from the areas where most of the nodes are located gradually due to a certain charging task, so that the problem of energy waste due to too long driving distance is caused. The technical scheme provides a wireless sensor network charging method based on region division, the region to be monitored is divided by the region division method, so that energy waste caused by the fact that a wireless charging trolley moves to the next node too far is avoided, in addition, in order to improve charging efficiency and reduce charging trolley cost, a new path planning algorithm framework is provided based on an intelligent optimization algorithm, and the path planning problem of the charging trolley is solved. The charging time of the whole network is fully shortened, and the long-term operation of the network is ensured.
Taking the area to be monitored in fig. 1 as an example, the area to be monitored is divided into 7 areas after the area division method is adopted in fig. 1, and each mobile charging trolley can only charge the sensor nodes in the specified area, so that the situation that the mobile charging trolley is far away from the area with a large number of charging nodes due to the fact that a single node is charged is avoided.
A wireless sensor network charging method based on region division comprises the following steps:
s1: abstracting a wireless chargeable sensor network into a region with the length L and the width W on a two-dimensional plane, and using S ═ S1，s2，s3，...，sn}. represents the set of n chargeable sensors contained within the area;
s2: dividing the two-dimensional plane area in the step S1 into q areas, wherein q is designated as the divided areas having isotropy, i.e., the performance values measured by an object in different directions are completely the same, and here, the number of areas with equal distances from the centroid of the area to each side of the area is referred to;
s3: dividing a two-dimensional planar area into k2A mesh grid with equal area, wherein
Figure BDA0003206477200000061
a is an input integer representing the precision index, and the larger the value of a is, the finer granularity can be obtained;
s4: starting from the first small square grid at the upper left corner of the two-dimensional plane not divided into areas, moving a grids to the right, and then moving a grids downwards to form a grid containing a2Regions of the small squares having isotropy;
s5: judging whether a small squares exist in the horizontal direction of the right side of the isotropic region divided in the previous step, if so, repeating the step S4, otherwise, executing the step S6;
s6: determining a correction parameter b by a, wherein
Figure BDA0003206477200000062
Receiving a-b grids which are horizontally moved rightwards on the right side of an area which is not divided on a two-dimensional plane, forming an isotropic area by moving the area surrounded by the grids a downwards, adding 1 to the value of m when a conforming area is found, wherein the value of m represents the divided area number of a-b small grids with the length being a and a small grid with the width being a, and the initial value of m is 0;
s7: circularly executing the steps S4, S5 and S6 from the first square grid at the upper left corner of the divided area until a small squares are not involved in the vertical direction of the divided area;
s8: and for the rest of the mesh-shaped small squares which are not divided, starting from the grid at the lower left corner, if m is larger than n, n represents the number of the isotropic regions taking a small squares and a + b small squares as two sides, and a adjacent small squares are adjacent to the divided isotropic regions, adding the adjacent a small squares into the adjacent divided isotropic regions, adding 1 to the value of n, and starting from the region which is not divided at the upper right corner in the same process. If m is n and the number of the divided regions is less than q-1, the first group a2Adjacent cells form an isotropic region. Repeatedly executing the above process, and executing the step S9 when the number of the divided areas is q-1;
s9: the number of remaining unallocated tiles must then beThen fall in [ a ]2，2a2-1]In the interval between the two, the last remaining small square grids form the last area;
s10: setting a charging threshold value beta for each sensor node, wherein beta is lambda E, 0 is more than lambda and less than 1, E is the maximum electric quantity when the sensor node is fully charged, and monitoring the sensor node s with the residual energy less than beta in the networkiAs a node of the sensor to be charged, the sensor to be charged sends a charging demand to the base station, and adds the node siAdding a set T, wherein elements in the set T represent charging tasks of corresponding nodes;
s11: before the charging path is generated, a better solution is found to participate in the following iteration, with the base station s0As a starting point, all sensor nodes in the set T are planned to be an initial solution Linit。
The step of S11 further includes the steps of:
s110: traversing all nodes in the set T to form a request path Lc；
S111: setting the system temperature t and the lower temperature limit tminSetting an iteration time as a temperature reduction index delta;
s112: exchange LcTo generate a new solution LnAnd calculating a fitness F (L)n) If F (L)n)＞F(Lc)
The optimal solution is updated, otherwise with a certain probability
Figure BDA0003206477200000071
Accepting a poor solution;
s113: gradually reducing the temperature, t ═ t × delta, if t > tminOr the iteration number does not reach the threshold value, the step S113 is repeated, otherwise, the initial solution L is obtainedinit。
5. The method of claim 1, wherein the method comprises: the step of S12 further includes the steps of: :
s120: setting a series of neighborhoods NkThe neighborhood action is a function by which to solve the current solutions, generate its corresponding set of neighbor solutions, defining the domain actions as: exchanging solution elements with each interval of q/3 in the solution set path and taking the solution element at the middle position in the solution path as solution elements in the symmetrical axis symmetrical exchange solution path;
s121: initialization k 1, Zc＝LinitIteratively obtaining the current solution Z according to the field actioncNeighbor solution set Z ofnAnd calculate the neighbor solution ZnIs a fitness of F (Z)n)＞F(Zc) Updating the optimal solution, resetting k to 1, continuing the iteration until the iteration is finished, otherwise, setting k to k +1, continuing the iteration, and finally outputting the approximate optimal solution Zbest。
For the area to be divided, the area to be divided is designated to be divided into q isotropic areas, and the area to be divided is divided into k2A small grid of equal area, while each isotropic region is assigned to contain a2A small grid of thereby
Figure BDA0003206477200000081
When the determined isotropic region contains a2When the grid is small, the region is called an ideal region. Setting l to record the number of ideal areas, and when the square area with the side length of a cannot be divided, accepting that the corrected side length of a certain side is [ a-b, a + b ]]In between, i.e. each isotropic region of the division contains
Figure BDA0003206477200000082
The small squares are provided with m and n numbers of isotropic regions having a side of a + -b (where m is the number of regions having a side of a-b and n is the number of regions having a side of a + b), and ideally the isotropic regions include
Figure BDA0003206477200000083
Small squares, and the ideal region generated by the method in the steps of S4, S5, S6, S7, S8, S9 contains a2Squares of small grids, at most one square containing small grids
Figure BDA0003206477200000084
Irregular shape in between.
For quantitative evaluation, a size deviation ratio index ε is further defined, representing the ratio of the difference between the maximum and minimum region sizes to the mean:
Figure BDA0003206477200000085
wherein:
Figure BDA0003206477200000086
Figure BDA0003206477200000087
assuming that the region to be detected is a rectangle with a length of 800m and a width of 800m, the region is represented by 8 × 8 small grids, each small grid is a small square with a side length of 100m, we designate that the region is divided into 7 regions with isotropy, and the result after division is shown in fig. 1.
For convenience of description and understanding of the technical solution, the area division is performed by taking fig. 1 as an example, and when the area division is performed on an area to be monitored, as shown in a flowchart of the method shown in fig. 2, the following steps are performed:
s1: for a wireless sensor network area to be monitored, firstly, specifying q to be 7, namely, dividing the area to be monitored into 7 small areas with isotropy, and setting a precision index a to be 3;
s2: by
Figure BDA0003206477200000091
Obtaining k as 8, thereby dividing the wireless sensor network area into 8 by 8 grid areas;
s3: starting from the upper left corner of the grid area, the 1 st isotropic area is determined, from left to right in the horizontal directionWalking a small grids as the length of the 1 st region, then walking a small grids downwards as the width of the 1 st region to form the 1 st region containing a2The regions of the small squares having isotropy, such as region a in fig. 1;
s4: the next region is derived further to the right, adjacent to the previous square region. Repeating the step 3 on the right side of the last area to form an area B as shown in FIG. 1, and executing the step S5 when no qualified area exists on the right side;
s5: at this time, the right horizontal direction does not contain a small square grid area, then the area formed by the length and the width of a-b and a respectively is accepted to form an isotropic area, such as an area C in the figure, and the value of m is added with 1;
s6: repeating the steps S3, S4 and S5, continuing to generate the region D, E, F in the figure 1 downwards, and executing the step S7 when no region meets the conditions;
s7: for the rest grids, starting from the grid at the lower left corner of the region which is not divided, a homodromous region meeting the condition cannot be found, at the moment, m is larger than n, a adjacent grids are adjacent to the divided region D, the a grids are added into the region D, and the value of n is added with 1;
s8: repeating the step of S7 to the right to form a new area E;
s9: when m is n and the number of the divided regions is less than q-1, forming a region by the adjacent a small grids which are not divided, and repeating the step of S9, otherwise, executing the step of S10;
s10: the remaining grid constitutes the last region, G in fig. 1.
S11: and setting an energy threshold value for each sensor node, and when the energy of the current sensor node is lower than the threshold value, sending a charging request to the base station and adding the charging request into the task set T.
S12: the trolley in the designated area generates an initial charging loop path according to the charging request task belonging to the current area in the charging task set T, as shown in fig. 3.
S13: the above path is optimized to obtain an approximately optimal path, as shown in fig. 4.
In a traditional method, under the condition that sensor nodes are distributed unevenly, a charging trolley is possibly away from the areas where most of the nodes are located gradually due to a certain charging task, so that energy is wasted due to the fact that the driving distance is too far. The invention provides a wireless sensor network charging method based on isotropic region division, which is used for dividing a region to be monitored so as to avoid energy waste caused by too far distance of a wireless charging trolley moving to a next node, and provides a variable neighborhood search algorithm framework based on an intelligent optimization algorithm so as to improve charging efficiency and reduce charging trolley cost and solve the problem of path planning of the charging trolley. The charging time of the whole network is fully shortened, and the long-term operation of the network is ensured.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein, and any reference signs in the claims are not intended to be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art. The invention has various embodiments, and all technical solutions formed by adopting equivalent transformation or equivalent transformation are within the protection scope of the invention.

Claims (5)

1. A wireless sensor network charging method based on region division is characterized in that: the method comprises the following steps:
s1: abstracting a wireless chargeable sensor network into a region with the length L and the width W on a two-dimensional plane, and using S ═ S1，s2，s3，…，sn}. represents the set of n chargeable sensors contained within the area;
s2: performing area division on the two-dimensional plane area in the step of S1, and dividing the two-dimensional plane area into q areas, wherein q is designated as isotropic after division;
s3: dividing a two-dimensional planar area into k2A mesh grid with equal area, wherein
Figure FDA0003206477190000011
a is an input integer representing a precision index;
s4: starting from the first small square grid at the upper left corner of the two-dimensional plane not divided into areas, moving a grids to the right, and then moving a grids downwards to form a grid containing a2Regions of the small squares having isotropy;
s5: judging whether a small squares exist in the horizontal direction of the right side of the isotropic region divided in the previous step, if so, repeating the step S4, otherwise, executing the step S6;
s6: determining a correction parameter b by a, wherein
Figure FDA0003206477190000012
Receiving a-b grids which are horizontally moved rightwards on the right side of an area which is not divided on a two-dimensional plane, forming an isotropic area by moving the area surrounded by the grids a downwards, adding 1 to the value of m when a conforming area is found, wherein the value of m represents the divided area number of a-b small grids with the length being a and a small grid with the width being a, and the initial value of m is 0;
s7: circularly executing the steps S4, S5 and S6 from the first square grid at the upper left corner of the divided area until a small squares are not involved in the vertical direction of the divided area;
s8: for the remaining undivided mesh smallsThe method comprises the following steps that (1) squares are arranged, starting from a grid at the lower left corner, if m is larger than n, n represents the number of isotropic regions taking a small squares and a + b small squares as two sides, and a number of adjacent small squares are adjacent to a divided isotropic region, the adjacent a small squares are added into the adjacent divided isotropic region, the value of n is added by 1, and the same process also starts from the region which is not divided at the upper right corner; if m is n and the number of the divided regions is less than q-1, the first group a2Forming a homodromous area by the adjacent small squares, repeatedly executing the process, and executing the step S9 when the number of the divided areas is q-1;
s9: the number of remaining unallocated tiles at this time must fall within [ a ]2，2a2-1]In the interval between the two, the last remaining small square grids form the last area;
s10: setting a charging threshold value beta for each sensor node, wherein beta is lambda E, 0 is more than lambda and less than 1, E is the maximum electric quantity when the sensor node is fully charged, and monitoring the sensor node s with the residual energy less than beta in the networkiAs a node of the sensor to be charged, the sensor to be charged sends a charging demand to the base station, and adds the node siAdding a set T, wherein elements in the set T represent charging tasks of corresponding nodes;
s11: before the charging path is generated, a better solution is found to participate in the following iteration, with the base station s0As a starting point, all sensor nodes in the set T are planned to be an initial solution Linit。
2. The method of claim 1, wherein the method comprises: in the step S2, the two-dimensional plane area is divided into seven areas by area division, and in the step S3, the accuracy index a is set to 3.
3. The method of claim 1, wherein the method comprises: in the step S1, for the region to be divided, it is designated to divide it into q isotropic regionsAnd dividing the region to be divided into k2A small grid of equal area, while each isotropic region is assigned to contain a2A small grid of thereby
Figure FDA0003206477190000021
When the determined isotropic region contains a2When the grid is small, the area is called as an ideal area, the number of the ideal areas is set and recorded, and when the square area with the side length of a cannot be divided, the corrected side length of a certain side is acceptable to be [ a-b, a + b ]]In between, i.e. each isotropic region of the division contains
Figure FDA0003206477190000022
Small squares, m and n respectively set the number of the isotropic areas with a side length of a +/-b, wherein m records the number of the areas with a side length of a-b, n records the number of the areas with a side length of a + b, ideally, the isotropic areas comprise
Figure FDA0003206477190000023
Small squares, and the ideal region generated by the method in the steps of S4, S5, S6, S7, S8, S9 contains a2Squares of small grids, at most one square containing small grids
Figure FDA0003206477190000024
Irregular shape of the cells;
for quantitative evaluation, a size deviation ratio index ε is further defined, representing the ratio of the difference between the maximum and minimum region sizes to the mean:
Figure FDA0003206477190000025
wherein:
Figure FDA0003206477190000031
Figure FDA0003206477190000032
4. the method of claim 1, wherein the method comprises: the step of S11 further includes the steps of:
s110: traversing all nodes in the set T to form a request path Lc；
S111: setting the system temperature t and the lower temperature limit tminSetting an iteration time as a temperature reduction index delta;
s112: exchange LcTo generate a new solution LnAnd calculating a fitness F (L)n) If F (L)n)＞F(Lc)
The optimal solution is updated, otherwise with a certain probability
Figure FDA0003206477190000033
Accepting a poor solution;
s113: gradually reducing the temperature, t ═ t × delta, if t > tminOr the iteration number does not reach the threshold value, the step S113 is repeated, otherwise, the initial solution L is obtainedinit。
5. The method of claim 1, wherein the method comprises: the step of S12 further includes the steps of: :
s120: setting a series of neighborhoods NkThe neighborhood action is a function by which, for the current solution s, its corresponding set of neighbor solutions is generated, defining the neighborhood action as: exchanging solution elements with each interval of q/3 in the solution set path and taking the solution element at the middle position in the solution path as solution elements in the symmetrical axis symmetrical exchange solution path;
s121: initializationk＝1，Zc＝LinitIteratively obtaining the current solution Z according to the field actioncNeighbor solution set Z ofnAnd calculate the neighbor solution ZnIs a fitness of F (Z)n)＞F(Zc) Updating the optimal solution, resetting k to 1, continuing the iteration until the iteration is finished, otherwise, setting k to k +1, continuing the iteration, and finally outputting the approximate optimal solution Zbest。
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