CN105307230A - Three-dimensional mine hybrid routing algorithm based on greedy thought - Google Patents

Abstract

The invention provides a three-dimensional mine hybrid routing algorithm based on a greedy thought, and belongs to a data transmission routing algorithm of a wireless sensor network of an underground coal mine. The three-dimensional mine hybrid routing algorithm comprises the following steps: at first, using the space mosaic theory to optimize a node deployment strategy, setting a deployment scheme suitable for the underground coal mine, then, optimizing a clustering routing algorithm of the network by use of the greedy thought, and using the residual energy and a broadcast factor as a weight reference of cluster head election, determining a weight function to select an optimal next hop node, and finally, forming an optimal data forwarding path to reduce the energy cost and the delay time of the network. The routing algorithm of the wireless sensor network with efficient global energy, balanced and small time delay is designed by use of the greedy thought; a triangular prism is selected according to the space mosaic theory to fill a three-dimensional space, and the three-dimensional space is converted into a two-dimensional expression when the node position is determined. Clustering is carried out by sensing the residual energy and the broadcast factor of the node, and optimal path multi-hop communication of the cluster head and a base station is achieved by the greedy thought when inter-cluster routing is established.

Description

A kind of Three-dimensional Mine mixed logic dynamic algorithm based on greedy thought

Technical field

The present invention relates to a kind of wireless sensor network under coal mine transfer of data route algorithm, particularly a kind of Three-dimensional Mine mixed logic dynamic algorithm based on greedy thought.

Background technology

Wireless sensor network (WSNs) is as one of emerging technology, on social life, there is great impact, underground coal mine environment is very complicated, wired monitoring mode is difficult to realize effectively, comprehensively monitoring, to coal production be made to leave huge potential safety hazard like this, adopt wireless mode to carry out monitoring the region that can be difficult to monitor to wired monitoring mode to mine disaster and implement effective monitoring.In actual applications, require that sensor node can work long hours when not makeup energy, the factor affecting wireless sensor and actor networks life cycle is a lot, the deployment scheme of its interior joint will directly affect the performance such as Data Collection, network life cycle, and efficient routing algorithm also can greatly improve the extensibility of WSNs and extend network life cycle.

At present, the research that expert disposes for wireless sensor network node is many, have for covering problem during node deployment, the node deployment algorithm that can meet the requirement of Cover treatment rate proposed, this algorithm can maximize the covering efficiency of node, but does not carry out node deployment covering for three dimensions; In addition also have based on spatial tessellations theory carry out space fill cover, can reach space cover requirement, but this algorithm does not solve the node deployment problem of specific long and narrow space.Multiple Routing Protocol has been proposed in research above, importantly plane Routing Protocol and hierarchical routing protocol, research shows, hierarchical routing protocol can improve network lifecycle significantly, wherein clustering route protocol has done sufficient Optimal improvements on cluster algorithm, but also have problems in the route transmission stage, developed into the multi-hop communication in later stage by the single-hop communication in early stage, but still have problems at path optimization.China's coal-mine Frequent Accidents, Coal Mine Safety Monitoring System is particularly important, and the environment special for colliery sets up the node deployment scheme be applicable to, and the Routing Protocol algorithm that design meets colliery feature is extremely important.

Spatial tessellations is from landscape ecology, and view is ecological and geographic(al) cross concept, refers to have the interactional ecosystem to inlay formation, and repeats with similar type, have the region of height space heterogeneity.Region is by not repeat mutually and comparative strong basic structural unit is formed, and the principal character of its mosaics is identifiability, space repeatability and heterogeneous.Theoretical according to spatial tessellations, the space-filling polyhedron with regular face has: triangular prism, hexagonal prismoid, cube, section octahedra and No. 26th, Johnson solid, in conjunction with the design feature of underground coal mine, selects triangular prism to carry out spatial tessellations.Greedy algorithm refers to when to problem solving, and being always made at current it seems is best selection, that is, does not take in from total optimization, the locally optimal solution that what he made is only in some sense.

Summary of the invention

The present invention seeks to a kind of energy expense will be provided little, well harmonious and the Three-dimensional Mine mixed logic dynamic algorithm based on greedy thought that time delay is less.

To achieve these goals, routing algorithm of the present invention is by the following technical solutions: first usage space mosaic theory optimizes node deployment strategy, the deployment scheme of applicable underground coal mine is set, then the Clustering Routing of greedy thought optimized network is utilized, use the weights reference that dump energy and the relay factor are elected as cluster head, finally determine that weight function selects optimum next-hop node, the final optimal path forming data retransmission, reduce energy expense and the delay time of network;

Concrete steps are as follows:

1. the node deployment stage:

(1) study underground coal mine space characteristics, choose node space deployment model;

(2) utilize spatial tessellations theory to select to be applicable to the filler cells of underground coal mine, and space, down-hole is carried out to the deployment of node; After disposing, the coordinate of tunnel interior joint represents, X-axis represents the distance along tunnel bottom centre axial line distance aggregation node (sink), and Y represents the arc length bottom node to tunnel, Y-coordinate value has three kinds to be respectively 0, π r, wherein r is the radius in tunnel;

2. the Route establishment stage:

A. node cluster process:

(1) the threshold value T (n) of computing network interior joint; For extending cycle of network life, the power consumption issues of balance node, in cluster process, dump energy should be increased as far as possible higher and relay the probability that the larger node of the factor is elected as cluster head;

(2) node in network produces a random number between 0 ~ 1, if this random number is less than threshold value T (n), so this node is elected as cluster head;

(3) after node is elected as cluster head node, node broadcasts oneself becomes the message of cluster head towards periphery, after other ordinary nodes receive message, according to information such as signal strength signal intensities, selects optimum cluster head to add certain bunch, becomes the member of this bunch;

B. mixed logic dynamic process of establishing:

(1) the candidate region scope of the next-hop node of decision node; The alignment regions of next-hop node be defined in the conical area that drift angle is θ, the axis being parallel of circular cone is in the center line in tunnel.θ=60 ° herein, the angle namely between element of cone and center line in roadway is 30 °, if the included angle between the straight line at two node places and center line in roadway is less than 30 °, then this node is in candidate region;

According to energy consumption model, computing node n _itransmit data to next-hop node n _jdump energy desired value E _r(i);

$E_r\left(i\right)=\left\{\begin{array}{c}{E}_{current}\left(i\right)-(l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;{d_{ij}}^2),(d_{ij}<d_0)\\ E_{current}\left(i\right)-(l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{mp}\&CenterDot;{d_{ij}}^4),(d_{ij}\&GreaterEqual;d_0)\end{array}\right.$

(2) use greedy algorithm is using the weight function P (i, j) of node as target function, is arranged from big to small by target function, selects the maximum node of target function as next-hop node;

P(i,j)＝αE _r(i)+βE(j)+λS(j)

(3) network determines overall optimal data transmission route by local optimum next-hop node.

The deployed position portion of described space nodes determines as follows:

Be two-dimensional coordinate by three dimensional space coordinate Information Simplification, in two-dimensional space, X-axis represents the distance along tunnel bottom centre axial line distance sink node, and Y represents the arc length bottom node to tunnel, and in long and narrow tunnel, the coordinate of known 2 is respectively n _i(x _i, y _i), n _j(x _j, y _j), utilize geometric knowledge can calculate distance d between two nodes _ij;

$d_{ij}=\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\&rsqb;}^2}.$

The threshold value T (n) of described network node is determined by following formula:

$T\left(n\right)=\left\{\begin{array}{cc}\frac{p}{1-p\&times;\&lsqb;r\mathrm{mod}(1/p)\&rsqb;}\&CenterDot;\frac{E_{current}\left(n\right)}{E_{init}\left(n\right)}\&CenterDot;F\left(n\right)& n\&Element;G\\ 0& others\end{array}\right.$

$F\left(n\right)=\left\{\begin{array}{c}1,S_{current}\left(n\right)\&GreaterEqual;S_{avg}\\ q,S_{current}\left(n\right)<S_{avg}\end{array}\right.$

Wherein, p is the percentage of cluster head shared by all nodes, and r is carried out election wheel number, and what rmod (1/p) represented is that this takes turns in circulation the node number being elected to cluster head node, E _currentn () is the current dump energy of this node, E _initn primary power that () is this node, G is the set taking turns in circulation the node not being elected to cluster head at this, S _currentthe n relay factor that () is present node, S _avgthe average relay factor, q is the random number between (0,1).

Described mixed logic dynamic process of establishing, the optimum next-hop node selection mode of transfer of data is as follows:

Known 2 n _i(x _i, y _i), n _j(x _j, y _j), wherein n _ifor source node, when node meet below formula time, then node n _jat n _inext-hop node candidate region in;

$\frac{x_i-x_j}{\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\&rsqb;}^2}}\&GreaterEqual;\frac{\sqrt{3}}{2}$

According to energy consumption model, computing node n _itransmit data to next-hop node n _jdump energy desired value E _r(i);

$E_r\left(i\right)=\left\{\begin{array}{c}{E}_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;({\left(x_i-x_j\right)}^2+{\left(2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\right)}^2)\&rsqb;,(d_{ij}<d_0)\\ E_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;{({\left(x_i-x_j\right)}^2+{\left(2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\right)}^2)}^2\&rsqb;,(d_{ij}\&GreaterEqual;d_0)\end{array}\right.$

Use greedy algorithm using the weight function P (i, j) of node as target function, arranged from big to small by target function, select the maximum node of target function as next-hop node, the expression formula of weight function P (i, j) is as follows:

P(i,j)＝αE _r(i)+βE(j)+λS(j)

Wherein α, β, λ are constant parameter, and alpha+beta+λ=1; Node chooses the next-hop node of local optimum according to weight function, and locally optimal solution combines and obtains the optimal path of transfer of data.

Beneficial effect, owing to have employed such scheme, underground coal mine long and narrow space feature, makes the monitoring effect that common deployment scheme can not reach good, and spatial tessellations theory effectively solves the problem in the deployment of space.The factor that should add dump energy based on routing algorithm of greedy thought on the basis of cluster algorithm and relay the factor carries out the election of cluster head, the cluster head determined in this approach has higher dump energy and larger relay speed, adopts greedy algorithm to select the optimal path of transfer of data.Should based on the Three-dimensional Mine routing algorithm of greedy thought can be maximum minimizing energy ezpenditure extend network lifecycle, and propagation delay time can be reduced to a certain extent, be applicable to the monitoring of underground coal mine.

Accompanying drawing explanation

Fig. 1 is schematic flow sheet of the present invention.

Fig. 2 is node deployment space transforming relation schematic diagram.

Embodiment

This routing algorithm: first usage space mosaic theory optimizes node deployment strategy, the deployment scheme of applicable underground coal mine is set, then the Clustering Routing of greedy thought optimized network is utilized, use the weights reference that dump energy and the relay factor are elected as cluster head, finally determine that weight function selects optimum next-hop node, the optimal path of final formation data retransmission, reduces energy expense and the delay time of network;

Concrete steps are as follows:

1. the node deployment stage:

(1) study underground coal mine space characteristics, choose node space deployment model;

(2) utilize spatial tessellations theory to select to be applicable to the filler cells of underground coal mine, and space, down-hole is carried out to the deployment of node; After disposing, the coordinate of tunnel interior joint represents, X-axis represents the distance along tunnel bottom centre axial line distance aggregation node sink, and Y represents the arc length bottom node to tunnel, Y-coordinate value has three kinds to be respectively 0, π r, wherein r is the radius in tunnel; Described filler cells is triangular prism, and choosing of this model is determined in conjunction with colliery domes feature and detection requirement;

2. the Route establishment stage:

A. node cluster process:

(1) the threshold value T (n) of computing network interior joint; For extending cycle of network life, the power consumption issues of balance node, in cluster process, dump energy should be increased as far as possible higher and relay the probability that the larger node of the factor is elected as cluster head;

(2) node in network produces a random number between 0 ~ 1, if this random number is less than threshold value T (n), so this node is elected as cluster head;

(3) after node is elected as cluster head node, node broadcasts oneself becomes the message of cluster head towards periphery, after other ordinary nodes receive message, according to information such as signal strength signal intensities, selects optimum cluster head to add certain bunch, becomes the member of this bunch;

B. mixed logic dynamic process of establishing:

(1) the candidate region scope of the next-hop node of decision node; The alignment regions of next-hop node be defined in the conical area that drift angle is θ, the axis being parallel of circular cone is in the center line in tunnel.θ=60 ° herein, the angle namely between element of cone and center line in roadway is 30 °, if the included angle between the straight line at two node places and center line in roadway is less than 30 °, then this node is in candidate region;

According to energy consumption model, computing node n _itransmit data to next-hop node n _jdump energy desired value E _r(i);

$E_r\left(i\right)=\left\{\begin{array}{c}{E}_{current}\left(i\right)-(l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;{d_{ij}}^2),(d_{ij}<d_0)\\ E_{current}\left(i\right)-(l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{mp}\&CenterDot;{d_{ij}}^4),(d_{ij}\&GreaterEqual;d_0)\end{array}\right.$

(2) use greedy algorithm is using the weight function P (i, j) of node as target function, is arranged from big to small by target function, selects the maximum node of target function as next-hop node;

P(i,j)＝αE _r(i)+βE(j)+λS(j)

(3) network determines overall optimal data transmission route by the most next-hop node in local.

The deployed position portion of described space nodes determines as follows:

Be two-dimensional coordinate by three dimensional space coordinate Information Simplification, in two-dimensional space, X-axis represents the distance along tunnel bottom centre axial line distance sink node, and Y represents the arc length bottom node to tunnel, and in long and narrow tunnel, the coordinate of known 2 is respectively n _i(x _i, y _i), n _j(x _j, y _j), utilize geometric knowledge can calculate distance d between two nodes _ij;

$d_{ij}=\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\&rsqb;}^2}.$

The threshold value T (n) of described network node is determined by following formula:

$T\left(n\right)=\left\{\begin{array}{cc}\frac{p}{1-p\&times;\&lsqb;r\mathrm{mod}(1/p)\&rsqb;}\&CenterDot;\frac{E_{current}\left(n\right)}{E_{init}\left(n\right)}\&CenterDot;F\left(n\right)& n\&Element;G\\ 0& others\end{array}\right.$

$F\left(n\right)=\left\{\begin{array}{c}1,S_{current}\left(n\right)\&GreaterEqual;S_{avg}\\ q,S_{current}\left(n\right)<S_{avg}\end{array}\right.$

Wherein, p is the percentage of cluster head shared by all nodes, and r is carried out election wheel number, and what rmod (1/p) represented is that this takes turns in circulation the node number being elected to cluster head node, E _currentn () is the current dump energy of this node, E _initn primary power that () is this node, G is the set taking turns in circulation the node not being elected to cluster head at this, S _currentthe n relay factor that () is present node, S _avgthe average relay factor, q is the random number between (0,1).

Described mixed logic dynamic process of establishing, the next-hop node selection mode of transfer of data is as follows:

Known 2 n _i(x _i, y _i), n _j(x _j, y _j), wherein n _ifor source node, when node meet below formula time, then node n _jat n _inext-hop node candidate region in;

$\frac{x_i-x_j}{\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\&rsqb;}^2}}\&GreaterEqual;\frac{\sqrt{3}}{2}$

According to energy consumption model, computing node n _itransmit data to next-hop node n _jdump energy desired value E _r(i);

$E_r\left(i\right)=\left\{\begin{array}{c}{E}_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;({\left(x_i-x_j\right)}^2+{\left(2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\right)}^2)\&rsqb;,(d_{ij}<d_0)\\ E_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;{({\left(x_i-x_j\right)}^2+{\left(2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\right)}^2)}^2\&rsqb;,(d_{ij}\&GreaterEqual;d_0)\end{array}\right.$

Use greedy algorithm using the weight function P (i, j) of node as target function, arranged from big to small by target function, select the maximum node of target function as next-hop node, the expression formula of weight function P (i, j) is as follows:

P(i,j)＝αE _r(i)+βE(j)+λS(j)

Wherein α, β, λ are constant parameter, and alpha+beta+λ=1; Node chooses the next-hop node of local optimum according to weight function, and locally optimal solution combines and obtains the optimal path of transfer of data.

Embodiment 1: the present invention is described in detail below, the present invention provides a kind of Three-dimensional Mine mixed logic dynamic algorithm based on greedy thought at this, comprises the following steps:

(1) the node deployment stage:

With reference to Fig. 2, this algorithm meets the node deployment model of its feature for the particular surroundings design of underground coal mine, theoretical according to spatial tessellations, in order to reduce costs, simultaneously in conjunction with the feature of coal mine roadway and the demand of safety monitoring, node deployment is at the vertex position of triangular prism.Be two-dimensional coordinate by three dimensional space coordinate Information Simplification, in two-dimensional space, X-axis represents the distance along tunnel bottom centre axial line distance sink node, and Y represents the arc length bottom node to tunnel, and in long and narrow tunnel, the coordinate of known 2 is respectively n _i(x _i, y _i), n _j(x _j, y _j), utilize geometric knowledge can calculate distance d between two nodes _ij.

$d_{ij}=\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\&rsqb;}^2}.$

(2) the Route establishment stage:

A, node cluster process:

Similar to LEACH agreement, the node in network produces a random number between 0 ~ 1, if this random number is less than threshold value T (n), so this node is elected as cluster head.For extending cycle of network life, the power consumption issues of balance node, in cluster process, dump energy should be increased as far as possible higher and relay the probability that the larger node of the factor is elected as cluster head.After node is elected as cluster head node, node broadcasts oneself becomes the message of cluster head towards periphery, after other ordinary nodes receive message, according to information such as signal strength signal intensities, selects optimum cluster head to add certain bunch, becomes the member of this bunch.When cluster head receive all add information after, produce a TDMA timed message, and by this message informing to all nodes in this bunch.

B, mixed logic dynamic process of establishing:

In bunch, routing forwarding adopts single-hop communication pattern, and between bunch, communication adopts the pattern of multi-hop.The selection of multi-hop communication mainly next node of node.

Known 2 n _i(x _i, y _i), n _j(x _j, y _j), wherein n _ifor source node, when node meet below formula time, then node n _jat n _inext-hop node candidate region in.

$\frac{x_i-x_j}{\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\&rsqb;}^2}}\&GreaterEqual;\frac{\sqrt{3}}{2}$

According to energy consumption model, computing node n _itransmit data to next-hop node n _jdump energy desired value E _r(i).

$E_r\left(i\right)=\left\{\begin{array}{c}{E}_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;({\left(x_i-x_j\right)}^2+{\left(2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\right)}^2)\&rsqb;,(d_{ij}<d_0)\\ E_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;{({\left(x_i-x_j\right)}^2+{\left(2r\sin \left(\frac{\left|y_i-y_j\right|}{2r}\right)\right)}^2)}^2\&rsqb;,(d_{ij}\&GreaterEqual;d_0)\end{array}\right.$

Use greedy algorithm using the weight function P (i, j) of node as target function, arranged from big to small by target function, select the maximum node of target function as next-hop node, the expression formula of weight function P (i, j) is as follows:

P(i,j)＝αE _r(i)+βE(j)+λS(j)

Wherein α, β, λ are constant parameter, and alpha+beta+λ=1.Node chooses the next-hop node of local optimum according to weight function, and locally optimal solution combines and obtains the optimal path of transfer of data.

Monitoring network utilizes above-mentioned routing algorithm to be sent in industrial control network by Monitoring Data, for the data processing in later stage provides foundation.This algorithm energy expense is little, well harmonious and time delay is less, is applicable to the monitoring of coal mine downhole safety data.

Claims (4)

1. the Three-dimensional Mine mixed logic dynamic algorithm based on greedy thought, it is characterized in that: this routing algorithm, first usage space mosaic theory optimizes node deployment strategy, the deployment scheme of applicable underground coal mine is set, then the Clustering Routing of greedy thought optimized network is utilized, use the weights reference that dump energy and the relay factor are elected as cluster head, finally determine that weight function selects optimum next-hop node, the optimal path of final formation data retransmission, reduces energy expense and the delay time of network; Concrete steps are as follows:

(1) the node deployment stage:

(1) study underground coal mine space characteristics, choose node space deployment model;

(2) utilize spatial tessellations theory to select to be applicable to the filler cells of underground coal mine, and space, down-hole is carried out to the deployment of node; After disposing, the coordinate of tunnel interior joint represents, X-axis represents the distance along tunnel bottom centre axial line distance aggregation node (sink), and Y represents the arc length bottom node to tunnel, Y-coordinate value has three kinds to be respectively 0, π r, wherein r is the radius in tunnel;

(2) the Route establishment stage:

A. node cluster process:

(1) the threshold value T (n) of computing network interior joint; For extending cycle of network life, the power consumption issues of balance node, in cluster process, dump energy should be increased as far as possible higher and relay the probability that the larger node of the factor is elected as cluster head;

(2) node in network produces a random number between 0 ~ 1, if this random number is less than threshold value T (n), so this node is elected as cluster head;

(3) after node is elected as cluster head node, node broadcasts oneself becomes the message of cluster head towards periphery, after other ordinary nodes receive message, according to information such as signal strength signal intensities, selects optimum cluster head to add certain bunch, becomes the member of this bunch;

B. mixed logic dynamic process of establishing:

(1) the candidate region scope of the next-hop node of decision node; The alignment regions of next-hop node be defined in the conical area that drift angle is θ, the axis being parallel of circular cone is in the center line in tunnel.θ=60 ° herein, the angle namely between element of cone and center line in roadway is 30 °, if the included angle between the straight line at two node places and center line in roadway is less than 30 °, then this node is in candidate region;

According to energy consumption model, computing node n _itransmit data to next-hop node n _jdump energy desired value E _r(i);

$E_r\left(i\right)=\left\{\begin{array}{c}{E}_{current}\left(i\right)-(l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;{d_{ij}}^2),(d_{ij}<d_0)\\ E_{current}\left(i\right)-(l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{mp}\&CenterDot;{d_{ij}}^4),(d_{ij}\&GreaterEqual;d_0)\end{array}\right.$

(2) use greedy algorithm is using the weight function P (i, j) of node as target function, is arranged from big to small by target function, selects the maximum node of target function as next-hop node;

P(i,j)＝αE _r(i)+βE(j)+λS(j)

(3) network determines overall optimal data transmission route by the most next-hop node in local.

2. the Three-dimensional Mine mixed logic dynamic algorithm based on greedy thought according to claim 1, it is characterized in that: the deployed position portion of described space nodes determines as follows: be two-dimensional coordinate by three dimensional space coordinate Information Simplification, in two-dimensional space, X-axis represents the distance along tunnel bottom centre axial line distance sink node, Y represents the arc length bottom node to tunnel, and in long and narrow tunnel, the coordinate of known 2 is respectively n _i(x _i, y _i), n _j(x _j, y _j), utilize geometric knowledge can calculate distance d between two nodes _ij;

$d_{ij}=\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{|y_i-y_j|}{2r}\right)\&rsqb;}^2}.$

3. the Three-dimensional Mine mixed logic dynamic algorithm based on greedy thought according to claim 1, is characterized in that: the threshold value T (n) of described network node is determined by following formula:

$T\left(n\right)=\left\{\begin{array}{cc}\frac{p}{1-p\&times;\&lsqb;r\mathrm{mod}(1/p)\&rsqb;}\&CenterDot;\frac{E_{current}\left(n\right)}{E_{init}\left(n\right)}\&CenterDot;F\left(n\right)& n\&Element;G\\ 0& others\end{array}\right.$

$F\left(n\right)=\left\{\begin{array}{c}1,S_{current}\left(n\right)\&GreaterEqual;S_{avg}\\ q,S_{current}\left(n\right)<S_{avg}\end{array}\right.$

Wherein, p is the percentage of cluster head shared by all nodes, and r is carried out election wheel number, and what rmod (1/p) represented is that this takes turns in circulation the node number being elected to cluster head node, E _currentn () is the current dump energy of this node, E _initn primary power that () is this node, G is the set taking turns in circulation the node not being elected to cluster head at this, S _currentthe n relay factor that () is present node, S _avgthe average relay factor, q is the random number between (0,1).

4. according to claim 1ly it is characterized in that: the process of establishing of described mixed logic dynamic based on mixed logic dynamic algorithm under the three-dimensional well of greedy thought, the next-hop node selection mode of transfer of data is as follows:

Known 2 n _i(x _i, y _i), n _j(x _j, y _j), wherein n _ifor source node, when node meet below formula time, then node n _jat n _inext-hop node candidate region in;

$\frac{x_i-x_j}{\sqrt{{(x_i-x_j)}^2+{\&lsqb;2r\sin \left(\frac{|y_i-y_j|}{2r}\right)\&rsqb;}^2}}\&GreaterEqual;\frac{\sqrt{3}}{2}$

According to energy consumption model, computing node n _itransmit data to next-hop node n _jdump energy desired value E _r(i);

$E_r\left(i\right)=\left\{\begin{array}{c}{E}_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;({(x_i-x_j)}^2+{\left(2r\sin \right(\frac{|y_i-y_j|}{2r}\left)\right)}^2)\&rsqb;,(d_{ij}<d_0)\\ E_{current}\left(i\right)-\&lsqb;l\&CenterDot;E_{elec}+l\&CenterDot;{\mathrm{\&epsiv;}}_{fs}\&CenterDot;{({(x_i-x_j)}^2+{\left(2r\sin \right(\frac{|y_i-y_j|}{2r}\left)\right)}^2)}^2\&rsqb;,(d_{ij}\&GreaterEqual;d_0)\end{array}\right.$

Use greedy algorithm using the weight function P (i, j) of node as target function, arranged from big to small by target function, select the maximum node of target function as next-hop node, the expression formula of weight function P (i, j) is as follows:

P(i,j)＝αE _r(i)+βE(j)+λS(j)

Wherein α, β, λ are constant parameter, and alpha+beta+λ=1; Node chooses the next-hop node of local optimum according to weight function, and locally optimal solution combines and obtains the optimal path of transfer of data.