CN108924895A - A kind of wireless sensor network mobile charging model and routing optimization method - Google Patents
A kind of wireless sensor network mobile charging model and routing optimization method Download PDFInfo
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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
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
- H02J50/80—Circuit arrangements or systems for wireless supply or distribution of electric power involving the exchange of data, concerning supply or distribution of electric power, between transmitting devices and receiving devices
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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
- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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Abstract
The invention discloses a kind of wireless sensor network mobile charging model and routing optimization method, the charge model includes：Mobile charger, service station, mobile charger is from service station, predeterminated position is moved to constant speed V, and wireless charging is carried out for one or more a certain range of node by WET mode, after charging complete, mobile charger returns to service station electric energy supplement, fundamentally solves the restricted problem of WSN energy, node probability of death is reduced to the full extent, effectively improves the technical effect of network lifecycle.
Description
Technical field
The present invention relates to field of power communication, and in particular, to a kind of wireless sensor network mobile charging model and road
By optimization method.
Background technique
In traditional WSN (wireless sensor network), usual sensor node electricity is provided by common batteries, energy
It is limited, the runing time of sensor node is limited, to make the runing time of WSN long as far as possible, it is ensured that node energy obtains
It makes full use of.Most research at this stage is generally focused on optimization aspect of the energy distribution with management strategy, but the knot of which
Fruit also only extends the life cycle of WSN in a certain range, and node still has when stop working.Current solution is done
Method is exactly battery by manually replacing, but in face of being difficult to realize manually replace the environment of battery, needs new solution
To guarantee the duration and controllability of WSN.
Wireless sensor network technology is with sensor technology, embedded technology, modern network technology and wireless communication skill
The rapid development of art is used widely, and by a large amount of sensor nodes, technology self-organizing constitutes network, node by wireless communication
It is deployed in region to be measured at random or specifically, acquires environmental information, realizes data quantization, fusion and transmission, and mutually assist
Work is adjusted to complete appointed task.In field environment monitoring, wireless sensor node fails maximum possible still due to itself energy
Source exhausts.
Summary of the invention
The present invention provides a kind of wireless sensor network mobile charging model and routing optimization methods, fundamentally solve
The restricted problem of WSN energy reduces node probability of death to the full extent, effectively improves the technology effect of network lifecycle
Fruit.
On the basis of the rapid development of wireless charging technology now, complicated ring can be deployed in by mobile charging facility
Domestic sensing node electric energy supplement, fundamentally solves the restricted problem of WSN energy.Node can be reduced to the full extent
Probability of death effectively improves network lifecycle.The current emphasis of the correlative study of the charging problems of wireless sensor network at present
On charging strategy, costly, and the mobile expense of its own is very big for wireless charging equipment price, in this regard, formulate it is reasonable
The shift strategy of effective charging equipment and particularly significant with the additional project of node energy.
For the life cycle of extend as far as possible WSN, wireless charging technology can use as sensing node charging.The present invention
Rechargeable wireless sensor network (Wireless will be studied on the basis of establishing wireless sensor network mobile charging model
Rechargeable Sensor Network, WRSN) routing algorithm, and its communication reliability is unfolded to study.
For achieving the above object, described to fill this application provides a kind of wireless sensor network mobile charging model
Electric model includes：
Mobile charger, service station, mobile charger move to predeterminated position from service station, with constant speed V, and
It is that one or more a certain range of node carries out wireless charging by WET mode, after charging complete, mobile charger is returned
To service station electric energy supplement.
Further, an energy supplement period is represented with T, i.e., the wireless charging device in mobile charger is continuous two
The secondary interval time that charging is left for by service station；In an energy supplement cycle T, WCV have moving condition, charged state and
Three kinds of states of rest and reorganization state, WCV is wireless charging device；WCV carries out the supplement of energy in service station and maintenance adjustment is
Rest and reorganization state, as shown in Equation 1：
T=TP+Tvac+∑i∈NTi (1)
In formula, the mobile total time-consuming of WCV is Tp, TiFor the charging time of arbitrary node i, TvacRest and reorganization for WCV in service station
Time, the optimization aim of periodical charge model are to realize MC rest and reorganization time and supplement periodic ratio TvacThe maximization of/T.
Wherein, U is that the charging of each sensor node receives power,fkiAnd GiIndicate that the arbitrary node i unit time connects
The data volume received and generated, and being sent to other nodes and base station is that data volume isfkiWith fiB, they are abided by such as 2 table of formula
The data volume conservation constraints shown：
Then the energy consumption r of node i unit time is：
Wherein, unit data energy consumption is ρ, and unit data is C by the energy consumption that node i is sent to node jij, CiBIndicate unit
Data are fed directly to the energy consumption of base station, wherein CijAnd CiBWith distance dependent；EmaxFor the maximum battery capacity of ordinary node, work as appearance
Amount is lower than EminWhen, node will stop working；When nodes all in network all work normally, node any time t is remaining
Energy ei(t) > Emin, i.e.,：
Emax-(T-Ti),ri> Emin,i∈N (4)
When only meeting the energy consumption of node in one cycle equal to its charge volume, the duration of node work could be maintained
And periodically：
T·ri=Ti·U,i∈N (5)
It is converted into:
T=Ttsp+Tvac+∑i∈NTi (6)
After determining the movement routine of WCV, relax constraint condition by introducing auxiliary variable, by the maximum charge period
Problem switchs to linear programming problem；
In charging, definition node receives power and is not less than threshold values δ sensor node, and the chargeable range of WCV is Dδ, node
The charging of i receive power U to apart from related：
In formula, UmaxIndicate peak power output when WCV charging, μ (Di) indicate energy transmission efficiency when charging, it depends on
The distance between WCV and node；Whole network is divided into centered on base station, side length is the regular hexagon cell of D, and WCV will
Periodically there are each cells of node for traversal, and in the center dwell of cell, and whole nodes charging in cell, guarantees thus
All node electric energy all reach E in cellmax。
Present invention also provides a kind of routing optimization methods based on LEACH algorithm after Optimal improvements, fill applied to described
In electric model, the method includes：Following Optimal improvements are carried out to traditional LEACH algorithm：
The node for being chosen as cluster head is linked to be a data chain, all the sensors node is connect by this cluster head chain
Power is communicated with Sink node；Sink node is inquired by ID number away from all nodes in nearest region first, records all energy
The node communicated, and it is selected as candidate cluster head；Then candidate cluster head inquires downwards its nearest regional nodes, looks into through excessively taking turns
After inquiry, the leader cluster node of all areas is found.
Wireless chargeable sensing network protocol network average energy consumption is lower, can effectively delay the first node death time, prolong
Long network lifecycle.Wherein, the Establishing process of routing is：
Step 1：Sink node starts path and finds；
Step 2：It is successively traversed by the ID of sensing node each in wireless sensor and actor networks；
Step 3：Judge whether to have traversed all nodes, if not traversed all nodes, continue step 2, if traversal
Complete all nodes, then store all paths；
Step 4：Measurement data packet loss number；
Step 5：Judge whether to obtain enough empirical values；If continuing step 4 without if；Optimal path is found if having, and
Sensing node in this path domain is established into cluster.
One or more technical solution provided by the present application, has at least the following technical effects or advantages：
The present invention is initially setting up wireless sensor network mobile charging model, and analyzes rechargeable wireless sensor
Network communication performance optimizes sub-clustering LEACH agreement as target using to improve WRSN communication reliability and sets on this basis
Meter proposes the routing algorithm improvement project that leader cluster node is linked to be to a data chain, and by emulation to improved routing
Algorithm carries out verifying analysis, and simulation result shows that the agreement has good data transmission credibility, is suitable for rechargeable wireless
Sensor network.
To wireless sensor network (Wireless Sensor Network, WSN) energy limit problem, by wireless charging
Technology is applied to WSN, establishes WSN mobile charging model, and analyze and cause rechargeable wireless sensor network communication reduced performance
Factor, propose a kind of improved cluster head chaining Routing Protocol on this basis.By all the sensors node in network with region
For unit set cluster, the node for being selected as cluster head is linked to be a data chain and is carried out data transmission.Simulation result shows the road
There is preferable data transmission credibility and real-time by agreement.
Detailed description of the invention
Attached drawing described herein is used to provide to further understand the embodiment of the present invention, constitutes one of the application
Point, do not constitute the restriction to the embodiment of the present invention；
Fig. 1 is the composition schematic diagram of WSN mobile charging model in the application；
Fig. 2 is the point-to-point charging network model schematic periodically traversed；
Fig. 3 is the point-to-multipoint charging schematic diagram of periodically traversal cell；
Fig. 4 is the Establishing process schematic diagram of routing.
Specific embodiment
To better understand the objects, features and advantages of the present invention, with reference to the accompanying drawing and specific real
Applying mode, the present invention is further described in detail.It should be noted that in the case where not conflicting mutually, the application's
Feature in embodiment and embodiment can be combined with each other.
In the following description, numerous specific details are set forth in order to facilitate a full understanding of the present invention, still, the present invention may be used also
Implemented with being different from the other modes being described herein in range using other, therefore, protection scope of the present invention is not by under
The limitation of specific embodiment disclosed in face.
Referring to FIG. 1, WSN mobile charging model：
In wireless sensor network, it is limited and have filling for wireless energy reception device that sensing node carries memory capacity
Battery, the maximum storage energy of node are Emax, and node will fail when energy is lower than Emin.In order to ensure the node in WSN
Effective charge level can be maintained to persistently work, proposition introduces mobile charging equipment in a network, according to
Whole network node energy state controls the movement and charging behavior of charging equipment, supplements energy in time for the node of low energy.
Mobile battery vehicle (also referred to as mobile charger MC) generally is used, the near nodal for needing charging is moved to constant speed V, and lead to
Crossing WET mode is that one or more a certain range of node carries out wireless charging.The amount that node receives depends on
Output power and MC at a distance from node (efficiency of transmission) when MC charging.The energy that mobile device carries is at most B, both
The movement of itself is provided, and network node need to be transmitted to.Initial mobile battery vehicle carries full energy from its all-in-service station, root
Different charging strategies is formulated according to the energy state of network.In order to ensure the duration of entire charging process, mobile battery vehicle must
All-in-service station must be returned to before its energy carried is lower than zero, carry out the supplement of self-energy.According to network size size, node
Deployment density and mobile charging device carry gross energy number, multiple mobile chargers can be chosen, effectively so as to can be right in time
All low energy sensing nodes carry out energy supplement in network.
In periodic charge model, the energy supplement of sensor node is by wireless charging device (Wireless
Charging Vehicle, WCV) position fixed in network is moved to from service station (i.e. all-in-service station), with the side of wireless transmission
Formula is realized.WCV all sensor node can return to service station after completing disposable energy supply in a network, and start from
The energy supplement of body.An energy supplement period is represented with T, i.e. WCV is at the interval for leaving for charging by service station twice in succession
Time.
In an energy supplement cycle T, WCV has three kinds of moving condition, charged state and rest and reorganization state states.WCV exists
The supplement and maintenance adjustment that energy is carried out in service station are rest and reorganization state, as shown in Equation 1：
T=TP+Tvac+∑i∈NTi (1)
In formula, the mobile total time-consuming of WCV is Tp, TiFor the charging time of arbitrary node i, TvacRest and reorganization for WCV in service station
Time, the optimization aim of periodical charge model are to realize MC rest and reorganization time and supplement periodic ratio TvacThe maximization of/T.
In periodic charge model, two kinds of periods of fixed base stations and mobile base station are divided whether being moved by base station
Property charge model.Wherein, mobile base station charge model is that base station and charger are installed in a mobile device, to complete to charge
Task.
(1) fixed base stations
The position of base station is kept fixed constant in entire charging process, is passed through by the data that sensor perceives direct
It send with the transmission mode of multi-hop to base station.In this monitoring process, the generation of unit time interior nodes, reception and the data flow sent
It will be invariable.Fig. 2 is the point-to-point charging network model of MC periodicity traverse node, only when MC is as close possible to node
It can charge.U is that the charging of each sensor node receives power,fkiAnd GiIndicate that the arbitrary node i unit time connects
The data volume received and generated, and being sent to other nodes and base station is that data volume isfkiWith fiB, they are abided by such as 2 table of formula
The data volume conservation constraints shown.
Then the energy consumption r of node i unit time is：
Wherein, unit data energy consumption is ρ, and unit data is C by the energy consumption that node i is sent to node jij, CiBIndicate unit
Data are fed directly to energy consumption (the wherein C of base stationijAnd CiBWith distance dependent).EmaxFor the maximum battery capacity of ordinary node, when
Capacity is lower than EminWhen, node will stop working.When nodes all in network all work normally, node any time t is remaining
Energy ei(t) > Emin, i.e.,：
Emax-(T-Ti),ri> Emin,i∈N (4)
When only meeting the energy consumption of node in one cycle equal to its charge volume, the duration of node work could be maintained
And periodically：
T·ri=Ti·U,i∈N (5)
To make WCV obtain the maximum rest and reorganization time in a complete charge cycle, need WCV in the task of execution time
The all sensors nodal distance gone through is as shorter as possible, and when being able to satisfy WCV and reaching each node and charged, each node can all be obtained
More energy is obtained to reduce the number of charging.The verified time in station for maximizing mobile charger is to minimize charger
Traveling time, therefore, formula 6 can be converted into:
T=Ttsp+Tvac+∑i∈NTi (6)
After determining the movement routine of WCV, relax constraint condition by introducing auxiliary variable, by the maximum charge period
Problem switchs to linear programming problem.
In charging, definition node receives power and is not less than threshold values δ sensor node, and the chargeable range of WCV is Dδ, node
The charging of i receive power U to apart from related：
In formula, UmaxIndicate peak power output when WCV charging, μ (Di) indicate energy transmission efficiency when charging, it depends on
The distance between WCV and node.Therefore whole network can be divided into centered on base station, side length is the regular hexagon cell of D,
As shown in Figure 3.
WCV will periodically there are each cells of node for traversal, and in the center dwell of cell, thus the whole in cell
Node charging guarantees that all node electric energy all reach E in cellmax。
2. routing algorithm：
LEACH algorithm is a kind of typical Clustering Routing, and every wheel recycles the establishment stage for being divided into cluster and stable data
Stage of communication.
In the establishment stage of cluster, node generates the random number between one 0~1, if this number is less than threshold value T (n),
The node becomes cluster head, and for cluster head to all node broadcasts message, nearest cluster is added according to signal strength or weakness is received in other nodes,
And notify corresponding cluster head.It had been elected to the node of cluster head, cluster head will not be elected as again when lower whorl establishes cluster.
Wherein, p is the percentage of total node number day shared by leader cluster node in network, and each node can take turns in operation in 1/p
Serve as a leader cluster node；R is completed wheel number, and symbol mod is modulo operator number, and r mod (1/P) represents this wheel circulation
In be elected to the node number of cluster head, G is the node set that cluster head is not acted as in last round of.
In the stabilized communication stage, cluster head generates a time division multiple acess according to the information that cluster is added in non-leader cluster node and accesses
(Time Division Multiple Access, TDMA) timetable is that all nodes distribute sending time slots, institute in cluster in cluster
There is node to send data to cluster head according to TDMA slot.
Referring to FIG. 4, being directed to the characteristic of chargeable sensing node, optimization is improved to LEACH algorithm：It will be chosen as cluster
The node of head is linked to be a data chain, and all the sensors node is communicated by the relay of this cluster head chain with Sink node.
Sink node is inquired by ID number away from all nodes in nearest region first, records all nodes that can be communicated, and
It is selected as candidate cluster head.Then candidate cluster head inquires downwards its nearest regional nodes and finds all areas after excessively taking turns inquiry
Leader cluster node.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic
Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as
It selects embodiment and falls into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (5)
1. a kind of wireless sensor network mobile charging model, which is characterized in that the charge model includes：
Mobile charger, service station, mobile charger moves to predeterminated position from service station, with constant speed V, and passes through
Wireless energy transfer mode is that one or more a certain range of node carries out wireless charging, after charging complete, moving charging
Electric appliance returns to service station electric energy supplement.
2. wireless sensor network mobile charging model according to claim 1, which is characterized in that represent an energy with T
The amount supplement period, i.e., the wireless charging device in mobile charger is when leaving for the interval of charging by service station twice in succession
Between；In an energy supplement cycle T, WCV has three kinds of moving condition, charged state and rest and reorganization state states, and WCV is wireless charging
Electric equipment；WCV carries out the supplement of energy in service station and maintenance adjustment is rest and reorganization state, as shown in Equation 1：
T=TP+Tvac+∑i∈NTi (1)
In formula, the mobile total time-consuming of WCV is Tp, TiFor the charging time of arbitrary node i, TvacThe rest and reorganization time for WCV in service station,
The optimization aim of periodical charge model is to realize MC rest and reorganization time and supplement periodic ratio TvacThe maximization of/T.
3. wireless sensor network mobile charging model according to claim 1, which is characterized in that U is each sensor section
The charging of point receives power,And GiThe data volume that the expression arbitrary node i unit time receives and generates, and be sent to
Other nodes are that data volume is with base stationWith fiB,Gi、fiBThe data indicated in accordance with such as formula 2
Measure conservation constraints：
Then the energy consumption r of node i unit time is：
Wherein, unit data energy consumption is ρ, and unit data is C by the energy consumption that node i is sent to node jij, CiBIndicate unit data
It is fed directly to the energy consumption of base station, wherein CijAnd CiBWith distance dependent；EmaxFor the maximum battery capacity of ordinary node, when capacity is low
In EminWhen, node will stop working；When nodes all in network all work normally, the remaining energy of node any time t
ei(t) > Emin, i.e.,：
Emax-(T-Ti),ri> Emin,i∈N (4)
When only meeting the energy consumption of node in one cycle equal to its charge volume, the duration that node could be maintained to work and week
Phase property：
T·ri=Ti·U,i∈N (5)
It is converted into:
T=Ttsp+Tvac+∑i∈NTi (6)
After determining the movement routine of WCV, relax constraint condition by introducing auxiliary variable, by maximum charge periodic problem
Switch to linear programming problem；
In charging, definition node receives power and is not less than threshold values δ sensor node, and the chargeable range of WCV is Dδ, node i fills
Electricity receive power U to apart from related：
In formula, UmaxIndicate peak power output when WCV charging, μ (Di) indicate charging when energy transmission efficiency, depend on WCV with
The distance between node；Whole network is divided into centered on base station, side length is the regular hexagon cell of D, and WCV will be periodical
There are each cells of node for traversal, and in the center dwell of cell, and whole nodes charging in cell, guarantees in cell thus
All node electric energy all reach Emax。
4. a kind of LEACH algorithm based on any one of charge model in claim 1-3 carries out routing optimization method, institute
The method of stating includes：
The node for being chosen as cluster head is linked to be a data chain, all the sensors node by the relay of this cluster head chain with
Sink node communication；Sink node is inquired by ID number away from all nodes in nearest region first, record it is all can be therewith
The node of communication, and it is selected as candidate cluster head；Then candidate cluster head inquires downwards its nearest regional nodes, is excessively taken turns inquiry
Afterwards, the leader cluster node of all areas is found.
5. LEACH algorithm according to claim 4 carries out routing optimization method, which is characterized in that the foundation of LEACH routing
Process is：
Step 1：Sink node starts path and finds；
Step 2：It is successively traversed by the ID of sensing node each in wireless sensor and actor networks；
Step 3：Judge whether to have traversed all nodes, if not traversed all nodes, continue step 2, if having traversed institute
There is node, then stores all paths；
Step 4：Measurement data packet loss number；
Step 5：Judge whether to obtain enough empirical values；If continuing step 4 without if；Find optimal path if having, and by this
Sensing node in path domain establishes cluster.
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| CN110662175A (en) * | 2019-09-11 | 2020-01-07 | 哈尔滨工程大学 | Moving vehicle speed control method based on wireless chargeable sensor network |
| CN110677892A (en) * | 2019-09-24 | 2020-01-10 | 深圳职业技术学院 | Wireless sensor network cyclic charging method and system |
| CN110677892B (en) * | 2019-09-24 | 2022-08-30 | 深圳职业技术学院 | Wireless sensor network circulating charging method and system |
| CN112788560A (en) * | 2020-12-18 | 2021-05-11 | 昆明理工大学 | Space-time charging scheduling method based on deep reinforcement learning |
| CN112788560B (en) * | 2020-12-18 | 2022-02-08 | 昆明理工大学 | Space-time charging scheduling method based on deep reinforcement learning |
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Application publication date: 20181130 |