CN109347680A - A kind of network topology reconstructing method, device and terminal device - Google Patents
A kind of network topology reconstructing method, device and terminal device Download PDFInfo
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Abstract
The present invention is suitable for information technology field, provides a kind of network topology reconstructing method, device and terminal device, and method includes: to obtain the network number of edges and network node number of target network；The process that a plurality of information is propagated is simulated in target network, it obtains information record matrix and information reaches matrix, wherein, information record matrix records the data that each network node is infected by one or more information, and information reaches matrix and records the time that every information infects each network node；Any two network node infected by same information is selected, matrix is recorded according to information and information reaches matrix, calculates two network node infected time differences；Select the time difference for two network nodes of nominal parameter, as similar node pair；Calculate the chronotaxis of similar node pair；According to chronotaxis and network number of edges, the topological structure of target network is reconstructed.It can be improved the accuracy of the connection lacked in prediction network topology structure through the invention.
Description
Technical field
The present invention relates to information technology field more particularly to a kind of network topology reconstructing methods, device and terminal device.
Background technique
Investigate disease propagating source or complex network in information propagating source when, generally first find important node, then
It is limited again, such as the control for certain disease sources and information source.But the basic information in relation to communication network is often
It is incomplete, it is therefore desirable to rationally using known information come topological structure unknown or hiding in reconstructed network.But it is big
Under data age, the speed and range that information is propagated constantly are riseing, and the structure of communication network is huge, so that reappearing network topology
Structure is extremely difficult.
Currently, being directed to the reconstruction of network topology structure, link prediction method is generallyd use, is believed according to a part of network
Breath, predicts the connection lacked in various networks.However, existing link prediction method, when being based on static similarity measure or multistep
Between chronotaxis measurement carry out node relationships prediction, precision is unstable, cannot accurately predict in network topology structure
The connection lacked.
Summary of the invention
It is existing to solve it is a primary object of the present invention to propose a kind of network topology reconstructing method, device and terminal device
Some network topology reconstructing method precision are unstable, cannot accurately predict asking for the connection lacked in network topology structure
Topic.
To achieve the above object, first aspect of the embodiment of the present invention provides a kind of network topology reconstructing method, comprising:
Obtain the network number of edges and network node number of target network；
The process that a plurality of information is propagated is simulated in the target network, obtains information record matrix and information reaches square
Battle array, wherein the information record matrix records the data that each network node is infected by one or more information, institute
It states information arrival matrix and records the time that every information infects each network node；
Any two network node infected by same information is selected, matrix is recorded according to the information and information reaches square
Battle array, calculates described two network nodes infected time difference；
Select the time difference for two network nodes of nominal parameter, as similar node pair；
Calculate the chronotaxis of the similar node pair；
According to the chronotaxis and the network number of edges, the topological structure of the target network is reconstructed.
In conjunction with first aspect present invention, in the first embodiment of first aspect present invention, the nominal parameter is 1.
It is described in the target network in the second embodiment of first aspect present invention in conjunction with first aspect present invention
Middle analog information communication process, acquisition information record matrix and information reach before matrix, comprising:
The network node, which is arranged, becomes the probability of information source；
According to the item number for the information that the network node number and the probability, calculating simulation are propagated.
It is described to calculate the similar section in the third embodiment of first aspect present invention in conjunction with first aspect present invention
The chronotaxis formula of point pair are as follows:
Wherein, | tiα-tjα| it is two network node infected time differences, R is that information records matrix, and T is information record
Matrix, i indicate that node, j indicate information.
It is described according to the time phase in the 4th embodiment of first aspect present invention in conjunction with first aspect present invention
Like property and the network number of edges, the topological structure for reconstructing the target network includes:
Select in the chronotaxis the biggish N number of similar node of numerical value to as even mid-side node pair, wherein N is network
Number of edges；
Two network nodes for connecting each even mid-side node pair, reconstruct the topological structure of the network.
Second aspect of the embodiment of the present invention provides a kind of network topology reconstruct device, comprising:
The network information obtains module, for obtaining the network number of edges and network node number of target network；
Matrix logging modle, the process propagated for simulating a plurality of information in the target network obtain information record
Matrix and information reach matrix, wherein the information record matrix records each network node described in one or more
The data of information infection, the information reach matrix and record the time that every information infects each network node；
Time difference computing module, any two network node for selecting to be infected by same information, according to the information
It records matrix and information reaches matrix, calculate described two network nodes infected time difference；
Similar node is to selecting module, for selecting the time difference for two network nodes of nominal parameter, as phase
Like node pair；
Chronotaxis computing module, for calculating the chronotaxis of the similar node pair；
Network reconfiguration module reconstructs the topology of the target network according to the chronotaxis and the network number of edges
Structure.
In conjunction with second aspect of the present invention, in the first embodiment of second aspect of the present invention, the nominal parameter is 1.
It further include probability setup module in the second embodiment of second aspect of the present invention in conjunction with second aspect of the present invention
And spread calculating module；
The probability setup module becomes the probability of information source for the network node to be arranged；
The spread calculating module, the letter for being propagated according to the network node number and the probability, calculating simulation
The item number of breath.
The third aspect of the embodiment of the present invention provides a kind of terminal device, including memory, processor and is stored in
In above-mentioned memory and the computer program that can be run on above-mentioned processor, when above-mentioned processor executes above-mentioned computer program
The step of realizing method provided by first aspect as above.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, above-mentioned computer-readable storage
Media storage has computer program, and above-mentioned computer program realizes method provided by first aspect as above when being executed by processor
The step of.
The embodiment of the present invention proposes a kind of network topology reconstructing method, passes through analog information being propagated through in target network
Journey, while information record matrix and information arrival matrix are recorded, arrival time of each information in each network node is obtained, so
The difference for calculating the arrival time of same information on any two network node afterwards selects similar node pair according to the above-mentioned time difference,
And calculate its chronotaxis；In conjunction with all similar nodes pair chronotaxis and target network in network number of edges, can be with
The reconstruct for realizing target network topological structure, obtains complete target network topological structure, meanwhile, pass through control nominal parameter
Value, can control the time measure between similar node pair, i.e. selection lesser two network nodes of nominal parameter, as similar
Node pair, to improve the accuracy of the connection lacked in prediction network topology structure.
Detailed description of the invention
Fig. 1 is the implementation process schematic diagram for the network topology structure reconstructing method that the embodiment of the present invention one provides；
Fig. 2 is the implementation process schematic diagram of network topology structure reconstructing method provided by Embodiment 2 of the present invention；
Fig. 3 is the algorithm implementation process schematic diagram of network topology structure reconstructing method provided by Embodiment 2 of the present invention；
The effect diagram of conventional link prediction technique in the BA network that Fig. 4 provides for the embodiment of the present invention three；
The effect diagram of conventional link prediction technique in the SW network that Fig. 5 provides for the embodiment of the present invention three；
Fig. 6 is the reconstruct of the network topology structure reconstructing method that the embodiment of the present invention three provides and conventional link prediction technique
Contrast on effect schematic diagram；
Fig. 7 is the network topology structure reconstructing method and multistep time chronotaxis method that the embodiment of the present invention three provides
Quality reconstruction contrast schematic diagram；
Fig. 8 is network topology structure reconstructing method and time time under the greater probability value that the embodiment of the present invention three provides
The quality reconstruction contrast schematic diagram of similarity method；
Fig. 9 is the structural schematic diagram that the network topology structure that the embodiment of the present invention four provides reconstructs device.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the device that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or device.
Herein, using the suffix for indicating such as " module ", " component " or " unit " of element only for advantageous
In explanation of the invention, there is no specific meanings for itself.Therefore, " module " can be used mixedly with " component ".
In subsequent description, inventive embodiments serial number is for illustration only, does not represent the advantages or disadvantages of the embodiments.
Embodiment one
As shown in Figure 1, passing through control similar node pair the embodiment of the invention provides a kind of network topology reconstructing method
Time difference, to improve the accuracy of connection lacked in prediction network topology structure, network topology reconstructing method includes but not
It is limited to:
S101, the network number of edges and network node number for obtaining target network.
In above-mentioned steps S101, the topological structure of network is to be connected with each other to be formed by knot by node each in network
Structure mainly includes the side connected between network node and network node；And the network for concealing topological structure, it still can be with
A part of information is read out, such as network number of edges and network node number in the embodiment of the present invention.
S102, the process that a plurality of information is propagated is simulated in the target network, obtain information record matrix and information arrives
Up to matrix.
In above-mentioned steps S102, information record matrix records the number that each network node is infected by one or more information
According to information reaches matrix and records the time that every information infects each network node.
In one embodiment, simulating the process that a plurality of information is propagated can be realized by SIR algorithm.
In a particular application, simulate in a network propagation information have it is a plurality of, for the angle of information, every information warp
The network node crossed is different, and the time that same information reaches different network node is also different.
For the angle of node, on the same node, may only it be infected by an information, it is also possible to by a plurality of different
Information infection.
In the embodiment of the present invention, information record matrix is set out with the angle of node, records each node by which item or several
The data that information is infected；Information is reached matrix and is set out with the angle of information, is recorded every information and is reached and infects a certain network
The time of node.
Data that above-mentioned each network node is infected by one or more information, every information infect each network node
Time be recorded in information record matrix and information reach matrix in, as matrix element RijAnd Tij, when network node is not by certain
When one information infects, RijValue be 0, when network node is infected by a certain information, RijValue be 1.In practical applications, believe
The content that breath record matrix is recorded can indicate are as follows:
Assuming that network node A is infected by information a, information b, information c；Network node B is infected by information a, information b；Network
Node C is infected by information b, information c, and above- mentioned information record matrix can indicate at this time are as follows:
Similarly, the content that information reaches that matrix is recorded can indicate are as follows:
Wherein, above- mentioned information reach the time that matrix has recorded information a infection network node A and network node B；Information b
Infect the time of network node A, network node B, network node C；The time of information c infection network node B and network node C.
Any two network node that S103, selection are infected by same information records matrix and information according to the information
Matrix is reached, described two network nodes infected time difference is calculated.
In above-mentioned steps S103, the time difference that same information infects two network nodes is indicated with vector, the time difference
Vector includes all differences, such as the time difference of same information two nodes of arrival can be 1,2,3 ....
S104, select the time difference for two network nodes of nominal parameter, as similar node pair.
S105, the chronotaxis for calculating the similar node pair.
For above-mentioned steps S104 into step S105, the time difference that same information infects two network nodes can be in certain journey
Reflect the structural relation between two network nodes on degree, indicate the time difference with nominal parameter, at this point, passing through control nominal parameter
Value, the time measure between similar node pair can be controlled, i.e., selection lesser two network nodes of nominal parameter, as phase
Like node pair, to improve the accuracy of the connection lacked in prediction network topology structure.
In one embodiment, the nominal parameter is 1.
In a particular application, two nodes are infected in independent communication process in the step-length that the time difference is 1, they have very
There is even side in maximum probability, illustrate that the time difference is that the contribution margin of 1 pair of reconstructed network is the largest.
In one embodiment, the chronotaxis formula for calculating the similar node pair can be with are as follows:
Wherein, | tiα-tjα| it is two network node infected time differences, R is that information records matrix, and T is information arrival
Matrix, i indicate that network node, j indicate information.
S106, according to the chronotaxis and the network number of edges, reconstruct the topological structure of the target network.
In one embodiment, according to the chronotaxis and the network number of edges, opening up for the target network is reconstructed
Flutterring structure may include:
Select in the chronotaxis the biggish N number of similar node of numerical value to as even mid-side node pair, wherein N is network
Number of edges；
Two network nodes for connecting each even mid-side node pair, reconstruct the topological structure of the target network.
Network topology reconstructing method provided in an embodiment of the present invention passes through analog information being propagated through in target network
Journey, while information record matrix and information arrival matrix are recorded, arrival time of each information in each network node is obtained, so
The difference for calculating the arrival time of same information on any two network node afterwards selects similar node pair according to the above-mentioned time difference,
And calculate its chronotaxis；In conjunction with all similar nodes pair chronotaxis and target network in network number of edges, can be with
The reconstruct for realizing target network topological structure, obtains complete target network topological structure, meanwhile, pass through control nominal parameter
Value, can control the time measure between similar node pair, i.e. selection lesser two network nodes of nominal parameter, as similar
Node pair, to improve the accuracy of the connection lacked in prediction network topology structure.
Embodiment two
As shown in Fig. 2, the embodiment of the invention provides a kind of network topology reconstructing methods, comprising:
S201, the network number of edges and network node number for obtaining target network.
S202, the setting network node become the probability of information source；
The item number of S203, the information propagated according to the network node number and the probability, calculating simulation.
S204, the process that a plurality of information is propagated is simulated in the target network, obtain information record matrix and information arrives
Up to matrix.
S205, two network nodes being infected by same information of selection, calculate described two network nodes it is infected when
Between it is poor.
S206, select the time difference for two network nodes of nominal parameter, as similar node pair.
S207, the chronotaxis for calculating the similar node pair.
S208, according to the chronotaxis and the network number of edges, reconstruct the topological structure of the target network.
Network topology reconstructing method provided by specific embodiment and embodiment of above-mentioned steps S201, S204 to S208
In step S101 to S106 it is identical, repeated no more in the embodiment of the present invention.
Above-mentioned steps S202 is into step S203, and network node becomes the probability of information source for indicating: each node
There is probability to become information source then to start to propagate；Assuming that the probability that network node becomes information source is f, then a plurality of information is being simulated
There to be N × f kind difference information propagating during propagation, in entire target network, wherein N is network node number.
In a particular application, simulation communication process can be executed, it is secondary for executing number, and every time by SIR algorithm
It is independent communication process.
As shown in figure 3, the embodiment of the present invention also provide nominal parameter be 1 when, the algorithm flow of network topology reconstructing method,
Include:
1, the information of target network, including network node number and network number of edges are obtained.
2, before the communication process of analog information, become the probability and network node number meter of information source according to network node
Calculate number realization, formula are as follows: N × f has N × f information in communication process.
3, the communication process of SIR algorithm simulation information is executed, and records in communication process each node by some information sense
The matrix R that contaminated and it is infected when time matrix T, R be one and have N row, the matrix of N × f column, Rij=1 indicates i-node by j
Information infects, and 0 expression is not infected；T size is as R, but the value in matrix indicates arrival time when infecting.
4, according to R matrix and T matrix, the time difference vector of any network node pair is calculated.
If 5, the time difference is not equal to 1, give up the time difference；If the time difference is equal to 1, it is used as similar node pair,
And calculate the chronotaxis S of all similar nodes pairij, the node of E is to can consider between it before chronotaxis ranking
There is even side, to reconstruct target network topological structure.
Embodiment three
The embodiment of the present invention uses no mark for network topology reconstructing method provided in embodiment one and embodiment two
Network model BA and Small World Model SW two artificial polymer fabric networks are spent, to provided in above-described embodiment one and embodiment two
Network topology reconstructing method is tested, and illustratively illustrates the beneficial effect of the above method in practical applications.
Based on network topology reconstructing method provided in embodiment one and embodiment two, the process of information independent propagation
In, a certain network node has probability to infect its adjacent network node, it is assumed that this probability is β, and value and the communication process breath of β ceases
Correlation, for example, the value with β is reduced, then communication process is withered away faster.
As shown in Figure 4 comprising 8 subgraphs of (a) to (h), what each subgraph referred to is above-described embodiment one and reality
The network topology reconstructing method in example two is applied, compared with applying with conventional link prediction technique in the effect in BA network.
In embodiments of the present invention, conventional link prediction technique includes the reconstructing method using staticametric (such as CN),
And the reconstructing method measured using chronotaxis；In reconstructing method based on chronotaxis measurement, when using multistep
Between chronotaxis measurement (such as TCN)；And the network topology reconstructing method in above-described embodiment one and embodiment two is base
In the reconstructing method of step time chronotaxis measurement (such as TCN1).
In Fig. 4, subgraph (a) to each subgraph of subgraph (h) is all shown staticametric (such as CN), when the multistep time
Between corresponding to the measurement (such as TCN) of similitude and the network topology reconstructing method in above-described embodiment one and embodiment two
, the result curve of the measurement (such as TCN1) of a step time chronotaxis.
In embodiments of the present invention, figure (a) includes the result of COS measurement, TCOS measurement, TCOS1 measurement in BA network
Curve, figure (b) include that SSI measurement, TSSI are measured, the result curve of TSSI1 measurement, figure (b) are included in BA net in BA network
In network SSI measurement, TSSI measurement, TSSI1 measurement result curve, and so on, figure (c) in measurement be HPI, THPI,
THPI1；Scheming the measurement in (d) is CN, TCN, TCN1；Scheming the measurement in (e) is JAC, TJAC, TJAC1；Scheme the measurement in (f)
For HDI, THDI, THDI1；Scheming the measurement in (g) is PA, TPA, TPA1；Scheming the measurement in (h) is LHN, TLHN, LHN1；Its
In, COS (Cosine Index, COS distance index), SSI (Sorensen Index, the gloomy index in Soren), HPI (Hub
Promoted Index, hub promoted index), JAC (Jaccard Index, Jie Kade index), CN (common
Neighbors, common neighbours), HDI (Hub Depressed Index, hinge inhibition index), PA (Preferential
Attachment, preference connection), LHN (Leicht-Holme-Newman Index, light-duty bar Newman index) be measurement
Method, T indicate that multistep chronotaxis algorithm, TX1 indicate a step time chronotaxis algorithm, and the X-axis generation of each subgraph
Table network node in communication process infects the probability β of its neighbour, and Y-axis is chosen after being reconstructed by measure
The accuracy value of Precision index.
For example, staticametric can also be COS, corresponding multistep time chronotaxis measurement is TCOS, a step at this time
Time chronotaxis measurement is TCOS1.
In embodiments of the present invention, for the metrology structure of each consideration, if probability β is sufficiently large, time step time
The corresponding network topology structure reconstruction result of similarity measurement (such as TCN1), hence it is evident that than multistep chronotaxis measurement (such as
TCN) corresponding network topology structure reconstruction result is more preferable.And as probability β is reduced, communication process is often quickly withered away,
Correctly rebuilding potential proliferation network becomes more and more difficult.When β value is smaller, a step time chronotaxis measures (example
Such as TCN1) it is similar with measurement (such as TCN) the index performance of multistep time chronotaxis, therefore, Time Perception measurement is obvious
Better than staticametric.
As shown in the subgraph (a) in Fig. 5 to subgraph (h), each subgraph is all referring to above-described embodiment one and embodiment two
In network topology reconstructing method apply with conventional link prediction technique in the effect in SW network compared with.Each of which subgraph generation
Table one kind measure, specific measure is identical with Fig. 4, including COS, SSI, HPI, JAC, CN, HDI, PA, LHN.And
The X-axis of each subgraph represents the probability β that a network node in communication process infects its neighbour, and Y-axis is by measure weight
The accuracy value of Precision index is chosen after structure.Similar with the result in BA network is applied, a step time chronotaxis is also
Being can be better than multistep time chronotaxis, but the gap is less than the gap in BA network.
It is on BA network and SW network the result shows that, the measurement of a step time chronotaxis is than multistep time time phase
Synthesis network is preferably rebuild like property measurement.For most data set, a step time chronotaxis is measured relative to quiet
Attitude amount and multistep time chronotaxis measurement, it is significant to improve reconstruction precision.Multistep time chronotaxis measurement can be with
It is network is that there are low cluster coefficients better than the unique conditional with step time chronotaxis measurement, this is clearly
: for the network of height cluster, long propagation path is less likely to reach two disconnected nodes.
As shown in Figure 6 and Figure 7, in embodiments of the present invention, the β of β=4 is enabledc, so that analysis 20 is of different nature true
It is network, wherein βcIt is popularity threshold.
Fig. 6 is the quality reconstruction contrast schematic diagram of network topology structure reconstructing method and conventional link prediction technique, such as Fig. 6
In subgraph (a) to shown in subgraph (h), each subgraph represents a kind of measure, specific measure and phase in Fig. 4
Together, including COS, SSI, HPI, JAC, CN, HDI, PA, LHN, and X-axis represents the coefficient that gathers of network, and Y-axis is the above-mentioned reality taken
The Precision evaluation index that the network topology reconstructing method in example one and embodiment two is showed is applied, with conventional method institute table
The relative value of the difference of existing Precision；Network topology reconstructing method i.e. based on step time chronotaxis measurement, with base
Comparison between the conventional method that staticametric, multistep time chronotaxis are measured；Point table in figure above horizontal line
Show, the network topology reconstructing method at this time based on step time chronotaxis measurement is better than conventional link prediction technique.
Fig. 7 is the quality reconstruction comparison signal of network topology structure reconstructing method and multistep time chronotaxis method
Figure, similar with Fig. 6 as shown in the subgraph (a) in Fig. 7 to subgraph (h), each subgraph represents a kind of measure, specifically
Measure is identical with Fig. 4, including COS, SSI, HPI, JAC, CN, HDI, PA, LHN, and X-axis represents gathering for network and is
Number, Y-axis are that the Precision evaluation that the network topology reconstructing method in the above-described embodiment one and embodiment two taken is showed refers to
Mark, and the relative value of the difference of Precision that conventional method is showed.In most network, it is based on a step time time phase
Like the network topology reconstructing method that property is measured, it is also an advantage over multistep time chronotaxis method.
In embodiments of the present invention, it completes to test using biggish β value, for example, enabling the β of β=8c。
As shown in figure 8, being the greater probability value (β of β=8c) under network topology structure reconstructing method it is similar to time time
Property method quality reconstruction contrast schematic diagram, for the subgraph (a) of Fig. 8 into subgraph (h), each subgraph represents a kind of measurement side
Method, specific measure is identical with Fig. 4, including COS, SSI, HPI, JAC, CN, HDI, PA, LHN, and X-axis represents network
Gather coefficient, Y-axis is that the network topology reconstructing method in the above-described embodiment one and embodiment two taken is showed
Precision evaluation index, and the relative value of the difference of Precision that conventional method is showed.Experimental result indicates, when a step
Between chronotaxis can preferably rebuild network in most of data sets and improve the precision of Precision index, and its tie
Fruit ratio β=4 βcWhen the effect that is showed it is more preferable.
Implement four
As shown in figure 9, the embodiment of the invention provides a kind of network topologies to reconstruct device 90, including but not limited to network is believed
Breath obtains module 91, matrix logging modle 92, time difference computing module 93, similar node to selecting module 94, chronotaxis
Computing module 95 and network reconfiguration module 96, in which:
The network information obtains module 91, for obtaining the network number of edges and network node number of target network.
Matrix logging modle 92, the process propagated for simulating a plurality of information in target network obtain information and record square
Battle array and information reach matrix；
Wherein, information record matrix records the data that each network node is infected by one or more information, and information reaches
Matrix records the time that every information infects each network node.
Time difference computing module 93, any two network node for selecting to be infected by same information, remembers according to information
It records matrix and information reaches matrix, calculate two network node infected time differences.
Similar node is to selecting module 94, for selecting the time difference for two network nodes of nominal parameter, as similar
Node pair.
In one embodiment, nominal parameter 1.
In a particular application, two nodes are infected in independent communication process in the step-length that the time difference is 1, they have very
There is even side in maximum probability, illustrate that the time difference is that the contribution margin of 1 pair of reconstructed network is the largest.
Chronotaxis computing module 95, for calculating the chronotaxis of similar node pair.
In one embodiment, in chronotaxis computing module 95, the chronotaxis formula of similar node pair is calculated
It can be with are as follows:
Wherein, | tiα-tjα| it is two network node infected time differences, R is that information records matrix, and T is information record
Matrix, i indicate that node, j indicate information.
Network reconfiguration module 96 reconstructs the topological structure of target network according to chronotaxis and network number of edges.
In one embodiment, network reconfiguration module 96 may include:
Even mid-side node selecting unit, for selecting in chronotaxis the biggish N number of similar node of numerical value to as even side
Node pair, wherein N is network number of edges.
Network node connection unit, for connecting two network nodes of each even mid-side node pair, the topology of reconstructed network
Structure.
In one embodiment, network topology reconstruct device can also include probability setup module and spread calculating module；
Wherein:
Probability setup module becomes the probability of information source for network node to be arranged；
Spread calculating module, the item number of the information for being propagated according to network node number and probability, calculating simulation.
The embodiment of the present invention also provide a kind of terminal device include memory, processor and storage on a memory and can be
The computer program run on processor when the processor executes the computer program, is realized as described in embodiment one
Network topology reconstructing method in each step.
The embodiment of the present invention also provides a kind of storage medium, and the storage medium is computer readable storage medium, thereon
It is stored with computer program, when the computer program is executed by processor, realizes the network topology as described in embodiment one
Each step in reconstructing method.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although previous embodiment
Invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each implementation
Technical solution documented by example is modified or equivalent replacement of some of the technical features；And these modification or
Replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all include
Within protection scope of the present invention.
Claims (10)
1. a kind of network topology reconstructing method characterized by comprising
Obtain the network number of edges and network node number of target network；
The process that a plurality of information is propagated is simulated in the target network, obtains information record matrix and information reaches matrix,
In, the information record matrix records the data that each network node is infected by one or more information, the letter
Breath reaches matrix and records the time that every information infects each network node；
Matrix is recorded according to the information and information reaches matrix, selects any two network node infected by same information,
Calculate described two network nodes infected time difference；
Select the time difference for two network nodes of nominal parameter, as similar node pair；
Calculate the chronotaxis of the similar node pair；
According to the chronotaxis and the network number of edges, the topological structure of the target network is reconstructed.
2. network topology reconstructing method as described in claim 1, which is characterized in that the nominal parameter is 1.
3. network topology reconstructing method as described in claim 1, which is characterized in that described to simulate letter in the target network
Communication process is ceased, acquisition information record matrix and information reach before matrix, comprising:
The network node, which is arranged, becomes the probability of information source；
According to the item number for the information that the network node number and the probability, calculating simulation are propagated.
4. network topology reconstructing method as described in claim 1, which is characterized in that it is described calculate the similar node pair when
Between similarity formula are as follows:
Wherein, | tiα-tjα| it is two network node infected time differences, R is that information records matrix, and T is that information records matrix,
I indicates that node, j indicate information.
5. network topology reconstructing method as described in claim 1, which is characterized in that described according to the chronotaxis and institute
Network number of edges is stated, the topological structure for reconstructing the target network includes:
Select in the chronotaxis the biggish N number of similar node of numerical value to as even mid-side node pair, wherein N is network edge
Number；
Two network nodes for connecting each even mid-side node pair, reconstruct the topological structure of the network.
6. a kind of network topology reconstructs device characterized by comprising
The network information obtains module, for obtaining the network number of edges and network node number of target network；
Matrix logging modle, the process propagated for simulating a plurality of information in the target network obtain information and record matrix
Matrix is reached with information, wherein the information record matrix records each network node by one or more information
The data of infection, the information reach matrix and record the time that every information infects each network node；
Time difference computing module, any two network node for selecting to be infected by same information are recorded according to the information
Matrix and information reach matrix, calculate described two network nodes infected time difference；
Similar node is to selecting module, for selecting the time difference for two network nodes of nominal parameter, as similar section
Point pair；
Chronotaxis computing module, for calculating the chronotaxis of the similar node pair；
Network reconfiguration module reconstructs the topological structure of the target network according to the chronotaxis and the network number of edges.
7. network topology as claimed in claim 6 reconstructs device, which is characterized in that the nominal parameter is 1.
8. network topology as claimed in claim 6 reconstructs device, which is characterized in that further include probability setup module and propagation meter
Calculate module；
The probability setup module becomes the probability of information source for the network node to be arranged；
The spread calculating module, the information for being used to be propagated according to the network node number and the probability, calculating simulation
Item number.
9. a kind of terminal device, which is characterized in that on a memory and can be on a processor including memory, processor and storage
The computer program of operation, which is characterized in that when the processor executes the computer program, realize such as claim 1 to 5
Each step in described in any item network topology reconstructing methods.
10. a kind of storage medium, the storage medium is computer readable storage medium, is stored thereon with computer program,
It is characterized in that, when the computer program is executed by processor, realizes such as network topology described in any one of claim 1 to 5
Each step in reconstructing method.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112104515A (en) * | 2020-11-19 | 2020-12-18 | 中国人民解放军国防科技大学 | Network reconstruction method and device, computer equipment and storage medium |
| CN115086178A (en) * | 2022-05-27 | 2022-09-20 | 量子科技长三角产业创新中心 | Dynamic reconfiguration method of computing power network and servo device |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080175171A1 (en) * | 2007-01-19 | 2008-07-24 | Lockheed Martin Corporation | Parallel wireless topologies |
| EP2568664A1 (en) * | 2011-09-12 | 2013-03-13 | Honeywell International Inc. | Apparatus and method for detecting critical nodes and critical links in a multi-hop network |
| US20140328212A1 (en) * | 2005-10-26 | 2014-11-06 | Memory Integrity, Llc | Method for Efficiently Retrieving Topology-Specific Data for Point-to-Point Networks |
-
2018
- 2018-11-08 CN CN201811322446.0A patent/CN109347680B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140328212A1 (en) * | 2005-10-26 | 2014-11-06 | Memory Integrity, Llc | Method for Efficiently Retrieving Topology-Specific Data for Point-to-Point Networks |
| US20080175171A1 (en) * | 2007-01-19 | 2008-07-24 | Lockheed Martin Corporation | Parallel wireless topologies |
| EP2568664A1 (en) * | 2011-09-12 | 2013-03-13 | Honeywell International Inc. | Apparatus and method for detecting critical nodes and critical links in a multi-hop network |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112104515A (en) * | 2020-11-19 | 2020-12-18 | 中国人民解放军国防科技大学 | Network reconstruction method and device, computer equipment and storage medium |
| CN115086178A (en) * | 2022-05-27 | 2022-09-20 | 量子科技长三角产业创新中心 | Dynamic reconfiguration method of computing power network and servo device |
| CN115086178B (en) * | 2022-05-27 | 2024-03-15 | 量子科技长三角产业创新中心 | Dynamic reconstruction method of power calculation network and servo device |
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