CN108770028A - A kind of wireless chargeable sensor network grid clustering method for routing - Google Patents
A kind of wireless chargeable sensor network grid clustering method for routing Download PDFInfo
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- CN108770028A CN108770028A CN201810353024.3A CN201810353024A CN108770028A CN 108770028 A CN108770028 A CN 108770028A CN 201810353024 A CN201810353024 A CN 201810353024A CN 108770028 A CN108770028 A CN 108770028A
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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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/46—Cluster building
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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
- H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
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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
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The present invention discloses a kind of wireless chargeable sensor network grid clustering method for routing, and the wireless chargeable sensor network grid clustering method for routing includes：Using sensor network described in virtual cellular mesh generation, the sensor node in each virtual cellular grid constitutes a cluster, and the charge path of charging equipment is calculated according to virtual cellular mesh generation result；The charging equipment executes charging tasks from service station S along charge path, according to the charging tasks that charging equipment executes, calculates the leader cluster node in each virtual cellular grid；According to the leader cluster node in the sensor node, charging equipment and each virtual cellular grid, the data transfer flow direction between the sensor node in sensor network is obtained.Present invention efficiently solves the unbalanced problems of sensor node energy, while reducing data transmission delay, extend the working life of wireless chargeable sensor network.
Description
Technical field
The invention belongs to wireless sensor network technology fields, more particularly to a kind of wireless chargeable sensor network network diagram
Lattice cluster routing method.
Background technology
Wireless sensor network (Wireless Sensor Networks, WSNs) is to pass through nothing by a large amount of sensor nodes
The network with certain data processing and forwarding capability that the mode of line communication is formed.Sensor node is deployed in specified area
Domain, forms to self-organizing a communications network system by way of single-hop or multi-hop, which is widely used in military, agriculture
Monitoring data and acquisition information in industry and various special or more severe physical environment.The application prospect of WSNs is very wide
It is general, more and more paid attention to by academia and industrial quarters.
In traditional WSNs, sensor node self-energy problem is always the main bottle that network maintains work
Neck.For the problem, many energy-efficient routing algorithms have been proposed in forefathers, wherein including just Clustering Routing.Point
Cluster routing algorithm mainly generates multiple clusters to the node in WSNs according to certain rule, has leader cluster node and several clusters in cluster
Interior nodes, cluster interior nodes are responsible for gathered data, and leader cluster node is responsible for collecting the data of cluster interior nodes and is transferred to fixed base stations.But
Be in traditional WSNs interior joint energy it is limited, node energy still can be depleted.
The pass that wireless charging has also obtained more people is introduced with the development of wireless charging technology, in wireless sensor network
Note introduces wireless chargeable sensor network (the Wireless Rechargeable Sensor after wireless charging technology
Networks, WRSNs) overcome the limited caused problem of node energy.By mobile charging device according to certain mechanism come
Energy supply is carried out to node, other than the hardware fault of node or other non-energy factors cause node dead, wireless sensing
The work that device network will continue.Because introducing the mechanism that mobile charging device carries out node energy supply, mobile charging
The position of equipment and the dump energy of node will influence whether node becomes cluster head, if be chosen as redirecting and mobile charging
Equipment the routing of node and redirects situation when charging to node, therefore the cluster routing method in traditional WSNs is no longer applicable in
In WRSNs, therefore there is an urgent need for proposing a kind of rational cluster routing method in WRSNs, and in the prior art can wirelessly fill
The problem of electric transducer mesh network lattice cluster routing method will appear unbalanced sensor node energy, data transmission delay.
Invention content
In view of the foregoing deficiencies of prior art, the purpose of the present invention is to provide a kind of wireless chargeable sensor networks
Network diagram lattice cluster routing method, for solving the sensor node energy in wireless chargeable sensor network in the prior art not
The problem of equilibrium, data transmission delay.
In order to achieve the above objects and other related objects, the present invention provides a kind of wireless chargeable sensor network grid point
Cluster method for routing, the wireless chargeable sensor network grid clustering method for routing include：In monitored H × M two dimensions area
Domain, H are the length of 2 dimensional region, and M is the width of 2 dimensional region, is provided with fixed base stations B, service station S, by N number of sensor section
The sensor network of point composition and the charging equipment for charging for sensor node, sensor node use set Π=
{s1,...,si,...,sN, 1≤i≤N, i ∈ Z are indicated, wherein siIndicate i-th of sensor node, sNIndicate n-th sensing
Device node, Z indicate positive integer；Using sensor network described in virtual cellular mesh generation, in each virtual cellular grid
Sensor node constitute a cluster, according to virtual cellular mesh generation result calculate charging equipment charge path；It is described to fill
Electric equipment executes charging tasks from service station S along charge path, according to the charging tasks that charging equipment executes, calculates
Leader cluster node in each virtual cellular grid；According to the sensor node, charging equipment and each virtual cellular grid
Interior leader cluster node obtains the data transfer flow direction between the sensor node in sensor network.
As a preferred embodiment of the present invention, the charging equipment is mobile charging device, the mobile charging device
It at the uniform velocity travels, movement speed v, charge power U.
As a preferred embodiment of the present invention, the consumption power of i-th of sensor node is pi, primary power be
It is described to include using sensor network described in virtual cellular mesh generation as a preferred embodiment of the present invention：
Calculate virtual cellular grid length of side l be：
Wherein, D indicates that the communication radius of sensor node, r indicate the charging radius of mobile charging device；
The node Grad of sensor node is calculated according to the length of side l of virtual cellular grid：
Wherein, giIndicate the node Grad of sensor node,Indicate the virtual cellular net belonging to sensor node
Distance of the center of a lattice to fixed base stations B, wherein πkIndicate that k-th of virtual cellular grid, k indicate the volume of virtual cellular grid
Number, 1≤k≤Ln, k ∈ Z, Ln indicate the number of the internal virtual cellular grid containing sensor node, as cluster number；
The shortest Hamilton cycle of the internal virtual cellular grid containing sensor node is calculated, the most short Hamilton is returned
Road is the charge path L of mobile charging device；
L={ π0,π1,π2,...πi,...πLn,π0, wherein π0Indicate the position of service station S, πiIndicate i-th of virtual bee
Nest net center of a lattice.
As a preferred embodiment of the present invention, the charging equipment is filled from service station S along charge path execution
Electric task includes：
From the position of service station S, the charge path L for moving along charging equipment is visited the mobile charging device successively
Ask virtual cellular grid of each inside containing sensor node, and for all the sensors node inside virtual cellular grid into
The energy of row wireless charging, all the sensors node inside i-th of virtual cellular grid all adds to maximum value i.e. Emax
When, the mobile charging device leaves i-th of virtual cellular grid, drives to next virtual cellular net in charge path L
Lattice, that is, i+1 virtual cellular grid executes charging tasks, until mobile charging device has accessed all void in charge path L
Quasi- honeycomb grid, finally returns to service station S.
As a preferred embodiment of the present invention, the charging tasks executed according to charging equipment calculate each void
Leader cluster node in quasi- honeycomb grid includes：
When mobile charging device accesses k-th of virtual cellular grid, calculates mobile charging device and reach the virtual bee
The time τ of nest grid element center coordinatek, time τkRunning time including mobile charging device and in each virtual cellular grid
Residence time：
Wherein, m indicates the number of the virtual cellular grid accessed by mobile charging device, 0≤m < k；Table
Show m-th of virtual cellular grid element center coordinate to the m+1 virtual cellular grid element center coordinate distance,Indicate moving charging
Residence time of the electric equipment in m-th of virtual cellular grid；
The time τ of the virtual cellular grid element center coordinate is reached according to mobile charging devicek, it is calculated k-th virtually
The dump energy of each sensor node in honeycomb grid
Wherein,Indicate s when the n-th c takes turns charging scheduleiThe primary power of node, piIndicate i-th sensor node
Consume power；
Calculate the charging time of each sensor node in k-th of virtual cellular grid
Wherein, EmaxIndicate that the energy of all the sensors node inside virtual cellular grid all adds to maximum value, u (d)
Indicate that energy acceptance efficiency function when sensor node is charged by mobile charging device, U indicate the charging of mobile charging device
Power；
Residence time of the mobile charging device in k-th of virtual cellular gridEqual to the virtual cellular grid
The energy of interior all sensor nodes is added EmaxRequired maximum time；
According to the charging time of each sensor node in k-th of virtual cellular gridBy the virtual cellular grid
The energy of interior all the sensors node is added EmaxThe sensor node of required shortest time is as leader cluster node；
The leader cluster node in virtual cellular grid of each inside containing sensor node is calculated successively, obtains cluster head section
Point set CH={ CH1,CH2,...,CHk,...,CHLn, CHkIndicate the leader cluster node in k-th of virtual cellular grid, CHLnTable
Show the leader cluster node in the Ln virtual cellular grid.
As a preferred embodiment of the present invention, according to the sensor node, charging equipment and each virtual cellular
Leader cluster node in grid, the data transfer flow direction obtained between the sensor node in sensor network include：
If having multiple leader cluster nodes, and multiple cluster heads with the adjacent virtual cellular grid of k-th of virtual cellular grid
The Grad of node differs, then CHkPreferentially select the node Grad g in multiple leader cluster nodesiReckling is used as and redirects
Node transfers data to base station by redirecting node；
If having multiple leader cluster nodes, and multiple cluster heads with the adjacent virtual cellular grid of k-th of virtual cellular grid
The Grad of node is identical, then calculates separately out the weights Cherd (k, j) of multiple leader cluster nodes, chooses weights Cherd (k, j)
Larger leader cluster node transfers data to base station, the calculating of weights Cherd (k, j) as node is redirected by redirecting node
Formula is：
Wherein, dkjIndicate that the distance between leader cluster node k and leader cluster node j, λ indicate Dynamic gene, EjIndicate cluster head section
Point present energy.
As described above, a kind of wireless chargeable sensor network grid clustering method for routing of the present invention, has with following
Beneficial effect：
1, the present invention has considered wireless chargeable sensor network in the case where there is mobile charging device addition
Energy expenditure and data transmission delay, the data transmission mechanism between sub-clustering and sensor node are improved, using virtual
Entire wireless chargeable sensor network is divided into multiple clusters by honeycomb grid, and present invention efficiently solves sensor node energy
Unbalanced problem is measured, while reducing data transmission delay, extends the working life of wireless chargeable sensor network.
2, the present invention is according to the leader cluster node in the sensor node, charging equipment and each virtual cellular grid,
The data transfer flow direction between the sensor node in sensor network is obtained, the node ladder in multiple leader cluster nodes is selected
Angle value giReckling transfers data to base station by redirecting node, can send data to faster as node is redirected
Base station greatly reduces the time delay of data.
3, the present invention is simple and efficient, and is had stronger versatility and practicability, is had wide range of applications.
Description of the drawings
Fig. 1 is shown as the flow diagram of the wireless chargeable sensor network grid clustering method for routing of the present invention.
Fig. 2 is shown as the schematic diagram of the WRSN network models of the present invention.
Fig. 3 is shown as the schematic diagram that the virtual cellular side length of element of the present invention calculates.
Fig. 4 is shown as the schematic diagram of the node Grad of the present invention.
Fig. 5 is shown as the schematic diagram of the virtual cellular mesh generation of the present invention.
Fig. 6 is shown as the schematic diagram of the mobile charging device charge path of the present invention.
Fig. 7 is shown as the schematic diagram of the data transmission of the present invention.
Component label instructions
S1~S4 steps
Specific implementation mode
Illustrate that embodiments of the present invention, those skilled in the art can be by this specification below by way of specific specific example
Disclosed content understands other advantages and effect of the present invention easily.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also be based on different viewpoints with application, without departing from
Various modifications or alterations are carried out under the spirit of the present invention.It should be noted that in the absence of conflict, following embodiment and implementation
Feature in example can be combined with each other.
It should be noted that the diagram provided in following embodiment only illustrates the basic structure of the present invention in a schematic way
Think, component count, shape and size when only display is with related component in the present invention rather than according to actual implementation in schema then
Draw, when actual implementation kenel, quantity and the ratio of each component can be a kind of random change, and its assembly layout kenel
It is likely more complexity.
The present embodiment provides a kind of wireless chargeable sensor network grid clustering method for routing, the present invention considers
The energy expenditure and data transmission delay of wireless chargeable sensor network, the data-set between sub-clustering and sensor node
System is improved, and entire wireless chargeable sensor network is divided into multiple clusters using virtual cellular grid.
The present embodiment provides a kind of wireless chargeable sensor network grid clustering method for routing specifically to please refer to figure
1, the wireless chargeable sensor network grid clustering method for routing includes：
Step S1, in monitored H × M 2 dimensional regions, H is the length of 2 dimensional region, and M is the width of 2 dimensional region, if
It is equipped with fixed base stations B, service station S, the sensor network being made of N number of sensor node and is used to carry out for sensor node
The charging equipment of charging, sensor node set Π={ s1,...,si,...,sN, 1≤i≤N, i ∈ Z are indicated, wherein si
Indicate i-th of sensor node, sNIndicate that n-th sensor node, Z indicate positive integer.
Step S2, using sensor network described in virtual cellular mesh generation, the biography in each virtual cellular grid
Sensor node constitutes a cluster, and the charge path of charging equipment is calculated according to virtual cellular mesh generation result.
Step S3, the charging equipment executes charging tasks from service station S along charge path, according to charging equipment
The charging tasks of execution calculate the leader cluster node in each virtual cellular grid.
Step S4 is obtained according to the leader cluster node in the sensor node, charging equipment and each virtual cellular grid
Data transfer flow direction between the sensor node in sensor network.
Specifically, in the present embodiment, the charging equipment is mobile charging device, and the mobile charging device is at the uniform velocity gone
It sails, movement speed v, charge power U；The consumption power of i-th of sensor node is pi, primary power is
Specifically, in the present embodiment, referring to Fig. 2 and Fig. 3, on the 2 dimensional region of 50m × 50m, random placement 40
Sensor node, the communication radius D=20m of sensor node, mobile charging device is using wireless chargeable small in the present embodiment
Vehicle, charging radius r=5m, the travel speed v=5m/s of trolley, the charge power U=5w of trolley of wireless chargeable trolley, passes
The ceiling capacity E of sensor nodemax=200J.
It is described to include using sensor network described in virtual cellular mesh generation：
Step S21, when first round charging schedule starts, the consumption power p of all the sensors nodei,piBetween being 0.1 to 1
Random number, primary powerNode Grad gi=0, node ID is respectively { 1,2 ..., i ... 40 }, Gu
Determine base station B to be deployed at the regional center, coordinate is (25m, 25m)；The coordinate of service station S is (18m, 0m).
Step S22 calculates virtual cellular side length of element, calculates firstIt is more than trolley charging radius r=
5m, to obtain virtual cellular side length of element l=5m.
Step S23 carries out virtual cellular mesh generation by whole network center of fixed base stations B, all until covering
Sensor node, the results are shown in Figure 5 for virtual cellular mesh generation.
Step S24 counts the virtual cellular meshes number containing sensor node, the number Ln of the cluster to be divided into
=11.
Step S25 the case where according to the virtual cellular grid of division, calculates mobile charging device and traverses all clusters most
Short hamiltonian circuit, shortest Hamilton cycle are the charge path L of mobile charging device, charge path L={ π0,π1,
π2,...,πk,...,π11,π0, referring to Fig. 6.
Step S26 is calculated according to the distance of the affiliated virtual cellular net center of a lattice of sensor node to fixed base stations B and is sensed
The node Grad g of device nodei, by taking a sensor node in Fig. 4 as an example, the affiliated virtual cellular grid of the sensor node
Centre coordinate be (33.66m, 40m), substitute into node Grad formula, calculate successively all the sensors node node ladder
Angle value.
The charging tasks executed according to charging equipment, calculate the leader cluster node packet in each virtual cellular grid
It includes：
Step S31, for being chosen referring to the leader cluster node in the virtual cellular grid 1 in Fig. 5, wherein four sensor sections
Point position coordinates are respectively s1(23.42m,4.35m)、s2(24.93m,6.92m)、s3(27.43m,9.0m)、s4(25.95m,
6.44m)；It is respectively p to consume power1=0.97w, p2=2.01w, p3=1.51w, p4=1.21w；Mobile charging device is from clothes
Business station S sets out, and calculates the time τ at the center for reaching virtual cellular grid 11：
Calculate τ1The dump energy of four sensor nodes in moment virtual cellular grid 1, respectively
Step S32 calculates the charging time of four sensor nodes in virtual cellular grid 1, the charging in the present embodiment
Receiving efficiency function u (Di) it is u (Di)=- 0.0328Di 2-0.0157Di+1.0；
Wherein DiIt is mobile charging device when honeycomb grid center is charged to sensor node, sensor node and movement
The distance between charging equipment is substituted by numerical value, and the energy for calculating four sensor nodes is added EmaxIt is required
Time is respectively
Step S33, according to above-mentioned result of calculation, when calculating the stop of mobile charging device in virtual cellular grid 1
Between
Step S34 is added E according to the energy of four sensor nodes in virtual cellular grid 1maxWhen required
Between comparison, the sensor node s of charging time minimum4It is selected as leader cluster node.
Step S35 calculates mobile charging device according to above-mentioned steps and arrives successively according to virtual cellular grid access order
Up to the time of each virtual cellular grid, the energy for calculating each sensor node in virtual cellular grid is added EmaxIt is required
Time, select wherein needed for charging time minimum sensor node be used as leader cluster node, obtain all leader cluster nodes and form
Set CH, the set CH of all leader cluster nodes compositions is referring to shown in the solid circles in Fig. 7.
According to the leader cluster node in the sensor node, charging equipment and each virtual cellular grid, sensed
The data transfer flow direction between sensor node in device network includes：
Cluster interior nodes in each virtual cellular grid transfer data to leader cluster node, and multi-hop is used between leader cluster node
Mode carry out data transmission.
Step S41, if CHkHave in adjacent virtual cellular grid and multiple redirects leader cluster node, CHkIt will preferentially select
These leader cluster nodes interior joint Grad smaller redirects.
Referring to the leader cluster node CH in virtual cellular grid 2 in 72Adjacent virtual cellular grid has 1 and 3, leader cluster node
CH1And CH3Node Grad be respectively g1=2 and g3=1, compared according to the node Grad of node, selects node Grad
Leader cluster node CH in smaller virtual cellular grid 33It is redirected, sends data to fixed base stations faster.
Step S42, if there is the identical leader cluster node of multiple node Grad, then working as further according to these leader cluster nodes
Distance ratio Cherd between preceding dump energy and two leader cluster nodes is compared as weights, chooses the larger cluster head section of weights
Point transfers data to fixed base stations as node is redirected.
Referring to the leader cluster node CH in virtual cellular grid 9 in Fig. 79Adjacent has virtual cellular grid 8,10, cluster head section
Point CH8And CH10Node Grad g8And g10It is 1.
Leader cluster node coordinate in virtual cellular grid 8,9,10 is respectively CH8=(18.26m, 29.2m), CH9=
(10.75m,23.49m)、CH10=(17.73m, 20.56m)；Leader cluster node CH in virtual cellular grid 8,108And CH10Currently
Dump energy distinguishes E8=169.17J, E10=121.59J；Take λ=0.5.It is calculated：
So as to obtain Cherd (9,8) > Cherd (9,10), leader cluster node CH9CH will be chosen8It is carried out to redirect node
Data transmission.
It charges to sensor node if this moment mobile charging device rests in virtual cellular grid 10, in data
When transmission, the leader cluster node CH in virtual cellular grid 1010Current remaining is considered as Emax, i.e. E10=Emax, calculate
It can obtain Cherd (9,8) < Cherd (9,10), leader cluster node CH9CH will be chosen10To redirect node into line number
According to transmission.
In conclusion present invention efficiently solves the unbalanced problem of sensor node energy, data transmission is reduced
While time delay, the working life of wireless chargeable sensor network is extended.
The above-described embodiments merely illustrate the principles and effects of the present invention, and is not intended to limit the present invention.It is any ripe
The personage for knowing this technology can all carry out modifications and changes to above-described embodiment without violating the spirit and scope of the present invention.Cause
This, institute is complete without departing from the spirit and technical ideas disclosed in the present invention by those of ordinary skill in the art such as
At all equivalent modifications or change, should by the present invention claim be covered.
Claims (7)
1. a kind of wireless chargeable sensor network grid clustering method for routing, which is characterized in that the wireless chargeable sensing
Device network grid cluster routing method includes：
In monitored H × M 2 dimensional regions, H is the length of 2 dimensional region, and M is the width of 2 dimensional region, is provided with fixed base stations
B, service station S, the sensor network that is made of N number of sensor node and for being set for the charging that sensor node charges
It is standby, sensor node set Π={ s1,...,si,...,sN, 1≤i≤N, i ∈ Z are indicated, wherein siIndicate i-th of biography
Sensor node, sNIndicate that n-th sensor node, Z indicate positive integer；
Using sensor network described in virtual cellular mesh generation, the sensor node in each virtual cellular grid is constituted
One cluster calculates the charge path of charging equipment according to virtual cellular mesh generation result；
The charging equipment executes charging tasks from service station S along charge path, the charging executed according to charging equipment
Task calculates the leader cluster node in each virtual cellular grid；
According to the leader cluster node in the sensor node, charging equipment and each virtual cellular grid, sensor network is obtained
The data transfer flow direction between sensor node in network.
2. a kind of wireless chargeable sensor network grid clustering method for routing according to claim 1, it is characterised in that：
The charging equipment is mobile charging device, and the mobile charging device at the uniform velocity travels, movement speed v, charge power U.
3. a kind of wireless chargeable sensor network grid clustering method for routing according to claim 2, it is characterised in that：
The consumption power of i-th of sensor node is pi, primary power be
4. a kind of wireless chargeable sensor network grid clustering method for routing according to claim 3, it is characterised in that：
It is described to include using sensor network described in virtual cellular mesh generation：
Calculate virtual cellular grid length of side l be：
Wherein, D indicates that the communication radius of sensor node, r indicate the charging radius of mobile charging device；
The node Grad of sensor node is calculated according to the length of side l of virtual cellular grid：
Wherein, giIndicate the node Grad of sensor node,Indicate the virtual cellular grid belonging to sensor node
Distance of the center to fixed base stations B, wherein πkIndicating k-th of virtual cellular grid, k indicates the number of virtual cellular grid, 1
≤ k≤Ln, k ∈ Z, Ln indicate the number of the internal virtual cellular grid containing sensor node, as cluster number；
The shortest Hamilton cycle of the internal virtual cellular grid containing sensor node is calculated, the shortest Hamilton cycle is
For the charge path L of mobile charging device；
L={ π0,π1,π2,...πi,...πLn,π0, wherein π0Indicate the position of service station S, πiIndicate i-th of virtual cellular net
Center of a lattice.
5. a kind of wireless chargeable sensor network grid clustering method for routing according to claim 4, which is characterized in that
The charging equipment executes charging tasks from service station S along charge path：
From the position of service station S, the charge path L for moving along charging equipment is accessed respectively the mobile charging device successively
Virtual cellular grid of a inside containing sensor node, and carry out nothing for all the sensors node inside virtual cellular grid
Micro USB electricity, the energy of all the sensors node inside i-th of virtual cellular grid all add to maximum value i.e. EmaxWhen, institute
It states mobile charging device and leaves i-th of virtual cellular grid, drive to next virtual cellular grid i.e. in charge path L
I+1 virtual cellular grid executes charging tasks, until mobile charging device has accessed all virtual cellulars in charge path L
Grid finally returns to service station S.
6. a kind of wireless chargeable sensor network grid clustering method for routing according to claim 5, which is characterized in that
The charging tasks executed according to charging equipment, the leader cluster node calculated in each virtual cellular grid include：
When mobile charging device accesses k-th of virtual cellular grid, calculates mobile charging device and reach the virtual cellular net
The time τ of lattice centre coordinatek, time τkRunning time including mobile charging device and stop in each virtual cellular grid
Stay the time：
Wherein, m indicates the number of the virtual cellular grid accessed by mobile charging device, 0≤m < k；Indicate the
M virtual cellular grid element center coordinate to the m+1 virtual cellular grid element center coordinate distance,Indicate that mobile charging is set
The standby residence time in m-th of virtual cellular grid；
The time τ of the virtual cellular grid element center coordinate is reached according to mobile charging devicek, k-th of virtual cellular net is calculated
The dump energy of each sensor node in lattice
Wherein,Indicate s when the n-th c takes turns charging scheduleiThe primary power of node, piIndicate the consumption work(of i-th of sensor node
Rate；
Calculate the charging time of each sensor node in k-th of virtual cellular grid
Wherein, EmaxIndicate that the energy of all the sensors node inside virtual cellular grid all adds to maximum value, u (d) is indicated
Energy acceptance efficiency function when sensor node is charged by mobile charging device, U indicate the charge power of mobile charging device；
Residence time of the mobile charging device in k-th of virtual cellular gridEqual to institute in the virtual cellular grid
The energy of some sensor nodes is added EmaxRequired maximum time；
According to the charging time of each sensor node in k-th of virtual cellular gridIt will be in the virtual cellular grid
The energy of all the sensors node is added EmaxThe sensor node of required shortest time is as leader cluster node；
The leader cluster node in virtual cellular grid of each inside containing sensor node is calculated successively, obtains leader cluster node collection
Close CH={ CH1,CH2,...,CHk,...,CHLn, CHkIndicate the leader cluster node in k-th of virtual cellular grid, CHLnIndicate the
Leader cluster node in Ln virtual cellular grid.
7. a kind of wireless chargeable sensor network grid clustering method for routing according to claim 6, which is characterized in that
According to the leader cluster node in the sensor node, charging equipment and each virtual cellular grid, obtain in sensor network
Sensor node between data transfer flow direction include：
If having multiple leader cluster nodes, and multiple leader cluster nodes with the adjacent virtual cellular grid of k-th of virtual cellular grid
Grad differ, then CHkPreferentially select the node Grad g in multiple leader cluster nodesiReckling is used as and redirects section
Point transfers data to base station by redirecting node；
If having multiple leader cluster nodes, and multiple leader cluster nodes with the adjacent virtual cellular grid of k-th of virtual cellular grid
Grad it is identical, then calculate separately out the weights Cherd (k, j) of multiple leader cluster nodes, it is larger to choose weights Cherd (k, j)
Leader cluster node as redirecting node, transfer data to base station, the calculation formula of weights Cherd (k, j) by redirecting node
For：
Wherein, dkjIndicate that the distance between leader cluster node k and leader cluster node j, λ indicate Dynamic gene, EjIndicate that leader cluster node is worked as
Preceding energy.
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| CN112272364A (en) * | 2020-10-19 | 2021-01-26 | 广州大学 | Non-cooperative game power control method based on rechargeable wireless sensor network |
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