CN105636067A - Method for deploying particle swarm algorithm in wireless sensor network based on virtual force guidance - Google Patents

Method for deploying particle swarm algorithm in wireless sensor network based on virtual force guidance Download PDF

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Publication number
CN105636067A
CN105636067A CN201610035962.XA CN201610035962A CN105636067A CN 105636067 A CN105636067 A CN 105636067A CN 201610035962 A CN201610035962 A CN 201610035962A CN 105636067 A CN105636067 A CN 105636067A
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node
network
communication radius
impact
barrier
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郑丽敏
李爽
朱虹
田立军
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China Agricultural University
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China Agricultural University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • 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
    • 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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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention relates to a method for deploying a particle swarm algorithm in a wireless sensor network based on virtual force guidance. The method provided by the invention is as follows: optimizing the network by using the particle swarm algorithm based on the virtual force guidance. The situation that the communication range of a network node will change when meeting a barrier wall in a pig breeding environment is considered, the network is optimized respectively for the two problems of network coverage and network connectivity.

Description

A kind of particle cluster algorithm based on fictitious force guiding is at the dispositions method of wireless sensor network
Technical field
The present invention relates to particle cluster algorithm, Internet of Things, pig-breeding field, particularly relate to a kind of particle cluster algorithm based on fictitious force guiding at the dispositions method of wireless sensor network.
Background technology
Wireless sensor network is the necessary technology realizing large-scale cultivation, it is possible to real-time high-efficiency also accurately acquires information, and wherein node deployment is underlying issue in wireless sensor network application, is also very important problem. Because the deployed position of sensor node, directly influence whole network and complete quality and the efficiency of task. Employing wireless sensor network in pig-breeding environment, it is necessary to consider the impact that wireless signal is produced by barrier, wherein notable with wall. Existing node deployment algorithm have ignored the impact of barrier mostly, but so there will be in the application of actual environment and can connect in theory, but after running into barrier, communication distance shortens, and causes situation about can not connect.
Fictitious force algorithm, by setting up the fictitious force model between sensing node and target, barrier and other sensing nodes, determines each sensing node position according to stress balance. However, for the radio sensing network being made up of fixing sensing node and mobile sensor node, the fictitious force of mobile sensor node is likely to restriction radio sensing network layout optimization by fixing sensing node, affects the global optimization of fictitious force algorithm. Particle cluster algorithm is a kind of Stochastic Optimization Algorithms based on intelligent Theory, produces swarm intelligence by the interparticle cooperation and competition of population and instructs Optimizing Search. Compared with conventional genetic algorithm, it realizes easily, and the parameter that need to adjust is few, thus obtains extensive attention, it has also become a kind of important optimization tool. Therefore by adopting the speed renewal process of fictitious force improved PSO, instruct microgranule Evolutionary direction, accelerate algorithmic statement. This strategy had both avoided the mobile sensor node optimization constraint that fictitious force algorithm causes, makes again particle swarm optimization on purpose evolve to the direction expanding coverage rate and target detection rate, accelerates algorithm the convergence speed.
Summary of the invention
It is an object of the invention to provide a kind of particle cluster algorithm based on fictitious force guiding at the dispositions method of wireless sensor network, when in considering pig breeding farm, transmission of wireless signals is affected by barrier, by the particle cluster algorithm that fictitious force leads, solve during wireless sensor network node is disposed major issue improve the network coverage and improve network connectivty.
For solving above-mentioned technical problem, the main technical content of the present invention is as follows:
A kind of method improving the network coverage based on the particle cluster algorithm of fictitious force guiding when barrier, specifically comprises the following steps that
1. pig breeding farm area size a*b is set; The big small-scale N of wireless sensor network, wherein can arrange stationary nodes number is N1, mobile node number is N2; The communication radius R of radio node.
2. thing wall quantity of placing obstacles is m, as m=4 has been four walls, zone leveling divides quinquepartite, and length of walls acquiescence is identical with zone length.
3. random distribution node within the scope of given area, and judge whether each node is subject to barrier impact, if there is no impact, keep the initial communication radius R set, otherwise changing communication radius according to the log path loss model of transmission of wireless signals is r (only changing the part receiving impact, the remainder former communication radius of maintenance is constant).
4. the node in wireless sensor network is optimized deployment by the particle cluster algorithm according to fictitious force guiding, the invariant position of stationary nodes, and mobile node changes accordingly, it is achieved improve the network coverage.
A kind of method improving network connectivty based on the particle cluster algorithm of fictitious force guiding when barrier, specifically comprises the following steps that
1. pig breeding farm area size a*b is set; The big small-scale N of wireless sensor network, gives tacit consent to all nodes and is stationary nodes; The communication radius R of radio node.
2. thing wall quantity of placing obstacles is m, as m=4 has been four walls, zone leveling divides quinquepartite, and length of walls acquiescence is identical with zone length.
3. random distribution node within the scope of given area, and judge whether each node is subject to barrier impact, if there is no impact, keep the initial communication radius R set, otherwise changing communication radius according to the log path loss model of transmission of wireless signals is r (only changing the part receiving impact, the remainder former communication radius of maintenance is constant).
4. the node that be distributed is connected cluster, find position optimum in regional extent according to the particle cluster algorithm of fictitious force guiding and can connect maximum nodes and become one new bunch, at one new node of this location arrangements.
5. till repetition step 4 all of node in region is all connected in one bunch.
Advantages of the present invention
1. effect of optimization is good. The particle cluster algorithm of contrast fictitious force guiding and simple fictitious force algorithm or particle cluster algorithm, effect of optimization can promote more than 10%.
2. practical, it is simple to amendment. Zones of different size or the parameter such as the scale of wireless sensor network, node radius can be carried out arranging; And consider the barrier impact on wireless signal, more meet practical application.
Accompanying drawing explanation
Fig. 1 is transmission range figure during sensor of the invention node chance barrier
Fig. 2 is the present invention algorithm flow chart when barrier
Fig. 3 is the present invention netinit figure when barrier
Fig. 4 is the particle cluster algorithm flow chart of the present invention
Fig. 5 is the design sketch of optimizing network coverage rate of the present invention
Fig. 6 is the design sketch that the present invention optimizes network connectivty
Detailed description of the invention
Below in conjunction with accompanying drawing, the present invention is described further.
Accompanying drawing 1 is the sensor node signal transmission ranges when running into barrier, the transmission range of sensor node is with himself position for the center of circle, transmission range is the circle of radius, after its wireless signal runs into barrier wall in transmitting procedure, can't directly decay to zero to cause transmitting, but can decay according to the attribute of barrier, reduce transmission radius so that the position that originally can receive signal becomes blind area.
The present invention, on the basis based on log path loss model, adds the impact of barrier wall, can calculate, according to this model, the communication radius r that sensor node reduces after running into barrier, and the relational expression of this model is:
P L ( d ) = P L ( d 0 ) + 10 n lg ( d d 0 ) + A F
In formula, PL (d) is path loss values; N represents path loss index, and its numerical value depends on the difference of environment, and the linear regression that according to actual measurement data, can set up method of least square is obtained; d0(d is generally chosen for near-earth reference distance0=1m); D is the distance between signal transmitter and receiver; AF is body of wall decay factor.
If the threshold value of received signal strength is P0, when in space the received signal strength of optional position lower than P0Time, it is believed that this point cannot be carried out perception or communication by the sending node of wireless signal. All can be by what measurement obtained due to strength of transmitted signals P, path loss index n and wall decay factor AF, and threshold value P0With reference distance d0Set, it is possible to calculate the communication distance r after wireless signal in actual environment receives barrier by following formula:
P L ( d ) = lg ( P P 0 ) = P L ( d 0 ) + 10 n lg ( r d 0 ) + A F
Accompanying drawing 2 is the overall flow of algorithm, specific as follows:
1. pig breeding farm area size a*b is set; The big small-scale N of wireless sensor network; The communication radius R of radio node.
2. thing wall quantity of placing obstacles is m, as m=4 has been four walls, zone leveling divides quinquepartite, and length of walls acquiescence is identical with zone length.
3. random distribution node within the scope of given area, and judge whether each node is subject to barrier impact, if there is no impact, keep the initial communication radius R set, otherwise changing communication radius according to the log path loss model of transmission of wireless signals is r (only changing the part receiving impact, the remainder former communication radius of maintenance is constant).
4. network is initialized by the setting value according to above step.
In above-mentioned steps 3, disturbance in judgement thing is on the whether influential principle of node, it it is the intersection point number by the communication circle of decision node with barrier, if there is no intersection point or only one of which intersection point, then not changing the communication radius of present node, if there being two intersection points, then calculating the communication radius r made new advances according to above-mentioned path loss model, but only changing the part receiving impact, remainder keeps former communication radius constant. Accompanying drawing 3 is the network after initialization.
Can be optimized according to the different purposes of node deployment scheme after netinit.
A kind of method improving the network coverage based on the particle cluster algorithm of fictitious force guiding when barrier, specifically comprises the following steps that
1. in the network of initial deployment, node is initialized, give node initial velocity value and position.
2. calculate the adaptive value of each node particle.
3. calculate inertia weight value, and judge whether more than 0, if less than 0, terminating algorithm.
If 4. in step 3, inertia weight value, less than 0, updates position and the speed of each particle node.
5. repeat step 2, and compare each adaptive value, preserve optimal value.
6. repeat step 3 until inertia weight is less than 0.
Accompanying drawing 4 is above-mentioned steps flow chart. Accompanying drawing 5 is the design sketch after the network optimization.
In above-mentioned steps 1, being that in continuous space coordinate system, the mathematical description of standard particle group's algorithm is as follows: set population scale as N to the initialization principle of population, search volume is Q dimension, then in space, the coordinate position vector of particle is Xi=(Xi1, Xi2..., XiQ), the velocity vector of particle is Vi=(Vi1, Vi2..., ViQ), the individual optimum position P of particle in search procedurei=(Pi1, Pi2..., PiQ), colony optimum position Pg=(Pg1, Pg2..., PgQ)��
In above-mentioned steps 3, inertia weight �� is initially set definite value, but it have been investigated that, dynamic reduce inertial factor w, it is possible to making algorithm more stable, effectiveness comparison is good, and wherein successively decreasing of linear function is better than the decreasing strategy of convex function. Because the algorithm incipient stage, big inertial factor can be that algorithm is not easy to be absorbed in local optimum, and to the later stage of algorithm, little inertial factor can make convergence rate accelerate, and makes convergence more steady, is unlikely to oscillatory occurences occur. So inertia weight w herein adopts linear decrease strategy, its decreasing function is
W=MaxW-CurCount* ((MaxW-MinW)/LoopCount)
Wherein LoopCount is iterations; CurCount represents current iteration number; MaxW represents initial weight; MinW is final weight.
In above-mentioned steps 4, particle cluster algorithm is as follows to the more new principle of position and speed:
Xi(k+1)=Xi(k)+r*Vi(k+1)
Vi(k+1)=w*Vi(k)+c1*r1*[Pi(k)-Xi(k)]+c2*r2*[Pg(k)-Xi(k)]
Wherein r is constraint factor; W represents inertia weight; c1��c2Represent the weight coefficient of Particle tracking individuality optimal value and colony's optimal value respectively; r1��r2It it is [0,1] interval interior equally distributed random number.
After introducing fictitious force algorithm, it is achieved the particle cluster algorithm of fictitious force guiding, the principle that particle rapidity is updated by this algorithm has been improved, as follows:
Vi(k+1)=w*Vi(k)+c1*r1*[Pi(k)-Xi(k)]+c2*r2*[Pg(k)-Xi(k)]+c3*r3*gi(t)
Wherein c3It is the accelerated factor for regulating fictitious force impact, r3It is independently of r1And r2Equally distributed random number, g in [0,1] is intervaliT () is corresponding and the position vector of particle i distance under fictitious force effect.
A kind of method improving network connectivty based on the particle cluster algorithm of fictitious force guiding when barrier, comprises the following steps that (accompanying drawing 6 is the design sketch after the network optimization):
1. initialize network, the node connected in network is connected cluster.
2. whether the number judged in network bunch is 1, if 1 algorithm terminates.
3. if not the number of clusters 1 in step 2, then the particle cluster algorithm led by fictitious force finds the position that can connect maximum node number in a network, a newly-increased sensor node, forms one new bunch.
4. repeat step 2, until whole network is one complete bunch.

Claims (2)

1. the method improving the network coverage based on the particle cluster algorithm of fictitious force guiding when barrier, what it included specifically comprises the following steps that
(1) pig breeding farm area size a*b is set; The big small-scale N of wireless sensor network, wherein can arrange stationary nodes number is N1, mobile node number is N2; The communication radius R of radio node;
(2) thing wall quantity of placing obstacles is m, as m=4 has been four walls, zone leveling divides quinquepartite, and length of walls acquiescence is identical with zone length;
(3) random distribution node within the scope of given area, and judge whether each node is subject to barrier impact, if there is no impact, keep the initial communication radius R set, otherwise changing communication radius according to the log path loss model of transmission of wireless signals is r (only changing the part receiving impact, the remainder former communication radius of maintenance is constant);
(4) node in wireless sensor network is optimized deployment by the particle cluster algorithm according to fictitious force guiding, the invariant position of stationary nodes, and mobile node changes accordingly, it is achieved improve the network coverage.
2. the method improving network connectivty based on the particle cluster algorithm of fictitious force guiding when barrier, specifically comprises the following steps that
(1) pig breeding farm area size a*b is set; The big small-scale N of wireless sensor network, gives tacit consent to all nodes and is stationary nodes; The communication radius R of radio node;
(2) thing wall quantity of placing obstacles is m, as m=4 has been four walls, zone leveling divides quinquepartite, and length of walls acquiescence is identical with zone length;
(3) random distribution node within the scope of given area, and judge whether each node is subject to barrier impact, if there is no impact, keep the initial communication radius R set, otherwise changing communication radius according to the log path loss model of transmission of wireless signals is r (only changing the part receiving impact, the remainder former communication radius of maintenance is constant);
(4) node that be distributed is connected cluster, find position optimum in regional extent according to the particle cluster algorithm of fictitious force guiding and can connect maximum nodes and become one new bunch, at one new node of this location arrangements;
(5) till repetition step 4 all of node in region is all connected in one bunch.
CN201610035962.XA 2016-01-20 2016-01-20 Method for deploying particle swarm algorithm in wireless sensor network based on virtual force guidance Pending CN105636067A (en)

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CN107396374A (en) * 2017-07-07 2017-11-24 江苏奥斯威尔信息科技有限公司 A kind of covering method based on fictitious force and Thiessen polygon
CN111065103A (en) * 2019-12-11 2020-04-24 哈尔滨工程大学 Multi-objective optimization wireless sensor network node deployment method
CN112911606A (en) * 2021-01-27 2021-06-04 山东省科学院海洋仪器仪表研究所 Sensor node distribution control method applied to underwater sensor network

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CN102625324A (en) * 2012-03-08 2012-08-01 上海大学 Wireless optical fiber sensor network deployment method based on particle swarm optimization
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107396374A (en) * 2017-07-07 2017-11-24 江苏奥斯威尔信息科技有限公司 A kind of covering method based on fictitious force and Thiessen polygon
CN107396374B (en) * 2017-07-07 2020-11-03 江苏奥斯威尔信息科技有限公司 Covering method based on virtual force and Thiessen polygon
CN111065103A (en) * 2019-12-11 2020-04-24 哈尔滨工程大学 Multi-objective optimization wireless sensor network node deployment method
CN111065103B (en) * 2019-12-11 2022-08-02 哈尔滨工程大学 Multi-objective optimization wireless sensor network node deployment method
CN112911606A (en) * 2021-01-27 2021-06-04 山东省科学院海洋仪器仪表研究所 Sensor node distribution control method applied to underwater sensor network

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