CN105722091A - Directional charging base station deployment method of wireless rechargeable sensor network - Google Patents
Directional charging base station deployment method of wireless rechargeable sensor network Download PDFInfo
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Abstract
The invention discloses a directional charging base station deployment method of a wireless rechargeable sensor network. According to the wireless rechargeable sensor network adopted by the invention, N rechargeable sensors are randomly deployed in a two-dimensional plane; according to the adopted wireless charging model, a directional base station only can charge one sensor at a moment, through rotating the direction of a charging antenna, different sensors can be charged at different moments in a time period, and moreover, one sensor only can be charged by one directional base station. The specific steps are as follows: 1, solving a sensor set with feasible base stations; 2, solving a candidate base station set corresponding to the result set RFS of the sensor set; 3, calculating appearing frequencies of the sensors; and 4, selecting the base stations from the candidate base stations as few as possible. According to the method, through combination of the time divided charging models of the rotary directional charging base stations, the method conforms to the practical application scene well; and through adoption of two heuristic algorithms based on cupidity, the operation speeds of the algorithms are improved.
Description
Technical field
The present invention relates to wireless chargeable sensor network field, particularly to a kind of orientation charging base station deployment method of wireless chargeable sensing network.
Background technology
Along with development and the scientific and technological progress of society, wireless charging technology is applied in the equipment such as RFID and sensor and the field such as wisdom electrical network and civil structure monitoring more and more widely.In the application of wireless chargeable sensor network, charging base station needs to dispose according to the feature of chargeable sensor, charging base station and charge model, meets the requirement making whole sensing network continuous service.Therefore, the deployment issue of charging base station is highly important problem in the application of wireless chargeable sensing network.
About the solution of base station deployment problem in wireless chargeable sensing network, researcheres propose corresponding solution for different charge model.Dai Haipeng et al. is in " the layout algorithm of a kind of efficient oriented wireless charger " literary composition, for the problem of the wireless charging benefit maximizing whole sensing network, it is proposed that a kind of approximate greedy algorithm.The directional base station chargeable range of finite number, based on the charge efficiency function of discretization, has been carried out geometrical analysis and conversion by it, is the problem with submodularity former problem reformulation, and then draws the directional base station deployment scheme of maximization network charging benefit.Wu Yifan et al. is in patent " the contactless charge node dispositions method of a kind of facing sensing device network " (patent No.: CN201310276000.X), for the problem minimizing charge node quantity while ensureing all the sensors node continuous firing, it is proposed that the dispositions method of a kind of contactless charge node.The method, on the basis of gridding sensor node institute distributed areas, selects Bestgrid point as the position disposing next charge node, until all the sensors node is all electrically charged.These base station deployment methods can not be directly applied for the application scenarios of rotatable directed wireless charging base station.Therefore, the present invention is proposed for being rotationally oriented the base station deployment method of charge model.
Summary of the invention
The present invention proposes a kind of orientation charging base station deployment method of wireless chargeable sensing network.First, using certain sensor finite element as set of sensors, distance according to other sensors to this sensor, from near to far successively other sensors being joined set, until set is sufficiently large, to such an extent as to when adding next sensor, a base station can not for till all the sensors charging in this set.Repeat said process, thus calculate their set of sensors for each sensor.Secondly, for several given set of sensors, according to the Fermat point convergence algorithm promoted, the candidate base station deployed position information corresponding to each set is obtained respectively.Then, the information according to candidate base station, calculate the frequency of occurrence of each sensor.Finally, prioritizing selection can be the base station of the maximum sensor not being electrically charged chargings.If there being multiple such base station, from all the sensors corresponding to these base stations, just screening that sensor that frequency of occurrence is minimum, be chosen as the base station of this sensor charging as a result.All the sensors repeats to select the process of candidate base station, until can be electrically charged.
This invention address that the technical scheme steps that its technical problem adopts is as follows:
The orientation charging base station deployment method of wireless chargeable sensing network, the wireless chargeable sensing network of employing is: on a two dimensional surface, the N number of chargeable sensing of random placement；The wireless charging model adopted is: directional base station is only a sensor charging a moment, but by rotating the direction of charging antenna, can not charging for different sensors in the same time in a period of time, meanwhile, a sensor can only be charged by a directional base station；Specifically include following steps:
Step 1: obtain the set of sensors that there is feasible base station；
Step 2: obtain the candidate base station set corresponding for result set RFS of set of sensors；
Step 3: calculate the frequency of occurrence of sensor；
Step 4: select as far as possible few base station from candidate base station；
There is the set of sensors of feasible base station in obtaining described in step 1, first on a two dimensional surface, and the N number of chargeable sensor of random placement, and using certain sensor finite element as set of sensors, use S={s1,s2,…,sNRepresent the N number of sensor in sensing network；Then following steps are adopted:
1-1, initialization j=1, the result set RFS making the set of sensors of feasible base station is sky；
1-2, calculating jth sensor sjAnd the distance between other N-1 sensor, and they are ordered as from small to large successively sj 1,sj 2,…,sj N-1, make set of sensors SS={sj, finite element number k=1 in set of sensors SS；
1-3, judging whether set of sensors SS exists a Feasible Basis station location, if existing, then carrying out step 1-4；If being absent from, then forward step 1-5 to；
If 1-4 is k=N, then forward step 1-6 to, otherwise, by sensor sj kAdd in set SS, and make k=k+1, return step 1-3；
1-5, make k=k-1, and the sensor s that will finally addj kLeave out from set SS；
1-6, being added in the result set RFS of set of sensors of feasible base station by set SS, if j=N+1, algorithm terminates, and otherwise makes j=j+1, returns step 1-2.
The candidate base station set corresponding for result set RFS obtaining set of sensors described in step 2, specific as follows:
A given set of sensors SS '=s '1,s’2,...,s’k, obtain the position c of the feasible base station of this set SS 'i, namely obtain satisfiedCiPosition；Wherein, PwjRepresent jth sensor s 'jRate of energy dissipation；D (ci,s’j) represent feasible base station ciWith sensor s 'jDistance；P (d) is charge efficiency function, is strictly monotone decreasing function, value and distance d (ci,s’j) relevant, functional equation isα and β is the parameter value determined by charger hardware, and D is the maximum charge distance of charging device；Can obtain after equation abbreviation, solve candidate base station location, namely to obtainMinima；
The convergence algorithm solving Fermat's problem being generalized to solves in the problems referred to above: the iteration function of transverse and longitudinal coordinate isWherein xj,yjRepresent sensor s 'jTwo-dimensional coordinate, x, y represents feasible base station c during last iterationiCoordinate；As distance d (ci,s’j) more than D time, the end value of Target is punished；Meanwhile, choose and do not cross the border, be i.e. d (ci,s’j) initial position less than or equal to D is iterated；When algorithm iteration to fixed number of times, or when the result of twice iteration differs less than certain threshold value, algorithm terminates；Now, the deployed position c of candidate base station can be tried to achievei。
The frequency of occurrence calculating sensor described in step 3, specific as follows:
The corresponding set of sensors needing its charging of each candidate base station；Information according to current candidate base station, calculates each sensor frequency of occurrence in current candidate base station.
Selecting from candidate base station described in step 4, first obtains the frequency of occurrence of sensor, afterwards operation specific as follows at as far as possible few base station from step 3:
4-1, initialize uncharged set of sensors S '={ s1,s2,…,sn, define and wait to select collection of base stations BS and final collection of base stations Res for sky；
4-2, according to the method in step 3, calculate the frequency of occurrence of all the sensors, therefrom filter out the sensor that all frequency of occurrences are 1, find out the base station charged for these sensors, and these base stations be recorded wait to select in collection of base stations BS；
4-3, the information in collection of base stations BS is selected to add in final collection of base stations Res by waiting, information according to final collection of base stations Res, recalculate uncharged set of sensors S ', if S ' is empty, then algorithm terminates, otherwise, according to the method in step 3, recalculate the frequency of occurrence of each sensor in uncharged set of sensors S '；
4-4, empty and wait to select collection of base stations BS, select from candidate base station and comprise the base station that in set of sensors S ', number of probes is maximum after renewal, and these base stations be recorded in set BS, if BS only comprises a base station, then forward step 4-3 to；
4-5, obtain waiting all the sensors TempS={s ' that selects the collection of base stations BS base station comprised corresponding1,…,s’kIn, from TempS, filter out the sensor s ' that frequency of occurrence is minimummin, and obtain as sensor s 'minThe base station of charging, makes and waits to select collection of base stations BS only to comprise this base station, forward step 4-3 to.
Beneficial effects of the present invention:
1. the present invention is directed to the application being rotationally oriented charging base station, consider the time-sharing charging model in radio sensing network in detail, more conform to practical application scene.
2. present invention employs two based on the heuritic approach of greed, improve the speed of service of algorithm such that it is able to suitable in the application scenarios that chargeable number of sensors is bigger.
Accompanying drawing explanation
Fig. 1 is the wireless chargeable sensing network and charge model schematic diagram that the present invention adopts；
Fig. 2 is the particular flow sheet that the present invention carries out being rotationally oriented base station deployment；
Fig. 3 (a) and (b) are the schematic diagram of the set of sensors solving feasible base station；
Fig. 4 (a) and (b) are sensor frequency of occurrence schematic diagram；
The running schematic diagram that Fig. 5 (a), (b), (c), (d), (e), (f) are base station selected algorithm.
Detailed description of the invention
Below in conjunction with accompanying drawing, the invention will be further described.
The present invention mainly proposes a kind of orientation charging base station deployment method of wireless chargeable sensing network.All of chargeable sensor, except respective consumption power difference, other specifications are all identical.One sensor can only be charged by a directional base station.The specification of directed charging base station is also all identical, and base station is only a sensor charging a moment, but they can pass through to rotate the direction of charging antenna, thus in a period of time not in the same time for different sensors charging.On the two dimensional surface of a H*W, the N number of chargeable sensor of random placement.Ensureing in whole sensing network that all the sensors can under the premise of continuous firing, it is necessary to find the deployment strategy of a kind of directional base station, and make the base station number in deployment strategy as far as possible few.
The present invention uses rotatable directed charging base station model.Its charged area is a sector, and fan-shaped angle is relevant with the physical parameter of directed charging antenna, and therefore, it is only a specific direction and provides energy.But, when charging, it can pass through to rotate charging direction, thus being the charging of multiple directions timesharing ground, it would therefore be desirable to consider the charging interval assignment problem of base station.It should be noted that when wireless charging antenna rotates, the situation that the sensor in other directions can not be electrically charged will necessarily be caused.Now, in addition it is also necessary to consider the dump energy of sensor may be depleted etc. situation.
Wireless chargeable sensing network model schematic according to Fig. 1, the wireless chargeable sensing network that the present invention adopts is: on a two dimensional surface, the N number of chargeable sensor of random placement.Ensureing in whole sensing network that all the sensors can under the premise of continuous firing, the present invention needs to find the deployment strategy of a kind of directional base station so that the base station number of needs is as far as possible few.
Time-sharing charging model schematic according to Fig. 1, the wireless charging model that the present invention adopts is: directional base station is only a sensor charging a moment, but it can pass through rotate charging antenna direction, thus in a period of time not in the same time for different sensors charging.Meanwhile, a sensor can only be charged by a directional base station.
Below in conjunction with accompanying drawing, specific embodiments of the present invention are described in further detail.Its concrete steps describe as shown in Figure 2.
Step 1: obtain the set of sensors that there is feasible base station
On a two dimensional surface, the N number of chargeable sensor of random placement, and using certain sensor finite element as set of sensors, distance according to other sensors to this sensor, from near to far successively other sensors being joined set, until set is sufficiently large, to such an extent as to when adding next sensor, a base station can not for till all the sensors charging in this set.Repeat said process, thus calculate their set of sensors for each sensor.
We use S={s1,s2,…,sNRepresent the N number of sensor in sensing network.Now, the set of sensors that there is feasible base station is obtained, it is possible to be divided into following six steps:
1-1, initialization j=1, the result set RFS making the set of sensors of feasible base station is sky；
1-2, calculating jth sensor sjAnd the distance between other N-1 sensor, and they are ordered as from small to large successively sj 1,sj 2,…,sj N-1, make set of sensors SS={sj, finite element number k=1 in set of sensors SS；
1-3, judging whether set of sensors SS exists a Feasible Basis station location, if existing, then carrying out step 1-4；If being absent from, then forward step 1-5 to；
If 1-4 is k=N, then forward step 1-6 to, otherwise, by sensor sj kAdd in set SS, and make k=k+1, return step 1-3；
1-5, make k=k-1, and the sensor s that will finally addj kLeave out from set SS；
1-6, being added in the result set RFS of set of sensors of feasible base station by set SS, if j=N+1, algorithm terminates, and otherwise makes j=j+1, returns step 1-2.
Fig. 3 (a), (b) are the schematic diagram of the set of sensors solving feasible base station.
Step 2: obtain the candidate base station set corresponding for result set RFS of set of sensors
A given set of sensors SS '=s '1,s’2,…,s’k, obtain the position c of the feasible base station of this set SS 'i, namely obtain satisfiedCiPosition.Wherein, PwjRepresent jth sensor s 'jRate of energy dissipation.D (ci,s’j) represent feasible base station ciWith sensor s 'jDistance.P (d) is charge efficiency function, and it is strictly monotone decreasing function, value and distance d (ci,s’j) relevant, functional equation isα and β is the parameter value determined by charger hardware, and D is the maximum charge distance of charging device.Can obtain after equation abbreviation, solve candidate base station location, namely to obtainMinima.
The convergence algorithm solving Fermat's problem is generalized to and solves in the problems referred to above by we.That is, the iteration function of transverse and longitudinal coordinate isWherein xj,yjRepresent sensor s 'jTwo-dimensional coordinate, x, y represents feasible base station c during last iterationiCoordinate.As distance d (ci,s’j) more than D time, the end value of Target is punished (plus positive infinity).Meanwhile, (i.e. d (the c that do not cross the border is choseni,s’j) less than or equal to D) and initial position be iterated.When algorithm iteration to fixed number of times, or when the result of twice iteration differs less than certain threshold value, algorithm terminates.Now, the deployed position c of candidate base station can be tried to achievei。
To all the sensors set in the result set RFS of the set of sensors obtained in step 1, it is carried out the Fermat point convergence algorithm once promoted, thus obtaining all candidate base station deployed position that set of sensors is corresponding.
Step 3: calculate the frequency of occurrence of sensor
The corresponding set of sensors needing its charging of each candidate base station.Information (obtaining from step 2 or step 4) according to current candidate base station, calculates each sensor frequency of occurrence in current candidate base station.
Fig. 4 (a), (b) are sensor frequency of occurrence schematic diagram.As shown in Figure 4, the information according to current candidate base station, it is possible to calculate each sensor frequency of occurrence in current candidate base station.As can be seen from Figure 4: figure has base station location C1, C2, the C3 of three candidates.Base station C1 is sensor S1, S2, S3 charging, and C2 is S1, S4 charging, and C3 is S2, S4 charging.Therefore, it can calculate respectively the frequency of occurrence of each sensor: the frequency of occurrence of sensor S1 is 2, S2 be 2, S3 be 1, S4 is 2.
Step 4: select as far as possible few base station from candidate base station
After obtaining the frequency of occurrence of sensor from step 3, the present invention uses the base station selected algorithm based on greed, selects as far as possible few base station from candidate base station.
The thinking of base station selected algorithm is: first find out the sensor that all frequency of occurrences are 1.Then, the charging base station corresponding with them is selected.Then, prioritizing selection can be the base station of the maximum sensor not being electrically charged chargings.If there being multiple such base station, from all the sensors corresponding to these base stations, just screening that sensor that frequency of occurrence is minimum, be finally chosen as the base station of this sensor charging as a result.All the sensors updates the frequency of occurrence of sensor iteration above-mentioned steps, until can be electrically charged.
The realization of base station selected algorithm is divided into following five steps:
4-1, initialize uncharged set of sensors S '={ s1,s2,…,sn, define and wait to select collection of base stations BS and final collection of base stations Res for sky；
4-2, according to the method in step 3, calculate the frequency of occurrence of all the sensors, therefrom filter out the sensor that all frequency of occurrences are 1, find out the base station charged for these sensors, and these base stations be recorded wait to select in collection of base stations BS；
4-3, the information in collection of base stations BS is selected to add in final collection of base stations Res by waiting, information according to final collection of base stations Res, recalculate uncharged set of sensors S ', if S ' is empty, then algorithm terminates, otherwise, according to the method in step 3, recalculate the frequency of occurrence of each sensor in uncharged set of sensors S '；
4-4, empty and wait to select collection of base stations BS, select from candidate base station and comprise the base station that in set of sensors S ', number of probes is maximum after renewal, and these base stations be recorded in set BS, if BS only comprises a base station, then forward step 4-3 to；
4-5, obtain waiting all the sensors TempS={s ' that selects the collection of base stations BS base station comprised corresponding1,…,s’kIn, from TempS, filter out the sensor s ' that frequency of occurrence is minimummin, and obtain as sensor s 'minThe base station of charging, makes and waits to select collection of base stations BS only to comprise this base station, forward step 4-3 to.
The running schematic diagram that Fig. 5 (a)-(f) is base station selected algorithm.
Claims (4)
1. the orientation charging base station deployment method of wireless chargeable sensing network, it is characterised in that the wireless chargeable sensing network of employing is: on a two dimensional surface, the N number of chargeable sensing of random placement；The wireless charging model adopted is: directional base station is only a sensor charging a moment, but by rotating the direction of charging antenna, can not charging for different sensors in the same time in a period of time, meanwhile, a sensor can only be charged by a directional base station；Specifically include following steps:
Step 1: obtain the set of sensors that there is feasible base station；
Step 2: obtain the candidate base station set corresponding for result set RFS of set of sensors；
Step 3: calculate the frequency of occurrence of sensor；
Step 4: select as far as possible few base station from candidate base station；
There is the set of sensors of feasible base station in obtaining described in step 1, first on a two dimensional surface, and the N number of chargeable sensor of random placement, and using certain sensor finite element as set of sensors, use S={s1,s2,…,sNRepresent the N number of sensor in sensing network；Then following steps are adopted:
1-1, initialization j=1, the result set RFS making the set of sensors of feasible base station is sky；
1-2, calculating jth sensor sjAnd the distance between other N-1 sensor, and they are ordered as from small to large successively sj 1,sj 2,…,sj N-1, make set of sensors SS={sj, finite element number k=1 in set of sensors SS；
1-3, judging whether set of sensors SS exists a Feasible Basis station location, if existing, then carrying out step 1-4；If being absent from, then forward step 1-5 to；
If 1-4 is k=N, then forward step 1-6 to, otherwise, by sensor sj kAdd in set SS, and make k=k+1, return step 1-3；
1-5, make k=k-1, and the sensor s that will finally addj kLeave out from set SS；
1-6, being added in the result set RFS of set of sensors of feasible base station by set SS, if j=N+1, algorithm terminates, and otherwise makes j=j+1, returns step 1-2.
2. the orientation charging base station deployment method of wireless chargeable sensing network according to claim 1, it is characterised in that the candidate base station set corresponding for result set RFS obtaining set of sensors described in step 2, specific as follows:
A given set of sensors SS '=s '1,s’2,...,s’k, obtain the position c of the feasible base station of this set SS 'i, namely obtain satisfiedCiPosition；Wherein, PwjRepresent jth sensor s 'jRate of energy dissipation；D (ci,s’j) represent feasible base station ciWith sensor s 'jDistance；P (d) is charge efficiency function, is strictly monotone decreasing function, value and distance d (ci,s’j) relevant, functional equation isα and β is the parameter value determined by charger hardware, and D is the maximum charge distance of charging device；Can obtain after equation abbreviation, solve candidate base station location, namely to obtainMinima；
The convergence algorithm solving Fermat's problem being generalized to solves in the problems referred to above: the iteration function of transverse and longitudinal coordinate isWherein xj,yjRepresent sensor s 'jTwo-dimensional coordinate, x, y represents feasible base station c during last iterationiCoordinate；As distance d (ci,s’j) more than D time, the end value of Target is punished；Meanwhile, choose and do not cross the border, be i.e. d (ci,s’j) initial position less than or equal to D is iterated；When algorithm iteration to fixed number of times, or when the result of twice iteration differs less than certain threshold value, algorithm terminates；Now, the deployed position c of candidate base station can be tried to achievei。
3. the orientation charging base station deployment method of wireless chargeable sensing network according to claim 1, it is characterised in that the frequency of occurrence calculating sensor described in step 3, specific as follows:
The corresponding set of sensors needing its charging of each candidate base station；Information according to current candidate base station, calculates each sensor frequency of occurrence in current candidate base station.
4. the orientation charging base station deployment method of wireless chargeable sensing network according to claim 3, it is characterized in that the base station that selection is as far as possible few from candidate base station described in step 4, first from step 3, the frequency of occurrence of sensor is obtained, afterwards operation specific as follows:
4-1, initialize uncharged set of sensors S '={ s1,s2,…,sn, define and wait to select collection of base stations BS and final collection of base stations Res for sky；
4-2, according to the method in step 3, calculate the frequency of occurrence of all the sensors, therefrom filter out the sensor that all frequency of occurrences are 1, find out the base station charged for these sensors, and these base stations be recorded wait to select in collection of base stations BS；
4-3, the information in collection of base stations BS is selected to add in final collection of base stations Res by waiting, information according to final collection of base stations Res, recalculate uncharged set of sensors S ', if S ' is empty, then algorithm terminates, otherwise, according to the method in step 3, recalculate the frequency of occurrence of each sensor in uncharged set of sensors S '；
4-4, empty and wait to select collection of base stations BS, select from candidate base station and comprise the base station that in set of sensors S ', number of probes is maximum after renewal, and these base stations be recorded in set BS, if BS only comprises a base station, then forward step 4-3 to；
4-5, obtain waiting all the sensors TempS={s ' that selects the collection of base stations BS base station comprised corresponding1,…,s’kIn, from TempS, filter out the sensor s ' that frequency of occurrence is minimummin, and obtain as sensor s 'minThe base station of charging, makes and waits to select collection of base stations BS only to comprise this base station, forward step 4-3 to.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106341825A (en) * | 2016-10-25 | 2017-01-18 | 南京大学 | Directional charger arranging method |
| CN107592604A (en) * | 2017-08-11 | 2018-01-16 | 杭州电子科技大学 | Wireless chargeable sensor network mobile data collection method based on off-line model |
| CN107708086A (en) * | 2017-08-16 | 2018-02-16 | 昆明理工大学 | A kind of mobile energy supplement method of wireless senser and actor network |
| CN109348483A (en) * | 2018-10-19 | 2019-02-15 | 杭州电子科技大学温州研究院有限公司 | The fixed point charging base station deployment method of wireless chargeable sensor network |
| CN109495843A (en) * | 2019-01-09 | 2019-03-19 | 杭州电子科技大学温州研究院有限公司 | A kind of fixed point wireless charging base station dispositions method based on convex closure selection |
| CN109688593A (en) * | 2019-01-10 | 2019-04-26 | 杭州电子科技大学温州研究院有限公司 | A kind of charging base station deployment method based on core node rule |
| CN109905883A (en) * | 2019-03-29 | 2019-06-18 | 福建师范大学 | A kind of method and terminal being connected to wireless sensor network |
| CN110943513A (en) * | 2019-12-16 | 2020-03-31 | 南京邮电大学 | Mobile charging scheduling method for rechargeable sensor network |
| CN109246602B (en) * | 2018-09-14 | 2020-06-23 | 杭州电子科技大学温州研究院有限公司 | Charging base station deployment method of wireless chargeable sensor network |
| CN113630737A (en) * | 2021-08-04 | 2021-11-09 | 西安电子科技大学 | Deployment method of mobile charger in wireless chargeable sensor network |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110064026A1 (en) * | 2008-03-17 | 2011-03-17 | Christoph Niedermeier | Method for operating a wireless sensor network and sensor node |
| CN202190128U (en) * | 2011-07-04 | 2012-04-11 | 东南大学 | Mobile wireless power charging device of wireless sensor network node |
| CN104581870A (en) * | 2014-12-30 | 2015-04-29 | 南京林业大学 | Wireless sensor network based on energy acquisition and low-delay routing method thereof |
| CN104822158A (en) * | 2015-05-20 | 2015-08-05 | 武汉大学 | Method of optimizing position of base station in radio frequency charging wireless sensor network |
| CN105006894A (en) * | 2015-06-11 | 2015-10-28 | 重庆大学 | Wireless charging system of wireless sensor network |
-
2016
- 2016-04-28 CN CN201610279938.0A patent/CN105722091B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110064026A1 (en) * | 2008-03-17 | 2011-03-17 | Christoph Niedermeier | Method for operating a wireless sensor network and sensor node |
| CN202190128U (en) * | 2011-07-04 | 2012-04-11 | 东南大学 | Mobile wireless power charging device of wireless sensor network node |
| CN104581870A (en) * | 2014-12-30 | 2015-04-29 | 南京林业大学 | Wireless sensor network based on energy acquisition and low-delay routing method thereof |
| CN104822158A (en) * | 2015-05-20 | 2015-08-05 | 武汉大学 | Method of optimizing position of base station in radio frequency charging wireless sensor network |
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