CN101621855A - Network data processing method, network node equipment and synthesis center equipment - Google Patents
Network data processing method, network node equipment and synthesis center equipment Download PDFInfo
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- CN101621855A CN101621855A CN200910089831A CN200910089831A CN101621855A CN 101621855 A CN101621855 A CN 101621855A CN 200910089831 A CN200910089831 A CN 200910089831A CN 200910089831 A CN200910089831 A CN 200910089831A CN 101621855 A CN101621855 A CN 101621855A
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Abstract
The invention provides a network data processing method, network node equipment and synthesis center equipment. The method comprises the steps: constructing a graphic wavelet corresponding to a network node, and exchanging node data on the network node by applying the graphic wavelet so as to obtain the transform data of the network node, wherein the graphic wavelet is used for comparing the network node with network node data in an adjacent region of the network node; compressing the transform data by applying a random compression sensing matrix generated by the network node so as to obtain the compression data of the network node; mixing the compression data and the compression data of other network nodes in a free space so as to obtain mixed compression data, and sending the mixed compression data to a synthesis center. The invention utilizes the graphic wavelet to realize the sparseness of data in space through jointing the whole network data, thereby realizing the compression of rarefactional data and non-rarefactional data based on a network data integer.
Description
Technical field
The embodiment of the invention relates to the wireless monitoring technology field, relates in particular to a kind of processing method, apparatus for network node and fusion center equipment of network data.
Background technology
In correlation technique, monitoring and interception system will depend on distributed wireless sensor network miscellaneous more and more, to guarantee still can to obtain data reliably under various extreme complexity and unsettled environment.At present, monitoring system adopts in each network node Information Monitoring and transmits the back and monitor in the mode that the purpose network node merges, and this mode has been widely used in comprising non-military fields such as control, communication, intellectual monitoring, tracking, remote sensing, navigation, meteorology, air traffic control and medical treatment.Comprise a large amount of wireless sensor nodes in the sensor network, be distributed in the physical environment that to observe.Comprise a fusion center in the wireless sensor network, its function mainly is to carry out the fusion and the reconstruct of data, is the final purpose node of sensor node.In addition, because the data of each node accumulate whole network data (network data) in the network, if interstitial content is bigger, then network data also can become greatly thereupon, and data mobile in network brought very big difficulty.Therefore, press for safe storage, transmission and the processing that active data compression and reconstructing method are realized data.
At present, data compression comprises with reconstructing method: relevant distributed source coding method, cooperation transmission method.Wherein, relevant distributed source coding method is carried out the Slepian-Wolf coding according to the correlation of known different node datas, and the Slepian-Wolf coding can be used for the data compression of non-cooperation.But in most of the cases, the data dependence of different nodes is difficult to determine.Cooperation transmission method utilizes the processing and the compression of internodal mutual realization network cooperation, and internodal correlation can be obtained by the cooperation part interactive information, but cooperation transmission requires than higher system complexity, is unfavorable for design and realization.
In correlation technique, also comprise compression sensing (Compressed Sensing; Hereinafter to be referred as CS) technology, this technology and traditional data sampling have obtained very big difference.The collection quantity of CS technique table clear signal can be much smaller than traditional sampled data.The realization of CS is based on two criterions: sparse property and incoherence.Wherein, sparse property is meant that the information rate of continuous time signal may be much smaller than its shared bandwidth, or the quantity of the discrete-time signal degree of freedom is much smaller than the length of signal.More precisely, the CS technology is based on natural signal by after some conversion, and the sparse or compressible fact realizes under suitable substrate is represented, for example, and discrete cosine transform, wavelet transform and Fourier transform etc.Incoherence has been represented a kind of antithesis characteristic, is similar to frequency and time relation.That is to say that sampled signal is very intensive at the subbasal waveform of specific base.But, because CS is based on the hypothesis of the sparse property of signal, only the data in the collection of single network node have under the situation of sparse property, just can use CS and carry out data compression,, just can't compress these data if the data of gathering do not have sparse property, in addition, because the incoherence criterion of CS makes CS to compress individual data, and does not consider the correlation between the whole network data.
Summary of the invention
The embodiment of the invention provides a kind of processing method, apparatus for network node and fusion center equipment of network data, in order to solve the defective that to compress the network node data of non-sparse property in the prior art and can only compress the single network node data, can utilize the figure small echo to realize data sparse property spatially, and carry out network level associating CS compression.
The embodiment of the invention provides a kind of processing method of network data, comprise: tectonic network node graph of a correspondence small echo, and the Graphics Application small echo carries out conversion to the node data on the network node, obtain the transform data of network node, wherein, the figure small echo is used for the comparison to the data of the network node in the adjacent area of network node and network node; The sensing matrix of compression at random that the application network node produces compresses transform data, obtains the packed data of network node; Packed data is mixed at free space with the packed data of other network nodes, obtain mixing compressed certificate and issue fusion center.
The embodiment of the invention also provides a kind of apparatus for network node, comprise: processing module, be used for tectonic network node graph of a correspondence small echo, and the Graphics Application small echo carries out conversion to the node data on the network node, obtain the transform data of network node, wherein, the figure small echo is used for the comparison to the data of the network node in the adjacent area of network node and network node; Compression module, the sensing matrix of compression at random that is used for the generation of application network node compresses transform data, obtains the packed data of network node; Mixing module is used for packed data is mixed at free space with the packed data of other network nodes, obtains mixing compressed certificate and issues fusion center.
The embodiment of the invention also provides a kind of fusion center equipment, comprising: receiver module is used to receive mixing compressed certificate; First reconstructed module is used for mixing compressed certificate is passed through iterative operation calculated data correlation, and according to the projection of data dependence computing node data at the figure small echo; Second reconstructed module is used for the figure inverse wavelet transform is carried out in projection, obtains the node data of reconstruct.
The processing method of the network data of the embodiment of the invention, apparatus for network node and fusion center equipment, by the data of whole network are united, utilize the figure small echo to realize data sparse property spatially, carry out network level associating CS compression, overcome the defective that to compress the network node data of non-sparse property in the prior art and can only compress the single network node data, can realize the compression of data integral body Network Based sparse property data and non-sparse property data.
Description of drawings
Fig. 1 is the flow chart of processing method of the network data of the embodiment of the invention;
Fig. 2 is the schematic diagram of the apparatus for network node of the embodiment of the invention;
Fig. 3 is the structural representation of the fusion center equipment of the embodiment of the invention.
Embodiment
Further specify the technical scheme of the embodiment of the invention below in conjunction with the drawings and specific embodiments.
According to embodiments of the invention, a kind of processing method of network data is provided, Fig. 1 is the flow chart of processing method of the network data of the embodiment of the invention.In embodiments of the present invention, the data of whole network are united consideration, utilize the correlation in space, represent, and carry out network level associating CS compression and reconstruct by the sparse property of figure small echo realization network data under spatial alternation.Below, the technical scheme of the embodiment of the invention is elaborated, as shown in Figure 1, comprise following processing according to the processing method of the network data of the embodiment of the invention:
Particularly, suppose that V represents the set of network node, E represents the set on the limit between the network node, connection layout G=(the V that can represent network node by V, E, E), the degree of this connection layout is N=|G|, and with the yardstick of the jumping figure between network node in the network as distance between the measurement network node.Wherein, N represents that this network node is a N network node in the network, N 〉=1, v
l∈ V, l=1,2..., N can represent network node in the network.
In step 101, the figure small echo mainly is the comparison that is used for the data of network node in network node in the network given area and the adjacent area.Wherein, the given area is meant with observation network node v
lBeing the center, is the circle of radius with the j jumping, and j 〉=0 is if node itself is promptly represented in 0 jumping.
In network, the notion in zone can reflect by jumping figure easily.Define v in embodiments of the present invention
lH hop neighbor N
h(v
l), h 〉=0 is that jumping figure is apart from network node v
lSmaller or equal to the set of the node of h, wherein, 0 to jump be exactly node v
lItself, i.e. N
0(v
l)=v
lIn addition, " the ring zone " in the embodiment of the invention is meant: suppose N
h(v
l) represent apart from v
lBe the network node of jumping, N smaller or equal to h
H-1(v
l) represent apart from v
lBe the network node of jumping, N ' smaller or equal to h-1
h(v
l) be v
lThe node that lucky h jumps, | N '
h(v
l) | expression is apart from v
lJust be the number of the network node of h jumping, N '
h(v
l)=N
h(v
l) N
H-1(v
l).Wherein, J
lRepresent network node v
lDistance, that is, and J
lEqual apart from v
lMaximum hop count h, j
1〉=0.That is to say non-null set
But
Below, the process of tectonic network node graph of a correspondence small echo is described in detail.
1, be positioned at l=1 for each, 2 ..., N, j≤J
lNetwork node v, the definition ψ
J, l: V → i, and according to
Construct the figure small echo Ψ of this network node
J, l(v), wherein,
C
J, lBe normalization factor,
By the figure small echo of above-mentioned processing structure, satisfy two characteristics of wavelet transformation:
With
Subsequently, figure small echo that can application construction acts on node data f
l, l=1,2 ..., N, that is, the Graphics Application small echo carries out conversion to the node data on the network node, obtains the transform data of network node, specifically comprises following processing:
According to
Obtain the transform data of network node, wherein, x
1Be transform data, f
1Be node data.x
lCan satisfy the requirement of the sparse property of signal.
Particularly, each network sensor node utilizes local media access control (Media AccessControl; Hereinafter to be referred as: MAC) address produces { A as the seed of pseudorandom number generator
l, l=1,2 ..., N random number.Fusion center only need know that the MAC Address of each node promptly can obtain { A easily
l, l=1,2 ..., N, wherein, { A
l, l=1,2 ..., N is k * n rank CS matrixes at random, k=n, k＞1, n＞1.
Be positioned at l=1,2 ..., the network node at N place is with transform data x
l∈ i multiply by { A
l, l=1,2 ..., N obtains packed data y
l=A
lx
l, l=1 ..., N, y
l∈ i.Through above-mentioned processing, with n * 1 rank vector x
lBecome k * 1 rank measurand y
l, in embodiments of the present invention, measurand also can become packed data.
Particularly, N network node sends packed data y simultaneously
lTo fusion center, since the characteristic of wireless transmission, packed data y
lCan mix at free space, the signal that fusion center receives then is
Wherein, Z is mixing compressed certificate, and e is the receiver noise of described fusion center.
A plurality of sensing datas are together interrelated, that is, and and X=[x
1, x
2..., x
N]
T, x
lBe node data at each sensor node place, in addition, A=[A
1..., A
N]
T, therefore, Z also can be expressed as Z=AX+E, and wherein, the represented physical significance of e and E is identical.
Because the dimension of Z is much smaller than the dimension of X, the processing at a certain node place to packed data all is being very effective aspect the wireless sensing still in fail safe.
By above-mentioned processing, can realize the compression of data integral body Network Based to sparse property data and non-sparse property data.
Packed data is being mixed at free space with the packed data of other network nodes, obtain mixing compressed certificate and issue after the fusion center, fusion center need be reconstructed the data of compression, specifically comprise following processing: at first, fusion center receive mixing compressed according to after, calculate mixing compressed certificate and the described data dependence that compresses sensing matrix at random by iterative operation, and extract of the projection of reconstruct node data at the figure small echo according to compressing in the sensing matrix row that have a data dependence with described mixing compressed certificate at random, subsequently, fusion center carries out the figure inverse wavelet transform to projection, obtains the node data of reconstruct.Particularly:
1, when iterations iter=1, the remaining matrix of variables Q of initialization
0=Z, and the null matrix Z on k * N rank is set
0
2, when the p time iteration, according to
Calculated data q with compress the correlation of each row in the sensing matrix at random, and find out and compress the row that have maximum correlation in the sensing matrix with data q, r at random
pExpression row mark, wherein, q
Jcol P-1The vector of representing the remaining matrix of variables of a preceding iteration, A
l JcolExpression A
lThe j column vector;
3, establish set omega
p=Ω
P-1Ur
p, from A
lThe middle row that extract are designated as Ω
pRow form k * p rank matrix
Belong to A
lThe subspace, subsequently, utilize
Estimate the x of the p time iteration
l p, then each iteration can obtain the vector x of p * 1
l pIn addition,
Then
Therefore, the participation matrix of the p time iteration is Q
p=Z-Z
p
4, iterative repetition is k time, obtains the projection x of node data at the figure small echo
l k, wherein, x
l kHave sparse property, k equals { A
M, lThe line number of matrix;
5, utilize the inverse transformation of figure small echo, according to f
l=Ψ
J, l -1x
lObtain original node data.
By above-mentioned processing, can utilize the figure small echo to realize the conversion of the sparse property of network data, and the node data on the network node is compressed and reconstruct.
According to embodiments of the invention, a kind of apparatus for network node also is provided, Fig. 2 is the schematic diagram of the apparatus for network node of the embodiment of the invention, as shown in Figure 2, comprises according to the apparatus for network node of the embodiment of the invention: processing module 20, compression module 22, mixing module 24.Below, the apparatus for network node of the embodiment of the invention is elaborated.
Particularly, processing module 20 is used for tectonic network node graph of a correspondence small echo, and the Graphics Application small echo carries out conversion to the node data on the network node, obtain the transform data of network node, wherein, the figure small echo is used for the comparison to the data of the network node in the adjacent area of network node and network node;
Particularly, processing module 20 is positioned at l=1 for each, and 2 ..., N, j≤J
lNetwork node v, according to
Construct the figure small echo Ψ of this network node
J, l(v); Wherein, N represents that this network node is a N network node in the network, N 〉=1, and j is to expression network node v
lDistance, j 〉=0, j
1〉=0; v
l∈ V, V are the set of network node in the network;
N '
h(v
l) be v
lH jump the node set of ring, N '
h(v
l)=N
h(v
l) N
H-1(v
l), N
h(v
l) represent apart from v
lBe the set of network nodes that h jumps, N
H-1(v
l) represent apart from v
lBe the set of network nodes that h-1 jumps, h 〉=0; C
J, lBe normalization factor,
Subsequently, processing module 20 can basis
Obtain the transform data of network node, wherein, x
1Be transform data, f
1Be node data.
Particularly, compression module 22 can be according to y
l=A
lx
l, l=1 ..., N obtains packed data, wherein, { A
l, l=1,2 ..., N is the sensing matrix of compression at random that network node utilizes k * n rank that the local media access control address produces as the seed of pseudorandom number generator, k=n wherein, k＞1, n＞1.
Particularly, mixing module 24 bases
Packed data is mixed at free space with the packed data of other network nodes, and wherein, Z is mixing compressed certificate, X=[x
1, x
2..., x
N]
T, A=[A
1..., A
N]
T, e is the receiver noise of fusion center.
More than the details of processing of each module can reference method embodiment related content understand, repeat no more inferior.
By above-mentioned processing, apparatus for network node can realize that data integral body Network Based compresses sparse property data and non-sparse property data.
According to embodiments of the invention, a kind of fusion center equipment is provided, Fig. 3 is the structural representation of the fusion center equipment of the embodiment of the invention, as shown in Figure 3, comprises according to the fusion center equipment of the embodiment of the invention: receiver module 30, first reconstructed module 32, second reconstructed module 34.Below, the fusion center equipment of the embodiment of the invention is elaborated.
Particularly, receiver module 30 receives the mixing compressed certificate that above-mentioned network node sends; Receiver module 30 receive mixing compressed according to after, 32 pairs of described mixing compressed certificates of first reconstructed module are by iterative operation calculated data correlation, and calculate the projection of described node data at described figure small echo according to described data dependence; Subsequently, the figure inverse wavelet transform is carried out in 34 pairs of described projections of second reconstructed module, obtains the described node data of reconstruct.
Particularly, 1, when iterations iter=1, the remaining matrix of variables Q of first reconstructed module, 32 initialization
0=Z, and the null matrix Z on k * N rank is set
0
2, when the p time iteration, first reconstructed module, 32 bases
The correlation of calculated data q and each row of matrix, and find out the row with maximum correlation, r
pExpression row mark,, wherein, q
Jcol P-1The vector of representing the remaining matrix of variables of a preceding iteration, A
l JcolExpression A
lThe j column vector.
3, first reconstructed module 32 is established set omega
p=Ω
P-1Ur
p, by Ω
pForm k * p rank matrix
Belong to A
lThe subspace, subsequently, utilize
Estimate the x of the p time iteration
l p, then each iteration can obtain the vector x of p * 1
l pIn addition,
Then
Therefore, the participation matrix of the p time iteration is Q
p=Z-Z
p
4, first reconstructed module, 32 iterative repetitions are k time, obtain the projection x of node data at the figure small echo
l k, wherein, x
l kHave sparse property, k equals { A
M, lThe line number of matrix.
5, second reconstructed module 34 is utilized the inverse transformation of figure small echo, according to f
l=Ψ
J, l -1x
lObtain original node data.
Device embodiment described above only is schematic, wherein said unit as the separating component explanation can or can not be physically to separate also, the parts that show as the unit can be or can not be physical locations also, promptly can be positioned at a place, perhaps also can be distributed on a plurality of network element.Can select wherein some or all of module to realize the purpose of present embodiment scheme according to the actual needs.Those of ordinary skills promptly can understand and implement under the situation of not paying performing creative labour.
The processing method of the network data of the embodiment of the invention, apparatus for network node and fusion center equipment, by the data of whole network are united, utilize the figure small echo to realize data sparse property spatially, carry out network level associating CS compression, overcome and can not the network node data of non-sparse property have been compressed in the prior art and can only compress, can realize compression and the reconstruct of data integral body Network Based sparse property data and non-sparse property data to the single network node data.
It should be noted that at last: above embodiment only in order to technical scheme of the present invention to be described, is not intended to limit; Although with reference to previous embodiment the present invention is had been described in detail, those of ordinary skill in the art is to be understood that: it still can be made amendment to the technical scheme that aforementioned each embodiment put down in writing, and perhaps part technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (10)
1, a kind of processing method of network data is characterized in that, comprising:
Tectonic network node graph of a correspondence small echo, and use described figure small echo the node data on the described network node is carried out conversion, obtain the transform data of described network node, wherein, described figure small echo is used for the comparison to the data of the network node in the adjacent area of described network node and described network node;
The sensing matrix of compression at random of using described network node generation compresses described transform data, obtains the packed data of described network node;
Described packed data is mixed at free space with the packed data of other network nodes, obtain mixing compressed certificate and issue fusion center.
2, the processing method of network data according to claim 1 is characterized in that, also comprises:
Described fusion center receive described mixing compressed according to after, calculate described mixing compressed certificate and the described data dependence that compresses sensing matrix at random by iterative operation, and have of the projection of the described node data of row extraction reconstruct of data dependence with described mixing compressed certificate at described figure small echo according to described the compression at random in the sensing matrix;
Described fusion center carries out the figure inverse wavelet transform to described projection, obtains the described node data of reconstruct.
3, the processing method of network data according to claim 2 is characterized in that, described tectonic network node graph of a correspondence small echo comprises:
Be positioned at l=1 for each, 2 ..., N, j≤J
lNetwork node v, according to
Construct the figure small echo Ψ of this network node
J, l(v);
Wherein, N represents that this network node is a N network node in the network, N 〉=1, j
lRepresent network node v
lDistance, j 〉=0; J represents apart from v
lJumping figure.L represents l node.v
l∈ V, V are the set of network node in the network;
4, the processing method of network data according to claim 3 is characterized in that, the described figure small echo of described application carries out conversion to the node data on the described network node, and the transform data that obtains described network node comprises:
According to
Obtain the transform data of described network node, wherein, x
lBe described transform data, f
lBe described node data.
5, the processing method of network data according to claim 4 is characterized in that, the sensing matrix of compression at random that the described network node of described application produces compresses described transform data, and the packed data that obtains described network node comprises:
According to y
l=A
lx
l, l=1 ..., N obtains described packed data, wherein, { A
l, l=1,2 ..., N is the described sensing matrix that compresses at random that described network node utilizes k * n rank that the local media access control address produces as the seed of pseudorandom number generator, k=n wherein, k＞1, n＞1.
6, the processing method of network data according to claim 5 is characterized in that, described described packed data is mixed at free space with the packed data of other network nodes comprises:
According to
Described packed data is mixed at free space with the packed data of other network nodes, and wherein, Z is described mixing compressed certificate, X=[x
1, x
2..., x
N]
T, A=[A
1..., A
N]
T, e is the receiver noise of described fusion center.
7, the processing method of network data according to claim 6, it is characterized in that, described to described mixing compressed certificate by iterative operation calculated data correlation, and calculate described node data according to described data dependence and comprise in the projection of described figure small echo:
In first time during iteration, the remaining matrix of variables Q of initialization
0=Z, and the null matrix Z on k * N rank is set
0
When the p time iteration, according to
Calculated data q and the described correlation of compressing each row in the sensing matrix at random, and find out the described row that have maximum correlation in the sensing matrix with described data q that compress at random, wherein, r
pExpression row mark, q
Jcol P-1The vector of representing the remaining matrix of variables of a preceding iteration, A
l JcolExpression A
lThe j column vector, the remaining matrix of variables of a described preceding iteration is: Q
p=Z-Z
p, wherein,
Set omega is set
p=Ω
P-1Ur
p, from A
lThe middle row that extract are designated as Ω
pRow form k * p rank matrix
According to
Estimate the x of the p time iteration
l p
Iterate k time, obtain the projection x of described node data at described figure small echo
l K.
8, the processing method of network data according to claim 7 is characterized in that, described the figure inverse wavelet transform is carried out in described projection, and the described node data that obtains reconstruct comprises:
According to f
l=Ψ
J, l -1x
lObtain original described node data.
9, a kind of apparatus for network node is characterized in that, comprising:
Processing module, be used for tectonic network node graph of a correspondence small echo, and use described figure small echo the node data on the described network node is carried out conversion, obtain the transform data of described network node, wherein, described figure small echo is used for the comparison to the data of the network node in the adjacent area of described network node and described network node;
Compression module is used to use the sensing matrix of compression at random that described network node produces described transform data is compressed, and obtains the packed data of described network node;
Mixing module is used for described packed data is mixed at free space with the packed data of other network nodes, obtains mixing compressed certificate and issues fusion center.
10, a kind of fusion center equipment is characterized in that, comprising:
Receiver module is used to receive described mixing compressed certificate;
First reconstructed module, be used for calculating described mixing compressed certificate and the described data dependence that compresses sensing matrix at random, and have of the projection of the described node data of row extraction reconstruct of data dependence with described mixing compressed certificate at described figure small echo according to described the compression at random in the sensing matrix by iterative operation;
Second reconstructed module is used for the figure inverse wavelet transform is carried out in described projection, obtains the described node data of reconstruct.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101932012A (en) * | 2010-07-27 | 2010-12-29 | 杭州电子科技大学 | Method for compressing sensor network data based on optimal order estimation and distributed clustering |
| CN102594515A (en) * | 2012-03-30 | 2012-07-18 | 清华大学 | Node data transmitting method and device of sensor network and node data reconfiguring method and device of sensor network |
| CN102760182A (en) * | 2012-05-31 | 2012-10-31 | 中国科学院自动化研究所 | Population travel demand calculating method based on compressive sensing technology |
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| CN101374150B (en) * | 2007-10-26 | 2011-11-30 | 湖南大学 | Sensor network concourse node and method for storing and transmitting data of the node |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101932012A (en) * | 2010-07-27 | 2010-12-29 | 杭州电子科技大学 | Method for compressing sensor network data based on optimal order estimation and distributed clustering |
| CN101932012B (en) * | 2010-07-27 | 2013-09-18 | 杭州电子科技大学 | Method for compressing sensor network data based on optimal order estimation and distributed clustering |
| CN102594515A (en) * | 2012-03-30 | 2012-07-18 | 清华大学 | Node data transmitting method and device of sensor network and node data reconfiguring method and device of sensor network |
| CN102760182A (en) * | 2012-05-31 | 2012-10-31 | 中国科学院自动化研究所 | Population travel demand calculating method based on compressive sensing technology |
| CN102760182B (en) * | 2012-05-31 | 2014-09-17 | 中国科学院自动化研究所 | Population travel demand calculating method based on compressive sensing technology |
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