CN108173302A - Charge completion time optimization method of the wireless charger in wireless sensor network - Google Patents
Charge completion time optimization method of the wireless charger in wireless sensor network Download PDFInfo
- Publication number
- CN108173302A CN108173302A CN201711465183.4A CN201711465183A CN108173302A CN 108173302 A CN108173302 A CN 108173302A CN 201711465183 A CN201711465183 A CN 201711465183A CN 108173302 A CN108173302 A CN 108173302A
- Authority
- CN
- China
- Prior art keywords
- charge
- path
- charge position
- represent
- wireless
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
- H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention discloses a kind of charge completion time optimization method of wireless charger in wireless sensor network, include the following steps：K region is divided into according to network node distributing position and determines the charge position in region；Charge position is connected as a closed path, calculates the minimum time cost, the movement speed on section and residence time in path；Using the convex closure of charge position point set as initial path；The location point of access time Least-cost is concentrated to repeat this step until including all location points in path as charge position next in path from remaining charge position point；Some charge position is selected in path as starting point, next charge position point is moved to after wireless charger residence time T1, the movement speed on section that holding charge mode is obtained by step B is moved to charge position in path and is kept for the corresponding residence time in charge position to complete the charging to entire wireless sensor network node successively, is taken using this method charging short.
Description
Technical field
The present invention relates to charging technique fields, and in particular to a kind of charging of wireless charger in wireless sensor network
Deadline optimization method.
Background technology
The main purpose for establishing wireless sensor network is to monitor real world and provide objective sight for a variety of applications
It examines and foundation.Traditional wireless sensor network node generally use battery powered, and sensor node battery capacity is usually very
It is small so that working time of node is limited to battery capacity, this becomes a weight for influencing wireless sensor network practical application
Big obstacle.In order to solve this problem, a kind of research direction concentrates on the energy expenditure for reducing node, another research direction is just
It is the supplement of node energy.Have benefited from the development of recent wireless energy transmission technology, a kind of wireless chargeable sensor network goes out
It is existing, with traditional sensors network difference lies in, wireless chargeable sensor network using can wireless charging battery functi on.
Consider the relationship of wireless energy transfer and transmission range, distance is longer, and charge rate is lower, wireless chargeable sensing
A mobile charging device is usually required to charge for node in device network.Because the limitation of charge rate, charging process are
Relatively time consuming, therefore the charging time is an important factor for influencing entire wireless chargeable sensor network performance.Based on above-mentioned
Description, the charging time delay of existing many wireless chargeable sensor networks of work sutdy optimization, most of work, which employs, " to move
The model of dynamic-charging "：One charger is first moved to charge position, then charges to the node of surrounding, this process until
All node charging completes.It is charged using which to node, time-consuming for entire charging process.
Invention content
In order to solve the above-mentioned technical problem the present invention provides a kind of charging of wireless charger in wireless sensor network
Deadline optimization method.
The present invention is achieved through the following technical solutions：
Charge completion time optimization method of the wireless charger in wireless sensor network, includes the following steps：
A, k non-overlapping regions are divided into according to network node distributing position, and determine the charging in k region
Position, wherein, k is the natural number more than or equal to 1；
B, k charge position is connected as a closed path, calculates the minimum time cost in path, the movement on section
Speed and the residence time in charge position；
C, using the convex closure of charge position point set as initial path；
D, the location point for choosing a time cost minimum is concentrated as next in path from remaining charge position point
Charge position point repeats this step until including all location points in path；
E, some charge position is selected in path as starting point, and next fill is moved to after wireless charger residence time T1
Electric position point keeps the movement speed on the section that is obtained by step B of charge mode to be moved in path charge position successively simultaneously
Kept for the corresponding residence time complete the charging to entire wireless sensor network node in charge position.
In wireless chargeable sensor network, movement comes to pass one mobile wireless charger of generally use in a network
Sensor charges.The present invention optimizes the charging time, to shorten taking for entire charging process.This programme equally uses one
Wireless charger charges for network node, the difference is that wireless charger charges in moving process for node simultaneously, without
It is that must first be moved to target location to charge again；Secondly, movement speed of the charger in each section is not fixed,
But change with charger position and node topology；Finally, by optimizing, reducing mobile and filling to path
The electric time.
Preferably, the determining method of the charge position is：
By charge rate discretization to L fixed charged levels；
Calculate discrete threshold values, the charge rate in each grade and the chargeable range in each grade；Chargeable range herein is
It is divided according to the positional distance of charger and node, the region charge rate of different distance is different, corresponding different charging etc.
Grade；
L concentric circles is formed using sensor node as the center of circle so that the chargeable Range-partition of sensor is a not into L respectively
The charged area of overlapping can be that sensor node charges when charger passes through any one chargeable region, rationally be utilized
The traveling time of charger.
Cut zone is clustered, to form K charge position.
Further, the cluster is using k-means clustering algorithms.
Preferably, movement speed on the time cost in the path, section and the residence time in charge position
Computational methods are：
Wherein, tiRepresent residence time, p on charge position iiRepresent the length of charging section i, siRepresent corresponding road
Movement speed in section, α are other fixed parameters in fries formula, and minT represents minimum time cost, and s.t represents constraint
Condition, niRepresent i-th of charge position point, N represents the number of charge position point, eiRepresent charger on the move to the charging of i
Rate, cTRepresent the threshold value of radio node charge capacity, eijRepresent charger in position j to the charge rate of i, dijRepresent i and j
Geometric distance, (xi,yi) and (xj,yj) the plan-position coordinate of location point i, j is represented respectively.
Compared with prior art, the present invention it has the following advantages and advantages：
1st, wireless charger of the present invention charges in moving process for node simultaneously, movement speed in each section with
Charger position and node topology variation；And its mobile route is path optimizing, the mobile and charging time takes short.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiment, the present invention is made
Further to be described in detail, exemplary embodiment of the invention and its explanation are only used for explaining the present invention, are not intended as to this
The restriction of invention.
Embodiment 1
Charge completion time optimization method of the wireless charger in wireless sensor network, includes the following steps：
A, k non-overlapping regions are divided into according to network node distributing position, and determine the charging in k region
Position, wherein, k is the natural number more than or equal to 1；
B, k charge position is connected as a closed path, calculates the minimum time cost in path, the movement on section
Speed and the residence time in charge position；
C, using the convex closure of charge position point set as initial path, i.e., one smallest subset of selection causes position from set of node
A concentration rest position point is put to connect in the closed loop to be formed all in all location points in this subset；
D, the location point for choosing a time cost minimum is concentrated as next in path from remaining charge position point
Charge position point repeats this step until including all location points in path；
E, some charge position is selected in path as starting point, and next fill is moved to after wireless charger residence time T1
Electric position point keeps the movement speed on the section that is obtained by step B of charge mode to be moved in path charge position successively simultaneously
Kept for the corresponding residence time complete the charging to entire wireless sensor network node in charge position.
This programme mobile charger uses the mechanism to charge in movement, and it is starting to select arbitrary charge position in path
Point is moved to next charge position, and keep the corresponding residence time in the position after stopping preset time T 1, so continues,
Until covering all charge positions, node electricity all in whole network is up to power threshold needed for work at this time.It is moving
Movement speed, next charge position and charge position residence time during dynamic by optimization, substantially reduce entire
The charge completion time of wireless sensor network.
Embodiment 2
The principle of embodiment 1 is given, the present embodiment discloses a detailed embodiment.
According to fries transmission formula it is found that charger is the rate of node charging and distance dependent between the two, distance
More remote, charge rate is smaller.Fries transmission formula is：
Comprising N number of node in setting sensor network, in the two dimensional surface in a limited areal, charger is by nobody
Machine or automatic Pilot trolley carry, and the symbol and meaning designed in formula see the table below.
A, charge position is planned：First by charge rate discretization to L fixed charged levels；According to Cmin=Cmax(1
+ε)-(L-1)Charge rate on calculating discrete threshold values ε, each grade；It can be calculated in each grade by fries transmission formula again
Chargeable range.
It is not overlapped limited cut zone so that network is formed using sensor node as center of circle L concentric circles of formation respectively,
Each region can be used as a charge position point.But cut zone quantity at this time is larger, if using each cut zone as
Charge position point, path length certainly will influence the charging time.In order to reduce the influence, using k-means clustering algorithms to segmentation
Region is clustered, to form K charge position, i.e., the k place that charger needs access.
According to the relationship of distance between charge rate, charger, node, distance is smaller between charger and node, charging
Rate is bigger.When charger is located at the low region of charge rate, charge efficiency is lower, and increases the mobile speed of charger at this time
Degree makes it be moved to the higher region of charge rate faster, improves charge efficiency, avoids waste of time.Positioned at charging
During the region that rate is high and surroundings nodes are relatively more, movement speed is reduced, increases the charging time, can preferably be risen to entire
The efficiency of network charging.
B, k charge position is connected as a closed path, for each charging in each charge cycle in the path
Position, wireless charger can only reach once, also can be that the node in chargeable range charges when charger moves.
Before path planning, the minimum time cost of a paths is first calculated, time cost, that is, charger is by this path to being located at road
Node in the range of diameter is full of the total time of institute's electricity demand.This problem can be used as a linear programming problem, when object function is
Between, restrictive condition must reach the movement speed limitation of power threshold and charger for all nodes, and problem is expressed as：
Wherein, tiRepresent residence time, p on charge position iiRepresent the length of charging section i, siRepresent corresponding road
Movement speed in section, α are other fixed parameters in fries formula, and min T represent minimum time cost, and s.t is represented about
Beam condition, niRepresent i-th of charge position point, N represents the number of charge position point, eiRepresent that charger on the move fills i
Electric rate, cTRepresent the threshold value of radio node charge capacity, eijRepresent charger in position j to the charge rate of i, dijRepresent i
With the geometric distance of j, (xi,yi) and (xj,yj) the plan-position coordinate of location point i, j is represented respectively.
Show charging of each node electricity source in charger in the node location
Electricity when position is on charging section for its supplement.Above-mentioned equation is solved, the time cost and charger that can obtain path exist
Speed on different sections of highway and the residence time on charge position.
C, using the convex closure of charge position point set as initial path, i.e., one smallest subset of selection causes position from set of node
A concentration rest position point is put to connect in the closed loop to be formed all in all location points in this subset；
D, the location point for choosing a time cost minimum is concentrated as next in path from remaining charge position point
Charge position point repeats this step until including all location points in path；
E, some charge position is selected in path as starting point, and next fill is moved to after wireless charger residence time T1
Electric position point keeps the movement speed on the section that is obtained by step B of charge mode to be moved in path charge position successively simultaneously
Kept for the corresponding residence time complete the charging to entire wireless sensor network node in charge position.
Step C, D is substantially to generate path, and the generation essence in path is to consider the traveling salesman problem of velocity variations, i.e. NP
Difficult problem, and using the time as measurement standard, we solve this problem using a heuritic approach.By charge position collection
Convex closure as an initial path, then optimal node optimal access order corresponding with its is gradually selected to add in path, until
Path includes all charge positions.Selecting the principle of optimal node and optimal access order is, this node is pressed access order
It is inserted into path, institute's increased charging time is minimum.The path corresponding charging time is calculated by the way of linear programming, limit
Condition processed reaches threshold value for the node electricity in path domain, and object function is the charging time.
This programme has the advantage that：One, different from single optimization charger displacement distance or on charge position
Charging time, the optimization aim of the invention is the charging time of end-to-end optimization whole network, can be caused entire wireless
Sensing network completes charging process faster.Secondly, charger can on the move to wireless sensor charge so that charger
Traveling time can be made full use of to charge for wireless sensor node, save the charging time.Thirdly, the movement speed of charger be
Variation, can be more efficiently in the moving process of charger for wireless sensor node charge.
Above-described specific embodiment has carried out the purpose of the present invention, technical solution and advantageous effect further
It is described in detail, it should be understood that the foregoing is merely the specific embodiment of the present invention, is not intended to limit the present invention
Protection domain, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should all include
Within protection scope of the present invention.
Claims (4)
1. charge completion time optimization method of the wireless charger in wireless sensor network, which is characterized in that including following
Step：
A, k non-overlapping regions are divided into according to network node distributing position, and determine the charge position in k region
It puts, wherein, k is the natural number more than or equal to 1；
B, k charge position is connected as a closed path, calculates the minimum time cost in path, the movement speed on section
With the residence time in charge position；
C, using the convex closure of charge position point set as initial path；
D, the position for choosing a time cost minimum is concentrated as charge position next in path from remaining charge position point
It puts, repeats this step until including all location points in path；
E, some charge position is selected in path as starting point, and next charge position is moved to after wireless charger residence time T1
The movement speed put on the section that charge mode a little, is kept to be obtained by step B is moved to charge position in path and is filling successively
Electric position is kept for the corresponding residence time complete the charging to entire wireless sensor network node.
2. charge completion time optimization method of the wireless charger according to claim 1 in wireless sensor network,
It is characterized in that, the determining method of the charge position is：
By charge rate discretization to L fixed charged levels；
Calculate discrete threshold values, the charge rate in each grade and the chargeable range in each grade；
L concentric circles is formed so that network forms nonoverlapping cut zone by the center of circle of sensor node respectively；
Cut zone is clustered, to form K charge position.
3. charge completion time optimization method of the wireless charger according to claim 2 in wireless sensor network,
It is characterized in that, the cluster is using k-means clustering algorithms.
4. charge completion time optimization method of the wireless charger according to claim 1 in wireless sensor network,
It is characterized in that, the calculating side of the movement speed on the time cost in the path, section and the residence time in charge position
Method is：
Wherein, tiRepresent residence time, p on charge position iiRepresent the length of charging section i, siIt represents in corresponding road section
Movement speed, α be fries formula in other fixed parameters, minT represent minimum time cost, s.t represent constraint item
Part, niRepresent i-th of charge position point, N represents the number of charge position point, eiRepresent charger on the move to the charging of i speed
Rate, cTRepresent the threshold value of radio node charge capacity, eijRepresent charger in position j to the charge rate of i, dijRepresent i's and j
Geometric distance, (xi,yi) and (xj,yj) the plan-position coordinate of location point i, j is represented respectively.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711465183.4A CN108173302B (en) | 2017-12-28 | 2017-12-28 | Charging completion time optimization method of wireless charger in wireless sensor network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711465183.4A CN108173302B (en) | 2017-12-28 | 2017-12-28 | Charging completion time optimization method of wireless charger in wireless sensor network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108173302A true CN108173302A (en) | 2018-06-15 |
| CN108173302B CN108173302B (en) | 2021-01-26 |
Family
ID=62519377
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711465183.4A Active CN108173302B (en) | 2017-12-28 | 2017-12-28 | Charging completion time optimization method of wireless charger in wireless sensor network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108173302B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108846522A (en) * | 2018-07-11 | 2018-11-20 | 重庆邮电大学 | UAV system combines charging station deployment and route selection method |
| CN109451556A (en) * | 2018-11-28 | 2019-03-08 | 广州大学 | The method to be charged based on UAV to wireless sense network |
| CN109866631A (en) * | 2019-01-21 | 2019-06-11 | 南京航空航天大学 | Unmanned plane formation on-air radio charging method |
| CN110418434A (en) * | 2019-07-08 | 2019-11-05 | 东南大学 | A kind of the wireless sensor network charging method and device of unmanned plane auxiliary |
| CN113853002A (en) * | 2021-10-19 | 2021-12-28 | 深圳壹账通智能科技有限公司 | State switching method and device of Wi-Fi switch, terminal equipment and medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105635964A (en) * | 2015-12-25 | 2016-06-01 | 河海大学 | Wireless sensor network node localization method based on K-medoids clustering |
| CN107277840A (en) * | 2017-06-09 | 2017-10-20 | 浙江工业大学 | A kind of rechargeable wireless sensor network data acquisition method |
-
2017
- 2017-12-28 CN CN201711465183.4A patent/CN108173302B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105635964A (en) * | 2015-12-25 | 2016-06-01 | 河海大学 | Wireless sensor network node localization method based on K-medoids clustering |
| CN107277840A (en) * | 2017-06-09 | 2017-10-20 | 浙江工业大学 | A kind of rechargeable wireless sensor network data acquisition method |
Non-Patent Citations (3)
| Title |
|---|
| CHILIN等: "Clustering and splitting charging algorithms for largescaled wireless rechargeable sensor networks", 《THE JOURNALOFSYSTEMSANDSOFTWARE》 * |
| LINGKUN FU等: "Optimal Charging in Wireless Rechargeable Sensor Networks", 《IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY》 * |
| 李晓波等: "基于贪心思想的三维空间定向混合路由协议", 《传感器与微***》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108846522A (en) * | 2018-07-11 | 2018-11-20 | 重庆邮电大学 | UAV system combines charging station deployment and route selection method |
| CN108846522B (en) * | 2018-07-11 | 2022-02-11 | 重庆邮电大学 | Unmanned aerial vehicle system combined charging station deployment and routing method |
| CN109451556A (en) * | 2018-11-28 | 2019-03-08 | 广州大学 | The method to be charged based on UAV to wireless sense network |
| CN109866631A (en) * | 2019-01-21 | 2019-06-11 | 南京航空航天大学 | Unmanned plane formation on-air radio charging method |
| CN109866631B (en) * | 2019-01-21 | 2021-11-30 | 南京航空航天大学 | Unmanned aerial vehicle formation aerial wireless charging method |
| CN110418434A (en) * | 2019-07-08 | 2019-11-05 | 东南大学 | A kind of the wireless sensor network charging method and device of unmanned plane auxiliary |
| CN110418434B (en) * | 2019-07-08 | 2022-12-06 | 东南大学 | Unmanned aerial vehicle-assisted wireless sensor network charging method and device |
| CN113853002A (en) * | 2021-10-19 | 2021-12-28 | 深圳壹账通智能科技有限公司 | State switching method and device of Wi-Fi switch, terminal equipment and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108173302B (en) | 2021-01-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108173302A (en) | Charge completion time optimization method of the wireless charger in wireless sensor network | |
| Luo et al. | Surface optimal path planning using an extended Dijkstra algorithm | |
| CN105717929B (en) | Mobile robot mixed path planing method under a kind of multiresolution obstacle environment | |
| CN102420392B (en) | Transformer substation inspection robot global path planning method based on magnetic navigation | |
| CN106767860B (en) | A method of shortening intelligent automobile path planning search time based on heuristic search algorithm | |
| CN104914866B (en) | Crusing robot global path planning method and system based on topology point classification | |
| WO2018176594A1 (en) | Artificial potential field path planning method for unmanned bicycle | |
| CN113821029B (en) | Path planning method, device, equipment and storage medium | |
| CN102520718A (en) | Physical modeling-based robot obstacle avoidance path planning method | |
| CN107633375A (en) | A kind of man-machine collaboration storage method for sorting | |
| Rao et al. | Optimal recharging with practical considerations in wireless rechargeable sensor network | |
| CN107092265A (en) | A kind of sorting trolley path planning method suitable for matrix form warehouse | |
| CN101769754A (en) | Quasi three-dimensional map-based mobile robot global path planning method | |
| Wang et al. | Summary of agv path planning | |
| CN106452513B (en) | A kind of mobile energy supplement method in the wireless sense network based on Delay Constraint | |
| CN109491389A (en) | A kind of robot trace tracking method with constraint of velocity | |
| CN104596508A (en) | Indoor navigation method based on combination of region location, inertial navigation and map path | |
| CN104992466B (en) | A kind of instant path-finding method of three-dimensional scenic | |
| CN109451556B (en) | Method for charging wireless sensor network based on UAV | |
| CN103678649A (en) | Traffic path searching system and method based on cloud self-adaptation particle swarm optimization | |
| CN107908899B (en) | Line selection system and line selection method for construction road of wind power plant | |
| CN110418434A (en) | A kind of the wireless sensor network charging method and device of unmanned plane auxiliary | |
| CN105451292A (en) | Grid structure-based hierarchical network charging method and system in WRSNs | |
| CN109275170A (en) | A kind of charging method and system of wireless chargeable sensing network | |
| Xu et al. | Research of Electric Cable Path Planning Based on Heuristic Optimization Algorithm in Mixed-Land Scenario |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |