CN109216812A - A kind of charging method of the wireless chargeable sensor network based on energy consumption classification - Google Patents
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/44—Methods for charging or discharging
- H01M10/441—Methods for charging or discharging for several batteries or cells simultaneously or sequentially
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- H—ELECTRICITY
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Abstract
The invention discloses a kind of charging methods of wireless chargeable sensor network based on energy consumption classification.Base station type charging modes charge efficiency is poor, and fan-shaped hierarchical approaches charging validity is inadequate.The present invention is as follows: one, establishing plane right-angle coordinate.Two, according to the length of life cycle, classify to n node.Three, secondary classification, and calculation optimization path total length are carried out to classification obtained by step 2.Four, it filters out always to put to concentrate in secondary classification and a primary subseries point set only occurs.Five, the node in each transfer point set is shifted.Six, a wheel charging is carried out.The present invention realizes the classification of wireless chargeable sensor by energy consumption classification, carries out the charging in batches for realizing wireless chargeable sensor, and then reduce the mobile energy loss of charging trolley.The present invention is realized and is advanced optimized to charging trolley path by the variation to the longer wireless chargeable sensor charging batch of life cycle.
Description
Technical Field
The invention belongs to the technical field of energy supply of a wireless chargeable sensor network, and particularly relates to a charging method of the wireless chargeable sensor network based on energy consumption classification.
Background
Because the wireless sensor nodes in a general wireless sensor network are small in size and limited in battery energy, the working time of the sensor nodes is limited. In order to solve the problem of insufficient energy of the Sensor, a Wireless Sensor Network (WRSN), which is a Wireless Rechargeable Sensor Network with an energy collection technology, is developed. For a deployed sensor network, a reasonable and efficient charging mode is found for charging the sensor nodes, and the method is a reasonable mode for enabling the sensor network to continuously survive. Xu cheng hua et al in the patent "directional charging base station deployment method of wireless chargeable sensor network" (patent number: 201610279938.0) propose a method of establishing a directional charging base station in a sensor network, charging the sensor by rotating an angle to cover the entire sensor network, but the charging efficiency of this remote charging method is low.
A movable charging trolley is placed in a wireless rechargeable sensor network, node sets with different residual life cycles are determined according to different energy consumption of sensors, the sensor nodes are charged according to requirements, and each sensor can be guaranteed to be supplemented with energy in a certain period, so that the WRSN can work normally. In related research, royal jade and the like in patent "a charging control method for wireless sensor network nodes" (patent number: 201611042178.8) divide the whole network into fan-shaped areas with different priorities according to the residual energy of the sensor nodes, and charge according to the charging emergency degree of the sensor nodes, but the classification strategy of the method cannot ensure that each sensor node is respectively in different fan-shaped areas according to different requirements, so that the moving path of a charging trolley cannot be reasonably planned.
Disclosure of Invention
The invention provides a charging method of a wireless chargeable sensor network based on energy consumption classification.
The method comprises the following specific steps:
step 1, establishing a planar rectangular coordinate system, wherein a base point in the planar rectangular coordinate system corresponds to the position of a trolley base station, and n nodes in the planar rectangular coordinate system correspond to the positions of n wireless chargeable sensors respectively.
And 2, classifying the n nodes according to the life cycle.
2-1, calculating the life cycle T of n nodesiI is 1, 2, …, n, and a life cycle set T is { T ═ T1，T2,…,Tn}。
Ti＝(ERi-ETHi)/Ei。
Wherein E isRiIs the remaining energy in the ith node; eTHiIs an energy threshold in the ith node, ETHi＝10％·ESi；ESiIs the initial energy in the ith node, EiIs the power in the ith node.
2-2, calculating the grading numberTmaxIs the maximum value within the set of life cycles T; t isminIs the minimum value in the life cycle set T;is (T)max-Tmin)/TminRounding the resulting value upward.
2-3.i ═ 1, 2, …, n, steps 2-4 are performed in sequence. Obtaining a primary classification total point set CC＝{CC1，CC2,…,CCh}。
2-4. ifAdding the ith node into the jth primary classification point set CCj。
2-5, assign 1 to j and 1 to k.
2-6, if j is a divisor of k, classifying the j first time into a point set CCjAdding the kth secondary classification point set Ck. And entering the step 2-7.
2-7, if j is less than h, increasing j by 1; if j is h and k is < h, then 1 is assigned to j and k is incremented by 1; if j is h and k is h; then the quadratic classification total point set C ═ C has been obtained1，C2，C3，…，ChAnd F, entering the step 3.
And 3, calculating the total length of the optimized path.
3-1.k is 1, 2, …, h, and step 3-2 is performed sequentially.
3-2, determining the kth classification point set C of the charging trolley pair through the ant colony algorithmkOptimized path A for chargingk(ii) a Path AkUsing base point as starting point and end point and passing through k-th classification point set CkAll nodes in the network; obtaining a k classification point set C of the charging trolleykOptimized path A for chargingkLength L ofk。
3-3, calculating the total length of the optimized path
And 4, screening out a primary classification point set which only appears once in the secondary classification total point set C.
4-1. assign 1 to M and j.
4-2. if the j first classification point set CCjIf the point set C appears only once in the secondary classification total point set C, the j-th primary classification point set C isCjAs the M-th transfer point set C'MThen, increasing M by 1 and proceeding to step 4-3; otherwise, directly entering the step 4-3.
4-3, if j is less than h, increasing j by 1, and turning to the step 4-2; if j is h, then a sorted total point set C 'is { C'1,C′2,...,C′MAnd F, entering the step 5.
And 5, transferring the nodes in each transfer point set.
5-1. assign M to r and 1 to s.
5-2. transfer the r to point set C'rS nodes with minimum middle life cycle are transferred to the r-1 transfer point set C'r-1。
5-3.k is 1, 2, …, h, and steps 5-4 are performed sequentially.
5-4, determining the kth classification point set C of the charging trolley pair through the ant colony algorithmkAlternate route A 'for charging'k(ii) a Route A'kUsing base point as starting point and end point and passing through k-th classification point set CkAll nodes in the network; obtaining a k classification point set C of the charging trolleykAlternate route A 'for charging'kLength of L'k。
5-5, calculating the total length of the undetermined path
5-6. if L'TSP＜LTSPThen the total length of the pending path L'TSPAs a new optimized total path length LTSP，L′1，L′2，...，L′hRespectively as a new L1，L2，...，LhAnd proceeds to step 5-8. Otherwise, transfer to the r-1 st transfer point set C 'in step 5-2'r-1S nodes of (C) are transferred back to the r-th set of transfer points C'rAnd proceeds to step 5-7.
5-7, if s is less than r transition point set C'rIncreasing s by 1 according to the number of the internal nodes, and repeating the steps from 5-2 to 5-6; otherwise, go to step 5-9.
5-8 if rTransfer Point Collection C'rIf nodes exist in the node, assigning 1 to s, and repeating the steps 5-2 to 5-6; otherwise, go to step 5-9.
5-9, if r > 2, decreasing r by 1 and repeating steps 5-2 to 5-8, otherwise, entering step 6.
Step 6, z is 1, 2, …, h, and step 7 is performed in sequence.
Step 7, waiting for TminAfter the time, the charging trolley collects C according to the z-th classification pointzOptimized path A for chargingzThe wireless chargeable sensor moves and charges the passing wireless chargeable sensor.
And 8, repeatedly executing the steps 2 to 7.
The invention has the beneficial effects that:
1. according to the wireless chargeable sensor, the classification of the wireless chargeable sensors is realized through energy consumption classification, the batch charging of the wireless chargeable sensors is realized, and the moving energy loss of the charging trolley is further reduced.
2. The charging trolley path is further optimized by changing the charging batch of the wireless chargeable sensor with a longer life cycle.
3. The invention can ensure the stable and continuous work of each wireless chargeable sensor.
Drawings
FIG. 1 is a schematic view of a wireless chargeable sensor, cart base station distribution in one example of the present invention;
FIG. 2(a), FIG. 2(b), FIG. 2(c) and FIG. 2(d) are diagrams of the paths of four trolleys after step 2 is performed according to an embodiment of the present invention;
fig. 3(a), 3(b), 3(c) and 3(d) are four trolley path diagrams obtained after step 5 is executed according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The invention relates to a charging method of a wireless chargeable sensor network based on energy consumption classification, which aims at the condition that all wireless chargeable sensors in the wireless sensor network are arranged on the same plane and the specifications of the wireless chargeable sensors are the same except for different power consumption. The charging mode is that the charging trolleys are driven out of the trolley base station and move to the position where the wireless chargeable sensor is needed to carry out near-field magnetic coupling resonance wireless charging one by one, and the charging efficiency is high.
The charging method of the wireless chargeable sensor network based on energy consumption classification comprises the following specific steps:
step 1, as shown in fig. 1, a WRSN model, i.e., a planar rectangular coordinate system, is established, so that the coordinates of the trolley base station are (R, R), and all the n wireless chargeable sensors are located in the charging square in the first quadrant of the planar rectangular coordinate system. Coordinate points (0,0), (0,2R), (2R,0), (2R,2R) are the four vertices of the charging square, respectively. The positions of the trolley base stations correspond to the base points, and the positions of the n wireless chargeable sensors correspond to the n nodes. The coordinates of the n nodes in the rectangular plane coordinate system are respectively (x)i,yi) I is 1, 2, …, n. The n nodes are sorted.
And 2, classifying the n nodes according to the life cycle.
2-1, calculating the life cycle T of n nodesi，i＝1，2，…，n，TiIs given in days, resulting in a set of life cycles T ═ T1，T2,…,Tn}。
Ti＝(ERi-ETHi)/Ei。
Wherein,ERithe remaining energy (i.e. the current remaining capacity of the battery) in the ith node; e, ETHiIs an energy threshold in the ith node, ETHi＝10％·ESi；ESiIs the initial energy (i.e. the full charge of the battery) E in the ith nodeiIs the power in the ith node.
When the energy of one node is less than the energy threshold ETHiAnd if so, the wireless chargeable sensor corresponding to the node is considered to be dead (incapable of working).
2-2, calculating the grading numberTmaxIs the maximum value within the set of life cycles T; t isminIs the minimum value in the life cycle set T;is (T)max-Tmin)/TminRounding the resulting value upward.
2-3.i ═ 1, 2, …, n, steps 2-4 are performed in sequence. Obtaining a primary classification total point set CC＝{CC1，CC2,…,CCh}。
2-4. ifAdding the ith node into the jth primary classification point set CCj。
2-5, assign 1 to j and 1 to k.
2-6, if j is a divisor of k (i.e., j is divided by k), the j-th primary classification point set CCjAdding the kth secondary classification point set Ck. And entering the step 2-7.
2-7, if j is less than h, increasing j by 1; if j is h and k is < h, then 1 is assigned to j and k is incremented by 1; if j is h and k is h; step 3 is entered, where a secondary classification total point set C ═ C is obtained1，C2，C3，…，Ch}。
And 3, solving the size of the path traversed by the charging trolley each time.
3-1.k is 1, 2, …, h, and step 3-2 is performed sequentially.
3-2, determining the kth classification point set C of the charging trolley pair through the ant colony algorithmkOptimized path A for chargingk(ii) a Path AkUsing the base point as the starting point and the end point, and passing through the k-th classification point set CkAll nodes within. Obtaining a k classification point set C of the charging trolleykLength L of optimized path for chargingk＝ACATSP(Ck)。ACATSP(Ck) Calculated by ant colony algorithm, the trolley base station is taken as a starting point and an end point, and passes through the k-th secondary classification point set CkPath length of all nodes within. The ant colony algorithm adopts an algorithm which is licensed to be put forward in 'TSP problem research based on the improved ant colony algorithm' published in software guide.
3-3, calculating the total length of the optimized path
And 4, screening out a primary classification point set which only appears once in the secondary classification total point set C.
4-1. assign 1 to M and j.
4-2. if the j first classification point set CCjOnly appears once in the quadratic classification total point set C (i.e. the jth quadratic classification point set CCjBelong to and only belong to C1，C2，C3,…,ChOne of them), the j-th primary classification point set C is sortedCjAs the M-th transfer point set C'M(at this time, the M-th transition point set C'MAnd j first classification point set CCjChanging Mth transfer point set C 'for different expressions of the same set'MI.e. change the jth classification point set CCj) Then, increasing M by 1 and proceeding to step 4-3; otherwise, directly entering the step 4-3.
4-3, if j is less than h, increasing j by 1, and turning to the step 4-2; if j is h, the process proceeds to step 5, where a total classification point set C 'is obtained as { C'1,C′2,...,C′M}。
And 5, transferring the nodes in each transfer point set.
5-1. assign M to r and 1 to s.
5-2. transfer the r to point set C'rS nodes with minimum middle life cycle are transferred to the r-1 transfer point set C'r-1Since the transition point set corresponds to one primary classification point set, the change of the transition point set is the change of the corresponding primary classification point set.
5-3.k ═ 1, 2, …, h, and steps 5-4 are performed sequentially
5-4, determining the kth classification point set C of the charging trolley pair through the ant colony algorithmkAlternate route A 'for charging'k(ii) a Route A'kUsing the base point as the starting point and the end point, and passing through the k-th classification point set CkAll nodes within. Obtaining a k classification point set C of the charging trolleykLength L 'of alternate path for charging'k＝ACATSP(Ck)。ACATSP(Ck) Calculated by ant colony algorithm, the trolley base station is taken as a starting point and an end point, and passes through the k-th secondary classification point set CkPath length of all nodes within.
5-5, calculating the total length of the undetermined path
5-6. if L'TSP＜LTSPThen the total length of the pending path L'TSPAs a new optimized total path length LTSP，L′1，L′2，...，L′hRespectively as a new L1，L2，...，LhAnd proceeds to step 5-8. Otherwise, transfer to the r-1 st transfer point set C 'in step 5-2'r-1S number of nodesShifted back to the r-th set of transfer points C'rAnd proceeds to step 5-7.
5-7, if s is less than r transition point set C'rIncreasing s by 1 according to the number of the internal nodes, and repeating the steps from 5-2 to 5-6; otherwise, go to step 5-9.
5-8, if the r is transferred to the point set C'rIf nodes exist in the node, assigning 1 to s, and repeating the steps 5-2 to 5-6; otherwise, go to step 5-9.
5-9, if r is more than 2, reducing r by 1, and repeatedly executing the steps 5-2 to 5-8, otherwise, entering the step 6, wherein the total length L of the optimized path is the sameTSPI.e. the final optimized path length. And the charging path corresponding to the final optimized path length is the final charging path. Proceed to step 6.
Step 6, z is 1, 2, …, h, and step 7 is performed in sequence.
Step 7, waiting for TminAfter time, the charging trolley is according to AzAnd moving the corresponding path and charging the passing wireless chargeable sensor.
And 8, repeatedly executing the steps 2 to 7.
The calculation is performed by taking 47300J as an example of n being 10, R being 50m, the initial energy of each wireless chargeable sensor, and the energy threshold being 4730J.
The coordinates of the corresponding nodes of each wireless chargeable sensor are as follows:
after the classification of step 2, a first primary classification point set CC1Including node S1And node S2. Set of second-order classification points CC2Including node S3Node S4And node S5. Third-order classification point set CC3Including node S6. The fourth time is divided intoClass point set CC4Including node S7Node S8Node S9And node S10。
L obtained in step 31、L2、L3、L4The corresponding paths are shown in fig. 2(a), fig. 2(b), fig. 2(c), fig. 2(d), respectively. L obtained in step five1、L2、L3、L4The corresponding paths are shown in fig. 3(a), 3(b), 3(c), and 3(d), respectively.
When the traditional node full traversal algorithm is applied, the charging trolley needs to travel 1098.2m when completing charging in one period. When the charging trolley is used, the charging trolley only needs to travel 732.5m after completing one cycle of charging. Therefore, the efficiency of the charging trolley can be greatly improved, and the loss of the charging trolley is reduced.
Claims (1)
1. A charging method of a wireless chargeable sensor network based on energy consumption classification is characterized in that:
step 1, establishing a planar rectangular coordinate system, wherein a base point in the planar rectangular coordinate system corresponds to the position of a trolley base station, and n nodes in the planar rectangular coordinate system respectively correspond to the positions of n wireless chargeable sensors;
step 2, classifying the n nodes according to the life cycle;
2-1, calculating the life cycle T of n nodesiI is 1, 2, …, n, to give raw materialSet of lifecycle T ═ T1，T2,…,Tn}；
Ti＝(ERi-ETHi)/Ei；
Wherein E isRiIs the remaining energy in the ith node; eTHiIs an energy threshold in the ith node, ETHi＝10％·ESi；ESiIs the initial energy in the ith node, EiIs the power in the ith node;
2-2, calculating the grading numberTmaxIs the maximum value within the set of life cycles T; t isminIs the minimum value in the life cycle set T;is (T)max-Tmin)/TminRounding up the value;
2-3.i ═ 1, 2, …, n, steps 2-4 are performed sequentially; obtaining a primary classification total point set CC＝{CC1，CC2,…,CCh}；
2-4. ifAdding the ith node into the jth primary classification point set CCj；
2-5, assigning 1 to j and 1 to k;
2-6, if j is a divisor of k, classifying the j first time into a point set CCjAdding the kth secondary classification point set Ck(ii) a Entering the step 2-7;
2-7, if j is less than h, increasing j by 1; if j is h and k is < h, then 1 is assigned to j and k is incremented by 1; if j is h and k is h; then the quadratic classification total point set C ═ C has been obtained1，C2，C3，…，ChFourthly, entering the step 3;
step 3, calculating the total length of the optimized path;
3-1.k ═ 1, 2, …, h, performing step 3-2 in sequence;
3-2, determining the kth classification point set C of the charging trolley pair through the ant colony algorithmkOptimized path A for chargingk(ii) a Path AkUsing base point as starting point and end point and passing through k-th classification point set CkAll nodes in the network; obtaining a k classification point set C of the charging trolleykOptimized path A for chargingkLength L ofk；
3-3, calculating the total length of the optimized path
Step 4, screening out a primary classification point set which only appears once in the secondary classification total point set C;
4-1, assigning 1 to M and j;
4-2. if the j first classification point set CCjIf the point set C appears only once in the secondary classification total point set C, the j-th primary classification point set C isCjAs the M-th transfer point set C'MThen, increasing M by 1 and proceeding to step 4-3; otherwise, directly entering the step 4-3;
4-3, if j is less than h, increasing j by 1, and turning to the step 4-2; if j is h, then a sorted total point set C 'is { C'1,C′2,...,C′MStep 5 is entered;
step 5, transferring the nodes in each transfer point set;
5-1, assigning M to r and 1 to s;
5-2. transfer the r to point set C'rS nodes with minimum middle life cycle are transferred to the r-1 transfer point set C'r-1；
5-3.k ═ 1, 2, …, h, sequentially performing steps 5-4;
5-4, determining the kth classification point set C of the charging trolley pair through the ant colony algorithmkAlternate route A 'for charging'k(ii) a Route A'kUsing base point as starting point and end point and passing through k-th classification point set CkAll nodes in the network; obtaining a k classification point set C of the charging trolleykAlternate route A 'for charging'kLength of L'k；
5-5, calculating the undetermined pathTotal length of the track
5-6. if L'TSP＜LTSPThen the total length of the pending path L'TSPAs a new optimized total path length LTSP，L′1，L′2，...，L′hRespectively as a new L1，L2，...，LhAnd proceeding to step 5-8; otherwise, transfer to the r-1 st transfer point set C 'in step 5-2'r-1S nodes of (C) are transferred back to the r-th set of transfer points C'rAnd proceeding to step 5-7;
5-7, if s is less than r transition point set C'rIncreasing s by 1 according to the number of the internal nodes, and repeating the steps from 5-2 to 5-6; otherwise, entering the step 5-9;
5-8, if the r is transferred to the point set C'rIf nodes exist in the node, assigning 1 to s, and repeating the steps 5-2 to 5-6; otherwise, entering the step 5-9;
5-9, if r is more than 2, reducing r by 1, and repeatedly executing the steps 5-2 to 5-8, otherwise, entering the step 6;
step 6, changing z to 1, 2, …, h, and executing step 7 in sequence;
step 7, waiting for TminAfter the time, the charging trolley collects C according to the z-th classification pointzOptimized path A for chargingzMoving and charging the passing wireless chargeable sensor;
and 8, repeatedly executing the steps 2 to 7.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103781146A (en) * | 2014-01-22 | 2014-05-07 | 南昌大学 | Wireless sensor network optimal route path establishing method based on ant colony algorithm |
| US20150059449A1 (en) * | 2012-03-05 | 2015-03-05 | Technische Universiteit Delft | New Lithographic Method |
| CN106403968A (en) * | 2016-06-06 | 2017-02-15 | 四川大学 | Planning method for charging of wireless rechargeable sensor networks (WRSNs) with heterogeneous mobile charging vehicles |
| CN106785131A (en) * | 2016-11-23 | 2017-05-31 | 南京邮电大学 | A kind of charge control method of radio sensing network node |
| CN106887887A (en) * | 2017-03-14 | 2017-06-23 | 南京邮电大学 | Movable charging vehicle dispatching method in a kind of wireless chargeable Sensor Network |
| CN107635238A (en) * | 2017-08-28 | 2018-01-26 | 昆明理工大学 | A kind of chargeable sensor network arrangement of repeaters method of multi-hop wireless based on Clustering |
| CN107657374A (en) * | 2017-09-25 | 2018-02-02 | 中南大学 | A kind of charging dispatching method on demand based on energy consumption and apart from dynamic change |
-
2018
- 2018-09-14 CN CN201811074009.1A patent/CN109216812B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150059449A1 (en) * | 2012-03-05 | 2015-03-05 | Technische Universiteit Delft | New Lithographic Method |
| CN103781146A (en) * | 2014-01-22 | 2014-05-07 | 南昌大学 | Wireless sensor network optimal route path establishing method based on ant colony algorithm |
| CN106403968A (en) * | 2016-06-06 | 2017-02-15 | 四川大学 | Planning method for charging of wireless rechargeable sensor networks (WRSNs) with heterogeneous mobile charging vehicles |
| CN106785131A (en) * | 2016-11-23 | 2017-05-31 | 南京邮电大学 | A kind of charge control method of radio sensing network node |
| CN106887887A (en) * | 2017-03-14 | 2017-06-23 | 南京邮电大学 | Movable charging vehicle dispatching method in a kind of wireless chargeable Sensor Network |
| CN107635238A (en) * | 2017-08-28 | 2018-01-26 | 昆明理工大学 | A kind of chargeable sensor network arrangement of repeaters method of multi-hop wireless based on Clustering |
| CN107657374A (en) * | 2017-09-25 | 2018-02-02 | 中南大学 | A kind of charging dispatching method on demand based on energy consumption and apart from dynamic change |
Non-Patent Citations (1)
| Title |
|---|
| ZHANG FAN: "A Multi-Node Rechargeable Algorithm via Wireless Charging Vehicle with Optimal Traveling Path in Wireless Rechargeable Sensor Networks", 《2018 TENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN)》 * |
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