CN103997748A - Difference coverage method based on hybrid sensor network - Google Patents

Abstract

The invention provides a difference coverage method based on a hybrid sensor network. According to the difference coverage method, a particle swarm method serves as the basis, a single-target function formed by linear combination obtained by weighting effective coverage rates of a key region and a general region serves as a fitness function, the fitness function is controlled by regulating a weighting coefficient, therefore, mobile nodes of sensors are guided to move close to the key region, and coverage quality of the key region is ensured. In order to increase computing efficiency of the particle swarm method, a fictitious force velocity component is added to guide the mobile nodes to move to the uncovered regions, and the size and the direction of fictitious force are solved by means of a gravitational field applied on the mobile nodes by monitoring points incapable of meeting effective monitoring threshold values in the deployment area. The difference coverage method is applicable to the hybrid sensor network with fixed nodes and the mobile nodes.

Description

A kind of difference covering method based on mixed type sensor network

Technical field

The present invention relates to a kind of difference covering method based on mixed type sensor network.

Background technology

Wireless sensor network is to produce a kind of emerging information gathering and event tracking monitoring technique along with the development of wireless communication technology, embedded technology and microprocessor technology.Sensor node can perception environmental information, simple computation and is sent information and formed a self-organizing multihop network by radio communication device.Due to environmental information, Real-Time Monitoring tracking target event that can remote collection deployment region, its in military battlefield, the aspect such as environmental monitoring forecast, agricultural science and technology, Smart Home, urban transportation demonstrates huge applications and is worth.

Network design is a basic problem in WSN research, and network performance is had to significant impact.Node deployment is applied in the WSN starting stage, is the basis of the key technologies such as Routing Protocol, energy efficiency, data fusion, has important Research Significance.At the severe guarded region of some environmental conditions, as nuclear radiation and chemical substance leakage area, adopt manual type to dispose sensor node and do not possess feasibility.In practice, sensor node is mainly shed by aircraft or other method is deployed in monitored area randomly.For sensor network, a rationally effective node deployment scheme can greatly reduce the networking time, rapid Cover target area, and control all right prolong network lifetime, the topological structure of Adaptive change by coordination.

For guaranteeing the covering quality of network, conventionally by large quantity sensor stationary nodes random placement in target area.But this deployment way can produce bulk redundancy node when promoting network service quality, causes communication contention aware and energy dissipation, shorten network life.And the sensor network environment adaptive faculty based on stationary nodes is poor, can not self-regeneration, once certain node goes wrong, may cause whole network topology structure destroyed.The mobile sensor network being comprised of transducer mobile node can improve coverage rate, optimized network quality by node motion, but transducer mobile node is expensive, has limited its large-scale application.The hybrid sensor network being formed by transducer stationary nodes and transducer mobile node, can repair the covering leak that transducer stationary nodes produces by adjusting the position of transducer mobile node, can on economy and network service quality, average out, there is very large actual application value.

In actual applications, most deployment task need to cover subregion emphasis in monitored area, for example, for the water quality monitoring in coastal waters, compares some unfrequented regions, at sewage draining exit or the more place of pollutant sources, Ship and port place, needs key monitoring.According to the significance level of target area, carry out difference covering, can make full use of limited sensor node resource, improve covering quality and the event monitoring probability of network.

Summary of the invention

The object of the present invention is to provide a kind of difference covering method based on mixed type sensor network, can be in given deployment region A, random placement m transducer stationary nodes and n transducer mobile node, the position of adjustment transducer mobile node, maximizes emphasis monitored area A _hotwith common monitored area ^a _ordinaryefficient Coverage Rate.

For addressing the above problem, the invention provides a kind of difference covering method based on mixed type sensor network, comprising:

Obtain the position of monitoring of environmental, the mode that adopts aircraft to shed is deployed in m transducer stationary nodes and n transducer mobile node in described monitoring of environmental;

Each transducer stationary nodes and transducer mobile node initialization self information be the location, position to own place also, and each transducer stationary nodes and transducer mobile node form network and by network, the information of self No. ID, initial position and sensor performance sent to an aggregation node;

Aggregation node is receiving that each transducer stationary nodes and transducer mobile node adopt after the information such as self ID that the modes such as inundation or directed pathfinding route send number, initial position and sensor performance, obtain the position of described monitoring of environmental, according to the location resolution of described monitoring of environmental, go out whole deployment region A, emphasis monitored area A _hot, general monitored area A _ordinary=A-A _hot, the effective monitoring threshold c in emphasis monitored area _{th_hot}with the effective monitoring threshold c in general monitored area _{th_ordinary}, determine the adjacent suffered fictitious force (potential field power) of transducer mobile node in monitoring point that does not reach coverage criteria in whole deployment region

${\stackrel{\→}{F}}_s^a=-\stackrel{\→}{\▿}{U}^a\left(s\right)=\left(\begin{array}{c}{F}_x\\ F_y\end{array}\right)=\left(\begin{array}{c}\frac{-\∂U^a\left(s\right)}{\∂x_s}\\ \frac{-\∂U^a\left(s\right)}{\∂y_s}\end{array}\right),$

F _xand F _ybe respectively the active force on x axle and y direction of principal axis, s is the position of transducer mobile node,

According to the monitoring capability mathematic(al) representation of transducer mobile node, can obtain $\frac{\∂U^a}{\∂x_s}=\underset{p\∈A_s}{\mathrm{\Σ}}[(x_s-x_p)(\frac{{\mathrm{\α}}_1{\mathrm{\β}}_1{{\mathrm{\λ}}_1}^{{\mathrm{\β}}_1-1}}{{{\mathrm{\λ}}_2}^{{\mathrm{\β}}_2}}+\frac{{\mathrm{\α}}_1{\mathrm{\β}}_2{{\mathrm{\λ}}_1}^{{\mathrm{\β}}_1}}{{{\mathrm{\λ}}_2}^{{\mathrm{\β}}_2+1}})e^{(-{\mathrm{\α}}_1{{\mathrm{\λ}}_1}^{{\mathrm{\β}}_1}/{{\mathrm{\λ}}_2}^{{\mathrm{\β}}_2}+{\mathrm{\α}}_2)}\·\underset{s^{\′}\∈S_{\mathrm{ov}}\backslash \left\{s\right\}}{\mathrm{\Π}}(1-c_p\left(s^{\′}\right))],$ $\frac{\∂U^a}{\∂y_s}=\underset{p\∈A_s}{\mathrm{\Σ}}[(y_s-y_p)(\frac{{\mathrm{\α}}_1{\mathrm{\β}}_1{{\mathrm{\λ}}_1}^{{\mathrm{\β}}_1-1}}{{{\mathrm{\λ}}_2}^{{\mathrm{\β}}_2}}+\frac{{\mathrm{\α}}_1{\mathrm{\β}}_2{{\mathrm{\λ}}_1}^{{\mathrm{\β}}_1}}{{{\mathrm{\λ}}_2}^{{\mathrm{\β}}_2+1}})e^{(-{\mathrm{\α}}_1{{\mathrm{\λ}}_1}^{{\mathrm{\β}}_1}/{{\mathrm{\λ}}_2}^{{\mathrm{\β}}_2}+{\mathrm{\α}}_2)}\·\underset{s^{\′}\∈S_{\mathrm{ov}}\backslash \left\{s\right\}}{\mathrm{\Π}}(1-c_p\left(s^{\′}\right))],$

P is the monitoring point in deployment region A, A _sfor transducer mobile node r-r _eto r+r _ein sensing range, do not reach the set A of the monitoring point of coverage criteria _s=A _{s_hot}∪ A _{s_ordinary}, wherein $A_{s\_\mathrm{hot}}=\{\&ForAll;p\&Element;A_{\mathrm{hot}}|c_p\left(S_{\mathrm{ov}}\right)<c_{\mathrm{th}\_\mathrm{hot}}\mathrm{and}|d(s_i,p)-r|\&le;r_e\},$ $A_{s\_\mathrm{ordinary}}=\{\&ForAll;p\&Element;A_{\mathrm{ordinary}}|c_p\left(S_{\mathrm{ov}}\right)<c_{\mathrm{th}\_\mathrm{ordinary}}\mathrm{and}|d(s_i,p)-r|\&le;r_e\},$

R _e(0 < r _e< r) be the measurement dependability parameter of transducer mobile node,

Wherein, the monitoring point that does not reach coverage criteria in deployment region A is to a gravitational field of adjacent sensors mobile node generation a is deployment region, c _p/sfor being placed on a s, transducer mobile node is in the combined measurement probability that monitoring point p produces

Transducer stationary nodes and transducer mobile node S set in deployment region A _ovrepresent certain transducer stationary nodes or transducer mobile node s _iworld coordinates be (x _i, y _i), in deployment region A, the coordinate of p monitoring point is (x _p, y _p), monitoring point p and s _idistance and in actual applications, owing to being subject to the impact of the factors such as environment, transducer self technique, the sensor model of transducer stationary nodes and transducer mobile node is certain probability distribution, monitoring probability is along with apart from d (s _i, p) successively decreasing, the monitoring capability mathematic(al) representation of transducer stationary nodes or transducer mobile node is:

$c_p\left(s_i\right)={\begin{array}{ccc}1& \mathrm{ifd}\left(s_{i}p\right)\&le;r-r_e& \\ e^{(-{\mathrm{\&alpha;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}\backslash {{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}+{\mathrm{\&alpha;}}_2)}& \mathrm{if}|d(s_i,p)-r|\&le;r_e& \\ 0& \mathrm{other}& \end{array}$

Wherein, r is the sensor senses radius of transducer stationary nodes or transducer mobile node, r _e(0 < r _e< r) be the measurement dependability parameter of transducer stationary nodes or transducer mobile node, α ₁, α ₂, β ₁, β ₂be and the parameter of sensor measurement probability correlation, this parameter is relevant with the measurement characteristics of sensing node, λ ₁and λ ₂for input parameter λ ₁=r _e-r+d (s _i, p), λ ₂=r _e+ r-d (s _i, p), if monitoring point p is at transducer stationary nodes or transducer mobile node s _isensing range in, i.e. d (s _i, p)≤(r+r _e), transducer stationary nodes or transducer mobile node s _ifor adjacent sensors stationary nodes or the adjacent sensors mobile node of monitoring point p, in deployment region A the combined measurement probability of monitoring point p be in deployment region A monitoring point p adjacent sensors stationary nodes and adjacent sensors mobile node at the combined measurement probability of this monitoring point p:

$c_p\left(S_{\mathrm{ov}}\right)=1-\underset{s_i\&Element;V_p}{\mathrm{\&Pi;}}(1-c_p\left(s_i\right)),$

V _pfor the set of monitoring point p adjacent sensors stationary nodes and adjacent sensors mobile node, c _thfor effectively measuring probability threshold value, if c _p(S _ov)>=c _th, monitoring point p is effectively covered by transducer stationary nodes and transducer mobile node;

Network for containing m transducer stationary nodes and n transducer mobile node, is abstracted into the particle in particle swarm optimization by the position coordinates of n transducer mobile node, particle search space dimensionality N=2n, the position vector X of particle i _i=(x _i1, x _i2..., x _in, y _i1, y _i2..., y _in), x wherein _ij, y _ijrepresent respectively the transverse and longitudinal coordinate of j transducer mobile node, 1<j<n, using the formed single-goal function of linear combination after the Efficient Coverage Rate weighting of key area and general area as adaptive value function f (X _i(t))=α * f _hot(X _i(t) * f)+(1-α) _ordinary(X _i(t)), wherein, f _hot(X _i) and f (t) _ordinary(X _i(t)) represent respectively the Efficient Coverage Rate of emphasis monitored area and common monitored area, α is the weight coefficient definite according to emphasis monitored area;

Determine the flying speed of particle, the flying speed of particle is determined by following formula:

Vi _j(t+1)=w (t) * v _ij(t)+c ₁r _1j(t) * (p _ij(t)-x _ij(t))+c ₂r _2j(t) * (p _gj(t)-x _ij(t))+c ₃r _3j(t) g _ij(t), wherein, c ₁for local optimum weight factor, c ₂for global optimization weight factor, c ₃for potential field power accelerated factor, r _1j, r _2jand r _3jfor the independent random number in [0,1] scope, corresponding i the particle of subscript i, the j dimension of the corresponding particle of subscript j, w is the affect inertial factor of past value on present value, conventionally gets 0.9～0.4, in iterative process, successively successively decrease, gi _jthe distance of j dimension element under the effect of potential field power in the position vector of corresponding particle i, as shown in the formula: $g_{\mathrm{ij}}\left(t\right)=\{\begin{array}{cc}\frac{F_x^{(i,j)}}{F_{\mathrm{xy}}^{(i,j)}}\&times;\mathrm{MaxStep}\&times;e^{1/F_{\mathrm{xy}}^{(i,j)}},& j=\mathrm{1,2}\&CenterDot;\&CenterDot;\&CenterDot;,n\\ \frac{F_y^{(i,j-n)}}{F_{\mathrm{xy}}^{(i,j-n)}}\&times;\mathrm{MaxStep}\&times;e^{1/F_{\mathrm{xy}}^{(i,j-n)}}& j=n+1,n+2,\&CenterDot;\&CenterDot;\&CenterDot;2n\end{array},$

Wherein, be the potential field power in the x direction that in i particle, j mobile node is subject to, be the potential field power in the y direction that in i particle, j mobile node is subject to,

According to the flying speed particle of particle, x is upgraded in the position of particle _ij(t+1)=x _ij(t)+v _ij(t+1), by adaptive value function f (X described in the position substitution of the particle after upgrading _i(t)), evaluate the locally optimal solution that decides particle $P_i(t+1)=\left\{\begin{array}{cc}{P}_i\left(t\right)& \mathrm{iff}\left(X_i(t+1)\right)<f\left(P_i\left(t\right)\right)\\ X_i(t+1)& \mathrm{iff}\left(X_i(t+1)\right)\&GreaterEqual;f\left(P_i\left(t\right)\right)\end{array}\right.,$ Then obtain the overall optimum position P of particle experience in colony _g(t)=max{f (P ₁(t)), f (P ₂(t)) ..., f (P _m(t)) }, according to described adaptive value function and locally optimal solution, overall optimum position is iterated, until reach default maximum iteration time, finally obtain optimal solution P _g;

Aggregation node is by optimal solution P _gpackaging broadcast is gone out, and transducer mobile node is resolved P after receiving packet _gto obtain the target location of this transducer mobile node, this transducer mobile node moves to described target location.

Further, in said method, each transducer stationary nodes and transducer mobile node form in the step of network, and each transducer stationary nodes and transducer mobile node adopt the mode of inundation or directed pathfinding route to form network.

Further, in said method, each transducer stationary nodes and transducer mobile node all have the ability of Information Monitoring, calculating and deal with data, transmission or receipt message and location, and transducer mobile node also has locomotivity.

Further, in said method, the information of described sensor performance comprises sensor senses radius r and sensor senses model parameter.

Further, in said method, transducer mobile node is resolved after receiving packet ^pg to be to obtain in the step of target location of this transducer mobile node,

For i transducer mobile node, its target location is (x _i, y _i)=(P _g(i), P _g(i+n)).

Compared with prior art, the present invention is by take particle swarm optimization as basis, using the formed single-goal function of linear combination after the Efficient Coverage Rate weighting of key area and general area as adaptive value function, by regulating weight coefficient, control adaptive value function, add fictitious force velocity component to guide mobile node to move to uncovered area, the gravitational field that the size and Orientation of fictitious force is applied to mobile node according to the monitoring point that does not meet effective monitoring threshold in deployment region is tried to achieve, and tool has the following advantages:

(1) coverage effect is good: according to the demand of monitoring task, adopt difference deployment strategy, guaranteed the covering quality of emphasis monitored area.

(2) fast convergence rate: more add potential field power velocity component in new formula in particle rapidity, can effectively instruct transducer mobile node not move to meeting overlay area, thereby accelerate algorithm the convergence speed.

(3) parameters is few: the present invention only need, on traditional particle group optimizing method, additionally arrange position, emphasis monitored area and its effective covering monitoring threshold and tri-parameters of weight coefficient α and just can realize difference deployment to monitoring environment.

(4) widely applicable: what the present invention considered is a kind of mixed type sensor network coverage method, is applicable in the network of different sensors stationary nodes and mobile node ratio.

Accompanying drawing explanation

Fig. 1 is the Wireless Sensor Network Structure figure of one embodiment of the invention;

Fig. 2 is the flow chart of the aggregation node calculating sensor mobile node target location of one embodiment of the invention;

Fig. 3 is initialization random placement transducer stationary nodes and the transducer mobile node distribution map of one embodiment of the invention;

Fig. 4 be the emphasis monitored area of one embodiment of the invention when deployment region center, nodes distribution map after overweight deployment;

Fig. 5 is that figure is moved in the position of emphasis monitored area transducer mobile node when center of one embodiment of the invention;

Fig. 6 be the emphasis monitored area of one embodiment of the invention when the deployment region lower left corner, nodes distribution map after overweight deployment;

Fig. 7 is that figure is moved in the position of emphasis monitored area transducer mobile node when the deployment region lower left corner of one embodiment of the invention.

Embodiment

For above-mentioned purpose of the present invention, feature and advantage can be become apparent more, below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.

As shown in Fig. 1～2, the invention provides the difference covering method based on mixed type sensor network, described method comprises:

Step S1, the position that obtains monitoring of environmental, the mode that adopts aircraft to shed is deployed in transducer stationary nodes and transducer mobile node in described monitoring of environmental; Concrete, in actual applications, most deployment task need to carry out non-homogeneous covering to monitored area, for example, for the water quality monitoring in coastal waters, compare some unfrequented regions, at sewage draining exit or the more place of pollutant sources, Ship and port place, need key monitoring, therefore, technical problem to be solved by this invention is: in given deployment region A as shown in Figure 1, random placement m transducer stationary nodes and n transducer mobile node, adjust the position of transducer mobile node, maximize emphasis monitored area A _hotwith common monitored area A _ordinaryefficient Coverage Rate, in Fig. 1, stationary nodes and mobile node form a clustering architecture as ordinary node, by bunch between multi-hop contribute information data send poly-node to; ;

Step S2, each transducer stationary nodes and transducer mobile node initialization self information be the location, position to own place also, and each transducer stationary nodes and transducer mobile node adopt the modes such as inundation or directed pathfinding route to form network and by network, the information such as self No. ID, initial position and sensor performance sent to and converge (Sink) node; Wherein, each transducer stationary nodes and transducer mobile node all have the ability of Information Monitoring, calculating and deal with data, transmission or receipt message and location, transducer mobile node is except possessing all functions of transducer stationary nodes, also have certain locomotivity, described sensor performance comprises sensor senses radius r and sensor senses model parameter;

Step S3, aggregation node is receiving that each transducer stationary nodes and transducer mobile node adopt after the information such as self ID that the modes such as inundation or directed pathfinding route send number, initial position and sensor performance, obtain the position of described monitoring of environmental, according to the location resolution of described monitoring of environmental, go out whole deployment region A, emphasis monitored area A _hot, general monitored area A _ordinary=A-A _hot, the effective monitoring threshold c in emphasis monitored area _{th_hot}with the effective monitoring threshold c in general monitored area _{th_ordinary}, determine the adjacent suffered fictitious force (potential field power) of transducer mobile node in monitoring point that does not reach coverage criteria in whole deployment region

${\stackrel{\&RightArrow;}{F}}_s^a=-\stackrel{\&RightArrow;}{\&dtri;}{U}^a\left(s\right)=\left(\begin{array}{c}{F}_x\\ F_y\end{array}\right)=\left(\begin{array}{c}\frac{-\&PartialD;U^a\left(s\right)}{\&PartialD;x_s}\\ \frac{-\&PartialD;U^a\left(s\right)}{\&PartialD;y_s}\end{array}\right),$

F _xand F _ybe respectively the active force on x axle and y direction of principal axis, s is the position of transducer mobile node,

According to the monitoring capability mathematic(al) representation of transducer mobile node, can obtain $\frac{\&PartialD;U^a}{\&PartialD;x_s}=\underset{p\&Element;A_s}{\mathrm{\&Sigma;}}[(x_s-x_p)(\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1-1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}}+\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_2{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2+1}})e^{(-{\mathrm{\&alpha;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}/{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}+{\mathrm{\&alpha;}}_2)}\&CenterDot;\underset{s^{\&prime;}\&Element;S_{\mathrm{ov}}\backslash \left\{s\right\}}{\mathrm{\&Pi;}}(1-c_p\left(s^{\&prime;}\right))],$ $\frac{\&PartialD;U^a}{\&PartialD;y_s}=\underset{p\&Element;A_s}{\mathrm{\&Sigma;}}[(y_s-y_p)(\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1-1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}}+\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_2{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2+1}})e^{(-{\mathrm{\&alpha;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}/{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}+{\mathrm{\&alpha;}}_2)}\&CenterDot;\underset{s^{\&prime;}\&Element;S_{\mathrm{ov}}\backslash \left\{s\right\}}{\mathrm{\&Pi;}}(1-c_p\left(s^{\&prime;}\right))],$

P is the monitoring point in deployment region A, A _sfor transducer mobile node r-r _eto r+r _ein sensing range, do not reach the set A of the monitoring point of coverage criteria _s=A _{s_hot}∪ A _{s_ordinary}wherein $A_{s\_\mathrm{hot}}=\{\&ForAll;p\&Element;A_{\mathrm{hot}}|c_p\left(S_{\mathrm{ov}}\right)<c_{\mathrm{th}\_\mathrm{hot}}\mathrm{and}|d(s_i,p)-r|\&le;r_e\},$ $A_{s\_\mathrm{ordinary}}=\{\&ForAll;p\&Element;A_{\mathrm{ordinary}}|c_p\left(S_{\mathrm{ov}}\right)<c_{\mathrm{th}\_\mathrm{ordinary}}\mathrm{and}|d(s_i,p)-r|\&le;r_e\},$

R _e(0 < r _e< r) be the measurement dependability parameter of transducer mobile node,

Wherein, the monitoring point that does not reach coverage criteria in deployment region A is to a gravitational field of adjacent sensors mobile node generation a is deployment region, and cp/s is that transducer mobile node is placed on the combined measurement probability that a s is in monitoring point p generation

Transducer stationary nodes and transducer mobile node S set in deployment region A _ovrepresent certain transducer stationary nodes or transducer mobile node s _iworld coordinates be (x _i, y _i), in deployment region A, the coordinate of p monitoring point is (x _p, y _p), monitoring point p and s _idistance and in actual applications, owing to being subject to the impact of the factors such as environment, transducer self technique, the sensor model of transducer stationary nodes and transducer mobile node is certain probability distribution, monitoring probability is along with apart from d (s _i, p) successively decreasing, the monitoring capability mathematic(al) representation of transducer stationary nodes or transducer mobile node is:

$c_p\left(s_i\right)={\begin{array}{ccc}1& \mathrm{ifd}\left(s_{i}p\right)\&le;r-r_e& \\ e^{(-{\mathrm{\&alpha;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}\backslash {{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}+{\mathrm{\&alpha;}}_2)}& \mathrm{if}|d(s_i,p)-r|\&le;r_e& \\ 0& \mathrm{other}& \end{array}$

Wherein, r is the sensor senses radius of transducer stationary nodes or transducer mobile node, r _e(0 < r _e< r) be the measurement dependability parameter of transducer stationary nodes or transducer mobile node, α ₁, α ₂, β ₁, β ₂be and the parameter of sensor measurement probability correlation, this parameter is relevant with the measurement characteristics of sensing node, λ ₁and λ ₂for input parameter λ ₁=r _e-r+d (s _i, p), λ ₂=r _e+ r-d (s _i, p), if monitoring point p is at transducer stationary nodes or transducer mobile node s _isensing range in, i.e. d (s _i, p)≤(r+r _e), transducer stationary nodes or transducer mobile node s _ifor adjacent sensors stationary nodes or the adjacent sensors mobile node of monitoring point p, in deployment region A the combined measurement probability of monitoring point p be in deployment region A monitoring point p adjacent sensors stationary nodes and adjacent sensors mobile node at the combined measurement probability of this monitoring point p:

$c_p\left(S_{\mathrm{ov}}\right)=1-\underset{s_i\&Element;V_p}{\mathrm{\&Pi;}}(1-c_p\left(s_i\right)),$

V _pfor the set of monitoring point p adjacent sensors stationary nodes and adjacent sensors mobile node, c _thfor effectively measuring probability threshold value, if c _p(S _ov)>=c _th, monitoring point p is effectively covered by transducer stationary nodes and transducer mobile node; Concrete, for realizing difference overlay strategy, emphasis monitored area scope A is set here _hot, general monitored area scope A _ordinary=A-A _hot, the quality monitoring of assurance emphasis monitored area;

Step S4, aggregation node is after knowing the positional information of all the sensors stationary nodes and transducer mobile node, according to covering mission requirements, dynamically adjust the position of transducer mobile node: for the mixed type sensor network that contains m transducer stationary nodes and n transducer mobile node, the position coordinates of n transducer mobile node is abstracted into the particle in population (PSO) method, particle search space dimensionality N=2n, the position vector X of particle i _i=(x _i1, x _i2..., x _in, _yi1, _yi2..., _yin), xi wherein _j, yi _jrepresent respectively the transverse and longitudinal coordinate of j transducer mobile node, 1<j<n, using the formed single-goal function of linear combination after the Efficient Coverage Rate weighting of key area and general area as adaptive value function f (X _i(t))=α * f _hot(X _i(t) * f)+(1-α) _ordinary(X _i(t)), f wherein _hot(X _i) and f (t) _ordinary(X _i(t)) represent respectively the Efficient Coverage Rate of emphasis monitored area and common monitored area, α is the weight coefficient definite according to emphasis monitored area; Can be by regulating weight coefficient control adaptive value function in this step, thus guiding sensor mobile node to key area, gather, guarantee the covering quality of key area;

Step S5, determines the flying speed of particle, and the flying speed of particle is determined by following formula:

V _ij(t+1)=w (t) * v _ij(t)+c ₁r _1j(t) * (p _ij(t)-x _ij(t))+c ₂r _2j(t) * (p _gj(t)-x _ij(t))+c ₃r _3j(t) g _ij(t), wherein, c ₁for local optimum weight factor, c ₂for global optimization weight factor, c ₃for potential field power accelerated factor, r _1j, r _2jand r _3jfor the independent random number in [0,1] scope, corresponding i the particle of subscript i, the j dimension of the corresponding particle of subscript j, w is the affect inertial factor of past value on present value, conventionally gets 0.9～0.4, in iterative process, successively successively decrease, g _ijthe distance of j dimension element under the effect of potential field power in the position vector of corresponding particle i, as shown in the formula: $g_{\mathrm{ij}}\left(t\right)=\{\begin{array}{cc}\frac{F_x^{(i,j)}}{F_{\mathrm{xy}}^{(i,j)}}\&times;\mathrm{MaxStep}\&times;e^{1/F_{\mathrm{xy}}^{(i,j)}},& j=\mathrm{1,2}\&CenterDot;\&CenterDot;\&CenterDot;,n\\ \frac{F_y^{(i,j-n)}}{F_{\mathrm{xy}}^{(i,j-n)}}\&times;\mathrm{MaxStep}\&times;e^{1/F_{\mathrm{xy}}^{(i,j-n)}}& j=n+1,n+2,\&CenterDot;\&CenterDot;\&CenterDot;2n\end{array},$

Wherein, be the potential field power in the x direction that in i particle, j mobile node is subject to, be the potential field power in the y direction that in i particle, j mobile node is subject to, concrete, speed in population (PSO) method in this step more adds the velocity component of fictitious force to come guiding sensor mobile node to move to uncovered area in new formula, thereby accelerate mobile efficiency, the gravitational field that the size and Orientation of fictitious force is applied to adjacent sensors mobile node according to the monitoring point that does not meet effective monitoring threshold in deployment region is tried to achieve;

Step S6, upgrades x according to the flying speed particle of particle to the position of particle _ij(t+1)=x _ij(t)+v _ij(t+1), by adaptive value function f (X described in the position substitution of the particle after upgrading _i(t)), evaluate the locally optimal solution that decides particle $P_i(t+1)=\left\{\begin{array}{cc}{P}_i\left(t\right)& \mathrm{iff}\left(X_i(t+1)\right)<f\left(P_i\left(t\right)\right)\\ X_i(t+1)& \mathrm{iff}\left(X_i(t+1)\right)\&GreaterEqual;f\left(P_i\left(t\right)\right)\end{array}\right.,$ Then obtain the overall optimum position P of particle experience in colony _g(t)=max{f (P ₁(t)), f (P ₂(t)) ..., f (P _m(t)) }, according to described adaptive value function and locally optimal solution, overall optimum position is iterated, until reach default maximum iteration time, finally obtain optimal solution P _g; Concrete, the principle of step S3～step S6 can be referring to Fig. 2;

Step S7, aggregation node is by optimal solution P _gpackaging broadcast is gone out, and transducer mobile node is resolved P after receiving packet _gto obtain the target location of this transducer mobile node, this transducer mobile node moves to described target location.Concrete, for i transducer mobile node, its target location is (x _i, y _i)=(P _g(i), P _g(i+n)).

Below in conjunction with accompanying drawing explanation, the present invention is further elaborated.Specifically be implemented as follows:

Scene one: as shown in Fig. 3～5, user determines the position of monitoring of environmental according to mission requirements, adopt 60 transducer mobile nodes of mode that aircraft sheds and 40 transducer stationary nodes to be randomly dispersed in 200 * 200 region, the square area of position 100 * 100 centered by emphasis monitored area.In Fig. 3, transducer stationary nodes represents with " * ", ". " expression for transducer mobile node.Transducer stationary nodes and transducer mobile node all comprise sensor assembly, processor module, wireless communication module and four parts of locating module, wherein, processor module is connected with sensor assembly, wireless communication module and locating module respectively, sensor assembly has the function of Information Monitoring, processor module has the function of calculating and deal with data, and wireless communication module has the function of transmission or receipt message, and locating module has the function of location.Transducer mobile node also contains in addition the mobile module being connected with described processor module and has mobile function, can after receiving the information that Sink sends, to target location, advance, the identical r=14m of perception radius of transducer stationary nodes and transducer mobile node, measures dependability parameter r _e=7m, other parameter alpha ₁=1, α ₂=0, β ₁=1, β ₂=1.5.

Each transducer stationary nodes and transducer mobile node are opened locating module and are determined own position in monitored area after disposing.Then transducer stationary nodes and transducer mobile node are opened wireless sending module, and the mode that adopts inundation or directed routing becomes a packet to send to a Sink node Information encapsulations such as self No. ID, position and sensor performance.

Sink node receives after the packet of all nodes in network, the node ID number in resolution data bag, position and sensor characteristics information.Then the message that Sink node sends according to client, parses whole deployment region A, emphasis monitored area A _hot, the effective monitoring threshold c in emphasis monitored area _{th_hot}with the effective monitoring threshold c in general monitored area _{th_ordinary}.The relevant parameters such as maximum iteration time and weight coefficient are set afterwards.After setting completes, by the position of transducer mobile node, the target location of calculating sensor mobile node in the information substitution formula such as sensor characteristics.Iterate, until meet end condition, finally obtain optimal solution P _g.Parameter configuration is as follows:

At Sink node, obtain optimal solution P _gafter, be translated into transducer mobile node target location.For i transducer mobile node, its target location is (x _i, y _i)=(P _g(i), P _g(i+n)).Sink node is packaged into a packet by No. ID of each transducer mobile node with target location, then by the mode of broadcast, by Packet Generation, gives each transducer mobile node.Transducer mobile node, after receiving the packet of broadcast, carries out inner bag and processes and obtain the target location of self, and coordinates self locating module to determine direction and the displacement of target location.At transducer mobile node, in the moving process of target location, can arrive at target location by sensor assembly disturbance of perception thing and with optimal path cut-through thing.Fig. 3 is initialization node distribution map, Fig. 4 and Fig. 5 are respectively node distribution map and the modal displacement figure of scene one after optimizing, wherein, emphasis monitored area is when deployment region center, after overweight deployment, nodes distributes as shown in Figure 4, move as shown in Figure 5 the position of emphasis monitored area transducer mobile node when center, transducer mobile node moves to " o " from position ". " and locates, 100 * 100 the square area that dotted line frame the surrounds monitored area of attaching most importance to.

Two: 60 transducer mobile nodes of scene and 40 transducer stationary nodes are randomly dispersed in 200 * 200 region, and emphasis monitored area is the square area of position, the lower left corner 100 * 100, and weight parameter is got α=0.4.All the other parameters arrange same scene one.Fig. 3 is initialization node distribution map, Fig. 6 and Fig. 7 are respectively node distribution map and the modal displacement figure of scene two after optimizing, wherein, emphasis monitored area is when the deployment region lower left corner, after overweight deployment, nodes distributes as shown in Figure 6, move as shown in Figure 7 the position of emphasis monitored area transducer mobile node when the deployment region lower left corner, and transducer mobile node moves to " o " from position ". " and locates.100 * 100 the square area that dotted line frame the surrounds monitored area of attaching most importance to.

In this specification, each embodiment adopts the mode of going forward one by one to describe, and each embodiment stresses is the difference with other embodiment, between each embodiment identical similar part mutually referring to.For the disclosed system of embodiment, owing to corresponding to the method disclosed in Example, so description is fairly simple, relevant part partly illustrates referring to method.

Professional can also further recognize, unit and the method step of each example of describing in conjunction with embodiment disclosed herein, can realize with electronic hardware, computer software or the combination of the two, for the interchangeability of hardware and software is clearly described, composition and the step of each example described according to function in the above description in general manner.These functions are carried out with hardware or software mode actually, depend on application-specific and the design constraint of technical scheme.Professional and technical personnel can specifically should be used for realizing described function with distinct methods to each, but this realization should not thought and exceeds scope of the present invention.

Obviously, those skilled in the art can carry out various changes and modification and not depart from the spirit and scope of the present invention invention.Like this, if within of the present invention these are revised and modification belongs to the scope of the claims in the present invention and equivalent technologies thereof, the present invention is also intended to comprise these change and modification.

Claims (5)

1. the difference covering method based on mixed type sensor network, is characterized in that, comprising:

Obtain the position of monitoring of environmental, the mode that adopts aircraft to shed is deployed in m transducer stationary nodes and n transducer mobile node in described monitoring of environmental;

Each transducer stationary nodes and transducer mobile node initialization self information be the location, position to own place also, and each transducer stationary nodes and transducer mobile node form network and by network, the information of self No. ID, initial position and sensor performance sent to an aggregation node;

Aggregation node is receiving that each transducer stationary nodes and transducer mobile node adopt after the information such as self ID that the modes such as inundation or directed pathfinding route send number, initial position and sensor performance, obtain the position of described monitoring of environmental, according to the location resolution of described monitoring of environmental, go out whole deployment region A, emphasis monitored area A _hot, general monitored area A _ordinary=A-A _hot, the effective monitoring threshold c in emphasis monitored area _{th_hot}with the effective monitoring threshold c in general monitored area _{th_ordinary}, determine the adjacent suffered fictitious force of transducer mobile node in monitoring point that does not reach coverage criteria in whole deployment region

F _xand F _ybe respectively the active force on x axle and y direction of principal axis, s is the position of transducer mobile node,

According to the monitoring capability mathematic(al) representation of transducer mobile node, can obtain $\frac{\&PartialD;U^a}{\&PartialD;x_s}=\underset{p\&Element;A_s}{\mathrm{\&Sigma;}}[(x_s-x_p)(\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1-1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}}+\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_2{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2+1}})e^{(-{\mathrm{\&alpha;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}/{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}+{\mathrm{\&alpha;}}_2)}\&CenterDot;\underset{s^{\&prime;}\&Element;S_{\mathrm{ov}}\backslash \left\{s\right\}}{\mathrm{\&Pi;}}(1-c_p\left(s^{\&prime;}\right))],$ $\frac{\&PartialD;U^a}{\&PartialD;y_s}=\underset{p\&Element;A_s}{\mathrm{\&Sigma;}}[(y_s-y_p)(\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1-1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}}+\frac{{\mathrm{\&alpha;}}_1{\mathrm{\&beta;}}_2{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}}{{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2+1}})e^{(-{\mathrm{\&alpha;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}/{{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}+{\mathrm{\&alpha;}}_2)}\&CenterDot;\underset{s^{\&prime;}\&Element;S_{\mathrm{ov}}\backslash \left\{s\right\}}{\mathrm{\&Pi;}}(1-c_p\left(s^{\&prime;}\right))],$

P is the monitoring point in deployment region A, A _sfor transducer mobile node r-r _eto r+r _ein sensing range, do not reach the set A of the monitoring point of coverage criteria _s=A _{s_hot}∪ A _{s_ordinary}, wherein $A_{s\_\mathrm{hot}}=\{\&ForAll;p\&Element;A_{\mathrm{hot}}|c_p\left(S_{\mathrm{ov}}\right)<c_{\mathrm{th}\_\mathrm{hot}}\mathrm{and}|d(s_i,p)-r|\&le;r_e\},$ $A_{s\_\mathrm{ordinary}}=\{\&ForAll;p\&Element;A_{\mathrm{ordinary}}|c_p\left(S_{\mathrm{ov}}\right)<c_{\mathrm{th}\_\mathrm{ordinary}}\mathrm{and}|d(s_i,p)-r|\&le;r_e\},$

R _e(0 < r _e< r) be the measurement dependability parameter of transducer mobile node,

Wherein, the monitoring point that does not reach coverage criteria in deployment region A is to a gravitational field of adjacent sensors mobile node generation a is deployment region, c _p/sfor being placed on a s, transducer mobile node is in the combined measurement probability that monitoring point p produces

Transducer stationary nodes and transducer mobile node S set in deployment region A _ovrepresent certain transducer stationary nodes or transducer mobile node s _iworld coordinates be (x _i, y _i), in deployment region A, the coordinate of p monitoring point is (x _p, y _p), monitoring point p and s _idistance and in actual applications, owing to being subject to the impact of the factors such as environment, transducer self technique, the sensor model of transducer stationary nodes and transducer mobile node is certain probability distribution, monitoring probability is along with apart from d (s _i, p) successively decreasing, the monitoring capability mathematic(al) representation of transducer stationary nodes or transducer mobile node is:

$c_p\left(s_i\right)={\begin{array}{ccc}1& \mathrm{ifd}\left(s_{i}p\right)\&le;r-r_e& \\ e^{(-{\mathrm{\&alpha;}}_1{{\mathrm{\&lambda;}}_1}^{{\mathrm{\&beta;}}_1}\backslash {{\mathrm{\&lambda;}}_2}^{{\mathrm{\&beta;}}_2}+{\mathrm{\&alpha;}}_2)}& \mathrm{if}|d(s_i,p)-r|\&le;r_e& \\ 0& \mathrm{other}& \end{array}$

Wherein, r is the sensor senses radius of transducer stationary nodes or transducer mobile node, r _e(0 < r _e< r) be the measurement dependability parameter of transducer stationary nodes or transducer mobile node, α ₁, α ₂, β ₁, β ₂be and the parameter of sensor measurement probability correlation, this parameter is relevant with the measurement characteristics of sensing node, λ ₁and λ ₂for input parameter λ ₁=r _e-r+d (s _i, p), λ ₂=r _e+ r-d (s _i, p), if monitoring point p is at transducer stationary nodes or transducer mobile node s _isensing range in, i.e. d (s _i, p)≤(r+r _e), transducer stationary nodes or transducer mobile node s _ifor adjacent sensors stationary nodes or the adjacent sensors mobile node of monitoring point p, in deployment region A the combined measurement probability of monitoring point p be in deployment region A monitoring point p adjacent sensors stationary nodes and adjacent sensors mobile node at the combined measurement probability of this monitoring point p:

$c_p\left(S_{\mathrm{ov}}\right)=1-\underset{s_i\&Element;V_p}{\mathrm{\&Pi;}}(1-c_p\left(s_i\right)),$

V _pfor the set of monitoring point p adjacent sensors stationary nodes and adjacent sensors mobile node, c _thfor effectively measuring probability threshold value, if c _p(S _ov)>=c _th, monitoring point p is effectively covered by transducer stationary nodes and transducer mobile node;

Network for containing m transducer stationary nodes and n transducer mobile node, is abstracted into the particle in particle swarm optimization by the position coordinates of n transducer mobile node, particle search space dimensionality N=2n, the position vector X of particle i _i=(x _i1, x _i2..., x _in, y _i1, y _i2..., y _in), x wherein _ij, y _ijrepresent respectively the transverse and longitudinal coordinate of j transducer mobile node, 1<j<n, using the formed single-goal function of linear combination after the Efficient Coverage Rate weighting of key area and general area as adaptive value function f (X _i(t))=α * f _hot(X _i(t) * f)+(1-α) _ordinary(X _i(t)), wherein, f _hot(X _i) and f (t) _ordinary(X _i(t)) represent respectively the Efficient Coverage Rate of emphasis monitored area and common monitored area, α is the weight coefficient definite according to emphasis monitored area;

By following formula, determine the flying speed of particle:

V _ij(t+1)=w (t) * v _ij(t)+c ₁r _1j(t) * (p _ij(t)-x _ij(t))+c ₂r _2j(t) * (p _gj(t)-x _ij(t))+c ₃r _3j(t) g _ij(t), wherein, c ₁for local optimum weight factor, c ₂for global optimization weight factor, c ₃for potential field power accelerated factor, r _1j, r _2jand r _3jfor the independent random number in [0,1] scope, corresponding i the particle of subscript i, the j dimension of the corresponding particle of subscript j, w is the affect inertial factor of past value on present value, conventionally gets 0.9～0.4, in iterative process, successively successively decrease, g _ijthe distance of j dimension element under the effect of potential field power in the position vector of corresponding particle i, as shown in the formula: $g_{\mathrm{ij}}\left(t\right)=\{\begin{array}{cc}\frac{F_x^{(i,j)}}{F_{\mathrm{xy}}^{(i,j)}}\&times;\mathrm{MaxStep}\&times;e^{1/F_{\mathrm{xy}}^{(i,j)}},& j=\mathrm{1,2}\&CenterDot;\&CenterDot;\&CenterDot;,n\\ \frac{F_y^{(i,j-n)}}{F_{\mathrm{xy}}^{(i,j-n)}}\&times;\mathrm{MaxStep}\&times;e^{1/F_{\mathrm{xy}}^{(i,j-n)}}& j=n+1,n+2,\&CenterDot;\&CenterDot;\&CenterDot;2n\end{array},$

Wherein, be the potential field power in the x direction that in i particle, j mobile node is subject to, be the potential field power in the y direction that in i particle, j mobile node is subject to,

According to the flying speed particle of particle, x is upgraded in the position of particle _ij(t+1)=x _ij(t)+v _ij(t+1), by adaptive value function f (X described in the position substitution of the particle after upgrading _i(t)), evaluate the locally optimal solution that decides particle $P_i(t+1)=\left\{\begin{array}{cc}{P}_i\left(t\right)& \mathrm{iff}\left(X_i(t+1)\right)<f\left(P_i\left(t\right)\right)\\ X_i(t+1)& \mathrm{iff}\left(X_i(t+1)\right)\&GreaterEqual;f\left(P_i\left(t\right)\right)\end{array}\right.,$ Then obtain the overall optimum position P of particle experience in colony _g(t)=max{f (P ₁(t)), f (P ₂(t)) ..., f (P _m(t)) }, according to described adaptive value function and locally optimal solution, overall optimum position is iterated, until reach default maximum iteration time, finally obtain optimal solution P _g;

Aggregation node is by optimal solution P _gpackaging broadcast is gone out, and transducer mobile node is resolved P after receiving packet _gto obtain the target location of this transducer mobile node, this transducer mobile node moves to described target location.

2. the difference covering method based on mixed type sensor network as claimed in claim 1, it is characterized in that, each transducer stationary nodes and transducer mobile node form in the step of network, and each transducer stationary nodes and transducer mobile node adopt the mode of inundation or directed pathfinding route to form network.

3. the difference covering method based on mixed type sensor network as claimed in claim 1, it is characterized in that, each transducer stationary nodes and transducer mobile node all have the ability of Information Monitoring, calculating and deal with data, transmission or receipt message and location, and transducer mobile node also has locomotivity.

4. the difference covering method based on mixed type sensor network as claimed in claim 1, is characterized in that, the information of described sensor performance comprises sensor senses radius r and sensor senses model parameter.

5. the difference covering method based on mixed type sensor network as claimed in claim 1, is characterized in that, transducer mobile node is resolved P after receiving packet _gto obtain in the step of target location of this transducer mobile node,

For i transducer mobile node, its target location is (x _i, y _i)=(P _g(i), P _g(i+n)).