CN102821422A - Network clustering method of mobile sensor based on partition - Google Patents

Network clustering method of mobile sensor based on partition Download PDF

Info

Publication number
CN102821422A
CN102821422A CN2012101826151A CN201210182615A CN102821422A CN 102821422 A CN102821422 A CN 102821422A CN 2012101826151 A CN2012101826151 A CN 2012101826151A CN 201210182615 A CN201210182615 A CN 201210182615A CN 102821422 A CN102821422 A CN 102821422A
Authority
CN
China
Prior art keywords
bunch
subregion
node
mobile sensor
network
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.)
Pending
Application number
CN2012101826151A
Other languages
Chinese (zh)
Inventor
孙咏梅
仇必青
纪越峰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing University of Posts and Telecommunications
Original Assignee
Beijing University of Posts and Telecommunications
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Beijing University of Posts and Telecommunications filed Critical Beijing University of Posts and Telecommunications
Priority to CN2012101826151A priority Critical patent/CN102821422A/en
Publication of CN102821422A publication Critical patent/CN102821422A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • 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

Abstract

The invention discloses a network clustering method of a mobile sensor based on partition, which belongs to the network field of the mobile sensor in the wireless communication. The method not only combines loading conditions of clusters, but also takes the mobility and the rest energy of nodes into consideration. By comparing the numbers of nodes in the clusters, the loading conditions of each cluster can be obtained. The partition of the clusters can be realized by dividing the clusters with large load into a proper amount of subdomains and degrading and fusing the clusters with undersized load. With the adoption of the network clustering method of the mobile sensor, the network connectivity and the stability of the cluster structure can be efficiently enhanced, and the service life of the network is prolonged.

Description

A kind of mobile sensor network cluster-dividing method based on subregion
Technical field
The present invention is research object with the mobile sensor network; Designed a kind of cluster-dividing method based on subregion mechanism; Not only consider mobility but also take into account residue energy of node, the life cycle that can effectively improve network connectivty and prolong network belongs to the mobile sensor network field in the radio communication.
Background technology
Mobile sensor network is mostly by being deployed in miniature, cheap, low-power consumption in the observing environment in a large number, having the network that the mobile node of wireless transmitter is formed; The ability that each node in the network not only possesses sensing, calculating and communicates by letter, and possess certain locomotivity.Generally, in order to prolong the life span of node, have only a spot of node to be responsible for sending query messages in the network, receive the data that other node is uploaded.
Because moving of node, mobile sensor network faces certain challenge: the mobile topologies change that causes of node is frequent, and can not set up message in advance and transmit network; In addition, the positions of mobile nodes frequent updating causes the limited battery of transducer too fast; The mobile node number increases and changes of topology structure needs each node constantly to peripheral network feedback information, has increased the possibility of Network Transmission bandwidth and wireless conflict; Because moving of node, network also of short duration released state may occur, can't guarantee the real-time that packet is transmitted.
Because the above-mentioned challenge of mobile sensor network, it is a kind of effective method that the node in the sensor network is carried out the control of level type topology.Carrying out the control of level type topology the most important thing is the node in the network is carried out rational sub-clustering.
Mobile node with bunch the form networking.Usually, in the monitored area, network is divided into plurality of nodes set, and this set is made up of one, two head node and a plurality of member node, and existing literature is gathered called after bunch to this.Bunch head is responsible for transmitting the Query Information of aggregation node, and sends the sensing data of collecting from member node to aggregation node.Member node is responsible for giving leader cluster node the data upload of collecting.The network redundancy property of this structure is good, and extensibility is strong, can improve the reliability of network, satisfies the demand of large scale deployment.
Early stage sub-clustering algorithm has two kinds: minimum sign priority algorithm (Lowest-ID) and maximum degree of connection priority algorithm (Max-Degree).In minimum identifier priority algorithm, each node has sign (ID) unique in the network-wide basis, and periodically to its ID of neighbor node broadcasting.Like this, each node just can compare ID and its immediate neighbor node of oneself, if find oneself to be the minimum node of ID, then becomes leader cluster node automatically.If a node is within the range of transmission of two or more bunches of heads, then become gateway node.The standard that bunch head of maximum connection degree algorithm is selected is the connection degree, just the immediate neighbor number of a node.The same with minimum ID algorithm; Each node is periodically broadcasted the connection degree of oneself to its immediate neighbor node; Like this, each node just can compare connection degree and the immediate neighbor node of oneself each other, if find that the connection degree of oneself is maximum; Then become leader cluster node automatically, its neighbor node becomes member node.The standard that they are all selected as bunch head with single factor, poor-performing.Therefore there is document to propose improvement to these two rudimentary algorithms, as: Modified Lowest-ID algorithm, the node of selecting to have higher connection degree when the connection degree is identical, are paid the utmost attention to the minimum node of ID as leader cluster node as bunch head.This algorithm has certain advantage in the maintenance of clustering architecture, but it requires the condition that network topology does not change in the clustering process too idealized, in reality, is difficult to satisfy; And a bunch selection standard is single; Lack fairness, therefore, Turgut etc. have proposed the sub-clustering algorithm (WCA) based on weights; The factors such as connection degree, translational speed, energy resource consumption and bunch member's restriction of node have been taken all factors into consideration in the calculating of weights, and have provided the computational methods of each item factor in the weights.Therefore, the connectedness of network improves.Chih-Yu Wen etc. has proposed Self-Adaptive Mobile Clustering Algorithm (SAMCA); Further improved the connectedness of network; This algorithm is mobility and the node degree factor as election of cluster head, and the average node of access speed value trend is as the both candidate nodes of bunch head, but owing to adopt the method for iteration to calculate; Algorithm is comparatively complicated, and does not consider the node energy consumption problem.S.Deng etc. have proposed the cluster-dividing method of mobility-based clustering (MBC); This algorithm synthesis is considered the dump energy and the mobility of node; Employing is similar to the method picked at random bunch head of LEACH, and algorithm is simple, is easy to large scale deployment; Yet the balancing energy of network does not take in, and this will influence the life cycle of network.
Take all factors into consideration above-mentioned factor, need a kind of sub-clustering of mobile sensor network more efficiently mechanism to come balance network load, improve the stability of internodal connectedness and clustering architecture, prolong network life.
Summary of the invention
The present invention be directed to the deficiency of prior art, propose a kind of mobile sensor network cluster-dividing method based on subregion.This method synthesis consider node energy consumption, mobility and bunch in factors such as load, through the subregion that will bunch be divided into right quantity realize to bunch subregion.When bunch in member node quantity when excessive, then select mobility is moderate and dump energy is many node as subregion bunch head, organize other node to form the subarea through a subregion bunch head; When bunch in member node quantity when too small, near then selecting to add bunch, near the subarea becoming bunch.Adopt the mechanism of subregion, the stability that is intended to improve bunch is improved the load-balancing performance of network, reduces the node energy consumption of network, the life cycle that prolongs network.The mobile sensor network sub-clustering step that the present invention is based on subregion is:
Step 1: the node sum in the statistics bunch;
Step 2: whether bunch internal segment of judging each bunch counts greater than mean value N/k (N is the sum of surveyed area interior nodes, and k is the quantity of subregion prevariety), if then execution in step 5; Otherwise, calculate the subregion of the required division of this bunch and count s;
Step 3: whether the node number is less than threshold value Th, if then execution in step 4; Otherwise, execution in step 1;
Step 4: near bunch admittance waiting for, change step 10;
Step 5: calculate Probability p s, energy factors Fe and compare threshold T (i) that member node in this bunch becomes subregion bunch head;
Step 6: each member node produces the random number of (0,1), whether judges random number less than compare threshold, if then execution in step 7; Otherwise, execution in step 8;
Step 7: become subregion bunch head,, change step 10 to neighbor node broadcasting bunch header;
Step 8: become node undetermined;
Step 9: judge whether to receive subregion bunch head broadcasting, if, then select nearest subregion bunch head to add, become the member node of this subregion bunch head; Otherwise, execution in step 8;
Step 10: become the subarea;
In the said step 2, the calculating formula of s is:
Figure BSA00000729369000031
This calculating formula draws through following equation:
n i = N k + s · ( s + 1 ) = sN + N k + s
Wherein, n iRepresent the node sum in i bunch; The sum that k is bunch; N is the sum of surveyed area interior nodes; The value of s is definite through rounding up.
In the said step 3, the calculating formula of Th is:
Th = 1 2 · N k + s
Wherein, the quantity of following bunch of interior nodes of N/ (k+s) expression ideal situation.
In the said step 5, the probability calculation formula that member node becomes subregion bunch head is:
p s = s n
In the said step 5, the energy factors calculating formula of member node is:
F e = e E
Wherein, e representes the current remaining value of mobile node; E representes the primary power value of node.
In the said step 5, the mobility factor calculating formula of member node is:
F v = | V current - 1 2 ( V max + V min ) | 1 2 ( V max - V min )
Wherein, V CurrentThe present rate value of expression mobile node; V MaxThe maximum rate value of expression mobile node; V MinThe minimum-rate value of expression mobile node; 1/2 (V Max+ V Min) estimated mean value of expression node speed.Through following formula, can guarantee that speed is more near 1/2 (V Max+ V Min) node, mobility factor F vMore little.
In the said step 5, the calculating formula of the compare threshold of member node is in bunch:
T ( i ) = p s 1 - p s × r mod ( 1 / p s ) · [ a F e + b ( 1 - F v ) ] , ∀ i ∈ G
Wherein, F vThe expression mobility factor; F eThe expression energy factors; A+b=1; p sThe expression member node becomes the probability of subregion bunch head; R representes the wheel number of current subregion election of cluster head; G representes not have election to be the node set of subregion bunch head.
The beneficial effect of subregion sub-clustering provided by the invention is:
Through contrast bunch interior nodes quantity, draw the loading condition of each bunch.Through with load overweight bunch divide subregion, bunch degradation that load is too small merges, can realize to bunch molecular domains, make each bunch realization load balancing, prolonged the life-span of mobile sensor network.Bunch the subarea cushioned the influence that node motion is brought, can effectively improve the stability of internodal connectedness and clustering architecture.Simultaneously, because the method for molecular domains has shortened internodal communication distance, so the energy consumption validity of node also can be improved.Algorithm is simple, is easy to large scale deployment.
Description of drawings
Fig. 1 is a kind of based on the machine-processed flow chart of the mobile sensor network sub-clustering of subregion of the embodiment of the invention;
Fig. 2 is the flow chart of control subarea scale in the embodiment of the invention;
Fig. 3 is a flow chart of dividing subregion in the embodiment of the invention;
Fig. 4 is the simplified schematic diagram of data acquisition in the partition method in the embodiment of the invention;
Embodiment
For making the object of the invention, technical scheme and advantage clearer, will combine accompanying drawing that embodiment of the present invention is done to describe in detail further below.
Fig. 1 is a kind of based on the machine-processed flow chart of the mobile sensor network sub-clustering of subregion of the embodiment of the invention.At first, the node number of each bunch statistics in separately bunch, bunch internal segment that will obtain the then mean value N/k that counts with bunch internal segment that counts compares, and whether a bunch internal segment of judging each bunch counts greater than mean value, if then carry out the division of subregion; Otherwise if the node number less than threshold value Th, is then waited near bunch admittance, if the node number is not less than threshold value Th, then a statistics bunch internal segment is counted, and repeats said process.
When the load of certain bunch occur unbalanced, perhaps certain key node depleted of energy, said process will repeat, the subregion division of a beginning new round.
Fig. 2 is the flow chart of control subarea scale in the embodiment of the invention.At first, the node sum of statistics in the subarea judges that whether node sum in the subarea is greater than mean value N/ (k+s), if then carry out the subarea and divide; Otherwise, if less than threshold value, then waiting for near subarea, the node sum in the subarea merges, if the node sum in the subarea is not less than threshold value, then repeat said process.
Fig. 3 is a flow chart of dividing subregion in the embodiment of the invention.At first, through calculating the subregion number of the required division of this bunch, draw the probability that member node in this bunch becomes subregion bunch head; Energy factors, mobility factor and the compare threshold of member node in the compute cluster again; Member node produces random number then, whether judges random number less than compare threshold, if; Then become subregion bunch head, and broadcasting subregion bunch header; Otherwise, become node undetermined, and wait for that receiving subregion bunch head broadcasts, when receiving subregion bunch head broadcasting, node then undetermined selects nearest subregion bunch head to add, and becomes the member node of subregion bunch head.
Fig. 4 is the simplified schematic diagram of data acquisition in the partition method in the embodiment of the invention.When bunch in the quantity of mobile node surpass certain value, then divide subregion, in subregion, select bunch head of appropriate nodes as subregion, other node in the subregion then becomes member node.Member node is given subregion bunch head with the information uploading that collects, and subregion bunch head is given bunch head with information uploading again, and bunch head will be given aggregation node from the message transmission of all subregion.
The present invention is through the calculating to the node energy factor and mobility factor; Taken all factors into consideration the factors such as energy consumption and mobility of node, haptophoric number of nodes is divided subregion for unbalanced bunch to load; When having avoided some bunch load overweight; Energy consumption is too fast and lost efficacy in advance, causes the problem of network division, has prolonged the life-span of mobile sensor network.And, as can be seen from Figure 4, bunch subregion cushioned the influence that node motion is brought, the stability of internodal connectedness and clustering architecture is improved.Simultaneously, because the method for molecular domains has shortened internodal communication distance, the energy consumption of node also further reduces.
The above is merely the preferable embodiment of the present invention, and in order to restriction the present invention, protection scope of the present invention should not be as the criterion with the protection range of claim.

Claims (4)

1. mobile sensor network cluster-dividing method based on subregion is characterized in that:
A. bunch load when overweight; Take all factors into consideration the factor such as energy consumption and mobility of node; In conjunction with the number of nodes of this bunch, it is divided into a plurality of subregions, promptly when the quantity of bunch interior nodes during greater than mean value; According to bunch in node sum, bunch sum and the sum of surveyed area interior nodes, be divided into suitable subregion with this bunch is required;
B. through to the too small subregion that bunch is downgraded to neighbours bunch of load, promptly when bunch in node number when too small, with this bunch head degradation, make it to become the subregion that neighbours' bunch head has under its command.
2. a kind of mobile sensor network cluster-dividing method according to claim 1 based on subregion, it is characterized in that selecting the big and speed of dump energy level off to mean value bunch in member node be alternative subregion leader cluster node.
3. a kind of mobile sensor network cluster-dividing method based on subregion according to claim 1 is characterized in that when the quantity of subarea interior nodes is too much, then the subarea is split into the zone of right quantity; When the number of nodes in the subarea is too small, then merge with near subarea.
4. a kind of mobile sensor network cluster-dividing method according to claim 1 based on subregion; It is characterized in that in subregion, selecting bunch head of appropriate nodes as subregion; Other node in the subregion then becomes the member node of subregion; The member node of subregion is given subregion bunch head with the information uploading that collects, and subregion bunch head is given bunch head with information uploading again, and bunch head will be given aggregation node from the message transmission of all subregion.
CN2012101826151A 2012-09-21 2012-09-21 Network clustering method of mobile sensor based on partition Pending CN102821422A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN2012101826151A CN102821422A (en) 2012-09-21 2012-09-21 Network clustering method of mobile sensor based on partition

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN2012101826151A CN102821422A (en) 2012-09-21 2012-09-21 Network clustering method of mobile sensor based on partition

Publications (1)

Publication Number Publication Date
CN102821422A true CN102821422A (en) 2012-12-12

Family

ID=47305212

Family Applications (1)

Application Number Title Priority Date Filing Date
CN2012101826151A Pending CN102821422A (en) 2012-09-21 2012-09-21 Network clustering method of mobile sensor based on partition

Country Status (1)

Country Link
CN (1) CN102821422A (en)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103281741A (en) * 2013-05-16 2013-09-04 东南大学 Wireless sensor network clustering routing method based on hexagonal regional division
CN103561406A (en) * 2013-09-03 2014-02-05 南京林业大学 Wireless sensing routing algorithm with cluster cellular segmentation based on energy balance
CN106304234A (en) * 2016-08-09 2017-01-04 南京邮电大学 A kind of wireless sensor network energy consumption optimization method based on clustering routing agreement
CN106900018A (en) * 2015-12-21 2017-06-27 北京信威通信技术股份有限公司 The frequency processing method and node of wireless ad hoc network
WO2018098753A1 (en) * 2016-11-30 2018-06-07 深圳天珑无线科技有限公司 Management method for distributed network, node and system
CN110312292A (en) * 2019-07-04 2019-10-08 哈尔滨工业大学 A kind of unmanned plane ad hoc network dynamic weighting cluster head electoral machinery
CN111583066A (en) * 2020-05-20 2020-08-25 安徽远洋电力工程有限公司 Power construction site informatization supervision system based on wireless sensor network
CN111726847A (en) * 2020-06-17 2020-09-29 荆门汇易佳信息科技有限公司 Improved grouping method of wireless sensor network based on node energy and density

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102143547A (en) * 2011-01-24 2011-08-03 中国人民大学 Continuous Top-k region query method in wireless sensor network
CN102244658A (en) * 2011-06-28 2011-11-16 南京工业大学 Partitioned type dynamic safety routing method for wireless sensor network on basis of hash chains

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102143547A (en) * 2011-01-24 2011-08-03 中国人民大学 Continuous Top-k region query method in wireless sensor network
CN102244658A (en) * 2011-06-28 2011-11-16 南京工业大学 Partitioned type dynamic safety routing method for wireless sensor network on basis of hash chains

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
CHENG LI等: "A Intra-cluster Routing Protocol—IHMDA", 《IEEE》 *
FEI YE 等: "Sub Cluster Aided Data Collection in Multihop Wireless Sensor Networks", 《IEEE》 *
GIRMA S. TEWOLDE等: "Energy aware adaptive clustering in wireless sensor networks", 《IEEE》 *

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103281741A (en) * 2013-05-16 2013-09-04 东南大学 Wireless sensor network clustering routing method based on hexagonal regional division
CN103281741B (en) * 2013-05-16 2016-01-20 东南大学 A kind of wireless sensor network clustering routing divided based on hexagonal area
CN103561406A (en) * 2013-09-03 2014-02-05 南京林业大学 Wireless sensing routing algorithm with cluster cellular segmentation based on energy balance
CN106900018A (en) * 2015-12-21 2017-06-27 北京信威通信技术股份有限公司 The frequency processing method and node of wireless ad hoc network
CN106304234A (en) * 2016-08-09 2017-01-04 南京邮电大学 A kind of wireless sensor network energy consumption optimization method based on clustering routing agreement
CN106304234B (en) * 2016-08-09 2019-07-23 南京邮电大学 A kind of wireless sensor network energy consumption optimization method based on clustering routing agreement
WO2018098753A1 (en) * 2016-11-30 2018-06-07 深圳天珑无线科技有限公司 Management method for distributed network, node and system
CN110312292A (en) * 2019-07-04 2019-10-08 哈尔滨工业大学 A kind of unmanned plane ad hoc network dynamic weighting cluster head electoral machinery
CN111583066A (en) * 2020-05-20 2020-08-25 安徽远洋电力工程有限公司 Power construction site informatization supervision system based on wireless sensor network
CN111726847A (en) * 2020-06-17 2020-09-29 荆门汇易佳信息科技有限公司 Improved grouping method of wireless sensor network based on node energy and density
CN111726847B (en) * 2020-06-17 2021-12-21 广域铭岛数字科技有限公司 Improved grouping method of wireless sensor network based on node energy and density

Similar Documents

Publication Publication Date Title
CN102821422A (en) Network clustering method of mobile sensor based on partition
Long et al. Energy-aware real-time routing for large-scale industrial internet of things
Nadeem et al. M-GEAR: Gateway-based energy-aware multi-hop routing protocol for WSNs
Prabhu et al. Variable power energy efficient clustering for wireless sensor networks
Gajjar et al. Lifetime improvement of LEACH protocol for Wireless Sensor Network
CN103209455A (en) Wireless sensor network routing method based on node position information
Afsar et al. A load-balanced cross-layer design for energy-harvesting sensor networks
CN103414632A (en) Banded wireless sensor network data routing method
Lehsaini et al. An improved k-means cluster-based routing scheme for wireless sensor networks
Sikeridis et al. Energy-efficient orchestration in wireless powered internet of things infrastructures
CN103209456A (en) Wireless sensing network routing method adopting layering
Bala et al. Proficient D-SEP protocol with heterogeneity for maximizing the lifetime of wireless sensor networks
Bouachir et al. Opportunistic routing and data dissemination protocol for energy harvesting wireless sensor networks
El Ouadi et al. Comparison of LEACH and PEGASIS hierarchical routing protocols in WSN
Kumar et al. Coverage and connectivity aware neural network based energy efficient routing in wireless sensor networks
Atero et al. A low energy and adaptive architecture for efficient routing and robust mobility management in wireless sensor networks
CN105764111A (en) Wireless-sensing-network autonomous routing method
Mehra et al. Energy efficient self organising load balanced clustering scheme for heterogeneous WSN
Khan et al. Gradient cost establishment (grace) for an energy-aware routing in wireless sensor networks
Dasgupta et al. Congestion avoidance topology in wireless sensor network using Karnaugh map
Hsieh Data aggregation model using energy-efficient delay scheduling in multi-hop hierarchical wireless sensor networks
Al Bassam et al. Energy aware and delay-tolerant data gathering in sensor networks with a mobile sink
Banu et al. A New Multipath Routing Approach for Energy Efficiency in Wireless Sensor Networks
Wu et al. A novel location-based routing algorithm for energy balance in wireless sensor networks
Singh et al. SEESH: Sleep-awake energy efficient super heterogeneous routing protocol for wireless sensor networks

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C05 Deemed withdrawal (patent law before 1993)
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20121212