CN103002590A - Scheduling method of directed nodes in wireless sensor network - Google Patents

Abstract

The invention discloses a scheduling method of directed nodes in a wireless sensor network. The method includes scene setting, node direction optimization and node scheduling. An adopted perceptual model is a sector area which takes a node as a circle center to lead out two rays and has a perceptual distance which is a perceptual diameter. Aiming at solving the problems that perceptual directions of some nodes are limited due to influences of various factors and the coverage rate of the network nodes for selected targets is low caused by the node placement randomness, the method determines the optimal perceptual directions of the directed nodes in the sensor network and optimally configures the network resources, therefore the network node coverage rate is improved, and the life cycle of the network is prolonged.

Description

The dispatching method of orientation node in the wireless sensor network

Affiliated field

The present invention relates to a kind of orientation node dispatching algorithm that is applied in the wireless sensor network, belong to software field.Particularly relate to the Node Scheduling Algorithms in Line that a kind of orientation node for disposing in the wireless sensor network proposes, need that at first the orientation node in the sensor network is carried out optimum perceived direction and determine, and then carry out node scheduling according to node and the covering relation between the target known to the direction after determining.

Background technology

Current, along with the development of microsensor technology, radio network technique and embedded processing technology etc., wireless sensor network all obtains diversified application in a lot of fields, such as industry, agricultural, building, biological, medical science and military etc.Sensor network generally is made of a large amount of sensor nodes, and the common inclusion information perception of node, data acquisition and communications portion.

Based on the applied environment of different situations, wireless sensor network exists different Coverage Control problems, to guarantee under the prerequisite of certain mass, reaches the network coverage maximization.Generally, covering is divided into a covering, the fully i.e. zone covering of covering, fence covering.Point cover for be the limited discrete point that distributes in the coverage goal zone, this is monitored and draws required minimum sensor node quantity and node location; The zone covers the everywhere that then needs the coverage goal zone, and any point all will be covered by a node at least, guarantees coverage ability and network connectivty, puts before this and uses minimum sensor node so that network cost is minimum as far as possible; What cover to consider as for fence is the probability problem that moving object passing through network deployment region is found and detects, and is divided into " the worst cover with optimal cases " and " exposure is passed through " two types.Generally speaking, regional covering problem is used many, and what the present invention relates to is a covering problem.

For covering problem, if the node perceived model that adopts is different, solution is also different so.Common node perceived model is divided into usually: omnidirectional's sensor model, oriented sensor model.Omnidirectional's sensor model refer to the node perceived scope be take node as the center of circle, perceived distance is as the border circular areas of radius, when the distance between node and the target during less than the perception radius, we just claim the coverage impact point.In omnidirectional's overlay model of wireless sensor network, the detection coverage of transducer can be similar to regards a border circular areas as, and detection range is the radius of border circular areas.Be different from omnidirectional's sensor model of introducing the front, the perception zone of oriented sensor model is subject to the restriction at " visual angle ".This moment the node perceived scope be one take node as the center of circle, its perceived distance is as the sector region of radius.Application demand along with development and the Practical Project of sensing technology, transducer based on oriented sensor model, occurred such as video sensor, ultrasonic sensor, infrared ray sensor etc., their perception is limited in the angular field of view, just effectively be embodied on the operative orientation, other directions then can't be carried out the perception monitoring.

When carrying out practical application, the perceived direction of usually supposing sensor node is omnidirectional.But owing to be subject to the impact of the various factorss such as technology, cost and surrounding environment, the perceived direction of some node still can be subject to restriction in various degree, causes its perception in different directions different.In general, when node only just possessed effective perceptional function on operative orientation, we were referred to as orientation node such node, and corresponding sensor network is called directional sensor network.

Because the energy of sensor node is provided by self entrained node battery, finite energy, but the time of maintenance work is shorter, energy consumption can't be carried out timely supply, be unfavorable for the work of network long-term stability, therefore in a lot of research topics for wireless sensor network, the life cycle that how to prolong network then is a study hotspot and difficult point, and the wireless sensor network of disposing orientation node also is like this.In the present multiple method that can prolong network lifetime, node scheduling is a kind of effective method, the operating state of rationalization's nodes, make part of nodes be in the resting state of low energy consumption and another part is in active state, take turns to operate, reduce the density of live-vertex in the network, improve energy utilization efficiency.

Satisfy under the condition of Poisson static distribution distributing based on node, node scheduling can be divided into two classes: node random schedule and node cooperation scheduling.(1) the node random schedule refers to random packet, and each node is assigned to a certain group or a few groups, the operation dispatching algorithm once, the sensor node of dispatching successively every group carries out work.The people such as Slijepcevic have proposed a kind of based on the mutually disjoint algorithm of node set of maximization, utilize the redundancy properties of network node, whole network's coverage area is divided into groups to divide, maximize so that cover the set number without occuring simultaneously, and then effectively prolong network lifetime.The people such as Kumar propose a kind of at random independent dormancy mechanism RIS, will the time be divided into time slot, and the node in each time slot determines independently according to probability P whether this node enters resting state.The people such as Liu propose a kind of Mathematical Modeling according to the coverage property of random placement network, calculate the node number that satisfies the service quality expectation by the ratio of known monitoring range and node perceived radius.The people such as Jiang consider that analysis gets the node scheduling problem under the node deployment failure conditions.The people such as Li have proposed two kinds of centralized and Distributed coverage algorithms in the situation of node location information the unknown.The people such as Wang utilize information-theoretical thought, propose a kind of information covering algorithm, analyze the probability higher limit that arbitrary node is not covered by information in the random placement zone, find out node deployment density and on average cover relation between the hole.The people such as Ding propose a kind of adaptive network segmentation strategy, by grouping the node scheduling problem are transformed into constrained optimization graph theoretic problem, and propose a kind of distributed heuristic algorithm-based on the partitioning algorithm that is communicated with.The people such as Deng propose a kind of based on bunch the dispatching algorithm of high density sensor network.(2) node cooperation scheduling refer to then that node needs and on every side node communicate, take turns the beginning execution algorithm once at each, the selection portion partial node is as active node in all nodes according to certain competition mechanism, and this algorithm needs to carry out repeatedly in scheduling process.The people such as DiTian propose the redundancy detection algorithm judged based on local neighbours geometric position, by being similar to the redundant situation of covering that central angle union corresponding to sector region come decision node by coverage is formed.The people such as Zhang adopt the redundant method of discrimination of the covering of Crossing Coverage, have proposed a kind of distributed node density control algolithm OGDC (Optimal Geographical Density Control); And Xing expands OGDC, has proposed the CCP algorithm, with coverage and the degree of communication of network configuration to appointment, needs comparatively accurate positional information.The people such as Xu propose the GAF algorithm based on the node geographical position, and the monitored area is divided into square dummy unit lattice, and node is put into respective cells according to positional information, and any two nodes of adjacent cells lattice can direct communication.The people such as Shao-Feng J propose a kind of enhancement mode circumference coverage density control algolithm for the Boundary Effect problem in the circumference coverage judgement.

But it should be noted that the directivity apperceive characteristic of orientation node so that existing coverage density control achievement in research can not directly apply to the sensor network based on oriented sensor model, therefore problem need to be transformed one and get off to take into account and solve.When using orientation node that selected target is covered, thereby the random distribution of node and perceived direction limited all can cause some target to be not easy cappedly to cause the not high problem of target coverage rate, so just reduced the life cycle of network and the utilance of resource.And the method for the perception of enhancing orientation node is a lot, wherein a kind of is that the orientation node that several directions are different is equal to a node, can also arrange in addition that sensor node comes along with mobile device so that self can the omnirange rotation, and node is set makes it can select different perceived direction.Select last a kind of situation that orientation node is set herein.

Summary of the invention

Technical problem: according to top described, because the node that has is because the impact of various factors and so that the perceived direction of node is limited, the randomness of adding node deployment causes network node to the not high problem of selected target coverage rate, for this situation, the objective of the invention is to propose a kind of orientation node dispatching method in the wireless sensor network that is applied to, described method is by determining the optimum perceived direction of orientation node in the sensor network, distribute Internet resources rationally, thus the life cycle that improves the network node coverage rate, prolongs network.

Technical scheme: the orientation node dispatching method is divided into scene setting, node direction optimization and 3 parts of node scheduling in the wireless sensor network that the present invention proposes; The sensor model of taking is to draw two rays and perceived distance as the center of circle as the formed sector region of perception radius take node, and the method mainly comprises following step:

Step 1: scene setting

1) required scene parameter, random distribution node and target are set;

2) relevant parameter of node is set, determines that the some of node may perceived direction;

Step 2: node direction optimization

21) criterion optimized of directions at first: the value of utility of node on each direction;

22) consideration affects some factors of value of utility size;

23) calculate the value of utility of each selected target;

24) summation of target value of utility on each direction of computing node is determined the finish node optimal direction according to size;

Step 3: node scheduling

Relate to two kinds of Node Scheduling Algorithms in Lines: optimized algorithm and heuritic approach.

Symbol description is as follows:

S: oriented sensor node set; T: regional aim set;

N: orientation node sum; M: regional aim sum;

R: node perceived radius; P: node direction number;

o _{O, p}: P the perceived direction of node O; F: regional aim coverage;

T _{O, P}: the goal set of node O on direction P; t _{O, P, i}: i the target of node O on direction P;

Q: node perceived visual angle; L: node intrinsic life cycle;

C _m: coverage goal k _mSensor node s _iIndexed set;

B _l: the sensor node s that covers l target _iIndexed set;

x _Ij: Boolean variable, if satisfy node s _i∈ J _j, x _IjValue be 1, otherwise be 0;

y _i: the integer variable between [0, M], and if only if node s _iBe set B _lIn the member time, y _iValue is l;

t _j: the real variable between [0,1], grouping J _jEnliven the time;

k _Critical: the also minimum target that sensor node covered of minimum and residue node energy by number;

α _i: be in the node s between [0,1] _iVerification and measurement ratio;

P _Tx: performance number between the node active period;

E _i: node s _iThe primary power value;

C _Mj: as grouping J _jWhen enlivening, coverage goal k _mSensor node s _iIndexed set;

D _Lj: as grouping J _jWhen enlivening, cover the sensor node s of l target _iIndexed set;

W _Ij: the integer variable between [0, M], and if only if node s _iBe set D _LjIn the member time, W _IjValue is l;

k _Critical: the also minimum target that sensor node covered of minimum and residue node energy by number.

As follows based on the algorithmic procedure that the node scheduling of optimized algorithm is related:

311) initialization is carried out in a given grouping, C is set _Mj=C _m, D _Lj=D _l, W _Ij=y _i, wherein satisfy

L=0,1 ..., M;

312) find out grouping set J _jIn overlapping target, for

313) for

In target k _m, find out and cover k _mThe set of overlapping nodes

Then select therein node s _r, s wherein _rBe the RS node;

314) more new node and relationship by objective (RBO), for

In all node s _i, satisfy s here _i≠ s _r, assignment C again _Mj=C _Mj-{ i}, D _Lj=D _Lj-{ i} and D _{(l-1) j=}D _{(l-1) j}+ { i}, W _Ij=W _Ij-1, return step 313);

315) C during update packet is gathered again _Mj, D _LjAnd W _Ij

In this optimized algorithm, for from the grouping J ₁, J ₂..., J _QIn remove redundancy object information, need to carry out Q time, secondly, in order to make the network lifecycle maximization, optimized algorithm also will satisfy following conditional plan when execution,

Total equation: $\mathrm{Maximize}\stackrel{Q}{\underset{j=1}{\mathrm{\Σ}}}{t}_j$

Satisfy condition for: $\left\{\begin{array}{cc}\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\left({\mathrm{\α}}_i{W}_{\mathrm{ij}}{P}_{\mathrm{tx}}\right)x_{\mathrm{ij}}{t}_j\≤E_i,\∀s_i\∈S& \\ \underset{i\∈C_m}{\mathrm{\Σ}}{x}_{\mathrm{ij}}\≥1,\∀k_m\∈T,j=\mathrm{1,2},......,Q& \end{array}\right.,\begin{array}{c}{x}_{\mathrm{ij}}\∈\left[\mathrm{0,1}\right]\\ W_{\mathrm{ij}}=l\end{array};$

As follows based on the algorithmic procedure that the node scheduling of heuritic approach is related:

321) network is carried out initialization, the sensor node energy is E _i, j=0, S _S=S;

322) when each target by S _SIn at least one coverage the time, produce a new grouping J _j, j=j+1 is set,

S _T=T；

323) when

The time, at first find a common-denominator target k among the ST _Ciritical, select a node and satisfy s _Select∈ S _S, J then divides into groups _j=J _j∪ s _Select, for S _TIn all targets, if target k _mBy node s _SelectWhen covering, S _T=S _T-{ k _m;

324) from grouping J _jIn remove the repeating part of redundancy object, for grouping J _jCarry out the optimized algorithm of front;

325) energy upgrades, for J _jIn all nodes, E _i=E _i-α _iW _IjP _TxW is if satisfy E _i-α _iW _IjP _TxW≤0, S _S=S _S-{ s _i, remove node s _i, return 322);

326) return grouping J ₁, J ₂..., J _jAnd network lifecycle j*w.

Beneficial effect: directional sensor network Node Scheduling Algorithms in Line proposed by the invention is mainly used in solving because the not high problem of point target coverage rate that the randomness of node perceived directivity and node deployment is brought.

In general wireless sensor network is used, usually can neglect the impact of objective reality factor, consider ideal situation, the sensor model of node is made as the binary sensor model, namely take node as the center of circle, perceived distance is as the circular perception zone of radius.But the node perceived direction that exists in the actual life presents non-whole circle but the situation of an angle, therefore need to also consider directional sensor network.And more existing Coverage Control dispatching algorithms can not directly just be applied in the directional sensor network in the wireless sensor network, need to consider and change thinking.The present invention is exactly in view of the situation, in conjunction with orientation node and node scheduling two parts situation, it is integrated conversion, proposes based on the dispatching algorithm in the directional sensor network.

Therefore, beneficial effect of the present invention is, the existing Node Scheduling Algorithms in Line that is applied in the wireless sensor network is changed integration, be applied in the directional sensor network, effectively improved the not high situation of target coverage degree in the network, distribute network node rationally, improve the Internet resources coverage rate, prolong the life cycle of network.

Description of drawings

Fig. 1 is the sensor model of oriented sensor node;

Fig. 2 is the flow chart of whole invention.

Embodiment

Regard the life cycle problem of directional sensor network as an optimization problem: how to make its perceived direction optimum by direction optimization, and how scheduling node just can farthest increase network lifecycle.If the optimum perceived direction of orientation node is determined that the scheduling of directional sensor network just can be converted into node scheduling problem generally so, this moment, the operating point dispatching algorithm got final product.

Sensor network orientation node dispatching algorithm proposed by the invention is based on the dispatching algorithm of carrying out again after the node direction optimization, its principle is: because in sensor network, node presents an angle but not omnirange with perceived direction more at random owing to distribute, cause target not covered by node or the target coverage rate lower, therefore first travel direction optimization, determine the optimum perceived direction of orientation node, and then carry out the resource coverage rate that dispatching algorithm is improved network, prolong the life cycle of network.

In order to narrate conveniently, hereinafter will no longer deliberately distinguish node, orientation node and sensor node, three's meaning all is made as identical.

Among the present invention related oriented sensor model for take node O as the center of circle, take perceived distance r as radius by two rays and one section formed sector region of circular arc, whole circular model is divided into P zone, wherein the angle theta of this sector region is referred to as the visual angle, and the vector that the θ visual angle is divided equally The direction of indication is referred to as the perceived direction of node O, supposes that itself and transverse axis forward angle are β and the 0≤β that satisfies condition≤2 π.Herein r, θ are constant, and as shown in Figure 1, oriented sensor model then uses four-tuple (ID _o, r, θ,

) represent.

The label symbol that occurs among paper the present invention once.

S: oriented sensor node set; T: regional aim set;

N: orientation node sum; M: regional aim sum;

R: node perceived radius; P: node direction number;

o _{O, p}: P the perceived direction of node O; F: regional aim coverage;

T _{O, P}: the goal set of node O on direction P; t _{O, P, i}: i the target of node O on direction P;

Q: node perceived visual angle; L: node intrinsic life cycle.

We suppose that usually a random placement N sensor node is monitored M target in the target area, and the set of supposing sensor node is S={S ₁, S ₂..., S _N, the set of target is T={k ₁, k ₂..., k _M.If target k is covered by node O, refer to that then the distance between node and the target is less than perception radius r, and vector

Direction satisfy interval

Definition 1: neighbor node.When the distance between two nodes in the deployment region satisfied condition d (i, j)≤2r, then node i, j can be referred to as neighbor node mutually.

Definition 2: network lifecycle.The life cycle of our General Definition wireless sensor network is to start working until also have at least the time that target is experienced by node observation station from network.

Definition 3: critical coverage.The coverage of critical target is critical coverage, and critical target refers to the target of coverage minimum in the sensor network.

Definition 4: cover collection.Suppose that the subset set D of a given finite aggregate A and of D divide S, one of A covers collection and refers to a subset

So that each element among the A belongs at least one member among the D ', and per two elements all can not belong to the identical member of S among the D '.

Definition 5: oriented covering collection.Divide S for one of the subset set D of a given finite aggregate A and D, can find one of A to cover collection.

Definition 6: the oriented collection that cover more.Suppose that the subset set D of a given finite aggregate A and of D divide S, find the K of A to cover set series

And non-negative weights t ₁+ t ₂+ ...+t _KMaximization for each s ∈ S, satisfies condition

Wherein L is given positive number.

Node scheduling method in the directional sensor network proposed by the invention mainly comprises two parts: direction optimization and node scheduling.Direction optimization refers to that adjustment node is operated in cover to consider on the maximum direction and pays the utmost attention to critical target regional aim, treats that optimum perceived direction determines that node no longer Dynamic Selection is adjusted its perceived direction; And node scheduling refers to that Area Node is divided into several covers collection, and each grouping set takes turns to operate and is in active state, and set is in resting state in addition, evenly consumes node energy, prolongs network lifecycle.

The below introduces the process of whole invention, sees Fig. 2.

Step 1 is carried out scene setting to whole zone.

(1) required scene parameter, random distribution node and target are set;

(2) relevant parameter of node is set, determines that the some of node may perceived direction.

Step 2 is carried out the optimization of orientation node direction.

In general, there is a criterion in node direction optimization in the directional sensor network, namely calculates the value of utility of each orientation node on each direction.Behind the network design, all nodes all scan the target information on all directions, after neighbor node exchange target information, at first calculate the value of utility of each target, next calculates the summation of target value of utility on each direction, namely calculate the value of utility on each direction, choose the direction of value of utility maximum as operative orientation, tell neighbor node with the set direction of oneself at last.

The factor that affects value of utility of considering among the present invention have following some:

(1) pays the utmost attention to the set direction of critical target;

(2) node that has made a policy;

(3) set direction of neighbor node;

(4) target sum.

After having obtained above information, can draw the computing formula of value of utility, as follows: about the value of utility of each target: U (k)=M ^{-(f+f '-1)}Value of utility about each direction:

Calculate the value of utility of each target on all directions according to above-mentioned formula, determine the final optimization pass direction of orientation node according to the size of value of utility.

Step 3, the directional sensor network node scheduling.

After the optimum perceived direction of orientation node is determined, can determine and obtain corresponding covering relation between node and the target.On this basis, adopt two kinds of methods to carry out node scheduling also relatively.

A, optimized algorithm

The at first relation between description node and the target and correlated variables.

C _m: coverage goal k _mSensor node s _iIndexed set;

B _l: the sensor node s that covers l target _iIndexed set;

x _Ij: Boolean variable, if satisfy node S _i∈ J _j, x _IjValue be 1, otherwise be 0;

y _i: the integer variable between [0, M], and if only if node s _iBe set B _lIn the member time, y _iValue is l;

t _j: the real variable between [0,1], grouping J _jEnliven the time;

k _Critical: the also minimum target that sensor node covered of minimum and residue node energy by number;

α _i: be in the node s between [0,1] _iVerification and measurement ratio;

P _Tx: performance number between the node active period;

E _i: node s _iThe primary power value.

Optimized algorithm be devoted to find out all grouping sets of covering relation between given node and the target, J ₁, J ₂..., J _QBe exactly resulting grouping set, this moment, q was the maximum number of the grouping set that can draw according to known covering relation.In order to remove the redundancy object information in the grouping set, the data message that a unique node R S is responsible for sending repetition in the node of supposing to repeat is to the sink node, and meanwhile other duplicate node does not then send.In order to select suitable RS node, the relation that need to be defined as follows and variable.

C _Mj: as grouping J _jWhen enlivening, coverage goal k _mSensor node s _iIndexed set;

D _Lj: as grouping J _jWhen enlivening, cover the sensor node s of l target _iIndexed set;

W _Ij: the integer variable between [0, M], and if only if node s _iBe set D _LjIn the member time, W _IjValue is l.

The flow process of optimized algorithm is described below:

Step1: initialization is carried out in a given grouping, C is set _Mj=C _m, D _Lj=B _l, W _Ij=y _i, wherein satisfy

L=0,1 ..., M;

Step2: find out grouping set J _jIn overlapping target, for

Step3: for

In target k _m, find out and cover k _mThe set of overlapping nodes

Then select therein node s _r, s wherein _rBe the RS node;

Step4: more new node and relationship by objective (RBO), for

In all node s _i, satisfy s here _i≠ sr, again assignment C _Mj=C _Mj-{ i}, D _Lj=D _Lj-{ i} and D _{(l-1) j}=D _{(l-1) j}+ { i}, W _Ij=W _Ij-1, return Step3;

Step5: the C during update packet is gathered again _Mj, D _LjAnd W _Ij

In this optimized algorithm, for from the grouping J ₁, J ₂..., J _QIn remove redundancy object information, algorithm need to be carried out Q time.Secondly, in order to make the network lifecycle maximization, optimized algorithm also will satisfy following conditional plan when carrying out.

Total equation: $\mathrm{Maximize}=\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}{t}_j$

Satisfy condition for: $\left\{\begin{array}{cc}\underset{j=1}{\overset{Q}{\mathrm{\Σ}}}\left({\mathrm{\α}}_i{W}_{\mathrm{ij}}{P}_{\mathrm{tx}}\right)x_{\mathrm{ij}}{t}_j\≤E_i,\∀s_i\∈S& \\ \underset{i\∈C_m}{\mathrm{\Σ}}{x}_{\mathrm{ij}}\≥1,\∀k_m\∈T,j=\mathrm{1,2},......,Q& \end{array}\right.,\begin{array}{c}{x}_{\mathrm{ij}}\∈\left[\mathrm{0,1}\right]\\ W_{\mathrm{ij}}=l\end{array};$

B, heuritic approach

Paper is correlated variables once.

k _Critical: the also minimum target that sensor node covered of minimum and residue node energy by number;

α _i: be in the node s between [0,1] _iVerification and measurement ratio;

P _Tx: performance number between the node active period;

E _i: node s _iThe primary power value.

In order to reduce the complexity of optimized algorithm, heuritic approach is the primary power of initialization node at first, iterations j, and node set S _S, S wherein _SIncluding abundant energy becomes unnecessary grouping set member's node set; Secondly, heuritic approach repeatedly carry out minute group task until each target by S _SIn at least one node cover S set _TComprise not by current group J _jThe target that covers; The 3rd, the optimized algorithm that heuritic approach is carried out the front comes from grouping set J _jIn remove redundant information in the overlapping target; Then heuritic approach is dispatched grouping J _jBe the node energy in time ω and the update packet; At last, heuritic approach is returned grouping number j and network lifecycle j* ω.

The flow process of heuritic approach:

Step1: network is carried out initialization, and the sensor node energy is E _i, j=0, S _S=S;

Step2: when each target by S _SIn at least one coverage the time, produce a new grouping J _j, j=j+1 is set,

S _T=T;

Step3: when The time, at first find S _TIn a common-denominator target k _Ciritical, select a node and satisfy s _Elect∈ S _S, J then divides into groups _j=J _j∪ s _Select, for S _TIn all targets, if target k _mBy node s _SelectWhen covering, S _T=S _T-{ k _m;

Step4: from grouping J _jIn remove the repeating part of redundancy object, for grouping J _jCarry out the optimized algorithm of front;

Step5: energy upgrades, for J _jIn all nodes, E _i=E _i-α _iW _IjP _TxW is if satisfy E _i-α _iW _IjP _TxW≤0, S _S=S _S-{ s _i, remove node s _i, return Step2;

Step6: return grouping J ₁, J ₂..., J _jAnd network lifecycle j*w.

Whole invention flow process finishes.

Emulation considers that node number, target sum, node perceived radius and perception angle are on the impact of network lifecycle.

Claims (1)

1. orientation node dispatching method in the wireless sensor network is characterized in that the method is divided into scene setting, node direction optimization and 3 parts of node scheduling; The sensor model of taking is to draw two rays and perceived distance as the center of circle as the formed sector region of perception radius take node, and the method mainly comprises following step:

Step 1: scene setting

1) required scene parameter, random distribution node and target are set;

2) relevant parameter of node is set, determines that the some of node may perceived direction;

Step 2: node direction optimization

21) criterion optimized of directions at first: the value of utility of node on each direction;

22) consideration affects some factors of value of utility size;

23) calculate the value of utility of each selected target;

24) summation of target value of utility on each direction of computing node is determined the finish node optimal direction according to size;

Step 3: node scheduling

Relate to two kinds of Node Scheduling Algorithms in Lines: optimized algorithm and heuritic approach;

Symbol description is as follows:

S: oriented sensor node set; T: regional aim set;

N: orientation node sum; M: regional aim sum;

R: node perceived radius; P: node direction number;

o _{O, p}: P the perceived direction of node O; F: regional aim coverage;

T _{O, P}: the goal set of node O on direction P; t _{O, P, i}: i the target of node O on direction P;

Q: node perceived visual angle; L: node intrinsic life cycle;

C _m: coverage goal k _mSensor node s _iIndexed set;

B _l: the sensor node s that covers l target _iIndexed set;

x _Ij: Boolean variable, if satisfy node s _i∈ J _j, x _IjValue be 1, otherwise be 0;

y _i: the integer variable between [0, M], and if only if node s _iBe set B _lIn the member time, y _iValue is l;

t _j: the real variable between [0,1], grouping J _jEnliven the time;

k _Critical: the also minimum target that sensor node covered of minimum and residue node energy by number;

α _i: be in the node s between [0,1] _iVerification and measurement ratio;

P _Tx: performance number between the node active period;

E _i: node s _iThe primary power value;

C _Mj: as grouping J _jWhen enlivening, coverage goal k _mSensor node s _iIndexed set;

D _Lj: as grouping J _jWhen enlivening, cover the sensor node s of l target _iIndexed set;

W _Ij: the integer variable between [0, M], and if only if node s _iBe set D _LjIn the member time, W _IjValue is l;

k _Critical: the also minimum target that sensor node covered of minimum and residue node energy by number;

As follows based on the algorithmic procedure that the node scheduling of optimized algorithm is related:

311) initialization is carried out in a given grouping, C is set _Mj=C _m, D _Lj=B _l, W _Ij=y _i, wherein satisfy

L=0,1 ..., M;

312) find out grouping set J _jIn overlapping target, for

313) for

In target k _m, find out and cover k _mThe set of overlapping nodes Then select therein node s _r, s wherein _rBe the RS node;

314) more new node and relationship by objective (RBO), for

In all node s _i, satisfy s here _i≠ s _r, assignment C again _Mj=C _Mj-{ i}, D _Lj=D _Lj-{ i} and D _{(l-1) j}=D _{(l-1) j}+ { i}, W _Ij=W _Ij-1, return step 313);

315) C during update packet is gathered again _Mj, D _LjAnd W _Ij

In this optimized algorithm, for from the grouping J ₁, J ₂..., J _QIn remove redundancy object information, need to carry out Q time, secondly, in order to make the network lifecycle maximization, optimized algorithm also will satisfy following conditional plan when execution,

Total equation:

Satisfy condition for:

As follows based on the algorithmic procedure that the node scheduling of heuritic approach is related:

321) network is carried out initialization, the sensor node energy is E _i, j=0, S _S=S;

322) when each target by S _SIn at least one coverage the time, produce a new grouping J _j, j=j+1 is set,

S _T=T；

323) when

The time, at first find S _TIn a common-denominator target k _Ciritical, select a node and satisfy s _Select∈ S _S, J then divides into groups _j=J _j∪ s _Select, for S _TIn all targets, if target k _mBy node s _SelectWhen covering, S _T=S _T-{ k _m;

324) from grouping J _jIn remove the repeating part of redundancy object, for grouping J _jCarry out the optimized algorithm of front;

325) energy upgrades, for J _jIn all nodes, E _i=E _i-α _iW _IjP _TxW is if satisfy E _i-α _iW _IjP _TxW≤0, S _S=S _S-{ s _i, remove node s _i, return 322);

326) return grouping J ₁, J ₂..., J _jAnd network lifecycle j*w.

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