CN107071811A - A kind of fault-tolerant Uneven Cluster algorithms of WSN based on fuzzy control - Google Patents
A kind of fault-tolerant Uneven Cluster algorithms of WSN based on fuzzy control Download PDFInfo
- Publication number
- CN107071811A CN107071811A CN201710255988.XA CN201710255988A CN107071811A CN 107071811 A CN107071811 A CN 107071811A CN 201710255988 A CN201710255988 A CN 201710255988A CN 107071811 A CN107071811 A CN 107071811A
- Authority
- CN
- China
- Prior art keywords
- cluster
- cluster head
- node
- message
- fuzzy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/04—Arrangements for maintaining operational condition
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0654—Management of faults, events, alarms or notifications using network fault recovery
- H04L41/0668—Management of faults, events, alarms or notifications using network fault recovery by dynamic selection of recovery network elements, e.g. replacement by the most appropriate element after failure
-
- 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
-
- 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
- H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
-
- 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
- H04W40/248—Connectivity information update
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The present invention relates to a kind of wireless sensor network cluster algorithm, the fault-tolerant Uneven Cluster algorithm DFUC of particularly a kind of WSN based on fuzzy control (Distributed Fuzzy controller based Unequal Clustering algorithm).The algorithm is based on multiple local parameters such as dump energy, node center degree, node and the distances of base station, calculated by fuzzy controller and be output into cluster head chance and cluster sizes values, optimal node is turned into cluster head and limit the size of cluster, member node constitutes backup cluster head list.By TDMA mechanism, the real-time update list makes most suitable node turn into backup cluster head.Once cluster head fails, the result is that can ensure a backup cluster head to substitute cluster head.Algorithm solves traditional Uneven Cluster algorithm cluster size at random and ignores the fault-tolerant unbalanced problem of the network energy consumption brought, extends network lifecycle while reduction network energy consumption, suitable for practical application.
Description
Technical field
The present invention relates to a kind of calculation of wireless sensor network WSN (Wireless Sensor Networks) Uneven Cluster
Method, fault-tolerant Uneven Cluster algorithm DFUC (the Distributed Fuzzy of particularly a kind of WSN based on fuzzy control
controller based Unequal Clustering algorithm).The algorithm is by residue energy of node, node center
Degree and node to base station distance input fuzzy controller, made inferences by IF-THEN rules be output into cluster head chance with
Cluster sizes values, make best performance node turn into cluster head and set up sizeable cluster.Carried out data transmission using TDMA modes, with
Tolerate the interim and permanent fault of cluster head and member node.Loaded between efficient balance cluster, reduction network energy consumption is so as to improve network
Life cycle.
Background technology
Wireless sensor network is widely used to the fields such as environmental monitoring, emergency reaction, military monitoring and space probation
Close.Effectively energy-conservation is the significant challenge that WSN faces, and sub-clustering is then one of effective method.Cluster algorithm can improve network can
Autgmentability, energy efficiency, reduce routing delay, extend network lifecycle.
Periodicity cluster head random-selection node is usually taken in uniform cluster algorithm, the cluster head of proper ratio is produced, so as to subtract
Small network energy consumption.When cluster head is communicated by way of multi-hop with base station, the cluster head of neighbor base station is caused to undertake plurality
The too early depleted of energy according to relay task, produces " focus " problem.Asked to solve " focus " that uniform cluster algorithm is present etc.
Topic, it is proposed that many Uneven Cluster algorithms, and Uneven Cluster algorithm is proved in most of network design better than equal
Even cluster algorithm.Uneven Cluster algorithm is generally according to residue energy of node, node to base station distance, node degree and node to cluster
The factors such as head distance select cluster head, so as to split the network into the cluster differed in size, by cluster between single-hop, cluster multi-hop it is logical
Letter mode transfers data to base station.By making different clusters have different cluster sizes balanced come proof load, and improve network life
The life cycle.
Existing uniform Uneven Cluster algorithm can improve some performances of network.However, they assume that node only
Have just dead in depleted of energy.Can actually no matter cluster head or member node be because many reasons such as power supply is unstable, physics
Damage etc. and be likely to occur failure.Existing method all solves the problem using backup cluster head, and thinks what those had determined
Backup cluster head is working properly always and is the node of most suitable replacement cluster head, generally only considers two backup cluster heads.However, at certain
In the case of a little, backup cluster head may consume energy more more than other nodes.Simultaneously, it is considered to which most two backup cluster heads can not
Effectively safeguard existing cluster.
The content of the invention
The technical problems to be solved by the invention can not be determined and held for existing Uneven Cluster algorithm cluster size
The problems such as wrong ability is weak, it is considered to the dump energy of node, node center degree and node and base station distance, with fuzzy controller
Carrying out calculate node with node local information turns into the chance and cluster sizes values of cluster head, the node with main chance value is turned into cluster
Head, and determine whether certain member node adds according to cluster sizes values, so as to form sizeable cluster.In data transfer phase
Using TDMA modes, the collection of data in cluster is carried out, and tolerates and is used between the interim and permanent fault of cluster head and member node, cluster
Shortest path multi-hop mode carries out data transmission, when permanent fault occurs in cluster head, and optimal backup cluster head turns into cluster head, member
When permanent fault occurs in node, the node is removed from network.So as to be loaded between efficient balance cluster, reduction network energy consumption is so as to carry
High network lifecycle.
A kind of fault-tolerant Uneven Cluster algorithm DFUC of WSN based on fuzzy control of the present invention include network model, cluster and
Fault-tolerant three parts.Network model is realized for DFUC algorithms provides model, specifically includes network model, energy model and Fuzzy Control
Device model processed.Cluster be determined by running fuzzy controller in each node in a distributed manner its turn into cluster head chance and
Cluster sizes values, so that network is divided into some clusters of different sizes, and the node of best performance turns into cluster head, specifically comprising cluster head
Election and cluster set up two processes.Fault-tolerant is to monitor that cluster head and member node are built to safeguard by time division multiplexing tdm A modes
Vertical cluster, i.e., when permanent fault occurs in cluster head, optimal backup cluster head turns into cluster head, when permanent fault occurs in member node,
The node is removed from network.
Described network model is realized for algorithm provides model, and wherein network model determines network type for static network
Network, network node isomorphism and with unique mark, and approximate distance can be calculated by RSSI, while node can pass through
HELLO messages obtain the distance and node center degree with base station.Energy model is that data communication energy expenditure is carried between cluster in cluster
For computation model, its basis is the radio communication energy consumption model E under free spacetx,Erx, based on Etx,ErxTo calculate in cluster and cluster
Between energy consumption.Wherein cluster self-energy consumption EintraIt is made up of three parts, i.e., the energy expenditure E that member node communicates with cluster headMemToCh、
Cluster head receives the ENERGY E of data consumption from its bunch member nodeChrxAnd the energy expenditure E of data fusionDA.And energy disappears between cluster
Consumption has two kinds of situations, if cluster head is directly and base station communication, its energy consumption EsinterFor the energy for the consumption that communicated between cluster head and base station
Amount;If cluster head passes through multi-hop mode and base station communication, its energy consumption EminterEnergy for the consumption that communicated between cluster head and add
Communicate the energy of consumption between last cluster head and base station.And fuzzy controller model uses Mandani fuzzy controllers, both
It is simple to produce better result again.Indistinct Input dump energy, node center degree, node to base station distance, inference engine according to
IF-THEN rule bases are controlled processing, output cluster head chance (Chance) and cluster size (Size).
Described cluster determines that it turns into cluster head machine by running fuzzy controller in each node in a distributed manner
Meeting and cluster sizes values, so that network is divided into some clusters of different sizes, and the node of best performance turns into cluster head, specifically includes
Election of cluster head and cluster set up two processes.In election of cluster head process, each node runs fuzzy controller, and clear input value is by mould
Paste inference engine turns to suitable linguistic variable by the way that given membership function is fuzzy.Then fuzzy input variable passes through IF-
THEN rule bases are handled, and the output of fuzzy inference engine is still a Fuzzy Linguistic Variable, and mould is solved using centroid method
Paste, so as to obtain clear output quantity " chance " and " size ".Process, neighbours of all nodes into its communication radius are set up in cluster
There is node broadcasts " cluster head competition message " CH_CP the node of " chance " value higher than other nodes to turn into cluster head and broadcast " competing
Strive successfully message " CH_SUCCESS, node received after CH_SUCCESS, updates its neighbouring cluster head list, and to nearest away from it
Cluster head sends " adding cluster message " CH_JOIN.The cluster head for receiving CH_JOIN messages checks its " size " to judge whether to receive
Newcomer.If bunch member node is less than " size " value, beam back " being successfully joined message " CH_JOIN_SUCCESS, and by this into
Member adds backup cluster head list according to its " chance " value size.Otherwise " addition failure message " CH_JOIN_FAIL is beamed back.When some
When node receives CH_JOIN_FAIL messages, such as its cluster head list non-NULL then sends CH_JOIN messages to next nearest
Cluster head, until adding some cluster.In the case of the worst, cluster head list space-time node still can not be added to certain cluster, then its own
Elect cluster head as.After cluster is formed, the opportunity values size of each node exported according to fuzzy controller, according to opportunity values from high to low
Principle formation " list of backup cluster head ", each cluster head broadcasts " backup cluster head list message " CH_Bch into cluster, receives CH_
Bch node preserves backup cluster head list.
It is described it is fault-tolerant be that cluster head and member node are monitored by time division multiplexing tdm A modes to safeguard set up cluster,
I.e. when permanent fault occurs in cluster head, optimal backup cluster head turns into cluster head, when permanent fault occurs in member node, the node from
Removed in network.Once cluster is set up, time slot of the bunch member node based on distribution can start data transfer.In order to safeguard establishment
Cluster, cluster member often calculates the output of its fuzzy controller, and the opportunity values as cluster head are sent into cluster head simultaneously with data.Cluster
Opportunity values of the head based on reception update backup cluster head list, and the list of renewal passes through the periodically transmission of a data request message
To cluster member to ensure the most suitable backup cluster head of real-time update.So as to realize that its member can be notified as early as possible when cluster head is dead
To avoid the loss of data in network, and during member's death, cluster head removes it from backup cluster head list.Specially member exists
Distributed time slot sends its packet if a data request message is received, if cluster head does not receive request in postamble
Data, then stamp error flag to the member.Then cluster head sends another request in next cycle time slot, if also not
Receive the data of request, then it is assumed that member's permanent fault simultaneously removes it from backup cluster head list.Equally, member is dividing
The time slot matched somebody with somebody waits the request of data from its cluster head, if member does not receive request of data message in succession in postamble, recognizes
Temporary derangement has been likely to occur for cluster head.It will wait next corresponding time slot to receive request of data message, if do not connect also
Receive request of data message, then it is assumed that cluster head occurs in that permanent fault.Then, member checks its cluster head recent renewal received
Backup cluster head list, and addition cluster message is sent using first node as cluster head, and wait confirmation message.However, the node
It may also fail, once being not received by confirmation message, then addition cluster message be sent by cluster head of the next node of list, directly
To being finally added to some cluster head.
Net is included by the visible fault-tolerant Uneven Cluster algorithm DFUC of a kind of WSN based on fuzzy control of the present invention described above
Network model, cluster and fault-tolerant three parts.Algorithm inputs residue energy of node, node center degree and node to base station distance
Fuzzy controller, is made inferences by IF-THEN rules and is output into cluster head chance and cluster sizes values, make best performance node into
For cluster head and set up sizeable cluster.Carried out data transmission using TDMA modes, to tolerate the interim of cluster head and member node
And permanent fault.Loaded between efficient balance cluster, reduction network energy consumption is so as to improve network lifecycle.
Brief description of the drawings
Fig. 1 is structure of fuzzy controller of the invention
Fig. 2 is fuzzy controller input and output membership function of the invention
Fig. 3 is fuzzy controller rule list of the invention
Fig. 4 is data transfer of the invention and fault-tolerant process
Fig. 5 is simulation parameter table of the invention
Fig. 6 is Network Survivability nodes comparison diagram of the invention
Fig. 7 is residue of network organization gross energy comparison diagram of the invention
Embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings, and a kind of WSN based on fuzzy control of the present invention holds
Unless uniform cluster algorithm DFUC includes network model, cluster and fault-tolerant three parts.Network model is realized for algorithm provides mould
Type, specifically includes network model, energy model and fuzzy controller model.Cluster is by operating in each node in a distributed manner
In fuzzy controller determine that it turns into cluster head chance and cluster sizes values, so that network is divided into some clusters of different sizes,
And the node of best performance turns into cluster head, specifically sets up two processes comprising election of cluster head and cluster.Fault-tolerant is by time division multiplexing
TDMA modes monitor cluster head and member node to safeguard set up cluster, i.e., when permanent fault occurs in cluster head, optimal is standby
Part cluster head turns into cluster head, and when permanent fault occurs in member node, the node is removed from network.
Described network model is realized for algorithm provides model, and it has following property:
1. all nodes are all static after network design, and node energy is limited and base station energy is unrestricted;
2. network node isomorphism, i.e., with identical primary power, identical handles, stores, sends and receives ability;
3. approximate distance can be calculated by receiving signal intensity instruction RSSI between node;
4. when network design starts, base station sends HELLO messages to the whole network node, and then each node is with its communication radius
R broadcasts the HELLO messages of oneself.Based on the information of these interactions, each node is calculated and obtained in distance and node with base station
Heart degree;
5. each node has unique mark, then set of node is represented by S={ s1,s2,...,sn, wherein siRepresent
I-th of node.
Energy model provides computation model for data communication energy expenditure, and its basis is the radio communication energy under free space
Consume model Etx,Erx, and have:
Erx=l*Eelec(2) wherein Etx,ErxRepresent that node sends and receives the energy of consumption, l is represented to send or connect
The data bits of receipts, EelecRepresent the energy sent or recruiting unit's data circuit is consumed, εfs、εmpRespectively represent free space and
Multipath transmisstion model power consumption.D represents the distance between two nodes,Represent transmission pattern be free space or
The threshold value of multipath transmisstion.
For cluster wireless sensor network, mainly there are two factors in the energy expenditure of data transfer phase, i.e.,
Transmitted in cluster between transmission and cluster.Wherein transmission is made up of three parts in cluster, as shown in formula (3), wherein EMemToChRepresent member
The energy expenditure that node communicates with cluster head, EChrxRepresent that cluster head receives the energy of data consumption, E from its bunch member nodeDARepresent
The energy expenditure of data fusion.
Eintra=EMemToCH+ECHrx+EDA (3)
The energy expenditure that member node communicates with cluster head is such as shown in (4), and wherein n represents the cluster head number of network, miRepresent certain
Member node number in cluster i, may be unequal for each cluster, and EtxRepresent that i-th of cluster interior nodes j sends data to it
The energy of cluster head consumption.
Cluster head is received from its bunch member node shown in the energy such as formula (5) of data consumption, wherein miRepresent in i-th cluster into
Member's nodes, n is the quantity of network intra-cluster, ErxRepresent to receive energy.
Shown in the energy expenditure of data fusion such as formula (6), wherein k represents data bits, EpDbRepresent that unit data fusion disappears
The energy of consumption.
Equally, transmission includes two kinds of situations between cluster, if cluster head is directly and base station communication, its energy expenditure such as formula (7)
It is shown:
Esinter=Etx(CH,BS) (7)
And shown in the energy expenditure such as formula (8) when cluster head is by multi-hop mode and base station communication:
Wherein nmFor the hop count of cluster head to base station, CH(i)Represent i-th of cluster head on from cluster head to base station multihop path.
Not only simple but also can produce better result and fuzzy controller model uses Mandani fuzzy controllers, its structure is such as
Shown in Fig. 1.Clear input value dump energy, node center degree, node to base station distance are blurred inference engine by giving
Membership function is fuzzy to turn to suitable linguistic variable.Then fuzzy input variable according to IF-THEN rule bases in inference system
In be controlled processing.Output quantity is as cluster head chance (Chance) and cluster size (Size), the output of fuzzy inference engine
It is still Fuzzy Linguistic Variable, by using centroid method ambiguity solution, so as to obtain clear output quantity " chance " and " size " value.
Described cluster determines that it turns into cluster head machine by running fuzzy controller in each node in a distributed manner
Meeting and cluster sizes values, so that network is divided into some clusters of different sizes, and the node of best performance turns into cluster head, specifically includes
Election of cluster head and cluster set up two processes.In election of cluster head process initially, all nodes in network are designated as cluster member section
Point.Next it is " dump energy ", " node center degree ", the specified fuzzy language of " node to base station distance " these three input variables
The Fuzzy Linguistic Variable of variable, wherein dump energy " Energy " and node center degree " Centrality " be " low ", " in ",
" height " (low, middle, high);Node to base station distance " Distance " Fuzzy Linguistic Variable for " near ", " in ", " remote "
(near、middle、far).And " low ", " near ", " height ", " remote " use trapezoidal membership function, fuzzy language " in " use triangle
Shape membership function.These membership functions are based on existing research experiment result and our own experimental result.Fuzzy output becomes
Chance " Chance " of the amount as cluster head uses nine fuzzy variables, i.e., " very low ", " low ", " relatively low ", " in low ", " in ", it is " high
In ", " higher ", " height ", " very high " (very low, low, rather low, low medium, medium, high medium,
rather high,high,very high).Wherein " very low " and " very high " use trapezoidal membership function, other output languages
Variable uses Triangleshape grade of membership function.Second output variable cluster size " Size " uses seven Fuzzy Linguistic Variables, they
It is respectively " very little ", " small ", " smaller ", " in ", " larger ", " big ", " very big " (very small, small, rather
small,medium,rather large,large,very large).It is wherein " very little " and " very big " using trapezoidal degree of membership
Function, it is other all to use Triangleshape grade of membership function.The membership function of input and output fuzzy variable is as shown in Figure 2.It is clear defeated
Enter value and be blurred inference engine and turn to suitable linguistic variable by the way that given membership function is fuzzy.Then fuzzy input variable
Handled by IF-THEN rule bases.One has 27 rules, and DFUC fuzzy IFs-THEN rules are as shown in Figure 3.It is fuzzy to push away
The output for managing engine is still a Fuzzy Linguistic Variable, using centroid method come ambiguity solution, so as to obtain clear output quantity " machine
Meeting " and " size ".
Process is set up in cluster, node is likely to be at one of three kinds of states, i.e. member, cluster head, backup cluster head.After deployment, institute
There is node to be in member condition, and start fuzzy controller and calculate its " chance " and cluster " size " as cluster head.Then, own
Neighbor node broadcast " the cluster head competition message " CH_CP of node into its communication radius, CH_CP messages are by type of message, node
ID and " chance " value are constituted, and wherein type of message shows that this is a cluster head competition message.With " machine higher than other nodes
The node of meeting " value turns into cluster head and broadcasts " competing successfully message " CH_SUCCESS, and CH_SUCCESS messages are by type of message, section
Point ID is constituted.Node is received after CH_SUCCESS, updates its neighbouring cluster head list, and " add to being sent away from its nearest cluster head
Cluster message " CH_JOIN, it is made up of type of message, node ID and cluster head ID, and the cluster head is deleted from cluster head list.
The cluster head for receiving CH_JOIN messages checks its " size " to judge whether to receive newcomer.If bunch member node is less than " big
It is small " value, " being successfully joined message " CH_JOIN_SUCCESS is beamed back, it is by type of message, node ID, member id and distribution
Time slot is constituted, and the member is added into backup cluster head list according to its opportunity values size.Otherwise " addition failure message " CH_ is beamed back
JOIN_FAIL, it includes type of message, node ID and member id and constituted, and shows the space without newcomer's node.When some
When node receives CH_JOIN_FAIL messages, such as its cluster head list non-NULL then sends CH_JOIN messages to next nearest
Cluster head, until it is added to some cluster.In the case of the worst, cluster head list space-time node still can not be added to certain cluster, then its
Itself elects cluster head as.After cluster is formed, the opportunity values size of each node exported according to fuzzy controller, according to opportunity values by height
To low principle formation " list of backup cluster head ", each cluster head broadcasts " backup cluster head list message " CH_Bch, the message into cluster
Including type of message, node ID and backup cluster head list.The node for receiving CH_Bch preserves backup cluster head list, node ID
With first backup cluster head ID identical in list, then as backup cluster head, other vertex ticks node is backup cluster head.
The false code of DFUC algorithms is as follows:
It is described it is fault-tolerant be that cluster head and member node are monitored by time division multiplexing tdm A modes to safeguard set up cluster,
I.e. when permanent fault occurs in cluster head, optimal backup cluster head turns into cluster head, when permanent fault occurs in member node, the node from
Removed in network.Once cluster is set up, time slot of the bunch member node based on distribution can start data transfer.In the stage, own
Sensor node is all in consumed energy, and therefore, either cluster head or cluster member are likely to occur the situation of depleted of energy.Once
There is bunch member node failure, node center degree will change, influence node turns into cluster head chance and cluster sizes values, and if cluster
Head node is dead, then whole cluster overlay area can not be all monitored.Therefore, cluster head and member node progress to failure is handled
Necessary.In order to safeguard the cluster of establishment, cluster member often calculates the output of its fuzzy controller, and by the chance as cluster head
Value is sent to cluster head simultaneously with data.Opportunity values of the cluster head based on reception update backup cluster head list, and the list of renewal passes through
One data request message is periodically sent to cluster member to ensure the most suitable backup cluster head of real-time update.Work as cluster so as to realize
Its member can be notified to avoid the loss of data in network as early as possible when head is dead, and member it is dead when, cluster head is by it from backup
Removed in cluster head list.Implement using TDMA modes to monitor cluster head and member, process is as shown in Figure 4.It can be seen that
Member sends its packet if a data request message is received, if cluster head does not receive the number of request in postamble
According to then stamping error flag to the member.Then cluster head sends another request in next cycle time slot, if do not received also
The data of request, then it is assumed that member's permanent fault simultaneously removes it from backup cluster head list.Equally, member is being distributed
Time slot waits the request of data from its cluster head, if member does not receive request of data message in succession in postamble, then it is assumed that cluster
Head has been likely to occur temporary derangement.It will wait next corresponding time slot to receive request of data message, if be also not received by
Request of data message, then it is assumed that cluster head occurs in that permanent fault.Then, member checks the backup of its cluster head recent renewal received
Cluster head list, and addition cluster message is sent using first node as cluster head, and wait confirmation message.However, the node also may be used
It can fail, once being not received by confirmation message, then addition cluster message be sent by cluster head of the next node of list, until most
After be added to some cluster head.
In order to verify a kind of fault-tolerant Uneven Cluster algorithm DFUC of WSN based on fuzzy control of present invention performance, use
MATLAB carries out algorithm simulating, and is compared with the progress emulation of LEACH, DUCF and WUCH algorithm, analyzes one kind of the present invention and is based on
Characteristics of the fault-tolerant Uneven Cluster algorithm DFUC of WSN of fuzzy control in terms of dump energy and life cycle.Set node
Random placement is in 200 × 200m2Square region in, and base station coordinates be (100,100).Specific simulation parameter is as shown in Figure 5.
Each to control bag size to be 25 bytes, data package size is 500 bytes, more much larger than control message, is also included in emulation
The communication cost of these control bags.The desired cluster head percentages of LEACH are 0.1.The communication radius of sensor node takes 40m,
Ensure that all nodes in network can add a cluster nearby.Fig. 6 is the situation of change that surviving node number takes turns number with operation, figure
7 take turns the situation of change of number for remaining gross energy with operation.As seen from Figure 6, with the increase of network operation wheel number, DFUC is calculated
Method compared with other three kinds of algorithms can equalising network energy consumption well, so as to effectively extend network lifecycle.Because
DFUC algorithm synthesis considers residue energy of node, node center degree and determines the size of cluster head and cluster with the distance of base station, and
Fault-tolerant ability is improved in data transfer phase, the energy consumption of cluster is reduced again.Fig. 7 compared for the remaining gross energy of four kinds of algorithms
With operation take turns the increased situation of change of number, due to DFUC algorithms considered in cluster formation stages and data transfer phase it is a variety of
Influence factor, therefore the smaller, life span of DFUC algorithms fluctuation is longer.
It can be seen that a kind of fault-tolerant Uneven Cluster algorithm DFUC of WSN based on fuzzy control of invention, based on residue
Multiple local parameters such as energy, node center degree, node and the distance of base station, are calculated by fuzzy controller and are output into cluster head
Chance and cluster sizes values, make optimal node turn into cluster head and limit the size of cluster, member node constitutes backup cluster head list.Pass through
TDMA mechanism, real-time update list makes most suitable node turn into backup cluster head.Once cluster head fails, the result is that total energy is really
A backup cluster head is protected to substitute cluster head.Emulated by Network Survivability nodes and residue of network organization gross energy to algorithm
Test, as a result show relative to LEACH, DUCF with and WUCH algorithms, DFUC obtains longer life cycle, and performance is better than it
Its algorithm, is more suitable for practical application.
Claims (3)
1. a kind of fault-tolerant Uneven Cluster algorithm DFUC of WSN based on fuzzy control, it is characterised in that:Including network model, into
Cluster and fault-tolerant three parts;Based on network model, it is considered to dump energy, node center degree and the node of node and base station away from
From carrying out calculate node with fuzzy controller and node local information turns into the chance and cluster sizes values of cluster head, makes have maximum
The node of opportunity values turns into cluster head, and determines whether certain member node adds according to cluster sizes values, so that it is suitable to form size
Cluster;TDMA modes are used in data transfer phase, the collection of data in cluster is carried out, and tolerate the interim of cluster head and member node
And permanent fault, carried out data transmission using shortest path multi-hop mode between cluster, when permanent fault occurs in cluster head, optimal is standby
Part cluster head turns into cluster head, and when permanent fault occurs in member node, the node is removed from network, so as to be born between efficient balance cluster
Carry, reduction network energy consumption is so as to improve network lifecycle.
2. the fault-tolerant Uneven Cluster algorithm DFUC of the WSN according to claim 1 based on fuzzy control, it is characterised in that:
Described cluster determines that it turns into cluster head chance and cluster is big by running fuzzy controller in each node in a distributed manner
Small value, so that network is divided into some clusters of different sizes, and the node of best performance turns into cluster head, specifically comprising election of cluster head
Two processes are set up with cluster;In election of cluster head process initially, all nodes in network are designated as bunch member node, next
Fuzzy Linguistic Variable is specified for " dump energy ", " node center degree ", " node to base station distance " these three input variables, wherein
The Fuzzy Linguistic Variable of dump energy " Energy " and node center degree " Centrality " be " low ", " in ", " height " (low,
middle、high);Node to base station distance " Distance " Fuzzy Linguistic Variable for " near ", " in ", " remote " (near,
Middle, far), and " low ", " near ", " height ", " remote " use trapezoidal membership function, fuzzy language " in " be subordinate to using triangle
Function, these membership functions are based on existing research experiment result and our own experimental result;Fuzzy output variable turns into
The chance " Chance " of cluster head uses nine fuzzy variables, i.e., " very low ", " low ", " relatively low ", " in low ", " in ", " senior middle school ",
" higher ", " height ", " very high " (very low, low, rather low, low medium, medium, high medium,
Rather high, high, very high), wherein " very low " and " very high " uses trapezoidal membership function, other output languages
Variable uses Triangleshape grade of membership function;Second output variable cluster size " Size " uses seven Fuzzy Linguistic Variables, they
It is respectively " very little ", " small ", " smaller ", " in ", " larger ", " big ", " very big " (very small, small, rather
Small, medium, rather large, large, very large), wherein " very little " and " very big " using trapezoidal degree of membership
Function, other all to use Triangleshape grade of membership function, the membership function of input and output fuzzy variable is as shown in Figure 2.
Clear input value is blurred inference engine and turns to suitable linguistic variable, Ran Houmo by the way that given membership function is fuzzy
Paste input variable is handled by IF-THEN rule bases, and one has 27 rules, and DFUC fuzzy IFs-THEN rules are such as Fig. 3 institutes
Show, the output of fuzzy inference engine is still a Fuzzy Linguistic Variable, using centroid method come ambiguity solution, so as to obtain clear defeated
Output " chance " and " size ".
Process is set up in cluster, node is likely to be at one of three kinds of states, i.e. member, cluster head, backup cluster head, after deployment, Suo Youjie
Put and be in member condition, and start fuzzy controller and calculate its " chance " and cluster " size " as cluster head, then, all nodes
Into its communication radius neighbor node broadcast " cluster head competition message " CH_CP, CH_CP messages by type of message, node ID with
And " chance " value is constituted, wherein type of message shows that this is a cluster head competition message;With " chance " higher than other nodes
The node of value turns into cluster head and broadcasts " competing successfully message " CH_SUCCESS, and CH_SUCCESS messages are by type of message, node
ID is constituted, and node is received after CH_SUCCESS, updates its neighbouring cluster head list, and " add cluster to being sent away from its nearest cluster head
Message " CH_JOIN, it is made up of type of message, node ID and cluster head ID, and the cluster head is deleted from cluster head list, is connect
The cluster head for receiving CH_JOIN messages checks its " size " to judge whether to receive newcomer, if bunch member node is less than " greatly
It is small " value, " being successfully joined message " CH_JOIN_SUCCESS is beamed back, it is by type of message, node ID, member id and distribution
Time slot is constituted, and the member is added into backup cluster head list according to its opportunity values size, otherwise beams back " addition failure message " CH_
JOIN_FAIL, it includes type of message, node ID and member id and constituted, and shows the space without newcomer's node;When some
When node receives CH_JOIN_FAIL messages, such as its cluster head list non-NULL then sends CH_JOIN messages to next nearest
Cluster head, until it is added to some cluster;In the case of the worst, cluster head list space-time node still can not be added to certain cluster, then its
Itself elect cluster head as, after cluster is formed, the opportunity values size of each node exported according to fuzzy controller, according to opportunity values by height
To low principle formation " list of backup cluster head ", each cluster head broadcasts " backup cluster head list message " CH_Bch, the message into cluster
Including type of message, node ID and backup cluster head list.The node for receiving CH_Bch preserves backup cluster head list, node ID
With first backup cluster head ID identical in list, then as backup cluster head, other vertex ticks node is backup cluster head.
The false code of DFUC algorithms is as follows:
DFUC algorithms
3. the fault-tolerant Uneven Cluster algorithm DFUC of the WSN according to claim 1 based on fuzzy control, it is characterised in that:
It is described it is fault-tolerant be to monitor that cluster head and member node to safeguard set up cluster, that is, work as cluster head by time division multiplexing tdm A modes
When there is permanent fault, optimal backup cluster head turns into cluster head, and when permanent fault occurs in member node, the node is moved from network
Remove, once cluster is set up, time slot of the bunch member node based on distribution can start data transfer, in the stage, all the sensors section
Point is all in consumed energy, and therefore, either cluster head or cluster member are likely to occur the situation of depleted of energy.Once there is cluster member
Node failure, node center degree will change, and influence node turns into cluster head chance and cluster sizes values, and if leader cluster node is dead
Die, then whole cluster overlay area can not be all monitored, therefore, the cluster head and member node progress processing to failure are necessary
's;In order to safeguard the cluster of establishment, cluster member often calculates the output of its fuzzy controller, and by the opportunity values as cluster head with data
Simultaneously it is sent to cluster head, opportunity values of the cluster head based on reception update backup cluster head list, and the list of renewal passes through a data
Request message is periodically sent to cluster member to ensure the most suitable backup cluster head of real-time update, so as to realize when cluster head is dead
Its member can be notified to avoid the loss of data in network as early as possible, and member it is dead when, cluster head is by it from backup cluster head list
It is middle to remove, implement using TDMA modes to monitor cluster head and member, process is as shown in Figure 4;Detailed process is that member is once
Receive a data request message and then send its packet, if cluster head does not receive the data of request in postamble, to this
Member stamps error flag, and then cluster head sends another request in next cycle time slot, if not receiving the number of request also
According to, then it is assumed that member's permanent fault simultaneously removes it from backup cluster head list, equally, and member waits in the time slot distributed
Request of data from its cluster head, if member does not receive request of data message in succession in postamble, then it is assumed that cluster head may go out
Temporary derangement is showed, it will wait next corresponding time slot to receive request of data message, if being also not received by request of data
Message, then it is assumed that cluster head occurs in that permanent fault, then, member checks the backup cluster head row of its cluster head recent renewal received
Table, and addition cluster message is sent using first node as cluster head, and wait confirmation message, however, the node may also fail,
Once being not received by confirmation message, then addition cluster message is sent by cluster head of the next node of list, is to the last added
To some cluster head.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710255988.XA CN107071811B (en) | 2017-04-18 | 2017-04-18 | WSN fault-tolerant non-uniform clustering method based on fuzzy control |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710255988.XA CN107071811B (en) | 2017-04-18 | 2017-04-18 | WSN fault-tolerant non-uniform clustering method based on fuzzy control |
Publications (2)
Publication Number | Publication Date |
---|---|
CN107071811A true CN107071811A (en) | 2017-08-18 |
CN107071811B CN107071811B (en) | 2019-12-27 |
Family
ID=59600974
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710255988.XA Expired - Fee Related CN107071811B (en) | 2017-04-18 | 2017-04-18 | WSN fault-tolerant non-uniform clustering method based on fuzzy control |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN107071811B (en) |
Cited By (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107612801A (en) * | 2017-09-30 | 2018-01-19 | 中国兵器装备集团上海电控研究所 | A kind of method of CAN dynamic group net |
CN108770029A (en) * | 2018-05-02 | 2018-11-06 | 天津大学 | Cluster-Based Routing Protocols for Wireless Sensor based on cluster and fuzzy system |
CN108848476A (en) * | 2018-06-21 | 2018-11-20 | 河南科技大学 | Power-efficient data assembly algorithms based on communication distance control in sensor network |
CN109462877A (en) * | 2018-11-16 | 2019-03-12 | 重庆邮电大学 | A kind of WSN energy neutral cluster routing method based on fuzzy logic |
CN109842508A (en) * | 2017-11-27 | 2019-06-04 | 华为技术有限公司 | The method that multiple terminals cooperates, terminal device and multiple terminals cooperative system |
CN109922511A (en) * | 2019-04-29 | 2019-06-21 | 中国联合网络通信集团有限公司 | Cluster-head node selection method, node clustering method and cluster-head node selection device |
CN110062432A (en) * | 2019-04-26 | 2019-07-26 | 长春师范大学 | A kind of Wireless sensor network clustering routing algorithm based on least energy consumption |
CN110490266A (en) * | 2019-08-23 | 2019-11-22 | 北京邮电大学 | A kind of sensing data uploads, Transducer-fault Detecting Method and device |
CN110536372A (en) * | 2019-07-17 | 2019-12-03 | 长春工业大学 | A kind of annular wireless sensor network Uneven Cluster algorithm based on fuzzy control |
CN111615166A (en) * | 2020-06-02 | 2020-09-01 | 赣南师范大学 | Unmanned aerial vehicle ad hoc network clustering judgment method for agricultural application |
CN111770512A (en) * | 2020-06-05 | 2020-10-13 | 长春工业大学 | Wireless sensor network fan-out routing protocol based on fuzzy logic |
CN111818553A (en) * | 2020-05-21 | 2020-10-23 | 长春工业大学 | Fuzzy logic-based wireless sensor network improved multi-hop LEACH protocol |
CN112020040A (en) * | 2020-08-12 | 2020-12-01 | 北京遥感设备研究所 | Data transmission method and system based on group scheduling |
CN113596950A (en) * | 2021-07-12 | 2021-11-02 | 南昌大学 | Energy-balanced non-equilibrium clustering method for circular wireless sensor network |
CN114223183A (en) * | 2019-08-20 | 2022-03-22 | 三菱电机株式会社 | Method for providing network cooperation for industrial communication system |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104936230A (en) * | 2015-06-15 | 2015-09-23 | 华侨大学 | Wireless sensor network energy balance route optimization method based on cluster head expectation |
CN105915451A (en) * | 2016-05-19 | 2016-08-31 | 东华大学 | Multi-sink deployment and fault tolerance method for wireless sensor network |
-
2017
- 2017-04-18 CN CN201710255988.XA patent/CN107071811B/en not_active Expired - Fee Related
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104936230A (en) * | 2015-06-15 | 2015-09-23 | 华侨大学 | Wireless sensor network energy balance route optimization method based on cluster head expectation |
CN105915451A (en) * | 2016-05-19 | 2016-08-31 | 东华大学 | Multi-sink deployment and fault tolerance method for wireless sensor network |
Non-Patent Citations (2)
Title |
---|
B.BARANIDHARAN等: "DUCF: Distributed load balancing Unequal Clustering in wireless sensor networks using Fuzzy approach", 《APPLIED SOFT COMPUTING》 * |
DAVOOD IZADI等: "An Alternative Clustering Scheme in WSN", 《IEEE SENSORS JOURNAL》 * |
Cited By (27)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107612801B (en) * | 2017-09-30 | 2020-05-22 | 中国兵器装备集团上海电控研究所 | CAN bus dynamic networking method |
CN107612801A (en) * | 2017-09-30 | 2018-01-19 | 中国兵器装备集团上海电控研究所 | A kind of method of CAN dynamic group net |
CN109842508A (en) * | 2017-11-27 | 2019-06-04 | 华为技术有限公司 | The method that multiple terminals cooperates, terminal device and multiple terminals cooperative system |
US11323854B2 (en) | 2017-11-27 | 2022-05-03 | Huawei Technologies Co., Ltd. | Multi-terminal cooperative working method, terminal device, and multi-terminal cooperative system |
CN109842508B (en) * | 2017-11-27 | 2022-04-05 | 华为技术有限公司 | Multi-terminal cooperative work method, terminal equipment and multi-terminal cooperative system |
CN108770029A (en) * | 2018-05-02 | 2018-11-06 | 天津大学 | Cluster-Based Routing Protocols for Wireless Sensor based on cluster and fuzzy system |
CN108770029B (en) * | 2018-05-02 | 2021-05-04 | 天津大学 | Wireless sensor network clustering routing protocol method based on clustering and fuzzy system |
CN108848476A (en) * | 2018-06-21 | 2018-11-20 | 河南科技大学 | Power-efficient data assembly algorithms based on communication distance control in sensor network |
CN109462877A (en) * | 2018-11-16 | 2019-03-12 | 重庆邮电大学 | A kind of WSN energy neutral cluster routing method based on fuzzy logic |
CN110062432A (en) * | 2019-04-26 | 2019-07-26 | 长春师范大学 | A kind of Wireless sensor network clustering routing algorithm based on least energy consumption |
CN110062432B (en) * | 2019-04-26 | 2021-11-23 | 长春师范大学 | Wireless sensor network clustering routing method based on minimum energy consumption |
CN109922511A (en) * | 2019-04-29 | 2019-06-21 | 中国联合网络通信集团有限公司 | Cluster-head node selection method, node clustering method and cluster-head node selection device |
CN110536372B (en) * | 2019-07-17 | 2022-05-31 | 长春工业大学 | Non-uniform clustering method for annular wireless sensor network based on fuzzy control |
CN110536372A (en) * | 2019-07-17 | 2019-12-03 | 长春工业大学 | A kind of annular wireless sensor network Uneven Cluster algorithm based on fuzzy control |
CN114223183A (en) * | 2019-08-20 | 2022-03-22 | 三菱电机株式会社 | Method for providing network cooperation for industrial communication system |
CN110490266B (en) * | 2019-08-23 | 2022-04-22 | 北京邮电大学 | Sensor data uploading and sensor fault detection method and device |
CN110490266A (en) * | 2019-08-23 | 2019-11-22 | 北京邮电大学 | A kind of sensing data uploads, Transducer-fault Detecting Method and device |
CN111818553A (en) * | 2020-05-21 | 2020-10-23 | 长春工业大学 | Fuzzy logic-based wireless sensor network improved multi-hop LEACH protocol |
CN111818553B (en) * | 2020-05-21 | 2022-05-31 | 长春工业大学 | Fuzzy logic-based data transmission method for improving multi-hop LEACH protocol of wireless sensor network |
CN111615166A (en) * | 2020-06-02 | 2020-09-01 | 赣南师范大学 | Unmanned aerial vehicle ad hoc network clustering judgment method for agricultural application |
CN111615166B (en) * | 2020-06-02 | 2022-06-07 | 赣南师范大学 | Unmanned aerial vehicle ad hoc network clustering judgment method for agricultural application |
CN111770512A (en) * | 2020-06-05 | 2020-10-13 | 长春工业大学 | Wireless sensor network fan-out routing protocol based on fuzzy logic |
CN111770512B (en) * | 2020-06-05 | 2023-05-23 | 长春工业大学 | Wireless sensor network sector routing method based on fuzzy logic |
CN112020040A (en) * | 2020-08-12 | 2020-12-01 | 北京遥感设备研究所 | Data transmission method and system based on group scheduling |
CN112020040B (en) * | 2020-08-12 | 2024-03-29 | 北京遥感设备研究所 | Data transmission method and system based on group scheduling |
CN113596950A (en) * | 2021-07-12 | 2021-11-02 | 南昌大学 | Energy-balanced non-equilibrium clustering method for circular wireless sensor network |
CN113596950B (en) * | 2021-07-12 | 2023-03-14 | 南昌大学 | Energy-balanced non-equilibrium clustering method for circular wireless sensor network |
Also Published As
Publication number | Publication date |
---|---|
CN107071811B (en) | 2019-12-27 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN107071811A (en) | A kind of fault-tolerant Uneven Cluster algorithms of WSN based on fuzzy control | |
Bouyer et al. | A new approach for decreasing energy in wireless sensor networks with hybrid LEACH protocol and fuzzy C-means algorithm | |
CN102448138B (en) | Method for clustering hierarchical routing protocols of wireless sensor network | |
CN102036308B (en) | Energy balancing wireless sensor network clustering method | |
CN102149160B (en) | Energy perception routing algorithm used for wireless sensing network | |
CN101466161B (en) | Data collection method suitable for multi-hop wireless sensor network | |
Tillapart et al. | An approach to hybrid clustering and routing in wireless sensor networks | |
CN107333314A (en) | A kind of wireless sense network cluster is built and its cluster head update method | |
Gajjar et al. | FUCP: Fuzzy based unequal clustering protocol for wireless sensor networks | |
CN102740394B (en) | Center calculation wireless sensor network 2-node disjoint multipath routing algorithm | |
CN105682175A (en) | Cluster routing method based on AdHoc Network | |
Kurtoglu et al. | Energy consumption in long-range linear wireless sensor networks using LoRaWan and ZigBee | |
CN102983948B (en) | A kind of radio sensing network self-adaption cluster transmission method and device thereof | |
CN103987102A (en) | Topology control method of underwater wireless sensor network based on non-cooperative game | |
Siqueira et al. | An integrated approach for density control and routing in wireless sensor networks | |
Gharajeh | A neural-MCDM-based routing protocol for packet transmission in mobile ad hoc networks | |
Wang et al. | Sleep scheduling for critical nodes in group-based industrial wireless sensor networks | |
Boucetta et al. | Hierarchical cuckoo search-based routing in wireless sensor networks | |
Yang et al. | A novel energy-efficient data gathering algorithm for wireless sensor networks | |
Ambreen | Wireless sensor network through shortest path route | |
CN107197480A (en) | A kind of tree-shaped method for routing of low-consumption wireless Personal Area Network network based on IPv6 | |
Mellier et al. | A clustering mutual exclusion protocol for multi-hop mobile ad hoc networks | |
Abbas et al. | Lchrep: Layer and cluster based hierarchical routing and energy optimization protocol in wireless sensor networks | |
Pitchai et al. | Game theoretical computation based energy efficient routing for wireless sensor networks | |
Ba et al. | A Novel Aggregation Approach Based on Cooperative Agents and Self-Stabilizing Clustering for WSNs |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20191227 Termination date: 20200418 |
|
CF01 | Termination of patent right due to non-payment of annual fee |