CN102202372B - Chain routing method of wireless sensor network based on fuzzy theory - Google Patents

Abstract

The invention discloses a chain routing method of a wireless sensor network based on a fuzzy theory in the communication technical field of communication of wireless sensor networks. The method is characterized by comprising the following steps of: constructing a network node into a chain with a branch; establishing a membership function that node surplus energy and the node become the chain fistpossibility and a membership function that the distance between the node and the node base station and the node become the chain fist possibility; after performing fusion of the two membership functions, selecting the maximum node as the chain first; and then establishing the routing. According to the invention, long-chain generation and uncertainty of threshold definition can be avoided; the defect of an EEPB (Energy-Efficient PEGASIS-Based) protocol is improved; energy consumption of the whole network node is balanced; and the life cycle of the network is further improved.

Description

Chain routing method of wireless sensor network based on fuzzy theory

Technical field

The invention belongs to the network communication of wireless sensor technical field, relate in particular to a kind of chain routing method of wireless sensor network based on fuzzy theory.

Background technology

The develop rapidly of MEMS (micro electro mechanical system), SOC (system on a chip), radio communication and low-power-consumption embedded technology is pregnant with wireless sensor network, the change that its low-power consumption, low cost, characteristics distributed and self-organizing have been brought information Perception.But, the wireless sensor network of design high energy efficiency is still one of significant challenge that we face, because the energy of node is extremely limited in wireless sensor network, node is placed in the complex environment, in case running down of battery, can't carry out power supply supplies with, simultaneously communication and the computing capability of node are all limited, thus how the optimize communicate path, improve the important issue that the problems such as energy efficiency and energy consumption balance, maximization network life cycle just become the design Wireless Sensor Network Routing Protocol.

Effectively Routing Protocol can be realized the equilibrium use of node energy, and many Wireless Sensor Network Routing Protocols are suggested.According to network topology structure, they can be divided into plane Routing Protocol and hierarchical routing, and wherein the hierarchy type route has higher energy efficiency, it is divided into the efficient forwarding data of different sub-network with sensor node, has avoided the overlapping energy dissipation that causes of neighbor node transmission message in the plane formula route.

The PEGASIS agreement is a kind of typical hierarchy type Routing Protocol based on chain structure, and its core concept is to utilize greedy algorithm to generate a strand that is comprised of all nodes, and node is only communicated by letter with the neighbor node of oneself on the chain.Except end node, the data that each node is received oneself merge with the data that oneself produces, and then the data after will merging pass to adjacent node on the chain along the first-in-chain(FIC) node direction, until data arrive the first-in-chain(FIC) node, the first-in-chain(FIC) node is responsible for data are sent to the base station of far-end.This method for routing is compared cluster routing method and has been obtained to a certain extent the equilibrium of node energy consumption and the prolongation of network life, produces the impact that the factors such as long-chain and base station position information are brought network performance between node but ignored.

The EEPB agreement is improved on the PEGASIS basis, and it avoids producing between adjacent node long-chain by introducing distance threshold value.Choose the first-in-chain(FIC) node and according to the gravity treatment frequency of nodes surplus ratio decision first-in-chain(FIC) node by considering residue energy of node and node to the distance of base station.This agreement has more superior performance than the PEGASIS agreement aspect balance node energy consumption and the prolong network lifetime, but because the uncertainty of definition threshold value, threshold value is chosen the improper long-chain that then is difficult to avoid, although and the choosing method of first-in-chain(FIC) considers residue energy of node and node to these 2 factors of base station distance but fails to disclose more accurately both and the first-in-chain(FIC) relation between choosing, and promotes limited to network performance.

Summary of the invention

Be difficult to avoid long-chain, threshold value to be difficult to the deficiencies such as selection for mentioning existing method in the above-mentioned background technology, the present invention proposes a kind of chain routing method of wireless sensor network based on fuzzy theory.

Technical scheme of the present invention is based on the chain routing method of wireless sensor network of fuzzy theory, to it is characterized in that the method may further comprise the steps:

Step 1: netinit is built into a chain that branch is arranged with nodes;

Step 2: set up the membership function that residue energy of node and node become the first-in-chain(FIC) possibility;

Step 3: set up node becomes the first-in-chain(FIC) possibility to the distance of base station and node membership function;

Step 4: two membership functions in step 2 and the step 3 are merged;

Step 5: choose node maximum after merging as first-in-chain(FIC), finish the foundation of route.

Described step 1 specifically may further comprise the steps:

Step 1.1: base station broadcast sends initial message, obtains current network survival node ID tabulation and node to the distance tabulation of base station;

Step 1.2: will be apart from base station node farthest as end node, nodal scheme is 1;

Step 1.3: the end node of chain arrives its range information by obtaining the node that does not enter chain in the network, find from the node i of its nearest node as chain to be added;

Step 1.4: node i is obtained i-1 node adding on the chain to its range information, find from its nearest node j and with its adding chain that directly links to each other, node i becomes end node new on the chain;

Step 1.5: repeating step 1.3 and step 1.4, until all nodes all add chain, build up a chain that branch is arranged.

The computing formula of the membership function of described step 2 is:

${\mathrm{\&mu;}}_e\left(i\right)=\left\{\begin{array}{c}\frac{150\&times;F_e\left(i\right)}{\log 2(1+200)},F_e\left(i\right)<\frac{1.0}{150}\\ \frac{\log 2(1+150\&times;F_e\left(i\right))}{\log 2(1+200)},\mathrm{else}\end{array}\right.$

Wherein:

μ _e(i) be node i is under the jurisdiction of first-in-chain(FIC) based on dump energy membership function value;

F _e(i) be the dump energy normalized value of node i.

Described F _e(i) computing formula is:

$F_e\left(i\right)=\frac{E_{\mathrm{res}}\left(i\right)}{E_0}$

Wherein:

E _Res(i) be the current dump energy of node i;

E ₀Primary power for node.

The computing formula of the membership function of described step 3 is:

${\mathrm{\&mu;}}_d\left(i\right)=e^{-\frac{{(F_d\left(i\right)-c)}^2}{2{\mathrm{\&sigma;}}^2}}$

Wherein:

μ _d(i) be node i is under the jurisdiction of first-in-chain(FIC) based on the distance to the base station membership function value;

F _d(i) be the range normalization value of node i to the base station;

σ is for regulating the parameter of membership function;

C is for regulating the parameter of membership function.

Described F _d(i) computing formula is:

$F_d\left(i\right)=\frac{d_{\mathrm{toBS}}\left(i\right)}{d_{\mathrm{MAX}}}$

Wherein:

d _ToBS(i) be the distance of node i to the base station;

d _MAXBe the distance to the base station of node farthest.

The value of described σ is:

σ＝1.0。

The value of described c is:

c＝0。

The fusion formula of described step 4 is:

$\mathrm{\&mu;}\left(i\right)=\frac{{\mathrm{\&mu;}}_e\left(i\right)\&times;{\mathrm{\&mu;}}_d\left(i\right)}{1-{\mathrm{\&mu;}}_e\left(i\right)-{\mathrm{\&mu;}}_d\left(i\right)+2\&times;{\mathrm{\&mu;}}_e\left(i\right)\&times;{\mathrm{\&mu;}}_d\left(i\right)}$

Wherein:

μ (i) is under the jurisdiction of the membership function value of first-in-chain(FIC) for node i.

Definite step of first-in-chain(FIC) is in the described step 5:

Step 5.1: each node calculates the membership function value μ (i) of oneself on the chain;

Step 5.2: the node with maximum μ (i) value becomes the first-in-chain(FIC) that this is taken turns by the base station broadcast notice.

Beneficial effect of the present invention is: in the link setup stage, and the distance between twice comparison node, and connect the node with shortest path and enter chain, avoided the uncertainty of generation and the threshold value definition of long-chain; Simultaneously, choose the stage at first-in-chain(FIC) and set up membership function based on fuzzy theory, utilize Triangle Module to merge operator and consider residue energy of node and node to 2 factors of distance of base station, characterizing node becomes the possibility of first-in-chain(FIC), thereby balance the energy consumption of whole network node, finally improve the whole life cycle of network.

Description of drawings

Fig. 1 is based on the flow chart of the chain routing method of wireless sensor network of fuzzy theory;

Fig. 2 is the flow chart of node link setup in the wireless sensor network;

Fig. 3 is the illustraton of model after utilizing chain routing method of wireless sensor network based on fuzzy theory with the sensor network nodes link setup;

Fig. 4 is node survival number comparative graph;

Fig. 5 is every average energy consumption comparative graph of taking turns.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.Should be emphasized that following explanation only is exemplary, rather than in order to limit the scope of the invention and to use.

The present invention has overcome the deficiency of existing chain routing method of wireless sensor network, a kind of chain routing method of wireless sensor network based on fuzzy theory has been proposed, by adopting new link constructing method, avoided the generation of long-chain, and when the first-in-chain(FIC) node selection by introducing fuzzy theory, consider residue energy of node and node to 2 factors of distance of base station, guarantee the harmony of node energy consumption, improve network lifecycle.

Below in conjunction with accompanying drawing, the method for the invention is elaborated.Should be emphasized that following explanation only is exemplary, rather than in order to limit the scope of the invention and to use.

The present invention includes following step:

1: netinit is built into a chain that branch is arranged with nodes;

2: set up the membership function that residue energy of node and node become the first-in-chain(FIC) possibility;

3: set up node becomes the first-in-chain(FIC) possibility to the distance of base station and node membership function;

4: utilize the Generalized Triangular Norm that two membership functions in step 2 and the step 3 are merged;

5: choose node maximum after merging as this first-in-chain(FIC) of taking turns, Route establishment is finished, beginning data acquisition and transmission.

Figure 1 shows that specific implementation process of the present invention.

Initialization network environment: at random, uniform broadcasting is a plurality of has an identical primary power E ₀, same communication ability and sensing ability sensor node, sensor node is known the geographical position of oneself and should be had unique ID, each node can both perception oneself dump energy, the sensor node of spreading adds up to 100 (disregarding aggregation node), and the area of overlay area is 100 meters * 100 meters; Base station (aggregation node) is deployed in the position away from meshed network, and coordinate is made as (50,300); Sensor node can be directly and base station communication; The power of base station and data-handling capacity will far be better than general sensor nodes.

The beginning link setup, its process may further comprise the steps as shown in Figure 2:

1) base station broadcast sends initial message " hello ", obtains the positional information of all nodes of network;

2) will be apart from base station node farthest as end node, nodal scheme is 1;

3) end node is by obtaining the residue of network organization node to its range information and seeking from the node of its nearest node as i chain to be added, and i represents that node adds the order of chain;

4) node i is obtained i-1 the node that adds on the chain and is arrived its range information, finds from its nearest node j and coupled, and node i adds chain also becomes new end node;

5) repeat above-mentioned steps until the residue node set is judged as empty set, namely all nodes have entered chain, build up a chain that branch is arranged.

Figure 3 shows that the chain that branch is arranged that 100 nodes of random distribution in the network obtain by above-mentioned link constructing method.The open circles node is apart from base station node farthest, and first adds chain, so label is 1.

Choose the stage at first-in-chain(FIC), it is close to the distance relation of base station whether node becomes first-in-chain(FIC) and residue energy of node and it.We preferentially choose dump energy high and apart from the near node in base station as first-in-chain(FIC), but because this relation is difficult to definite statement, the present invention adopts the membership function of variable to characterize the possibility that node becomes first-in-chain(FIC), set up respectively the membership function that these two characteristic parameters and node become the first-in-chain(FIC) possibility based on fuzzy theory, utilize at last the Generalized Triangular Norm that judgement is unified in its fusion, choose first-in-chain(FIC) according to the maximum principle of degree of membership value.

Setting up residue energy of node situation and node becomes the membership function of first-in-chain(FIC) possibility:

${\mathrm{\&mu;}}_e\left(i\right)=\left\{\begin{array}{c}\frac{150\&times;F_e\left(i\right)}{\log 2(1+200)},F_e\left(i\right)<\frac{1.0}{150}\\ \frac{\log 2(1+150\&times;F_e\left(i\right))}{\log 2(1+200)},\mathrm{else}\end{array}\right.$

Wherein:

μ _e(i) be node i is under the jurisdiction of first-in-chain(FIC) based on dump energy membership function value;

F _e(i) be the dump energy normalized value of node i,

Wherein, E _Res(i) be the current dump energy of node i; E ₀Primary power for node.

Set up node and become the membership function of first-in-chain(FIC) possibility to the base station apart from situation and node:

${\mathrm{\&mu;}}_d\left(i\right)=e^{-\frac{{(F_d\left(i\right)-c)}^2}{2{\mathrm{\&sigma;}}^2}}$

Wherein:

μ _d(i) be node i is under the jurisdiction of first-in-chain(FIC) based on the distance to the base station membership function value;

F _d(i) be the range normalization value of node i to the base station, d _ToBS(i) be the distance of node i to the base station; d _MAXBe the distance to the base station of node farthest;

σ is for regulating the parameter of membership function, σ=1.0;

C is for regulating the parameter of membership function, c=0.

Use fuzzy theory, utilize the Generalized Triangular Norm that above-mentioned two membership functions are merged:

$\mathrm{\&mu;}\left(i\right)=\frac{{\mathrm{\&mu;}}_e\left(i\right)\&times;{\mathrm{\&mu;}}_d\left(i\right)}{1-{\mathrm{\&mu;}}_e\left(i\right)-{\mathrm{\&mu;}}_d\left(i\right)+2\&times;{\mathrm{\&mu;}}_e\left(i\right)\&times;{\mathrm{\&mu;}}_d\left(i\right)}$

Wherein:

μ (i) is under the jurisdiction of the membership function value of first-in-chain(FIC) for node i, chooses the node of μ (i) value maximum as this first-in-chain(FIC) node of taking turns according to the maximum principle of membership function value.

Definite step of first-in-chain(FIC) is:

(1) each node calculates the membership function value μ (i) of oneself on the chain;

(2) node that has maximum μ (i) value becomes the first-in-chain(FIC) that this is taken turns by the base station broadcast notice.

Base station broadcast was notified all nodes after the first-in-chain(FIC) node selection was finished, and sent Beacon information and triggered this Data Collection of taking turns and transmission, and adopt the TDMA mode to distribute the time slot of each node.By the end node log-on data transmission course of the control token packet after the process first-in-chain(FIC) node initializing from chain, end node is passed to adjacent node with its data along the first-in-chain(FIC) node direction, until data arrive the first-in-chain(FIC) node, the first-in-chain(FIC) node sends telepoint base station to after with data fusion, and one takes turns data transfer procedure finishes.

For the performance based on the chain routing method of wireless sensor network of fuzzy theory of checking that the present invention proposes, itself and EEPB agreement are carried out emulation and relatively under the identical network environment.

Adopt Matlab as emulation tool, the system emulation environmental parameter arranges as follows:

1) base station is away from sensor node, and static, and coordinate is (50,300);

2) all node isomorphisms in the network, primary power is the identical erg-ten that is also, and sensor node does not have mobility;

3) 100 nodes are randomly dispersed in 100 meters * 100 meters the zone, abscissa scope (0,100), ordinate scope (0,100);

4) transmitting and receiving dynamo-electric road, to process the energy that 1 Bit data consumes be 50 joules ^-9, i.e. E _Elec=50 joules ^-9/ bit;

5) adopting the free space model to transmit and receive dynamo-electric road direction unit are, to launch the energy that 1 Bit data consumes be 100 joules ^-12, i.e. ε _Fs=100 joules ^-12/ bit/rice ²

6) adopt the Multipath Transmission model transmit and receive dynamo-electric road direction unit are square the zone in the energy that consumes of emission 1 Bit data be 0.0013 joule ^-12, i.e. ε _Mp=0.0013 joule ^-12/ bit/rice ⁴

7) length L of each packet=3000 bits;

8) EEPB agreement middle distance threshold value coefficient value is α=1.2;

Above parameter is also non-constant, can change as required some parameter for different emulation contents.

Fig. 4 is the simulation result of survival node number in the network, and wherein, dotted line is the EEPB agreement; Solid line is the chain type Routing Protocol based on fuzzy theory.

EEPB agreement first node when the 383rd takes turns is dead, and 50% node is dead when 1864 take turns, and 100% node is dead when 1916 take turns.And dead based on chain type Routing Protocol first node when the 1596th takes turns of fuzzy theory, 50% node is dead when 1981 take turns, and 100% node is dead when taking turns to 2063.Can find out that the method among the present invention can improve the life cycle of network effectively.

Fig. 5 uses two kinds of agreements at every afterwards average residual energy simulation result of node of transfer of data of taking turns under the equivalent environment, dotted line is the EEPB agreement; Solid line is the chain type Routing Protocol based on fuzzy theory.

Can find out that use can remain more energy based on the node of the chain type Routing Protocol of fuzzy theory than the node that uses the EEPB agreement, and along with the increase of taking turns number, its advantage is more and more obvious.

Simulation result shows, method for routing among the present invention has been avoided the generation of long-chain between node and has been reduced transmission range sum between the whole network node, reduced the energy consumption of the whole network the transmission of data, optimized choosing of first-in-chain(FIC) node, the energy consumption that guarantees node is more balanced, thereby has effectively improved the life cycle of wireless sensor network.

The above; only for the better 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 the technical scope that the present invention discloses; the variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.

Claims (4)

1. based on the chain routing method of wireless sensor network of fuzzy theory, it is characterized in that the method may further comprise the steps:

Step 1: netinit, nodes is built into a chain that branch is arranged, specifically may further comprise the steps:

Step 1.1: base station broadcast sends initial message, obtains current network survival node ID tabulation and node to the distance tabulation of base station;

Step 1.2: will be apart from base station node farthest as end node, nodal scheme is 1;

Step 1.3: the end node of chain arrives its range information by obtaining the node that does not enter chain in the network, find from the node i of its nearest node as chain to be added;

Step 1.4: node i is obtained i-1 node adding on the chain to its range information, find from its nearest node j and with its adding chain that directly links to each other, node i becomes end node new on the chain;

Step 1.5: repeating step 1.3 and step 1.4, until all nodes all add chain, build up a chain that branch is arranged;

Step 2: set up node is under the jurisdiction of first-in-chain(FIC) based on dump energy membership function; The computing formula of described membership function is:

${\mathrm{\&mu;}}_e\left(i\right)=\left\{\begin{array}{c}\frac{150\&times;F_e\left(i\right)}{{\log }_2(1+200)},F_e\left(i\right)<\frac{1.0}{150}\\ \frac{{\log }_2(1+150\&times;F_e\left(i\right))}{{\log }_2(1+200)},\mathrm{else}\end{array}\right.$

Wherein:

μ _e(i) be node i is under the jurisdiction of first-in-chain(FIC) based on dump energy membership function value;

F _e(i) be the dump energy normalized value of node i;

Step 3: set up node is under the jurisdiction of first-in-chain(FIC) based on the distance to the base station membership function; The computing formula of described membership function is:

${\mathrm{\&mu;}}_d\left(i\right)=e^{\frac{{(F_d\left(i\right)-c)}^2}{2{\mathrm{\&sigma;}}^2}}$

Wherein:

μ _d(i) be node i is under the jurisdiction of first-in-chain(FIC) based on the distance to the base station membership function value;

F _d(i) be the range normalization value of node i to the base station;

σ is for regulating the parameter of membership function; The value of described σ is:

σ=1.0；

C is for regulating the parameter of membership function; The value of described c is:

c=0；

Step 4: two membership functions in step 2 and the step 3 are merged; Described fusion formula is:

$\mathrm{\&mu;}\left(i\right)=\frac{{\mathrm{\&mu;}}_e\left(i\right)\&times;{\mathrm{\&mu;}}_d\left(i\right)}{1-{\mathrm{\&mu;}}_e\left(i\right)-{\mathrm{\&mu;}}_d\left(i\right)+2\&times;{\mathrm{\&mu;}}_e\left(i\right)\&times;{\mathrm{\&mu;}}_d\left(i\right)}$

Wherein:

μ (i) is under the jurisdiction of the membership function value of first-in-chain(FIC) for node i;

Step 5: choose the node of fusion membership function value maximum as first-in-chain(FIC), finish the foundation of route.

2. the chain routing method of wireless sensor network based on fuzzy theory according to claim 1 is characterized in that described F _e(i) computing formula is:

$F_e\left(i\right)=\frac{E_{\mathrm{res}}\left(i\right)}{E_0}$

Wherein:

E _Res(i) be the current dump energy of node i;

E ₀Primary power for node.

3. the chain routing method of wireless sensor network based on fuzzy theory according to claim 1 is characterized in that described F _d(i) computing formula is:

$F_d\left(i\right)=\frac{d_{\mathrm{toBS}}\left(i\right)}{d_{\mathrm{MAX}}}$

Wherein:

d _ToBS(i) be the distance of node i to the base station;

d _MAXBe the distance to the base station of node farthest.

4. the chain routing method of wireless sensor network based on fuzzy theory according to claim 1 is characterized in that definite step of first-in-chain(FIC) is in the described step 5:

Step 5.1: each node calculates the membership function value μ (i) of oneself on the chain;

Step 5.2: the node with maximum μ (i) value becomes the first-in-chain(FIC) that this is taken turns by the base station broadcast notice.

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