CN102438291A - Data aggregation method for increasing capacity of wireless sensor network - Google Patents
Data aggregation method for increasing capacity of wireless sensor network Download PDFInfo
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Abstract
The invention discloses a data aggregation method for increasing the capacity of a wireless sensor network. The method comprises the following steps of: homalographically clustering the wireless sensor network by using a circular grid; determining aggregated nodes of the clusters, a data aggregation mode of the network and a data transmission mode of the network; and creating a virtual node and thus acquiring a reachable throughput of the node by adopting a scheduling scheme with a load and correlation. By utilizing the method, an actual communication condition of the wireless sensor network is described by using a mode with the communication characteristic, closer to that of a sensor; and furthermore, the data transmission times in the network are reduced, therefore, the balance of the effectiveness and redundancy of information is realized, and the capacity of the wireless sensor network is increased.
Description
Technical field
The present invention relates to a kind of data fusion method, relate in particular to a kind of data fusion method that improves the wireless sensor network capacity.
Background technology
MEMS (Micro-Electro-Mechanism System; MEMS), SOC(system on a chip) (SOC; System on Chip), the develop rapidly of radio communication and low-power-consumption embedded technology; (Wireless Sensor Networks WSNs), and has brought a change of information perception with its low-power consumption, low cost, characteristics distributed and self-organizing to be pregnant with wireless sensor network.Wireless sensor network is formed by being deployed in microsensor nodes a large amount of in the monitored area; The network system of the self-organizing of a multi-hop that forms through communication; Its objective is in the perception of cooperation ground, collection and the processing network's coverage area by the information of perceptive object, and sensing results is sent to aggregation node (Sink).In many fields such as military and national defense, industrial or agricultural, city management, intelligent transportation, environmental monitoring, rescue and relief work, Smart Home, anti-probably anti-terrorism, deathtrap Long-distance Control important scientific research value and application prospects are arranged all.
For wireless sensor network, general final purpose is that the transfer of data that all the sensors is collected arrives aggregation node, further handles and analyzes at aggregation node then, and this process is called data collection.Owing to the energy that sensor node is self-contained is very limited, and the arrangement of sensor network and applied environment have determined impossible frequent change node battery, therefore for data collection; An important challenge is exactly under the prerequisite that guarantees the data collection success rate; Reduce the number of times of transmission, reach the balance of effectiveness of information and redundancy, improve the wireless sensor network capacity; Reduce the energy consumption of wireless sensor network, thus the life-span of prolonging wireless sensor network.
In general, the data that sensor node collected that are arranged in the same area all have correlation on time and space, and these correlation of data have just caused the data redundancy that is transferred to aggregation node at last.On some crucial connected nodes; Before the data that it is gathered and receive institute are passed to aggregation node forward; If can dispose the redundant information in these data; So just can reduce the data amount transmitted of whole network, thereby improve the active block capacity, this technology is called data fusion.In WSNs, adopt the data fusion technology significant to the capacity that improves whole network.
People such as Mingyan Liu have proposed to improve based on dummy node the method for network capacity in " Data-gathering wireless sensor networks:Organization and capacity (wireless sensor network of data collection: structure and capacity) " that 2003 the 43rd phase Computer Networks deliver.Under the pattern of many-to-one network scenarios and TDMA (Time Division Multiple Access), the notion of introducing dummy node can improve the network capacity of system to a certain extent.But they do not consider correlation of data, just the data that collected all are transferred to aggregation node.
" A scalable correlation aware aggregation strategy for wireless sensor networks (being used for the convergence strategy that expanding of wireless sensor network has correlation consciousness) " that people such as Raghupathy Sivakumar delivered at Proceedings.of The First International Conference on Wireless Internet in 2005 provided the strategy that a kind of wireless sensor network data correlation merges.They have at first provided the model of data fusion, then whole network are carried out sub-clustering, then in dividing each good bunch, carry out data fusion, will merge good transfer of data at last again and give aggregation node.But they have only provided the structure of whole network, do not have analysis influence to whole network capacity after merging.
People such as Xiang-Yang Li in 2009 at Proc.of The 6th Annual IEEE Communications Society Conference on Sensor; In " Order-Optimal Data Collection in Wireless Sensor Networks:Delay and Capacity (the suboptimal data collection of wireless sensor network scala media: time delay and capacity) " that Mesh and Ad Hoc Communications and Networks (SECON ' 09) delivers; Whole network is divided into a lot of little square nets; Then data all in each grid are merged, will merge good transfer of data again and give aggregation node.But they have only considered the most simply to merge situation, and just all data can both be fused into a packet on same node, can lose the effective information of a lot of data like this, and this does not conform to a lot of actual conditions.
Therefore, those skilled in the art is devoted to develop a kind of data fusion method that improves the wireless sensor network capacity, reduces the number of transmissions and the energy expense of wireless sensor network in the data-gathering process, reaches the purpose that improves the wireless sensor network capacity.
Summary of the invention
Because the above-mentioned defective of prior art; Technical problem to be solved by this invention provides a kind of data fusion method that improves the wireless sensor network capacity; Use dummy node (Virtual Source) and merge (Correlation Aware Aggregation) through combination based on the correlation data of circular grid sub-clustering; Realize the data collection of wireless sensor network, and improved the network capacity after the data fusion.
For realizing above-mentioned purpose, the invention provides a kind of data fusion method that improves the wireless sensor network capacity, it is characterized in that, may further comprise the steps:
Confirm the quantity of area that wireless sensor network covers, transducer that said network comprises, the channel capacity of said network, the transmission range R of said transducer;
Confirm the interference model of said network; Confirm the degree of correlation between the comentropy that said transducer gathers, said comentropy is the average information that data comprised that said transducer is gathered;
To said network cluster dividing, comprising: the aggregation node with said network is the center of circle, with several concentric circless said network is divided into m layer, and said layer is the annulus that width is r, said width
Each said layer is divided at least one bunch, and said bunch is fan-shaped, and said bunch area is π r
2
In each said bunch, select a sensor node as said bunch fusion node;
Confirm the data fusion mode of said network, comprising: data fusion in the layer, each fusion node of said bunch that the interior data fusion of said layer is said layer receives the comentropy that all the sensors collected in said bunch, and the data fusion of carrying out; Interlayer data fusion, said interlayer data fusion are the comentropies that the fusion node of said layer receives the fusion node of all layers more farther than the said aggregation node of said layer distance, and the data fusion of carrying out;
Confirm the data transfer mode of said network, comprising: the transducer in each said bunch all is transferred to the comentropy that it collected said bunch fusion node; The comentropy of each fusion node of said bunch after data fusion in the said layer and said interlayer data fusion is transferred to than comprises the fusion node of said bunch nearer, the adjacent layer of the said aggregation node of layer distance; Fusion node of each said layer has only accomplishes the comentropy that just continues after the data fusion and said interlayer data fusion in the said layer to transmit after the said data fusion; Comentropy after the said data fusion is transferred to said aggregation node at last;
Create the dummy node of said layer; According to said data transfer mode, the scheduling scheme of employing tool load and correlation obtains reached at the throughput of node, and reached at the throughput of said node is for the average throughput that comprises said dummy node and said source node.
Further, each fusion node of said bunch is the nearest sensor node in arcuate midway point position of the interior circle apart from said bunch in said bunch.
Further, be said aggregation node near said bunch fusion node of said aggregation node.
Further, the degree of correlation between the said transducer comentropy of gathering is based on that the interference model of said network confirms.
Further, the interference model of said network is the interference model of protocol layer or the interference model of physical layer.
Further, the dummy node of creating said layer comprises step: according to the degree of correlation between the said comentropy, and the comentropy total amount of said layer after the data fusion in the said layer of calculating completion; The comentropy total amount of said layer after the said interlayer data fusion of calculating completion; The summation of described result of calculation is exactly the quantity of the dummy node of said layer.
Further, the scheduling scheme of said tool load and correlation comprises step: the interference region that obtains said network according to the interference model of said network; Calculate the quantity of the said dummy node in the said interference region; Obtain the maximal degree of network diagram in the said interference region according to the quantity of the interference region of said network and said dummy node; Confirm the scheduling length of said scheduling scheme, said scheduling length is no more than the maximal degree of network diagram in the said interference region; According to the channel capacity and the said scheduling length of said network, obtain reached at the throughput of said node.
Further, the quantity of the said dummy node in the said interference region is the summation of the dummy node quantity of the said layer in the said interference region.
In preferred embodiments of the present invention; The transmission range r of quantity, channel capacity and the transducer of the transducer that at first confirmed area that wireless sensor network covers, comprises; Adopt the interference model of protocol layer, confirmed the degree of correlation between the comentropy that transducer gathers; Adopt circular grid that network is carried out sub-clustering then, obtain m with the aggregation node of this network be the center of circle, width is the layer of the annulus of r, and then obtain area and be π r
2Fan-shaped bunch; Select in each bunch the fusion node of the nearest sensor node in the arcuate midway point position of interior circle of distance bunch as this bunch, wherein, near aggregation node bunch the fusion node be aggregation node; Through data fusion in the layer and interlayer data fusion; Completion is to the data fusion of this network; Wherein, The data transfer mode of network is: the transducer in each bunch all is transferred to the comentropy that it collected the fusion node of this bunch; The comentropy of the fusion node of each bunch after data fusion is transferred to than comprises the fusion node of the layer of this bunch apart from nearer, the adjacent layer of aggregation node, and the fusion node of each layer has only in the complete layer after the data fusion and interlayer data fusion the comentropy after data fusion is transmitted in just continuation, and all comentropies finally all are transferred to aggregation node; At last, create the dummy node of layer, according to above-mentioned data transfer mode, the scheduling scheme of employing tool load and correlation obtains reached at the throughput of node, and reached at the throughput of node is for the average throughput that comprises dummy node and source node.
Can find out; The present invention carries out the data fusion method of homalographic sub-clustering and sub-clustering through using circular grid to wireless sensor network; The signal intelligence of the reality of wireless sensor network has been described out with the mode of the communication characteristics that more are close to transducer; And reduced the number of times of the transfer of data in the network, reached the balance of effectiveness of information and redundancy, thereby improved the wireless sensor network capacity; Reduce the energy consumption of wireless sensor network in transmission, therefore prolonged the life-span of wireless sensor network.In addition, the present invention combines the technology of dummy node and correlation data fusion, has taken into account the contact between the transducer institute Information Monitoring entropy, and this has improved the capacity of whole network further, thereby has prolonged the life-span of wireless sensor network further.
Below will combine accompanying drawing that the technique effect of design of the present invention, concrete structure and generation is described further, to understand the object of the invention, characteristic and effect fully.
Description of drawings
Fig. 1 is the layout sketch map of the wireless sensor network of preferred embodiment of the present invention;
Fig. 2 is the flow chart of the data fusion method of raising wireless sensor network capacity of the present invention;
Fig. 3 is the sketch map of cluster-dividing method of the circular grid of preferred embodiment of the present invention.
Embodiment
As shown in Figure 1, in the wireless sensor network of present embodiment, be positioned at home position as the sensor node of aggregation node, other sensor nodes (i.e. source node among the figure) are randomly dispersed in current region.Source node can directly be transferred to aggregation node with information through the mode of a jumping, also can message transmission be arrived aggregation node through the mode of multi-hop.
Set current network and only use single channel to transmit, utilize TDMA to carry out the scheduling of message transmission, the comentropy that each transducer collected all is the unit information amount, and each sensor node all has enough buffering areas simultaneously.The step of data fusion method that improves this wireless sensor network capacity is as shown in Figure 2, for:
At first, confirm the number of sensors, the channel capacity of current network and the transmission range of transducer that are comprised in area that whole wireless sensor network covers, the current network.
In this example, the border circular areas area that wireless network is covered is set at 1, and the number of sensors that is comprised is n, and the channel capacity of current network is W, and the transmission range of each transducer all is R.
Secondly, confirm the degree of correlation between the interference model of wireless sensor network and the comentropy (Entropy) that transducer is gathered, comentropy is the average information that data comprised that transducer is gathered.
Adopt the interference model of protocol layer in this example.If X
iAnd X
jBe that two distances are d
I, jNode, if nodes X
kTransmit data, having only the d of satisfying so
I, j≤r and d
K, j＞r+ Δ, Δ>=0 (i, j, k=1,2 ..., when n, i ≠ j ≠ k), just can carry out the transmission of success between these two nodes.Therefore, if the distance between two nodes will produce interference less than the 2r+ Δ when they transmit data simultaneously.
In this example, the degree of correlation between the comentropy is taken as ρ ∈ [0,1], if the comentropy that each node collected is H
0, the part that comentropy is associated between two nodes so will be ρ H
0, unconnected part will be 2 (1-ρ) H
0, therefore, the comentropy total amount is (2-ρ) H after the data fusion
0
Area and number of sensors according to the wireless sensor network that obtains in the step 101 covers come whole network is carried out sub-clustering, guarantee that the area of each bunch all equates, and guarantee that the transducer that is in cluster can communication within a jumping.
Adopt the method for circular grid to come whole border circular areas is carried out sub-clustering in this example.At first; With the aggregation node is the center of circle; With whole area dividing is m donut; And make that the width of each annulus all is r; The sensor node (being source node) of the 1st annulus of width
(promptly near the annulus of aggregation node) lining is jumped through 1 and can be reached aggregation node; The sensor node of the 2nd annulus (i.e. the annulus of the cylindrical adjacency of the 1st annulus) lining is jumped through 2 and can be reached aggregation node, and the sensor node in m annulus is jumped through m and can be reached aggregation node, all is that 1 jumping can reach between 2 simultaneously adjacent annulus.Jumping figure according to reaching aggregation node is different, we with annulus be numbered 1,2 respectively ..., m, and be called respectively wireless sensor network layer 1,2 ..., m.In the wireless sensor network of the circular grid sub-clustering of Fig. 3, m=5.
For layer j, promptly j annulus (j=1,2 ... M), we further it to be divided into 2j-1 isogonism fan-shaped, as shown in Figure 3; Through after dividing, layer 1 constitutes by bunches 11, and layer 2 constitutes by bunches 21,22,23; Layer 3 by bunches 31,32 ..., 35 constitute, layer 4 by bunches 41,42 ..., 47 constitute, layer 5 by bunches 51,52 ..., 59 constitute.For the situation of j＞5, by that analogy.Can find out that the area of these bunches equates, all is A
r=π r
2Like this, through division comprise in the network of back bunch add up to m
2(that is: 1+3+...+2m-1).Because all transducers all are random distribution, the number of sensors V that each bunch comprised so
rJust there is very big probability to be in the interval
Sequence { α wherein
nLim satisfies condition
N → ∞α
n/ n=ε, ε be one positive indivisible, n representes the quantity of transducer in the whole network.
According to the sub-clustering result who obtains in the step 102; In each bunch, select a sensor node as merging node; In this example; Choose in each bunch (fan-shaped) apart from the fusion node of the nearest sensor node in the arcuate midway point position of circle in it as this bunch, the sensor node of (being within bunches 11 among Fig. 3) will directly be chosen aggregation node as the fusion node within aggregation node 1 is jumped.
According to the fusion node of each bunch that obtains in the step 103, all sensor node all carries out data fusion with the fusion node that the comentropy that it collected is transferred to this bunch in each bunch, i.e. data fusion in the layer.The sensor node of (being within bunches 11 among Fig. 3) was directly passed to aggregation node with comentropy within aggregation node 1 was jumped.
According to the distance relation of the place layer that merges node, with from confirm to merge the transmission sequence between the node as far as near mode apart from aggregation node.Each layer represent one to merge rank in the present embodiment, the fusion node of each layer all to wait outer field fusion node with transfer of data to after it, merge again, and then data passed to the fusion node of nexine.That is: the fusion node of the layer far away apart from aggregation node is transferred to the comentropy of accomplishing data fusion the fusion node of the layer nearer apart from aggregation node; And; For each layer; Have only fusion node to receive all comentropies, and after having carried out the maximization fusion, could allow its fusion node that transfer of data is arrived the fusion node than its layer nearer apart from aggregation node than the fusion node of its layer farther apart from aggregation node when it.Merge node receive all layers more farther apart from aggregation node than the layer at its place the fusion node comentropy and the data fusion of carrying out is the interlayer data fusion.This process is accomplished through step 105-121.
Like this; For the wireless sensor network of having confirmed to merge node in the step 103; The fusion node of layer k+1 is a certain fusion node of the transfer of data of accomplishing data fusion to layer k, and this merges node select ground is that nearest fusion node of fusion node that layer k middle distance need transmit data.The fusion node of layer among the k is only in the comentropy of the fusion node of having accepted all layers k+1; And the comentropy of having accepted all the sensors node among the layer k is carried out data fusion afterwards again, is transferred to the comentropy of accomplishing data fusion the fusion node of layer k-1 then.
The fusion node of each layer carries out data fusion with its own comentropy that is collected with the comentropy that other nodes are transferred to it, is merging the dummy node that total the number of transmissions equates in generation and this layer after accomplishing.
Sub-clustering result according to confirming in the step 102 uses n
jThe all the sensors quantity of presentation layer j has very big probability n so
jBe in the interval
In, use k
jRepresent that all numbers of plies (jumping figure) greater than the number of sensors in the layer of j, have very big probability k so
jBe in the interval
In, the quantity of the fusion node that is comprised among the layer j is S
j=2j-1.
All comentropies are transferred to that to merge the needed the number of transmissions of node be exactly n in the layer j so
j, all numbers of plies are exactly the size that they accomplish data fusion comentropy afterwards, just ρ S greater than the needed the number of transmissions of fusion node that the comentropy in the layer of j is transferred to layer j
j+ k
j(1-ρ), therefore, the quantity of all dummy nodes that produced in the layer j is exactly H
j=ρ S
j+ k
j(1-ρ)+n
j
Can obtain the interference region in the wireless sensor network according to determined interference model in the step 101, calculate the quantity that is in all dummy nodes in the interference region then, can obtain the maximal degree of network diagram in the interference region thus.Be in particular: with the summit of dummy nodes all in the network when mapping, the summit that is in the interference region is then linked to each other by the limit of figure, constructs the figure of the whole network characteristic of representative thus; According to the quantity of dummy node and the characteristic of said figure, obtain the maximal degree of network diagram in the interference region by the graph theory theory.
In the present embodiment, the interference length that obtains in the step 101 is the 2r+ Δ, and when Δ=0, interference region is exactly 2 jumping scopes, and when Δ=r, interference region is exactly 3 jumping scopes.Because the quantity the closer to its dummy node of zone of aggregation node is many more, the interference region that therefore comprises maximum dummy node quantity is exactly the zone of jumping to the jumping of 2r+ Δ from aggregation node 1.The quantity of dummy node is
in this interference region
Thus, necessarily have a kind of scheduling scheme, its scheduling length is no more than the maximal degree of network diagram in the interference region.Therefore there is a kind of scheduling scheme of dispatching length s≤k, can interference-free all comentropies all be transferred to aggregation node.
Step 124 obtains current network average nodal throughput.According to the data transfer mode among the step 105-121; Adopt LCAS (load and correlation aware; Tool load and correlation) scheduling scheme can obtain reached at the throughput of node, and reached at the throughput of node is for the average throughput that comprises dummy node and source node.
According to the scheduling length that obtains in the channel capacity of the wireless sensor network that obtains in the step 101 and the step 123, can obtain the throughput that reaches of each node.
The throughput of representing each node with λ; Can obtain
so further; When Δ=0; Interference region is from aggregation node 2 jumping scopes;
is when Δ=r; Interference region is from aggregation node 3 jumping scopes,
This instance has so far just obtained final network capacity result; Compare the method that other improve network capacity; One aspect of the present invention through sub-clustering balanced energy consumption, prolonged network useful life, combined the technology of dummy node and correlation data fusion on the other hand; Better utilization the correlation between the data that transducer collected, thereby improved the network capacity of wireless sensor network.
More than describe preferred embodiment of the present invention in detail.Should be appreciated that those of ordinary skill in the art need not creative work and just can design according to the present invention make many modifications and variation.Therefore, the technical staff in all present technique field all should be in the determined protection range by claims under this invention's idea on the basis of existing technology through the available technical scheme of logical analysis, reasoning, or a limited experiment.
Claims (8)
1. data fusion method that improves the wireless sensor network capacity; It is characterized in that, may further comprise the steps: confirm the quantity of area that wireless sensor network covers, transducer that said network comprises, the channel capacity of said network, the transmission range R of said transducer;
Confirm the interference model of said network; Confirm the degree of correlation between the comentropy that said transducer gathers, said comentropy is the average information that data comprised that said transducer is gathered;
To said network cluster dividing, comprising: the aggregation node with said network is the center of circle, with several concentric circless said network is divided into m layer, and said layer is the annulus that width is r, said width
Each said layer is divided at least one bunch, and said bunch is fan-shaped, and said bunch area is π r
2
In each said bunch, select a sensor node as said bunch fusion node;
Confirm the data fusion mode of said network, comprising: data fusion in the layer, each fusion node of said bunch that the interior data fusion of said layer is said layer receives the comentropy that all the sensors collected in said bunch, and the data fusion of carrying out; Interlayer data fusion, said interlayer data fusion are the comentropies that the fusion node of said layer receives the fusion node of all layers more farther than the said aggregation node of said layer distance, and the data fusion of carrying out;
Confirm the data transfer mode of said network, comprising: the transducer in each said bunch all is transferred to the comentropy that it collected said bunch fusion node; The comentropy of each fusion node of said bunch after data fusion in the said layer and said interlayer data fusion is transferred to than comprises the fusion node of said bunch nearer, the adjacent layer of the said aggregation node of layer distance; Fusion node of each said layer has only accomplishes the comentropy that just continues after the data fusion and said interlayer data fusion in the said layer to transmit after the said data fusion; Comentropy after the said data fusion is transferred to said aggregation node at last;
Create the dummy node of said layer; According to said data transfer mode, the scheduling scheme of employing tool load and correlation obtains reached at the throughput of node, and reached at the throughput of said node is for the average throughput that comprises said dummy node and said source node.
2. the data fusion method of raising wireless sensor network capacity as claimed in claim 1, wherein said bunch fusion node are the nearest sensor nodes in arcuate midway point position of the interior circle apart from said bunch in said bunch.
3. the data fusion method of raising wireless sensor network capacity as claimed in claim 2 is said aggregation node near said bunch fusion node of said aggregation node wherein.
4. the data fusion method of raising wireless sensor network capacity as claimed in claim 3, the degree of correlation between the comentropy that wherein said transducer is gathered are based on that the interference model of said network confirms.
5. the data fusion method of raising wireless sensor network capacity as claimed in claim 4, the interference model of wherein said network are the interference model of protocol layer or the interference model of physical layer.
6. the data fusion method of raising wireless sensor network capacity as claimed in claim 5; The dummy node of wherein creating said layer comprises step: according to the degree of correlation between the said comentropy, and the comentropy total amount of said layer after the data fusion in the said layer of calculating completion; The comentropy total amount of said layer after the said interlayer data fusion of calculating completion; The summation of described result of calculation is exactly the quantity of the dummy node of said layer.
7. the data fusion method of raising wireless sensor network capacity as claimed in claim 6, the scheduling scheme of wherein said tool load and correlation comprises step: the interference region that obtains said network according to the interference model of said network; Calculate the quantity of the said dummy node in the said interference region; According to the interference region of said network, obtain the maximal degree of network diagram in the said interference region; Confirm the scheduling length of said scheduling scheme, said scheduling length is no more than the maximal degree of network diagram in the said interference region; According to the channel capacity and the said scheduling length of said network, obtain reached at the throughput of said node.
8. the data fusion method of raising wireless sensor network capacity as claimed in claim 7, the quantity of the said dummy node in the wherein said interference region are the summations of the dummy node quantity of the said layer in the said interference region.
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