CN110248377A - Connection target coverage method based on adjustable the perception radius probability sensor model - Google Patents
Connection target coverage method based on adjustable the perception radius probability sensor model Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
- H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract
The connection target K covering method based on adjustable the perception radius model that the invention discloses a kind of.Steps are as follows by the present invention: 1: constructing network according to the location information of sensor in network；2: finding out any sensor to the shortest path of Sink and calculate communication cost；3: calculating the sets of target points for being unsatisfactory for covering threshold value that each sensor can monitor under each monitoring radius；4: calculating the candidate sensor set of each target point；5: one target point with least candidate sensor of selection；6: covering and gather for the target selection；7: repeating step 5-6, until selecting a connection covering set, algorithm terminates, and provides the node state scheduling strategy of sensor.The present invention preferably simulates sensor under actual scene to the monitoring form of target by way of probability covers；Based on the covering method of adjustable the perception radius model, reduces cost of energy of the network work within the unit time, promote network operation efficiency.
Description
Technical field
The present invention relates to wireless sensor network fields, in particular to a kind of to be based on adjustable the perception radius probability sensor die
The connection target coverage method of type.
Background technique
With the development of society and the progress of science and technology, wireless sensor network is applied to military security protection, ring more and more widely
Many fields such as border monitoring.In complicated class 2D terrain objective monitoring application, for example, forest, desert etc., wireless sensor node
Point needs to dispose sensor node by way of shedding at random, meets the monitoring to all target positions in monitoring region.With
Machine disposes the lower deployment cost for reducing network, but also increases the difficult point of scheduling sensor working condition.Therefore, wireless sensing
The target coverage problem of device network is problem particularly significant in wireless sensor network monitoring application.
It since sensor is difficult to receive energy supply, can only power by battery, therefore, energy is that target coverage solves
Object is paid close attention to for one in scheme.The target coverage solution to the problem in about wireless sensor network is felt for fixed
The dispatching method for having researched and proposed plurality of target covering for knowing radius sensor, if Yu et al. is in " On Connected Target
K-Coverage in Heterogeneous Wireless Sensor Networks " in a text, research is wirelessly passed in isomery
Sensor as few as possible how is selected in sensor network to maintain the K of network to cover and be connected to, and has proposed two sides
Method, centralized target k covering algorithm is connected to K covering algorithm with distribution, to solve the problems, such as this.Shan et al. is in " A Max-
Flow Based Algorithm for Connected Target Coverage with Probabilistic
Sensors " in a text, how research selects sensor as few as possible that network is maintained to connect in isomery probability sensor network
Logical and covering, and minimum vertex maximum-flow algorithm is proposed to solve the problems, such as this based on network flow thought.These are based on fixing
The method of the perception radius model is no longer desirable in the probability sensor network of adjustable the perception radius.Therefore, the present invention proposes needle
To the connection target coverage method of the probability sensor network of adjustable the perception radius.What the present invention studied be how scheduling sensor
Working condition and working radius so that the probability that each target point is monitored in meeting network not less than ε ∈ (0,1) and
While maintaining network connectivty, the energy cost of network units time is reduced as far as possible, promotes network operation efficiency.
Summary of the invention
The invention proposes a kind of connection target coverage method based on adjustable the perception radius probability sensor model, the party
Method passes through the working condition and working radius of scheduling sensor, so that the probability that each target point is monitored in meeting network
While not less than ε ∈ (0,1) and maintaining network connectivty, the energy cost of network units time is reduced as far as possible, promotes net
Network operational efficiency.Firstly, constructing network according to the location information of collected sensor；Secondly, according to side in network
Information, calculate any sensor node to the shortest path between meeting point, to obtain the communication of each sensor to meeting point
The communication energy cost of routing and unit time；Then, the distribution situation for acquiring each sensor surrounding objects point, that is, sense
The sets of target points and each target point that device can monitor under the corresponding monitoring radius of different operating power are currently supervised
The status information of survey；Then, it according to collected information, obtains the candidate of each target point for not meeting cover probability demand and passes
Sensor set；Again, selection target point selects one group of sensor and work in the candidate sensor set of the target point one by one
Make radius, so that the target point meets cover probability demand, until all target points can meet cover probability demand.Finally,
It obtains one group and meets the set of sensors of the network coverage with the demand that is connected to, to obtain each working sensor state in network
Scheduling scheme.
The technical scheme adopted by the invention to solve the technical problem, and steps are as follows:
Connection target coverage method based on adjustable the perception radius probability sensor model, the wireless sensor network of use
Are as follows: in an interested plane domain, there are target point O={ o known to M position1, o2..., oMAnd a meeting point
Sink.The cover probability threshold value of the required satisfaction of each target point is ε.Into the region, random placement LiaoNGe omnidirectional's probability is passed
Sensor S={ s1, s2..., sN, for each sensor there are K operating power, each power corresponds to a monitoring radius, therefore every
A sensor has an adjustable the perception radius collection R={ r1, r2..., rK}.There are a fixed communications half for each sensor
Diameter is Rtra.All sensors data acquisition rate having the same, it is assumed that the unit time acquires the data of a unit.Tool
The step of body, is as follows:
Step 1: network is constructed according to the location information of sensor in network；
Step 2: finding out any sensor from network to the shortest path of Sink and calculating is transmitted according to current path
The communication cost that the data of one unit are spent；
Step 3: calculating the target for being unsatisfactory for covering threshold value that each sensor can monitor under each monitoring radius
Point set；
Step 4: calculating the candidate sensor set of each target point；
Step 5: one target point with least candidate sensor of selection.
Step 6: calculating the covering effectiveness of each sensor in the candidate sensor set of the target point, and select a tool
There are the sensor and radius of maximal cover effectiveness, updates the coverage condition for the target that the sensor covers under current radius, more
The candidate sensor set of new each target point.The step is repeated until current target point meets covering demand.
Step 7: step 5-6 is repeated, until selecting a connection covering set.Algorithm terminates, and provides sensor
Node state scheduling strategy.
Building network described in step 1, constructs undirected weight figure G=(V, E, W), and the vertex V of figure is to own in scene
The set of sensor node and Sink；Whether side E is connected between representing vertex；Weight W represents the communication cost between two vertex.If two
Vertex siWith sjAdjacent (two vertex distance d (si, sj)≤Rtra), then a line E=E ∪ e (s is added for iti, sj), the weight on side
For ω (si, sj)=eTr(si, sj)+eRe, the wherein transmission energy cost e of unit dataTr(si, sj)=a+bd (si, sj)β,
A, b, β are constant, can be according to sensor physics featured configuration, the reception energy cost e of unit dataReIt, can be according to biography for constant
The setting of sensor physical characteristic；If vertex siWith sjIt is non-conterminous, then it is assumed that side e (si, sj) be not present, even side right ω (si, sj)=+
∞；If any vertex siIt is adjacent with Sink, then add side E=E ∪ e (si, Sink), the weight on side is ω (si, Sink) and=eTr
(si, Sink) and+eRe。
Calculating shortest path and energy cost described in step 2 are calculated using the dijkstra's algorithm for solving shortest path
Any vertex s in undirected weight figure G outiShortest path between Sink, and calculate the length in path, the path length indicate from
siThe energy cost that the data for transmitting a unit to Sink are spent, is denoted as e (path (si).If siThere is no communicate with Sink
Path, by siIt is set as unavailable sensor.
Calculating monitoring objective point set described in step 3, according to positional information calculation available sensors in different power
Existing target point in corresponding sensing region, and by sensor siThe sets of target points perceived under k-th of power is denoted as
OCov(i, k).
The candidate sensor set that target point is calculated described in step 4 will be in maximum power according to the information in step 3
Under can monitor target point ojThe sensor for having neither part nor lot in scheduling be put into setIn.
Selection described in step 5 has the target point o of least candidate sensorCri, that is:
From target point o described in step 6CriCandidate sensor set in selection covering collection the step of it is as follows:
6-1 calculates unit time energy consumption of the sensor under each power, formulae express eSe(k)=δ rk 2。
Wherein, δ is constant, related with sensor physics characteristic.
6-2. calculates sensor under each power to the monitoring capability of target point.Monitoring capability can pass through following formula
It indicates:
Wherein pI, j, kIndicate sensor siTo target point o under k-th of powerjMonitoring probability；α (k) indicates sensor
Physical characteristic parameter under k-th of power, pminThe minimum effectively monitoring probability for indicating sensor, i.e., at monitoring range edge
The monitoring probability at place.
6-3. is by sensor to the monitoring Probability p of target pointI, j, kIt is converted into monitoring gain φI, j, k, wherein φI, j, k=-ln
(1-pI, j, k), for the monitoring threshold ε of target point, Φ=- ln (1- ε) can be converted into.
The openable minimum monitoring radius r of each sensor in 6-4. set of computationsmin(S).According to step 3 and step 4 institute
Obtained set,
Wherein,Indicate ojCurrent desired monitoring gain, SjIt indicates
Monitoring o can be participated in scheduled sensorjMonitoring set of sensors.
In 6-5 set of computations each sensor in openable minimum power into maximum power, covering under each power
Lid effectiveness, by sensor siCovering effectiveness under k-th of power is set as CW (i, k), formulae express are as follows:
CW (i, k)=CPG (i, k) (CSG (i, k)+CEG (i, k))
Wherein, OucThe sets of target points of foot monitoring probability with thumb down,Indicate the maximum monitoring cost of sensor,Indicate the maximum communication path cost of sensor.
6-6 selection has the sensor and power of maximum utility value, updates the institute that the sensor monitors under the power
There is the monitoring gain of target point and add it in the monitoring set of sensors of these target points, and by the sensor from all
It is removed in the candidate sensor of target point.
6-7. judges φneed(ojWhether)≤0 is true.If not, step 6-1 is repeated to step 6-6；If so,
End step 6.
Repetition step 5-6 described in step 7, until selecting a connection covering set, detailed step is as follows:
7-1. judges whether there is φneed(o) target point of > 0.If it exists, step 5 and step 6 are repeated；If no
In the presence of performing the next step；
The set of sensors currently chosen in conjunction with the communication path of each sensor, is constituted connection covering by 7-2.
Collection.Algorithm terminates, and provides the node state scheduling strategy of sensor, including whether sensor opens monitoring or communication unit, with much
Power opens monitoring unit, and communication unit should send information to which sensor.
Beneficial effects of the present invention:
1. the present invention is directed to two dimensional terrain application scenarios, the connection based on adjustable the perception radius probability sensor model is proposed
Target coverage method preferably simulates sensor under actual scene to the monitoring shape of target by way of probability covers
Formula.
2. reducing energy of the network work within the unit time the present invention is based on the covering method of adjustable the perception radius model
Cost is measured, network operation efficiency is promoted.
Detailed description of the invention
Fig. 1 is the wireless sensor network schematic diagram that the present invention uses；
Fig. 2 is specific flow chart of the invention；
Fig. 3 is sensor model schematic diagram；
Fig. 4 is the working condition of sensor after dispatching in Fig. 1；
Fig. 5 is the covering and signal intelligence after dispatching in Fig. 1；
Specific embodiment
The present invention will be further explained below with reference to the attached drawings.
The present invention mainly proposes a kind of connection target coverage method based on adjustable the perception radius probability sensor model.Root
According to the network diagram of Fig. 1, wireless sensor network that the present invention uses are as follows: in the 2D region scene of a L*M size,
Prior random placement M target point, N number of sensor and a meeting point Sink.There are identical cover probabilities for each target point
Threshold value is ε.Need to dispatch the working condition of this N number of sensor, so that network is in the covering threshold value and network-in-dialing for guaranteeing target
While, the cost of energy in the unit time can be reduced as far as possible.Here 200 biographies are deployed in the region of 100*100
Sensor and 20 target points.
As shown in Fig. 2, used in the present invention is the adjustable the perception radius probability sensor of omnidirectional of the work in 2D scene
Model.There are K operating power, the corresponding monitoring radiuses of each power for each sensor, therefore each sensor has one
Adjustable the perception radius collection R={ r1, r2..., rK}.Each sensor is R there are a fixed communication radiustra.All
Sensor data acquisition rate having the same, it is assumed that the unit time acquires the data of a unit.Sensor is in monitoring range
The monitoring probability of edge is pmin。
As shown in figure 3, specific steps of the present invention are described as follows:
Step 1: network is constructed according to the location information of sensor in network；
Undirected weight figure G=(V, E, W) is constructed, the vertex V of figure is the set of all the sensors node and Sink in scene；
Whether side E is connected between representing vertex；Weight W represents the communication cost between two vertex.If two vertex siWith sjIt is adjacent (two vertex away from
From d (si, sj)≤Rtra), then a line E=E ∪ e (s is added for iti, sj), the weight on side is ω (si, sj)=eTr(si, sj)+
eRe, the wherein transmission energy cost e of unit dataTr(si, sj)=a+bd (si, sj)β, a, b, β is constant, can be according to sensing
Implements manage featured configuration, the reception energy cost e of unit dataReIt, can be according to sensor physics featured configuration for constant；If vertex
siWith sjIt is non-conterminous, then it is assumed that side e (si, sj) be not present, even side right ω (si, sj)=+ ∞；If any vertex siWith Sink phase
Neighbour then adds side E=E ∪ e (si, Sink), the weight on side is ω (si, Sink) and=eTr(si, Sink) and+eRe。
Step 2: finding out any sensor from network to the shortest path of Sink and calculating is transmitted according to current path
The communication cost that the data of one unit are spent；
Using the dijkstra's algorithm for solving shortest path, any vertex s in undirected weight figure G is calculatediBetween Sink
Shortest path, and calculate the length in path, which indicates from siThe data for transmitting a unit to Sink are spent
Energy cost, be denoted as e (path (si).If siCommunication path is not present with Sink, by siIt is set as unavailable sensor.
Step 3: calculating the target for being unsatisfactory for covering demand that each sensor can monitor under each monitoring radius
Point set；
According to positional information calculation available sensors in the different corresponding sensing regions of power existing target point, and
By sensor siThe sets of target points perceived under k-th of power is denoted as OCov(i, k).
Step 4: calculating the candidate sensor set of each target point；
According to the information in step 3, target point o will can be monitored under maximum powerjThe sensor for having neither part nor lot in scheduling
It is put into setIn
Step 5: one target point with least candidate sensor of selection.
Select the target point o with least candidate sensorCri, that is:
Step 6: calculating the covering effectiveness of each sensor in the candidate sensor set of the target point, and select a tool
There are the sensor and radius of maximal cover effectiveness, updates the coverage condition for the target that the sensor covers under current radius, more
The candidate sensor set of new each target point.The step is repeated until current target point meets covering demand.
6-1 calculates unit time energy consumption of the sensor under each power, formulae express eSe(k)=δ rk 2。
Wherein, δ is constant, related with sensor physics characteristic.
6-2 calculates sensor under each power to the monitoring capability of target point.Monitoring capability can pass through following formula
It indicates:
Wherein pI, j, kIndicate sensor siTo target point o under k-th of powerjMonitoring probability；α (k) indicates sensor
Physical characteristic parameter under k-th of power, pminThe minimum effectively monitoring probability for indicating sensor, i.e., at monitoring range edge
The monitoring probability at place.
6-3 is by sensor to the monitoring Probability p of target pointI, j, kIt is converted into monitoring gain φI, j, k, wherein φI, j, k=-ln
(1-pI, j, k), for the monitoring threshold ε of target point, Φ=- ln (1- ε) can be converted into.
The openable minimum monitoring radius r of each sensor in 6-4 set of computationsmin(s).According to step 3 and step 4 institute
Obtained set, Wherein, Indicate ojCurrent desired monitoring gain, SjExpression can participate in supervising in scheduled sensor
Survey ojMonitoring set of sensors.
In 6-5 set of computations each sensor in openable minimum power into maximum power, covering under each power
Lid effectiveness, by sensor siCovering effectiveness under k-th of power is set as CW (i, k), formulae express are as follows:
CW (i, k)=CPG (i, k) (CSG (i, k)+CEG (i, k))
Wherein, OucThe sets of target points of foot monitoring probability with thumb down,Indicate the maximum monitoring cost of sensor,Indicate the maximum communication path cost of sensor.
6-6 selection has the sensor and power of maximum utility value, updates the institute that the sensor monitors under the power
There is the monitoring gain of target point and add it in the monitoring set of sensors of these target points, and by the sensor from all
It is removed in the candidate sensor of target point.
6-7 judges φneed(ojWhether)≤0 is true.If not, step 6-1 is repeated to step 6-6；If so,
End step 6
Step 7: step 5-6 is repeated, until selecting a connection covering set.Algorithm terminates, and provides sensor
Node state scheduling strategy.
7-1 judges whether there is φneed(o) target point of > 0.If it exists, step 5 and step 6 are repeated；If not depositing
It is performing the next step；
The set of sensors currently chosen in conjunction with the communication path of each sensor, is constituted connection covering by 7-2
Collection.Algorithm terminates, and provides the node state scheduling strategy of sensor, including whether sensor opens monitoring or communication unit, with much
Power opens monitoring unit, and communication unit should send information to which sensor.As shown in Figure 4 and Figure 5, Fig. 4 provides Fig. 1
In one group of covering collection selecting of network, Fig. 5 provides the scheduling strategy of connection covering collection and communication path.
Claims (8)
1. the connection target coverage method based on adjustable the perception radius probability sensor model, it is characterised in that the wireless biography of use
Feel network are as follows: in an interested plane domain, there are target point O={ o known to M position1,o2,…,oMAnd one
A meeting point Sink；The cover probability threshold value of the required satisfaction of each target point is ε；The random placement LiaoNGe omnidirectional into the region
Probability sensor S={ s1,s2,…,sN, there are K operating power, each power to correspond to a monitoring radius for each sensor,
Therefore each sensor has an adjustable the perception radius collection R={ r1,r2,…,rK}；Each sensor is fixed there are one
Communication radius is Rtra；All sensors data acquisition rate having the same, it is assumed that the unit time acquires the number of a unit
According to；Specific steps are as follows:
Step 1: network is constructed according to the location information of sensor in network；
Step 2: finding out any sensor from network to the shortest path of Sink and calculate according to current path transmission one
The communication cost that the data of unit are spent；
Step 3: calculating the target point set for being unsatisfactory for covering threshold value that each sensor can monitor under each monitoring radius
It closes；
Step 4: calculating the candidate sensor set of each target point；
Step 5: one target point with least candidate sensor of selection；
Step 6: calculating the covering effectiveness of each sensor in the candidate sensor set of the target point, and select one to have most
The sensor and radius of big covering effectiveness, update the coverage condition for the target that the sensor covers under current radius, update every
The candidate sensor set of a target point；The step is repeated until current target point meets covering demand；
Step 7: step 5-6 is repeated, until selecting a connection covering set；Algorithm terminates, and provides the shape of sensor
State scheduling strategy.
2. the connection target coverage method according to claim 1 based on adjustable the perception radius probability sensor model,
It is characterized in that building network described in step 1, constructs undirected weight figure G=(V, E, W), the vertex V of figure is to own in scene
The set of sensor node and Sink；Whether side E is connected between representing vertex；Weight W represents the communication cost between two vertex；If two
Vertex siWith sjAdjacent (two vertex distance d (si,sj)≤Rtra), then a line E=E ∪ e (s is added for iti,sj), the weight on side
For ω (si,sj)=eTr(si,sj)+eRe, the wherein transmission energy cost e of unit dataTr(si,sj)=a+bd (si,sj)β,
A, b, β are constant, can be according to sensor physics featured configuration, the reception energy cost e of unit dataReIt, can be according to biography for constant
The setting of sensor physical characteristic；If vertex siWith sjIt is non-conterminous, then it is assumed that side e (si,sj) be not present, even side right ω (si,sj)=+
∞；If any vertex siIt is adjacent with Sink, then add side E=E ∪ e (si, Sink), the weight on side is ω (si, Sink) and=eTr
(si,Sink)+eRe。
3. the connection target coverage method according to claim 1 based on adjustable the perception radius probability sensor model,
It is characterized in that calculating shortest path and energy cost described in step 2, using the dijkstra's algorithm for solving shortest path, calculates
Any vertex s in undirected weight figure G outiShortest path between Sink, and calculate the length in path, the path length indicate from
siThe energy cost that the data for transmitting a unit to Sink are spent, is denoted as e (path (si)；If siThere is no communicate with Sink
Path, by siIt is set as unavailable sensor.
4. the connection target coverage method according to claim 1 based on adjustable the perception radius probability sensor model,
Calculating monitoring objective point set described in step 3 is characterized in that, according to positional information calculation available sensors in different power
Existing target point in corresponding sensing region, and by sensor siThe sets of target points perceived under k-th of power is denoted as
OCov(i,k)。
5. the connection target coverage method according to claim 1 based on adjustable the perception radius probability sensor model,
It is characterized in that the candidate sensor set that target point is calculated described in step 4 will be in maximum power according to the information in step 3
Under can monitor target point ojThe sensor for having neither part nor lot in scheduling be put into setIn.
6. the connection target coverage method according to claim 1 based on adjustable the perception radius probability sensor model,
It is characterized in that selection described in step 5 has the target point o of least candidate sensorCri, that is:
7. the connection target coverage method according to claim 1 based on adjustable the perception radius probability sensor model,
It is characterized in that described in step 6 from target point oCriCandidate sensor set in selection covering collection the step of it is as follows:
6-1 calculates unit time energy consumption of the sensor under each power, formulae express eSe(k)=δ rk 2；
Wherein, δ is constant, related with sensor physics characteristic；
6-2 calculates sensor under each power to the monitoring capability of target point；Monitoring capability can pass through following formula table
Show:
Wherein pi,j,kIndicate sensor siTo target point o under k-th of powerjMonitoring probability；α (k) indicates sensor in kth
Physical characteristic parameter under a power, pminIndicate minimum effectively the monitoring probability, the i.e. prison in monitoring range edge of sensor
Survey probability；
6-3 is by sensor to the monitoring Probability p of target pointi,j,kIt is converted into monitoring gain φi,j,k, wherein φi,j,k=-ln (1-
pi,j,k), for the monitoring threshold ε of target point, Φ=- ln (1- ε) can be converted into；
The openable minimum monitoring radius r of each sensor in 6-4 set of computationsmin(s)；According to obtained by step 3 and step 4
Set,
Wherein,Indicate ojCurrent desired monitoring gain, SjIt indicates scheduled
Sensor in can participate in monitoring ojMonitoring set of sensors；
Covering effect of each sensor in openable minimum power into maximum power, under each power in 6-5 set of computations
With by sensor siCovering effectiveness under k-th of power is set as CW (i, k), formulae express are as follows:
CW (i, k)=CPG (i, k) (CSG (i, k)+CEG (i, k))
Wherein, OucThe sets of target points of foot monitoring probability with thumb down,Indicate the maximum monitoring cost of sensor,
Indicate the maximum communication path cost of sensor；
6-6 selection has the sensor and power of maximum utility value, updates all mesh that the sensor monitors under the power
The monitoring gain of punctuate simultaneously adds it in the monitoring set of sensors of these target points, and by the sensor from all targets
It is removed in the candidate sensor of point；
6-7 judges φ need(ojWhether)≤0 is true；If not, step 6-1 is repeated to step 6-6；If so, terminate
Step 6.
8. the connection target coverage method according to claim 1 based on adjustable the perception radius probability sensor model,
It is characterized in that repetition step 5-6 described in step 7, until selecting a connection covering set, detailed step is as follows:
7-1 judges whether there is φneed(o) target point of > 0；If it exists, step 5 and step 6 are repeated；If it does not exist,
It performs the next step；
The set of sensors currently chosen in conjunction with the communication path of each sensor, is constituted connection covering collection by 7-2；
Algorithm terminates, and provides the node state scheduling strategy of sensor, including whether sensor opens monitoring or communication unit, with much power
Monitoring unit is opened, communication unit should send information to which sensor.
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| CN102647726A (en) * | 2012-02-17 | 2012-08-22 | 无锡英臻科技有限公司 | Balancing optimizing strategy for energy consumption of coverage of wireless sensor network |
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| US20180176103A1 (en) * | 2016-01-29 | 2018-06-21 | State Grid Jiangsu Electric Power Company Nanjing Power Supply Company | Cooperative coverage method of information perception for distributed network |
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| CN102647726A (en) * | 2012-02-17 | 2012-08-22 | 无锡英臻科技有限公司 | Balancing optimizing strategy for energy consumption of coverage of wireless sensor network |
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| US20180176103A1 (en) * | 2016-01-29 | 2018-06-21 | State Grid Jiangsu Electric Power Company Nanjing Power Supply Company | Cooperative coverage method of information perception for distributed network |
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