CN106658641A - Distributed wireless sensor network clustering routing method - Google Patents
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- CN106658641A CN106658641A CN201611235772.9A CN201611235772A CN106658641A CN 106658641 A CN106658641 A CN 106658641A CN 201611235772 A CN201611235772 A CN 201611235772A CN 106658641 A CN106658641 A CN 106658641A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
- H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
- H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a distributed wireless sensor network clustering routing method, which mainly solves a problem that network energy load is unbalance caused by a hot area problem when a node in a wireless sensor network cluster performs data transmission by utilizing a multi-hopping communication mod. The method is a distributed method, and the node does not depend on perception on a network whole topological structure and only depends on self information and neighbor node information to elect a reasonable cluster head node with combination of fuzzy logic. At a cluster head election stage, the node is subject to performance analysis by utilizing the fuzzy logic. According to the distributed wireless sensor network clustering routing method, node energy, node degree (neighbor node number) and neighbor node energy are taken as evaluation indexes, thereby effectively alleviating the common hot area problem during multi-hopping communication, improving the robustness of a structure network, prolonging life cycle of the network, and improving system data transmission efficiency.
Description
Technical field
The present invention relates to radio sensing network Internet optimisation technique, and in particular to a kind of Distributed Wireless Sensor Networks point
Cluster method for routing.
Background technology
Radio sensing network (Wireless Sensor Networks, WSNs) is a kind of multihop self-organizing network system,
It is made up of a large amount of sensor nodes, is interconnected by way of radio communication between node.In general, wireless sensing
Network is made up of sensor node and aggregation node, and each sensor node has the work(of data receiver and data forwarding
Can, that is to say, that each node both can be ordinary node, it is also possible to realize the effect of routing forwarding.Aggregation node then equivalent to
The role of gateway, the information that sensor node is collected for being both responsible for administering designated area carries out data fusion, in addition it is also necessary to
It is responsible for being communicated with external network (internet, mobile communications network, satellite communication etc.).With the development of wireless communication technology
And application of the low-consumption wireless radio-frequency module on sensor node, radio sensing network has been widely used for intelligence now
Among household, environmental monitoring, communications and transportation, disaster assistance and Homeland Security, become the important technical of Internet of Things development.
Because there is sensor node Numerous, random in large scale, deployment, finite energy and topology to be difficult to control to
The features such as, the Internet of radio sensing network generally adopts Clustering Routing, and network system is changed into composition by planar structure
Rotating fields, the autgmentability of network is lifted with this, reduces the energy consumption of system, lifts overall performance.Clustering Routing is proposed
The concept of " wheel ", is elected by regularly cluster head, and the energy load of whole network is evenly distributed into each sensor node
On, to improve the high efficiency and robustness of dynamic network.When each wheel starts, new cluster is produced by certain election mechanism
Head node and member node.Member node transfers information to leader cluster node and carries out data to melt by way of multi-hop communication in cluster
Close, and then realize by the way of single-hop communication that data are uploaded between leader cluster node and base station.
Clustering Routing can generally be divided into centralized and distributed two class.Concentrated route algorithm generally requires to pass
Sensor node obtains Global Topological information, and combined with intelligent algorithm (PSO, ant group algorithm, k-means etc.) enters to self performance
So as to elect suitable leader cluster node, this mode can no doubt obtain rational cluster distributed topology for row analysis, but to node
Huge energy ezpenditure is also brought along for itself, and for large-scale wireless sensing network, its flexibility is not so good as distributed calculation
Method.Therefore, it is more likely to use distributed clustering algorithm in fact in radio sensing network practical application.
In Clustering Routing, leader cluster node is due to needing to undertake in cluster data fusion and being led to aggregation node
No doubt often there is hot-zone in multi-hop communication much larger than the member node in cluster in the task of letter, its energy ezpenditure, i.e., from
The nearer node of cluster head, the data receiver and data forwarding task that needs undertake is also more, the additional energy consumption for being brought
Also bigger, node also easier premature death destroys the stability of communication link, load balancing to whole network and
Overall performance will produce serious influence.It can thus be seen that whole mistake of the neighbor node of leader cluster node in data transfer
It is also required to undertake larger energy ezpenditure in fact in journey.Therefore, cluster head election algorithm is considering node residual energy in Cluster Networks
While amount and node degree, the neighbor node dump energy of node is also a factor that can not be ignored.
The content of the invention
To overcome disadvantage mentioned above, the present invention to propose a kind of Distributed Wireless Sensor Networks cluster routing method.Methods described
Clustering Routing and fuzzy logic are combined, using residue energy of node, node degree, neighbor node dump energy as judgement
Index, realizes the election of rational leader cluster node, efficiently avoid hot-zone problem that multi-hop communication brought to network system
The impact of energy, realizes the overall load balancing of system, extends Network morals, improves the overall performance of system.
Distributed Wireless Sensor Networks cluster routing method of the present invention is achieved through the following technical solutions：
1st, a kind of Distributed Wireless Sensor Networks cluster routing method, comprises the following steps：
(1.1) sending Node_MSG packets between the sensor node in communication range mutually carries out message intercommunication, saves
Point it is possible thereby to complete the renewal of self information Table I nfo_table, so as to obtain the node ID and correspondence of all neighbor nodes
Present node energy Neighbor_Nodeid.Eresidual.Using the Info_table after renewal, node is it is possible thereby to obtain
To node energy Er, node degree d and neighbor node dump energy Ea=∑ Neighbor_Nodeid.Eresidual/ d these three joins
Number, and cluster head election algorithm duration t=k × T × (Ea/Er), wherein k for (0.9,1) between random number, T for definition
The initial election of cluster head duration；
(1.2) each sensor node defines the fuzzy set of node energy using the fuzzy inference engine system for carrying
Close { low, medium, high }, its membership function is low (0 ＜ x≤0.5), medium (0 ＜ x≤1.0), high (x ＞
0.5)；The fuzzy set { less, average, enormous } of node degree, its membership function is less (0 ＜ x≤15),
Average (0 ＜ x≤30), enormous (x ＞ 15), neighbor node dump energy fuzzy set weak, normal,
Strong }, membership function is weak (0 ＜ x≤0.35), normal (0 ＜ x≤1.0), strong (x >=0.83)；Output parameter
The fuzzy set { very_low, low, rather_low, medium, less_high, high, very_high } of probability, is subordinate to
Function is very_low (0<Y≤10), low (0<Y≤40), rather_low (30<Y≤50), medium (40<Y≤70),
less_high(60<Y≤80), high (70<Y≤90), very_high (y>90).With the accurate node that step 1.1 is obtained
Energy, node degree and neighbor node dump energy, with reference to above-mentioned membership function, are converted into corresponding obscuring as |input paramete
Fuzzy Linguistic Variable in set.Fuzzy Linguistic Variable, using Mamdani algorithms, obtains fuzzy output in conjunction with fuzzy rule
Collection.Finally by center area algorithm by fuzzy output collection be converted to intuitively accurate output valve so that node enters to self performance
Row assessment, as node itself the weights V of leader cluster node is become；
(1.3) node is obtained after itself Performance Evaluation weights V, state is campaigned for into cluster head, into neighbouring communication radius r
All neighbor nodes send the packet Head_compete comprising own node ID and weights V.Node and the neighbours for receiving
Joint behavior weights are compared, and the low node of weights is changed into ordinary node state, by nearby after waiting election of cluster head to terminate
Principle selects suitable cluster to be added, and the high node of weights is then changed into elected cluster head status；
(1.4) it is elected as the node of cluster head to a large amount of broadcast packet bag containing the node ID data CH_Message of surroundings nodes.Shape
State for ordinary node node then according to the power of the signal of the CH_Message packets for receiving judging the transmission data
The nodal distance of the bag distance of oneself, so as to selecting suitable leader cluster node with nearby principle and sending comprising own node information
Node_JOIN packets.Leader cluster node is received after the application request into clusters of member node, can return one to the node
Node_ACCEPT packets, confirm the request into clusters of the node, so as to complete the forming process of whole cluster.
Relative to prior art, the invention has the advantages that and beneficial effect：
1st, in the election of cluster head stage, existing technology mostly employs fixed joint behavior evaluation mechanism, as traditional
By the way of random number, or according to corresponding factor of evaluation so as to providing joint behavior weight computing formula V=x1E1+
x2E2+x3E3+...+xnEn.But in actual radio sensing network, As time goes on, network overall topology
Change is being constantly occurring, it is this kind of that the weights that the method that weight computing parameter is fixed is calculated can not in real time be reflected into section
The performance state of point.This method is estimated using fuzzy logic inference engine to joint behavior.Fuzzy logic is by fuzzy
Linguistic variable, simulates thinking and the decision mode of human brain, is a kind of efficient multifactor evaluation mechanism.What it was adopted is subordinate to letter
Number, according to the different parameter curve of different situation correspondences, it is ensured that the real-time effectiveness of joint behavior analysis；
2nd, when assessment is analyzed to joint behavior, this method is surplus with residue energy of node, node degree and neighbor node
Complementary energy causes the leader cluster node for electing more reasonable as factor of evaluation.Leader cluster node is used as member node in cluster and system
The tie linked up between aggregation node, generally requires the undertaking data fusion and data forwarding of the task, and its energy ezpenditure is also long-range
The member node in cluster, thus the dump energy to being elected to node necessarily has very high requirement.If elected leader cluster node
The premature death because self-energy is not enough, cluster interior nodes just lose the bridge with aggregation node data interaction, then the piece sensing
Device region also just loses and is contacted with overall network, so as to having had a strong impact on the performance of system.Therefore, residue energy of node is past
Toward being evaluation node if appropriate for one of of paramount importance index for becoming cluster head.And node degree can improve data transfer in cluster
High efficiency.Because if the node degree of elected leader cluster node is bigger, the neighbor node around it is also more, each node is needed
The data forwarding task to be shared is also less, and the integral energy load of network is also just more balanced, the overall performance of network
Better.And higher node degree can also share the pressure of communication link, stand-by period when reducing data transfer between node.
Finally, this index of neighbor node dump energy, it is intended to weaken the hot-zone problem that multi-hop communication brings, realizes the negative of node energy
Carry balanced.For example for the underwater wireless sensing network of environmental monitoring, during data multi-hop transmission in cluster, via node is such as
Because the too low premature death of energy, the node of distant place associated there is accomplished by re-starting route discovery fruit, with cluster head section
Point re-establishes communication link, so as to bring extra energy expense, or even the performance for having had a strong impact on network data transmission.
Thus select the node with higher neighbor node energy to be effectively prevented from this kind of hot-zone problem as leader cluster node as far as possible；
3rd, this method is a kind of method based on distributed thought, it is not necessary to safeguard the perception to network Global Topological, only
Node self information, and the information of the neighbor node obtained during message intercommunication are only relied on, with reference to fuzzy logic, to joint behavior
It is analyzed, obtains electing rational leader cluster node, effectively alleviates hot-zone problem common in multi-hop communication, it is balanced
The energy ezpenditure of each position in network, improves the mean survival time of node, and then extends the life of whole network system
In the life cycle, considerably improve the volume of transmitted data of system so that whole radio sensing network has more preferable energy efficiency.
Specific embodiment
To become apparent from the purpose of the present invention and technical scheme, the principle and concrete steps of the present invention are retouched below
State：
1st, this method is described as follows using the principle that fuzzy logic lifts radio sensing network data transmission efficiency：
For the clustering routing structure that radio sensing network is generally adopted, whether the leader cluster node that each wheel is elected closes
Reason directly influences the overall performance of network.The fuzzy logic inference engine that this method is adopted is a kind of with Real-time Decision
Multifactor multiple index evaluation mechanism, using parameter fuzzy collection, difference is defined according to the topological condition of different time sections network
Membership function, it is different because of the change of actual network topology structure to the evaluation criterion of joint behavior, more have
Real-time effectiveness, the leader cluster node for electing is also more reasonable.
The election of cluster head stage has three to the Judging index of joint behavior in this method：Residue energy of node, node degree, neighbour
Occupy residue energy of node.High node dump energy can ensure that node before next round election of cluster head, have enough energy complete
Cluster interior nodes information fusion and the realizing that data are uploaded of the task that carries out communicating with aggregation node, improve stablizing for network entirety
Property；High node degree can improve the high efficiency of cluster interior nodes data transfer, stand-by period when reducing data transfer between node；It is high
Neighbor node dump energy can effectively weaken impact of the hot-zone problem to multi-hop communication, realize cluster interior nodes load balancing,
The stability of communication link in cluster is improved, so as to extend Network morals, the overall performance of lift system.
2nd, the process of wheel election of cluster head each to radio sensing network, concrete steps are described as follows：
(1) sending Node_MSG packets between the sensor node in communication range mutually carries out message intercommunication.Complete
After the Node_MSG message intercommunication stages, node can realize the renewal of self information Table I nfo_table, so as to get
There are the present node energy Σ Neighbor_Node corresponding to the node ID and the node ID of neighbor nodeid.Eresidual.Profit
With the Info_table after renewal, node is it is possible thereby to get node energy Er, node degree d and neighbor node dump energy Ea
=∑ Neighbor_Nodeid.Eresidual/ d these three parameters, and further obtain cluster head election algorithm duration t=k ×
T×(Ea/Er), wherein k for (0.9,1) between random number, T be definition the initial election of cluster head duration；
(2) each sensor node is carried and fuzzy inference engine system, define not only the fuzzy set of node energy
CloseThe fuzzy set of node degree Neighbours
The fuzzy set of residue energy of nodeAnd fuzzy set y=of output parameter probability
{ very_low, low, rather_low, medium, less_high, high, very_high }, also defines each corresponding
Membership function.Node energy membership function：Low (0 ＜ x≤0.5), medium (0 ＜ x≤1.0), high (x >=0.5).Section
Point degree membership function：Less (0 ＜ x≤15), average (0 ＜ x≤30), enormous (x ＞ 15).Neighbor node residual energy
Amount membership function：Weak (0 ＜ x≤0.35), normal (0 ＜ x≤1.0), strong (x >=0.83).Probability subjection function：
very_low(0<Y≤10), low (0<Y≤40), rather_low (30<Y≤50), medium (40<Y≤70), less_
high(60<Y≤80), high (70<Y≤90), very_high (y>90).Using these membership functions, we are by step (1)
During the accurate node energy (NE) of middle acquisition, node degree (ND) and neighbor node dump energy (NNE) are converted to fuzzy set
Corresponding Fuzzy Linguistic Variable.And then we can be by the Fuzzy Linguistic Variable for obtaining again according to fuzzy rule
With reference to Mamdani algorithms, using formula
Draw the corresponding fuzzy output collection of every fuzzy ruleBy center area algorithmWill
Fuzzy output collection is converted to intuitively accurate output valve, so that node is estimated to self performance, as node itself cluster is become
The weights V of head node；
(3) node is obtained after itself Performance Evaluation weights V, and into cluster head state, the institute into neighbouring communication radius r are campaigned for
There is neighbor node to send the packet Head_compete comprising own node ID and weights V.Node and the neighbours' section for receiving
Point performance weights are compared, and the low node of weights is changed into ordinary node state, by former nearby after waiting election of cluster head to terminate
Suitable cluster is then selected to be added, and the high node of weights is then changed into elected cluster head status；
(4) it is elected as the node of cluster head to a large amount of broadcast packet bag containing the node ID data CH_Message of surroundings nodes.State
For ordinary node node then according to the power of the signal of the CH_Message packets for receiving judging to send the packet
Nodal distance oneself distance, include own node information so as to selecting suitable leader cluster node and send with nearby principle
Node_JOIN packets.Leader cluster node is received after the application request into clusters of member node, can return a Node_ to the node
ACCEPT packets, confirm the request into clusters of the node, so as to complete the forming process of whole cluster.
Claims (1)
1. a kind of Distributed Wireless Sensor Networks cluster routing method, it is characterised in that comprise the following steps：
Sending Node_MSG packets between sensor node in step 1.1 communication range mutually carries out message intercommunication.Complete
Node_MSG message intercommunication stages, node it is possible thereby into the self information Table I nfo_table more new stage, so as to obtain
The node ID of all neighbor nodes and corresponding present node energy Neighbor_Nodeid.Eresidual；After renewal
Info_table, node can get node energy Er, node degree d and neighbor node dump energy Ea=∑ Neighbor_
Nodeid.Eresidual/ d these three parameters, and election of cluster head duration t=k × T × (Ea/Er), wherein k for (0.9,1)
Between random number, T be definition the initial election of cluster head duration；
Each sensor node of step 1.2 defines the fuzzy set of node energy using the fuzzy inference engine system for carrying
{ low, medium, high }, its membership function is low (0 ＜ x≤0.5), medium (0 ＜ x≤1.0), high (x ＞ 0.5)；
The fuzzy set { less, average, enormous } of node degree, its membership function is less (0 ＜ x≤15), average (0
＜ x≤30), enormous (x ＞ 15), the fuzzy set { weak, normal, strong } of neighbor node dump energy is subordinate to
Function is weak (0 ＜ x≤0.35), normal (0 ＜ x≤1.0), strong (x >=0.83)；The fuzzy set of output parameter probability
Close { very_low, low, rather_low, medium, less_high, high, very_high }, membership function is very_
low(0<Y≤10), low (0<Y≤40), rather_low (30<Y≤50), medium (40<Y≤70), less_high (60<
Y≤80), high (70<Y≤90), very_high (y>90)；With step 1.1 obtain accurate node energy, node degree and
Neighbor node dump energy, with reference to above-mentioned membership function, is converted into fuzzy in corresponding fuzzy set as |input paramete
Linguistic variable.Fuzzy Linguistic Variable, using Mamdani algorithms, obtains fuzzy output collection in conjunction with fuzzy rule.Finally by
Heart area algorithm by fuzzy output collection be converted to intuitively accurate output valve so that node is estimated to self performance, as section
Point itself becomes the weights V of leader cluster node；
Step 1.3 node is obtained after itself Performance Evaluation weights V, and into cluster head state, the institute into neighbouring communication radius r are campaigned for
There is neighbor node to send the packet Head_compete comprising own node ID and weights V；Node and the neighbours' section for receiving
Point performance weights are compared, and the low node of weights is changed into ordinary node state, by former nearby after waiting election of cluster head to terminate
Suitable cluster is then selected to be added, and the high node of weights is then changed into elected cluster head status；
Step 1.4 is elected as the node of cluster head to a large amount of broadcast packet bag containing the node ID data CH_Message of surroundings nodes；State
For the node CH_Message packets that then basis is received of ordinary node, judgement is passed judgment on according to the signal strength for receiving
Distance between node, selects suitable leader cluster node and sends the Node_JOIN numbers comprising own node information with nearby principle
According to bag；Leader cluster node is received after the application request into clusters of member node, and to the node Node_ACCEPT packet is returned,
The request into clusters of the node is confirmed, so as to complete the forming process of whole cluster.
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| CN110650456A (en) * | 2019-09-26 | 2020-01-03 | 赣南师范大学 | Fuzzy comprehensive evaluation-based cluster head election method in unmanned aerial vehicle self-organizing network |
| CN110839222A (en) * | 2019-11-14 | 2020-02-25 | 南昌诺汇医药科技有限公司 | Effective wire and cable safety state evaluation system |
| CN111510983A (en) * | 2020-03-19 | 2020-08-07 | 东北电力大学 | Wireless sensor network cluster head election method combining trust |
| CN111836327A (en) * | 2020-07-03 | 2020-10-27 | 山东大学 | Routing data transmission method for underwater sensor network and underwater sensor network |
| CN111836327B (en) * | 2020-07-03 | 2022-05-17 | 山东大学 | Routing data transmission method for underwater sensor network and underwater sensor network |
| CN115048274A (en) * | 2022-08-11 | 2022-09-13 | 中国通信建设第三工程局有限公司 | Operation and maintenance system based on big data |
| CN115048274B (en) * | 2022-08-11 | 2022-11-18 | 中国通信建设第三工程局有限公司 | Operation and maintenance system based on big data |
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