CN103118373A - Wireless sensor network low energy-consumption coverage optimization algorithm - Google Patents

Abstract

The invention discloses wireless sensor network low energy-consumption coverage optimization algorithm. On the premise of lowest energy consumption of round clusters, backbone node optimal value which can satisfy coverage capacity can be obtained. By using PSO (particle swarm optimization) to dynamically adjust flying direction and speed of nodes and a backbone node deployment scheme which uses step-by-step iteration to obtain optimal coverage, data information in a sensing area can be collected effectively, sensor network resources can be fully managed, the problems that uneven backbone node distribution, optimal backbone node number cannot be achieved, network energy consumption is unbalanced, network coverage capacity is low and the like are solved effectively, technical support is provided for reasonably effectively deploying backbone nodes to reach high network coverage uniformity and network coverage rate on the premise of low energy consumption of sensor networks, and a novel solution is provided for improving area coverage capacity of networks on the premise of network low energy consumption.

Description

A kind of wireless sensor network low energy consumption coverage optimization algorithm

Technical field

The present invention relates to a kind of wireless sensor network low energy consumption coverage optimization algorithm, belong to the wireless sensor network technology field.

Background technology

Wireless, the multi-hop that wireless sensor network is comprised of a large amount of micro wireless sensor nodes, self-organizing network, its effect is perception synergistically, the information of processing perceptive object in the monitored area, and perception data is sent to aggregation node, be widely used in the numerous areas such as national defence, industry, agricultural, environment, medical treatment, logistics, anti-terrorism, deathtrap remote monitoring, key area protection.

Powerup issue is a Main Bottleneck that restricts at present the wireless sensor network technology development.Its system must be followed energy-conservation principle, to improve the energy service efficiency, extends the useful life of network.Under the prerequisite that guarantees the network low energy consumption, to satisfy simultaneously network node to the perception of physical world, namely reach the validity that network node covers.Therefore low energy consumption and the network coverage are taken into consideration and will more effectively be improved the network aware quality, the extensive use that promotes wireless sensor network is had important practical significance.

In the application of extensive hazardous environment, the node of wireless sensor network is all random placement.In the situation that the transducer random placement for guaranteeing that perception data can transmit smoothly, generally adopts hierarchical routing, i.e. clustering route protocol.The most basic problem of clustering route protocol is exactly selection and the distribution problem of backbone node.Classical hierarchical routing mainly contains LEACH agreement, HEED agreement, SEP agreement, MARQ agreement etc.The LEACH agreement adopts distributed bootstrapping Clustering Algorithm and backbone node rotation mechanism, solves the problem of backbone node energy consumption undue concentration.But still have some problems: the randomness of backbone node election may cause backbone node at the same area too intensive or too close network edge, the backbone node number is difficult to reach optimal value, network coverage ability can't obtain effectively guaranteeing etc.The HEED agreement by to residue energy of node and bunch in the assessment iteration cluster of communication energy consumption.But be difficult to take full advantage of the energy heterogeneous characteristics under heterogeneous network environment, and the value of certain variable has a direct impact to the harmony that convergence rate reaches bunch distribution.The SEP agreement is for the design of the sensor network of two-stage energy heterogeneous, adopt the method for energy factors weighting, backbone node bootstrapping thresholding to two category nodes in network is optimized, and makes higher-level node that the larger probability that becomes backbone node be arranged, and has extended the stationary phase of network.But shortcoming is the network that this agreement is only applicable to the two-stage energy heterogeneous.The MARQ agreement adopts loose Fourier Series expansion technique, has introduced the concept of contact node, at the source node of initiating Query Information with provide between the destination node of information and set up a path optimizing.

Although above-mentioned these agreements can be improved hierarchical routing to a certain extent, these agreements all face an identical key problem, are exactly the problem that backbone node is chosen.The reasonability that backbone node is chosen directly has influence on harmony and the network coverage ability of network energy consumption, and then has influence on the life cycle of network and the reliability of network aware quality, and therefore, this is a reality technology difficult problem anxious to be resolved.

Summary of the invention

The objective of the invention is to overcome the weak point of the aspect such as the network energy consumption in the first election of wireless sensor network cluster algorithm and the network coverage in prior art, for improve the network application of network coverage ability under the prerequisite that guarantees the network low energy consumption, a kind of wireless sensor network low energy consumption coverage optimization algorithm is proposed.Core of the present invention is to obtain optimum backbone node number and neighbor node selection principle in conjunction with the coverage optimal models under the prerequisite of round bunch low energy consumption, improves the algorithm iteration computing according to PSO, obtains the optimum deployment scheme of backbone node.

The present invention proposes a kind of wireless sensor network low energy consumption coverage optimization algorithm, comprises the following steps:

1) based on the backbone node number optimized algorithm that guarantees round bunch energy consumption and covering power:

11) energy consumption of ordinary node comes from the transmission energy of perception data, and the energy consumption of backbone node mainly comes from and receives perception data, Data Fusion, data retransmission to the energy consumption of aggregation node, so the energy consumption of ordinary node is:

The energy consumption of backbone node is: $E_{\mathrm{CH}}={\mathrm{lE}}_{\mathrm{elec}}(N/k-1)+{\mathrm{lE}}_{\mathrm{DA}}N/k+{\mathrm{lE}}_{\mathrm{elec}}+{\mathrm{l\ϵd}}_{\mathrm{toSink}}^{\mathrm{\α}},$ Energy consumption in certain is taken turns bunch is:

E _C=L _CH+ (N/k-1) E _M, the network total energy consumption is $E_{\mathrm{total}}=l({2\mathrm{NE}}_{\mathrm{elec}}+{\mathrm{NE}}_{\mathrm{DA}}+{\mathrm{k\ϵd}}_{\mathrm{toSink}}^{\mathrm{\α}}+{\mathrm{N\ϵ}}_{\mathrm{fs}}{d}_{\mathrm{toCH}}^2).$ In formula, E _ElecBe the bit of transmission circuit unit data energy consumption; ε _fs, ε _mpBe respectively closely and power attenuation coefficient at a distance; d _ToCHBe the average of each ordinary node to the backbone node distance; E _DAFor merging the energy of the bit of unit data consumes; d _ToSinkBe the average of each backbone node to the aggregation node distance; d ₀Be reference distance, be generally

12) suppose that the monitored area length of side is M, a bunch shared zone is circular, and backbone node is positioned at a bunch center, and according to the coverage optimal models, namely adjacent any three backbone nodes become equilateral triangle, and the area approximation that can obtain thus each bunch shared zone is

The distribution law of node is

Ordinary node to the mathematical expectation of backbone node square distance is:

$E\left[d_{\mathrm{toCH}}^2\right]=\&Integral;\&Integral;(x^2+y^2)k/M^2{d}_x{d}_y=\sqrt{27}{\mathrm{<figure-callout\; id="2"\; label="M"\; filenames="HDA00002774233400021.png"\; state="\{\{state\}\}">M</figure-callout>}}^2/{\left(2\mathrm{\&pi;}\right)}^{2}k.$

13) according to network total energy consumption and ordinary node in round to the mathematical expectation of backbone node square distance, can obtain energy consumption the optimal value of hour backbone node k be

$k_{\mathrm{opt}}=\left\{\begin{array}{c}\frac{\sqrt[4]{27}\sqrt{\mathrm{<figure-callout\; id="2"\; label="N\; M"\; filenames="HDA00002774233400021.png"\; state="\{\{state\}\}">N</figure-callout>}}M}{2\mathrm{\&pi;}{d}_{\mathrm{toSink}}^2}\sqrt{\frac{{\mathrm{\&epsiv;}}_{\mathrm{fs}}}{{\mathrm{\&epsiv;}}_{\mathrm{mp}}}},d_{\mathrm{toSink}}\&GreaterEqual;{\mathrm{<figure-callout\; id="0"\; label="d"\; filenames="HDA00002774233400021.png"\; state="\{\{state\}\}">d</figure-callout>}}_0\\ \frac{\sqrt[4]{27}}{2\mathrm{\&pi;}{d}_{\mathrm{toSink}}^2},d_{\mathrm{toSink}}<{\mathrm{<figure-callout\; id="0"\; label="d"\; filenames="HDA00002774233400021.png"\; state="\{\{state\}\}">d</figure-callout>}}_0\end{array}\right.,$

ε _fs, ε _mpBe respectively closely and power attenuation coefficient at a distance; d ₀Be reference distance, be generally

2) be used for guaranteeing the inhomogeneity improvement sub-clustering of network coverage Deployment Algorithm:

21) cover uniformity and reflected the distribution situation of sensor node in the area to be monitored, according to the relation that covers distance between uniformity and node, adopt improvement sub-clustering Deployment Algorithm to obtain the covering uniformity index, the criterion distance difference is less, cover uniformity higher, the energy consumption of nodes is lower, specific as follows simultaneously:

$U=\frac{1}{k_{\mathrm{opt}}}\underset{i=1}{\overset{k_{\mathrm{opt}}}{\mathrm{\&Sigma;}}}{U}_i$

$U_i={\left(\frac{1}{k_i}\underset{j=1}{\overset{k_i}{\mathrm{\&Sigma;}}}{(D_{i,j}-M_i)}^2\right)}^{\frac{1}{2}}$

In formula U is for covering uniformity index, i.e. criterion distance difference index, k _optBe backbone node total number, k _iBe the neighbor node number of i backbone node, D _{I, j}Be the distance between i backbone node and j backbone node, M _iThe mean value that represents i backbone node and neighbours' backbone node distance.

22) choosing of neighbor node, the optimum distance that can obtain between backbone node according to coverage optimal models and optimum backbone node quantity is

In order to guarantee the network coverage, i backbone node of selected distance be (0, Ropt ± 2 (Rs-Ropt/2)] node be the neighbor node of this backbone node, R _sPerceived distance for backbone node.

3) be used for solving the backbone node skewness, balancing network coverage rate and the inhomogeneity improvement PSO of covering cover the efficiency optimized algorithm:

31) optimization aim is to satisfy the network coverage to maximize and cover the uniformity maximization, i.e. network coverage maximization, criterion distance difference minimize, and can obtain thus minimizing target function and be: f (X)=C ^-(1-α)U ^α, in formula, C and U are respectively the network coverage and the network coverage uniformity index of set of node N institute map network deployable state, and α is weight coefficient, is used for regulating the weight of optimizing two indexs, to adapt to the different constraints of wireless sensor network.

32) initialization Particle Swarm, according to the positional information of each particulate, the nearest node of backbone node in each particulate of detection range in set of node N, and as the initial particle X that troops.

33) according to the coverage optimal models, obtain desirable backbone node deployment information L in the monitored area, according to following formula, backbone node is carried out iterative evolution

$v_{\mathrm{ij}}^{k+1}={\mathrm{\&omega;v}}_{\mathrm{ij}}^k+c_1{r}_1(p_{\mathrm{ij}}^k-x_{\mathrm{ij}}^k)+c_2{r}_2(p_{\mathrm{gj}}^k-x_{\mathrm{ij}}^k)$

$x_{\mathrm{ij}}^{k+1}=x_{\mathrm{ij}}^k+v_{\mathrm{ij}}^{k+i},(V\max \&Subset;[\mathrm{Ropt}-2(\mathrm{Rs}-\mathrm{Ropt}/2),\mathrm{Ropt}+2(\mathrm{Rs}-\mathrm{Ropt}/2)\left]\right),$

The complete rear acquisition of per generation evolution has the backbone node collection positional information S of minimum fitness value, whether search satisfies set of node N in the scope of S ± 2 (Rs-Ropt/2), if satisfied upgrade corresponding backbone node positional information, (S ± L) is the heading of this node iteration next time otherwise λ is set.

the present invention is based on the backbone node number optimized algorithm that guarantees round bunch energy consumption and covering power, the present invention is guaranteeing under the minimum prerequisite of round bunch energy consumption, can obtain the backbone node optimal value that satisfies covering power, pass through simultaneously heading and the flying speed of the dynamic knot modification of PSO, progressively iteration is obtained the optimum backbone node deployment scheme that covers, can effectively gather the data message in perception zone, abundant management of sensor Internet resources again, the present invention has solved the backbone node skewness in the wireless sensor network application effectively, it is optimum that the backbone node number can't reach, the network energy consumption is unbalanced, the problems such as network coverage ability is on the low side, rationally effectively dispose backbone node for wireless sensor network and provide technical support to reach higher network coverage uniformity and the network coverage under the prerequisite that guarantees low energy consumption, for the regional covering power that improves network under the prerequisite of network low energy consumption provides a kind of brand-new solution.

Description of drawings

Fig. 1 is the main flow chart of a kind of wireless sensor network low energy consumption coverage optimization algorithm of the present invention;

Fig. 2 is the detail flowchart of a kind of wireless sensor network low energy consumption coverage optimization algorithm of the present invention.

Embodiment

Describe the present invention below in conjunction with drawings and Examples.As shown in Figure 1 and Figure 2, the present invention includes following steps:

(1) node adopts random intensive deployment way;

(2) each node periodicity reported energy information, positional information, node ID etc. are to aggregation node.Aggregation node is according to step 1) in energy consumption in epicycle and ordinary node to the mathematical expectation of backbone node square distance, can obtain the optimal value of the interior backbone node number of epicycle, namely

$k_{\mathrm{opt}}=\left\{\begin{array}{c}\frac{\sqrt[4]{27}\sqrt{\mathrm{<figure-callout\; id="2"\; label="N\; M"\; filenames="HDA00002774233400021.png"\; state="\{\{state\}\}">N</figure-callout>}}M}{2\mathrm{\&pi;}{d}_{\mathrm{toSink}}^2}\sqrt{\frac{{\mathrm{\&epsiv;}}_{\mathrm{fs}}}{{\mathrm{\&epsiv;}}_{\mathrm{mp}}}},d_{\mathrm{toSink}}\&GreaterEqual;{\mathrm{<figure-callout\; id="0"\; label="d"\; filenames="HDA00002774233400021.png"\; state="\{\{state\}\}">d</figure-callout>}}_0\\ \frac{\sqrt[4]{27}}{2\mathrm{\&pi;}{d}_{\mathrm{toSink}}^2},d_{\mathrm{toSink}}<{\mathrm{<figure-callout\; id="0"\; label="d"\; filenames="HDA00002774233400021.png"\; state="\{\{state\}\}">d</figure-callout>}}_0\end{array}\right.;$

(3) initialization Particle Swarm, according to the positional information of each particulate, the nearest node of backbone node in each particulate of detection range in set of node N, and as the initial particle X that troops;

(4) aggregation node according to network coverage model and Particle Swarm information, obtains the network coverage of each particulate, namely

$C=\frac{{\&Integral;}_0^M{\&Integral;}_0^{M}p(x,y,X)\mathrm{dxdy}}{M\&times;M};$

(5) according to step 2) obtain the network coverage uniformity index of each particulate;

(6) particulate of choosing the fitness value minimum is as optimal value, according to step 33) in the PSO iterative formula each particulate is evolved,

$v_{\mathrm{ij}}^{k+1}={\mathrm{\&omega;v}}_{\mathrm{ij}}^k+c_1{r}_1(p_{\mathrm{ij}}^k-x_{\mathrm{ij}}^k)+c_2{r}_2(p_{\mathrm{gj}}^k-x_{\mathrm{ij}}^k)$

$x_{\mathrm{ij}}^{k+1}=x_{\mathrm{ij}}^k+v_{\mathrm{ij}}^{k+1}$

C wherein ₁And c ₂Be generally equal to 2; Vmax=[Ropt-2 (Rs-Ropt/2), Ropt+2 (Rs-Ropt/2)]; r ₁And r ₂Be [0,1] interval interior equally distributed random number;

(7) the complete rear acquisition of per generation evolution has the backbone node collection positional information S of minimum fitness value, whether search satisfies set of node N in the scope of S ± 2 (Rs-Ropt/2), if satisfied upgrade corresponding backbone node positional information, (S ± L) is the heading of this node iteration next time otherwise λ is set;

(8) satisfy maximum iteration time after, obtain the particulate with adaptive optimal control degree value, and obtain the optimum deployment scheme of backbone node;

(9) information of aggregation node broadcasting backbone node, corresponding backbone node is claimed as cluster head, but and sends broadcast message to the ordinary node of interaction data, so far network topology structure formation.

The above; be only the specific embodiment of the present invention, but protection scope of the present invention is not limited to this, anyly is familiar with those skilled in the art in scope disclosed by the invention; the variation that can expect easily or replacement all should be encompassed in the protection range of claim of the present invention.

Claims (3)

1. the present invention proposes a kind of wireless sensor network low energy consumption coverage optimization algorithm, it is characterized in that, comprises the following steps:

1) based on the backbone node number optimized algorithm that guarantees round bunch energy consumption and covering power:

11) energy consumption of ordinary node comes from the transmission energy of perception data, and the energy consumption of backbone node mainly comes from and receives perception data, Data Fusion, data retransmission to the energy consumption of aggregation node, so the energy consumption of ordinary node is: The energy consumption of backbone node is: $E_{\mathrm{CH}}={\mathrm{lE}}_{\mathrm{elec}}(N/k-1)+{\mathrm{lE}}_{\mathrm{DA}}N/k+{\mathrm{lE}}_{\mathrm{elec}}+{\mathrm{l\&epsiv;d}}_{\mathrm{toSink}}^{\mathrm{\&alpha;}},$ Energy consumption in certain is taken turns bunch is:

E _C=E _CH+ (N/k-1) E _M, the network total energy consumption is $E_{\mathrm{total}}=l({2\mathrm{NE}}_{\mathrm{elec}}+{\mathrm{NE}}_{\mathrm{DA}}+{\mathrm{k\&epsiv;d}}_{\mathrm{toSink}}^{\mathrm{\&alpha;}}+{\mathrm{N\&epsiv;}}_{\mathrm{fs}}{d}_{\mathrm{toCH}}^2),$ In formula, E _ElecBe the bit of transmission circuit unit data energy consumption; ε _fs, ε _mpBe respectively closely and power attenuation coefficient at a distance; d _ToCHBe the average of each ordinary node to the backbone node distance; E _DAFor merging the energy of the bit of unit data consumes; d _ToSinkBe the average of each backbone node to the aggregation node distance; d ₀Be reference distance, be generally

12) suppose that the monitored area length of side is M, a bunch shared zone is circular, and backbone node is positioned at a bunch center, and according to the coverage optimal models, namely adjacent any three backbone nodes become equilateral triangle, and the area approximation that can obtain thus each bunch shared zone is

The distribution law of node is

Ordinary node to the mathematical expectation of backbone node square distance is:

$E\left[d_{\mathrm{toCH}}^2\right]=\&Integral;\&Integral;(x^2+y^2)k/M^2{d}_x{d}_y=\sqrt{27}{M}^2/{\left(2\mathrm{\&pi;}\right)}^{2}k;$

13) according to network total energy consumption and ordinary node in round to the mathematical expectation of backbone node square distance, can obtain energy consumption the optimal value of hour backbone node k be

$k_{\mathrm{opt}}=\left\{\begin{array}{c}\frac{\sqrt[4]{27}\sqrt{N}M}{2\mathrm{\&pi;}{d}_{\mathrm{toSink}}^2}\sqrt{\frac{{\mathrm{\&epsiv;}}_{\mathrm{fs}}}{{\mathrm{\&epsiv;}}_{\mathrm{mp}}}},d_{\mathrm{toSink}}\&GreaterEqual;d_0\\ \frac{\sqrt[4]{27}}{2\mathrm{\&pi;}{d}_{\mathrm{toSink}}^2},d_{\mathrm{toSink}}<d_0\end{array}\right.,$

ε _fs, ε _mpBe respectively closely and power attenuation coefficient at a distance; d ₀Be reference distance, be generally

2) be used for guaranteeing the inhomogeneity improvement sub-clustering of network coverage Deployment Algorithm:

21) cover uniformity and reflected the distribution situation of sensor node in the area to be monitored, according to the relation that covers distance between uniformity and node, adopt improvement sub-clustering Deployment Algorithm to obtain the covering uniformity index, the criterion distance difference is less, cover uniformity higher, the energy consumption of nodes is lower, specific as follows simultaneously:

$U=\frac{1}{k_{\mathrm{opt}}}\underset{i=1}{\overset{k_{\mathrm{opt}}}{\mathrm{\&Sigma;}}}{U}_i$

$U_i={\left(\frac{1}{k_i}\underset{j=1}{\overset{k_i}{\mathrm{\&Sigma;}}}{(D_{i,j}-M_i)}^2\right)}^{\frac{1}{2}}$

In formula U is for covering uniformity index, i.e. criterion distance difference index, k _optBe backbone node total number, k _iBe the neighbor node number of i backbone node, D _{I, j}Be the distance between i backbone node and j backbone node, M _iThe mean value that represents i backbone node and neighbours' backbone node distance;

22) choosing of neighbor node, the optimum distance that can obtain between backbone node according to coverage optimal models and optimum backbone node quantity is

In order to guarantee the network coverage, i backbone node of selected distance be (0, Ropt ± 2 (Rs-Ropt/2)] node be the neighbor node of this backbone node, R _sPerceived distance for backbone node;

3) be used for solving the backbone node skewness, balancing network coverage rate and the inhomogeneity improvement PSO of covering cover the efficiency optimized algorithm:

31) optimization aim is to satisfy the network coverage to maximize and cover the uniformity maximization, i.e. network coverage maximization, criterion distance difference minimize, and can obtain thus minimizing target function and be: f (X)=C ^-(1-α)U ^α, in formula, C and U are respectively the network coverage and the network coverage uniformity index of set of node N institute map network deployable state, and α is weight coefficient, is used for regulating the weight of optimizing two indexs, to adapt to the different constraints of wireless sensor network;

32) initialization Particle Swarm, according to the positional information of each particulate, the nearest node of backbone node in each particulate of detection range in set of node N, and as the initial particle X that troops;

33) according to the coverage optimal models, obtain desirable backbone node deployment information L in the monitored area, according to following formula, backbone node is carried out iterative evolution

$v_{\mathrm{ij}}^{k+1}={\mathrm{\&omega;v}}_{\mathrm{ij}}^k+c_1{r}_1(p_{\mathrm{ij}}^k-x_{\mathrm{ij}}^k)+c_2{r}_2(p_{\mathrm{gj}}^k-x_{\mathrm{ij}}^k)$

$x_{\mathrm{ij}}^{k+1}=x_{\mathrm{ij}}^k+v_{\mathrm{ij}}^{k+i},(V\max \&Subset;[\mathrm{Ropt}-2(\mathrm{Rs}-\mathrm{Ropt}/2),\mathrm{Ropt}+2(\mathrm{Rs}-\mathrm{Ropt}/2)\left]\right),$

The complete rear acquisition of per generation evolution has the backbone node collection positional information S of minimum fitness value, whether search satisfies set of node N in the scope of S ± 2 (Rs-Ropt/2), if satisfied upgrade corresponding backbone node positional information, (S ± L) is the heading of this node iteration next time otherwise λ is set.

2. a kind of wireless sensor network low energy consumption coverage optimization algorithm according to claim 1, it is characterized in that, described step 1) is to obtain optimum backbone node number and neighbor node selection principle in conjunction with the coverage optimal models under the prerequisite of round bunch low energy consumption, improve the algorithm iteration computing according to PSO, obtain the optimum deployment scheme of backbone node.

3. a kind of wireless sensor network low energy consumption coverage optimization algorithm according to claim 1, it is characterized in that, by heading and the flying speed of the dynamic knot modification of PSO, progressively iteration is obtained the optimum backbone node deployment scheme that covers to described step 3) simultaneously.

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