CN107453919A - Complex network node importance evaluation method and system - Google Patents

Complex network node importance evaluation method and system Download PDF

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CN107453919A
CN107453919A CN201710773510.6A CN201710773510A CN107453919A CN 107453919 A CN107453919 A CN 107453919A CN 201710773510 A CN201710773510 A CN 201710773510A CN 107453919 A CN107453919 A CN 107453919A
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node
load
failure
complex network
mrow
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CN107453919B (en
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黄健
孔江涛
李尔玉
龚建兴
郝建国
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National University of Defense Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876—Network utilisation, e.g. volume of load or congestion level
    • H04L43/0882—Utilisation of link capacity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
    • H04L43/0817—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/50—Testing arrangements

Abstract

The invention discloses a method and a system for evaluating the importance of complex network nodes, wherein the method comprises the following steps: s1, initializing the actual load of each node in the complex network, and calculating the initial total load of the complex network; s2, sequentially carrying out failure investigation on each node of the complex network, and carrying out cascade failure simulation; in the cascade failure simulation process, after a failure node is deleted, the actual load of the neighbor node is adjusted and updated, the load capacity of the complex network node is updated, a new round of failure judgment is carried out on the complex network according to the updated load and the updated load capacity until the complex network is stable, and the residual total load of the complex network is calculated; and S3, evaluating the importance of the node according to the initial total load and the residual total load. The method has the advantages that the dynamic deepening characteristic of the cascade failure of the complex network is fully considered, the intrinsic characteristics of important nodes can be deeply prompted, and the importance of the nodes in the complex network can be more truly and accurately evaluated.

Description

Complex network node importance appraisal procedure and system
Technical field
The present invention relates to complex network technical field, more particularly to a kind of complex network node importance appraisal procedure and it is System.
Background technology
The research of complex network has become a focus of scientific research now, and penetrates into every field, such as biology , economics, sociology etc..Complex network model develops in research, and the importance ranking of node is core research contents, so-called Important node refer to can to influence to a greater extent for network other nodes network structure and function some are special Different node, the distribution of network structure degree of relating generally to, average distance, degree of communication, cluster coefficients, degree correlation etc., network function relates to And the survivability of network, propagation, synchronization, control etc..Document " Ren Xiaolong, Lv Linyuan.Network-critical node sequencing method survey. Science Bulletin, 2014,59,：Comprehensive summaries of the 1175-1197 " to existing network-critical node sequencing method progress now, And point out that it is a study hotspot that assessment is carried out to node importance based on network specific function and structure.The cascading failure of network It is the dynamic characteristic that a kind of network has, the anti-Kill capability of a kind of function that network has, i.e. network can be regarded as, remove certain Individual node may cause the change of network structure, traffic flow, information flow or data flow in network can further be influenceed, so as to lead The cascading failure phenomenon of network is caused, it is exactly of the invention for assessing the importance of node by weighing the degree of cascading failure Basic point of departure.Document " Zhu Tao, Chang Guocen, Zhang Shuiping, Guo Rongxiao.Commander based on complex network controls cascade failure model Research.Journal of System Simulation.Vol.22, No.8,2010 " propose that overload function represents the Congestion Level SPCC of node, so that load Distribution is more reasonable.Document " Shen Di, Li Jianhua, bear metal and stone, Zhang Qiang, Zhu Rui.A kind of double-deck complex network cascade based on betweenness Failure model.Complication system and complexity science.Vol.11, No.3,2014 " establish double-layer network, and define Double-level Reticulated Influence relation between network so that cascading failure model more conforms to physics reality.In general, at present on network-critical section The research of point sort method and the achievement in research of complex network cascading failure are relatively abundant, but the achievement in research being incorporated into compared with It is few.
The content of the invention
The technical problem to be solved in the present invention is that：For technical problem existing for prior art, the present invention provides one Kind has taken into full account the dynamic in-depth characteristic of complex network cascading failure, can prompt the intrinsic characteristic of important node more deeply, can Truer, the complex network node importance appraisal procedure more accurately assessed the importance of Node Contraction in Complex Networks and it is System.
In order to solve the above technical problems, technical scheme proposed by the present invention is：A kind of complex network node importance is assessed Method, including：
S1. the real load of each node in complex network is initialized, and calculates the initial full payload of complex network；
S2. failure investigation is carried out successively to each node of complex network, carries out cascading failure emulation；The cascading failure In simulation process, after failure node is deleted, adjustment updates the real load of its neighbor node, and updates complex network node Load bearing capacity, and according to the renewal load and failure judgement of the load bearing capacity to a complex network progress new round is updated, until Complex network is stable, and calculates the remaining full payload of complex network；
S3. the importance of node is assessed according to the initial full payload and remaining full payload.
As a further improvement on the present invention, the real load of formula calculate node shown in formula (1) is passed through：
Li=αi×Ki+(1-αi)×BCi (1)
In formula (1), LiFor node NiReal load, αiRepresent node NiLoad stoichiometric factor, KiFor node NiDegree, BCiRepresent node NiNormalization betweenness；
Further, the normalization betweenness is calculated by formula shown in formula (2)：
In formula (2), BCiRepresent node NiNormalization betweenness, n is total node number mesh, gstRepresent node NsTo node Nt's The number of all shortest paths,Represent node NsTo node NtGstPass through node N in bar shortest pathiPath number, i, S, t are node serial number.
As a further improvement on the present invention, the specific method of the real load of its neighbor node of adjustment renewal is：By institute The real load for stating failure node proportionally distributes to neighbor node；The ratio for some neighbor node current load with The ratio of the current load sum of whole neighbor nodes.
As a further improvement on the present invention, by formula shown in formula (3) by the real load of the failure node according to Pro rate is to neighbor node：
In formula (3), ΓiFor failure node NiNeighbor node set, L'i→jFor failure node NiNeighbours are distributed to after failure Node Nj∈ΓiReal load, LsFor neighbor node Ns∈ΓiReal load, LjFor neighbor node Nj∈ΓiActual load Lotus, η are to be lost in the load ratio of dissipation, L after node failureiFor failure node NiReal load.
As a further improvement on the present invention, the specific method of the load bearing capacity of adjustment renewal renewal complex network node For：According to the tolerance coefficient, degree, the load bearing capacity for normalizing betweenness more new node of node.
As a further improvement on the present invention, the load for renewal complex network node being adjusted by formula shown in formula (4) is held Amount：
CLj=(1+ βj)×[αj×Kj+(1-αj)×BCj] (4)
In formula (4), CLjFor complex network node NjLoad bearing capacity, βjFor node NjLoad tolerance coefficient, αjFor node NjLoad stoichiometric factor, KjFor current Node Contraction in Complex Networks NjDegree, BCjRepresent current Node Contraction in Complex Networks NjNormalizing Change betweenness.
As a further improvement on the present invention, in the failure of a step S2 new round judges, when the real load of node More than node load bearing capacity when, predicate node failure.
A kind of complex network node importance assessment system, including：
Initialization module：For initializing the real load of each node in complex network, and calculate the first of complex network Beginning full payload；
Failure simulation module：For carrying out failure investigation successively to each node of complex network, carry out cascading failure and imitate Very；In the cascading failure simulation process, after failure node is deleted, adjustment updates the real load of its neighbor node, and more The load bearing capacity of new complex network node, and a new round is carried out to complex network according to the renewal load and renewal load bearing capacity Failure judge, until complex network is stable, and calculate the remaining full payload of complex network；
Evaluation module：For assessing the importance of node according to the initial full payload and remaining full payload.
As a further improvement on the present invention, the failure simulation module is by the way that the real load of the failure node is pressed According to pro rate the real load of its neighbor node of renewal is adjusted to neighbor node；The ratio is worked as some neighbor node The ratio of preceding load and the current load sum of whole neighbor nodes.
As a further improvement on the present invention, the failure simulation module is situated between according to the tolerance coefficient of node, degree, normalization The load bearing capacity of number more new node.
Compared with prior art, the advantage of the invention is that：
1st, in the present invention, after simulating the failure of actual complex nodes by the cascading failure of node, because failure saves The load of point can not be fully allocated to other nodes and necessarily cause part real load to be lost, and can more accurately reflect Real node failure situation, the present invention assess more true, science to the importance of complex network node.
2nd, for the present invention in node failure, redistributing for real load is that the panel load capacity based on dynamic change enters It is capable, compare and in existing technology, the load bearing capacity that the redistributing of load is all based on initial complex network node is entered Capable, the process that the load bearing capacity of node caused by more accurately reflecting complex network structures change certainty changes, The result of assessment compares the appraisal procedure with prior art, more accurately, reliably.
3rd, the present invention calculates reservation load ratio by the ratio of initial full payload and remaining full payload, and to retain load Than evaluating the importance of complex network node, assessment result is more directly perceived.
Brief description of the drawings
Fig. 1 is specific embodiment of the invention schematic flow sheet.
Fig. 2 is specific embodiment of the invention uncalibrated visual servo weighted network schematic diagram.
Fig. 3 is the schematic diagram that the specific embodiment of the invention presses importance ranking without the cascading failure time.
Fig. 4 is that the specific embodiment of the invention has the schematic diagram that the cascading failure time presses importance ranking.
Fig. 5 is angle value distribution schematic diagram corresponding to each node of the specific embodiment of the invention.
Fig. 6 is betweenness distribution schematic diagram corresponding to each node of the specific embodiment of the invention.
Embodiment
Below in conjunction with Figure of description and specific preferred embodiment, the invention will be further described, but not therefore and Limit the scope of the invention.
As shown in figure 1, the complex network node importance appraisal procedure of the present embodiment, step are：S1. complex web is initialized The real load of each node in network, and calculate the initial full payload of complex network；S2. to each node of complex network successively Failure investigation is carried out, carries out cascading failure emulation；In the cascading failure simulation process, after failure node is deleted, adjustment is more The real load of its new neighbor node, and the load bearing capacity of complex network node is updated, and according to the renewal load and renewal The failure that load bearing capacity carries out a new round to complex network judges, until complex network stabilization, and calculates the residue of complex network Full payload；S3. the importance of node is assessed according to the initial full payload and remaining full payload.
In the present embodiment, illustrated by taking a uncalibrated visual servo air net as an example, start node numerical digit 5, increase node newly Even 5, side, finish node number are 50 for increase again afterwards, and the weight on each side obeys being uniformly distributed for section (0,1).Constructed Uncalibrated visual servo weighted network is as shown in Figure 2.Then the connection matrix of the complex network be 50 × 50 symmetrical matrix A, the i-th of matrix Row, jth column element are aijRepresent node NiWith node NjConnection status, aij=0 represents node NiWith node NjDo not connect, If aij≠ 0, then it represents that node NiWith node NjIt is connected, and distance is aij, and arrange aii=0.
In the present embodiment, for constructed complex network, the actual load of formula calculate node shown in formula (1) is passed through Lotus：
Li=αi×Ki+(1-αi)×BCi (1)
In formula (1), LiFor node NiReal load, αiRepresent node NiLoad stoichiometric factor, KiFor node NiDegree, BCiRepresent node NiNormalization betweenness.In the present embodiment, load stoichiometric factor α=0.006 is taken.
Wherein normalization betweenness is calculated by formula shown in formula (2)：
In formula (2), BCiRepresent node NiNormalization betweenness, n is total node number mesh, gstRepresent node NsTo node Nt's The number of all shortest paths,Represent node NsTo node NtGstPass through node N in bar shortest pathiPath number, i, S, t are node serial number.The betweenness distribution of each node is as shown in Figure 6.
Wherein, node NiDegree KiCalculated by formula shown in formula (5)：
If (aij>0, then f (aij)=1, otherwise f (aij)=0) (5)
In formula (5), KiFor node NiDegree, aijFor node NiWith node NjConnection status.The angle value distribution of each node is such as Shown in Fig. 5.
In the present embodiment, by calculating the real load sum of whole nodes, produce to obtain the initial total of complex network Load.As shown in formula (6),
In formula (6), LiFor node NiReal load, sum_L be complex network initial full payload.
In the present embodiment, after complex network is initialized, failure is carried out to each node in complex network successively and examined Examine, carry out cascading failure emulation.In the present embodiment, failure node is stored by way of queue of failing, with some node Ni Failure investigate exemplified by illustrate.
First, it is assumed that node NiFailure, that is, set NiFor failure node.Under original state, there was only failure node in queue of failing NiOne node.Failure node N is taken out from failure queuei, carry out cascading failure emulation.By node NiReal load to its Neighbor node is allocated, node NiNeighbor node i.e. and node NiThe node being joined directly together, is designated as Γi.Its neighbour of adjustment renewal The specific method for occupying the real load of node is：The real load of the failure node is proportionally distributed into neighbor node； The ratio is the current load and the ratio of the current load sum of whole neighbor nodes of some neighbor node.The present embodiment In, the real load of the failure node is proportionally distributed to by neighbor node by formula shown in formula (3)：
In formula (3), ΓiFor failure node NiNeighbor node set, L'i→jFor failure node NiNeighbours are distributed to after failure Node Nj∈ΓiReal load, LsFor neighbor node Ns∈ΓiReal load, LjFor neighbor node Nj∈ΓiActual load Lotus, η are to be lost in the load ratio of dissipation, L after node failureiFor failure node NiReal load.
By the above method, the real load such as formula (7) after neighbor node renewal is shown：
Lj=Lj+L'i→j (7)
In formula (7), LjFor neighbor node NjReal load, L'i→jFor failure node NiNeighbor node is distributed to after failure NjReal load.
By failure node NiReal load distribute to neighbor node after, by failure node NiDeleted from complex network, And set failure node NiReal load Li=0.
After node failure, the node can be deleted from complex network figure, and the deletion of node causes network structure to become Change.In traditional method, panel load capacity and changeless place are determined using the real load using original complex network Reason mode.And in the present embodiment, it is necessary to update each node in Exist Network Structure after complex network structures change Load bearing capacity, the specific method of load bearing capacity of adjustment renewal renewal complex network node is：According to the tolerance coefficient of node, The load bearing capacity of degree, normalization betweenness more new node.Specifically as shown in formula (4)：
CLj=(1+ βj)×[αj×Kj+(1-αj)×BCj] (4)
In formula (4), CLjFor complex network node NjLoad bearing capacity, βjFor node NjLoad tolerance coefficient, αjFor node NjLoad stoichiometric factor, KjFor current Node Contraction in Complex Networks NjDegree, BCjRepresent current Node Contraction in Complex Networks NjNormalizing Change betweenness.In the present embodiment, load tolerance factor beta=0.2 is taken.
In the present embodiment, by by failure node NiAnd the real load of its neighbor node is adjusted, and it is multiple After the load bearing capacity of miscellaneous network node is adjusted, new round failure judgement is carried out to the node of complex network.When the reality of node When border load is more than the load bearing capacity of node, predicate node failure.And the node for being determined as failure is added to failure queue.
In the present embodiment, it is located at real load and after load bearing capacity is adjusted, failure node NiNeighbor node Nj's Real load is more than its load bearing capacity, then by neighbor node NjIt is judged to failing.The neighbor node N of failure will be determined asjAdd To failure queue.Failure node is taken out from failure queue successively again, such as neighbor node Nj, repeat above-mentioned adjustment process.Will Failure node NjReal load distribute to failure node NjNeighbor node, and update the load bearing capacity of Node Contraction in Complex Networks. Said process is repeated until complex network is stable, that is, queue of failing completes the cascading failure emulation to complex network for sky.This When, calculate the full payload of complex network, i.e., remaining full payload.As shown in formula (8)：
In formula (8), LkFor node NkReal load, sum_L'iFor to node NiObtained after progress cascading failure emulation The remaining full payload of complex network.
Remaining full payload corresponding to one can be obtained after carrying out cascading failure emulation to each node.In the present embodiment In, according to the initial full payload and the importance of remaining full payload assessment node.Specifically, pass through initial full payload and residue Full payload, which calculates, retains load ratio, as shown in formula (9)：
In formula (9), RiFor node NiThe reservation load ratio of failure, sum_L'iFor to node NiAfter carrying out cascading failure emulation The remaining full payload of obtained complex network, sum_L are the initial full payload of complex network.
In the present embodiment, according to the parameter of complex network, when cascading failure does not occur, node NiThe reservation of failure carries Lotus compares RiIt is represented by as shown in formula (10)：
In formula (9), RiFor node NiThe reservation load ratio of failure, η are to be lost in the load ratio of dissipation, L after node failureiFor Node NiReal load, sum_L be complex network initial full payload.
Node NiReservation load ratio it is smaller, represent node NiThe failure load that causes whole complex network to be lost get over It is more, so it is more important to retain the smaller node of load ratio.It is ranked up by the way that load ratio will be retained, you can clear, intuitively Reflect the importance of each node in complex network.
In the present embodiment, load stoichiometric factor α=0.006 is taken, load tolerance factor beta=0.2 is taken, after taking node failure When being lost in the load ratio η=0.3 to dissipate, cascading failure phenomenon does not occur, passes through the importance of each node determined by this method Sequence is as shown in Figure 3.When the parameter of modification complex network, take load stoichiometric factor α=0.006, take load tolerance factor beta= 0.1, take when the load ratio η of dissipation=0.15 is lost in after node failure, cascading failure phenomenon is produced, by determined by this method The importance ranking of each node is as shown in Figure 4.It can be found that node N2With node N8Failure can cause cascading failure phenomenon, therefore Come first and second.It can be found that if cascading failure occurs, sort method of the present invention and traditional dependence degree and Jie The sequence of counting method differs because the inventive method consider node degree and betweenness while, also further combined with The cascading failure Dynamic Evolution of complex network, the intrinsic characteristic of announcement important node that can be more deep.
The complex network node importance assessment system of the present embodiment, including：Initialization module：For initializing complex web The real load of each node in network, and calculate the initial full payload of complex network；Failure simulation module：For to complex network Each node carry out failure investigation successively, carry out cascading failure emulation；In the cascading failure simulation process, work as failure node After deletion, adjustment updates the real load of its neighbor node, and updates the load bearing capacity of complex network node, and according to it is described more Newly load and renewal load bearing capacity carry out the failure judgement of a new round to complex network, until complex network stabilization, and calculate multiple The remaining full payload of miscellaneous network；Evaluation module：For assessing the important of node according to the initial full payload and remaining full payload Property.
In the present embodiment, initialize for example above-mentioned formula (1) of calculation formula of the real load of each node in complex network, (2), shown in (5), calculate shown in the method or above-mentioned formula (6) of the initial full payload of complex network.Failure simulation module pass through by The real load of the failure node proportionally distributes to neighbor node to adjust the real load of its neighbor node of renewal；Institute State the current load and the ratio of the current load sum of whole neighbor nodes that ratio is some neighbor node.Its specific calculating side Shown in for example above-mentioned formula (3) of method, (7).Failure simulation module is according to the tolerance coefficient of node, degree, normalization betweenness more new node Load bearing capacity.Shown in for example above-mentioned formula (4) of its circular.Failure simulation module calculates the method for remaining full payload such as Shown in above-mentioned formula (8).Evaluation module assesses the importance of node especially by reservation load ratio is calculated, and retains load ratio and leads to Cross such as above-mentioned formula (9) to calculate, node NiReservation load ratio it is smaller, represent node NiFailure cause whole complex web The load that network is lost is more, and it is more important to retain the smaller node of load ratio.
Above-mentioned simply presently preferred embodiments of the present invention, not makees any formal limitation to the present invention.It is although of the invention It is disclosed above with preferred embodiment, but it is not limited to the present invention.Therefore, it is every without departing from technical solution of the present invention Content, according to the technology of the present invention essence to any simple modifications, equivalents, and modifications made for any of the above embodiments, it all should fall In the range of technical solution of the present invention protection.

Claims (10)

  1. A kind of 1. complex network node importance appraisal procedure, it is characterised in that：
    S1. the real load of each node in complex network is initialized, and calculates the initial full payload of complex network；
    S2. failure investigation is carried out successively to each node of complex network, carries out cascading failure emulation；The cascading failure emulation During, after failure node is deleted, adjustment updates the real load of its neighbor node, and updates the load of complex network node Capacity, and according to the renewal load and failure judgement of the load bearing capacity to a complex network progress new round is updated, until complexity Network stabilization, and calculate the remaining full payload of complex network；
    S3. the importance of node is assessed according to the initial full payload and remaining full payload.
  2. 2. complex network node importance appraisal procedure according to claim 1, it is characterised in that：By formula (1) Suo Shi The real load of formula calculate node：
    Li=αi×Ki+(1-αi)×BCi (1)
    In formula (1), LiFor node NiReal load, αiRepresent node NiLoad stoichiometric factor, KiFor node NiDegree, BCiTable Show node NiNormalization betweenness；
    Further, the normalization betweenness is calculated by formula shown in formula (2)：
    <mrow> <msub> <mi>BC</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mn>2</mn> <mrow> <mo>(</mo> <mi>n</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> <mo>(</mo> <mi>n</mi> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> </mfrac> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>&amp;NotEqual;</mo> <mi>s</mi> <mo>,</mo> <mi>i</mi> <mo>&amp;NotEqual;</mo> <mi>t</mi> <mo>,</mo> <mi>s</mi> <mo>&amp;NotEqual;</mo> <mi>t</mi> </mrow> </munder> <mfrac> <msubsup> <mi>g</mi> <mrow> <mi>s</mi> <mi>t</mi> </mrow> <mi>i</mi> </msubsup> <msub> <mi>g</mi> <mrow> <mi>s</mi> <mi>t</mi> </mrow> </msub> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>
    In formula (2), BCiRepresent node NiNormalization betweenness, n XXXX, gstRepresent node NsTo node NtAll shortest paths The number in footpath,Represent node NsTo node NtGstPass through node N in bar shortest pathiPath number, i, s, t be section Point numbering.
  3. 3. complex network node importance appraisal procedure according to claim 1, it is characterised in that：Adjustment updates its neighbour The specific method of the real load of node is：The real load of the failure node is proportionally distributed into neighbor node；Institute State the current load and the ratio of the current load sum of whole neighbor nodes that ratio is some neighbor node.
  4. 4. complex network node importance appraisal procedure according to claim 3, it is characterised in that：By formula (3) Suo Shi The real load of the failure node is proportionally distributed to neighbor node by formula：
    <mrow> <msubsup> <mi>L</mi> <mrow> <mi>i</mi> <mo>&amp;RightArrow;</mo> <mi>j</mi> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>=</mo> <mfrac> <msub> <mi>L</mi> <mi>j</mi> </msub> <mrow> <msub> <mi>&amp;Sigma;</mi> <mrow> <msub> <mi>N</mi> <mi>s</mi> </msub> <mo>&amp;Element;</mo> <msub> <mi>&amp;Gamma;</mi> <mi>i</mi> </msub> </mrow> </msub> <msub> <mi>L</mi> <mi>s</mi> </msub> </mrow> </mfrac> <mo>&amp;times;</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mi>&amp;eta;</mi> <mo>)</mo> </mrow> <mo>&amp;times;</mo> <msub> <mi>L</mi> <mi>i</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>
    In formula (3), ΓiFor failure node NiNeighbor node set, L'i→jFor failure node NiNeighbor node is distributed to after failure Nj∈ΓiReal load, LsFor neighbor node Ns∈ΓiReal load, LjFor neighbor node Nj∈ΓiReal load, η To be lost in the load ratio of dissipation, L after node failureiFor failure node NiReal load.
  5. 5. complex network node importance appraisal procedure according to claim 3, it is characterised in that：Adjustment renewal renewal is multiple The specific method of the load bearing capacity of miscellaneous network node is：According to the tolerance coefficient, degree, the load for normalizing betweenness more new node of node Lotus capacity.
  6. 6. complex network node importance appraisal procedure according to claim 5, it is characterised in that：By formula (4) Suo Shi The load bearing capacity of formula adjustment renewal complex network node：
    CLj=(1+ βj)×[αj×Kj+(1-αj)×BCj] (4)
    In formula (4), CLjFor complex network node NjLoad bearing capacity, βjFor node NjLoad tolerance coefficient, αjFor node Nj's Load stoichiometric factor, KjFor current Node Contraction in Complex Networks NjDegree, BCjRepresent current Node Contraction in Complex Networks NjNormalization Betweenness.
  7. 7. complex network node importance appraisal procedure according to claim 5, it is characterised in that：New the one of step S2 During the failure of wheel judges, when the real load of node is more than the load bearing capacity of node, predicate node failure.
  8. A kind of 8. complex network node importance assessment system, it is characterised in that including：
    Initialization module：For initializing the real load of each node in complex network, and calculate the initial total of complex network Load；
    Failure simulation module：For carrying out failure investigation successively to each node of complex network, cascading failure emulation is carried out；Institute State in cascading failure simulation process, after failure node is deleted, adjustment updates the real load of its neighbor node, and updates complexity The load bearing capacity of network node, and according to the renewal load and update failure of the load bearing capacity to a complex network progress new round Judge, until complex network stabilization, and calculate the remaining full payload of complex network；
    Evaluation module：For assessing the importance of node according to the initial full payload and remaining full payload.
  9. 9. complex network node importance assessment system according to claim 8, it is characterised in that：The failure simulation mould Block adjusts the reality of its neighbor node of renewal by the way that the real load of the failure node is proportionally distributed into neighbor node Border load；The ratio is the current load and the ratio of the current load sum of whole neighbor nodes of some neighbor node.
  10. 10. complex network node importance assessment system according to claim 9, it is characterised in that：The failure simulation Module tolerates coefficient, degree, the load bearing capacity for normalizing betweenness more new node according to node.
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Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108123847A (en) * 2017-12-14 2018-06-05 华北电力大学 Powerline network model interior joint influence power judgment value determines method and device
CN108683448A (en) * 2018-04-24 2018-10-19 中国民航大学 Influence power node recognition methods suitable for air net and system
CN108898300A (en) * 2018-06-21 2018-11-27 南京邮电大学 The construction method of supply chain network risk cascade model
CN108965127A (en) * 2018-07-19 2018-12-07 中国人民解放军战略支援部队信息工程大学 A kind of method and device identifying inter-domain routing system key node
CN109543960A (en) * 2018-11-02 2019-03-29 北京电子工程总体研究所 A kind of the reliability critical product analysis method and system of complex large system
CN110224930A (en) * 2019-05-30 2019-09-10 国网福建省电力有限公司 A kind of power telecom network service restoration method of logic-based cascading failure model
CN111008311A (en) * 2019-12-25 2020-04-14 中国人民解放军国防科技大学 Complex network node importance evaluation method and device based on neighborhood weak connection
CN111327484A (en) * 2020-04-09 2020-06-23 东北大学秦皇岛分校 Improved load redistribution method based on maximum residual capacity of node
CN111881545A (en) * 2020-06-11 2020-11-03 杭州师范大学 Node importance identification method based on complex network dependent seepage model
CN112087328A (en) * 2020-08-27 2020-12-15 西安理工大学 Complex time-lag network synchronization and identification method based on optimal node selection strategy
CN114120643A (en) * 2021-11-23 2022-03-01 燕山大学 Method for relieving cascade failure of urban road traffic network
CN114928546A (en) * 2022-04-06 2022-08-19 杭州电子科技大学 Method for identifying key recovery node based on spatial network
CN114938338A (en) * 2022-05-18 2022-08-23 南京理工大学 Resource protection allocation method under limited resource condition in rail transit network
CN116109117A (en) * 2023-04-14 2023-05-12 北京科技大学 Method and medium for evaluating importance of data stream of item

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070143442A1 (en) * 2005-12-20 2007-06-21 Nec Laboratories America, Inc. Scalable Publish/Subscribe Broker Network Using Active Load Balancing
CN102270388A (en) * 2011-06-03 2011-12-07 王正武 Method for measuring and calculating importance of traffic network nodes with consideration of cascading failure
CN103957032A (en) * 2014-04-17 2014-07-30 华北电力大学 Load redistribution method for electric power coupling network to resist cascade failure
CN104766141A (en) * 2015-04-20 2015-07-08 国家电网公司 Power grid risk prevention and control system based on cascading failure sequence
CN104811397A (en) * 2015-03-24 2015-07-29 中国人民解放军国防科学技术大学 Method for estimating node significance of complex network based on node state evolution
CN105656198A (en) * 2015-12-29 2016-06-08 中国电力科学研究院 Electric power communication network redundant path strategy acquiring method
CN106789376A (en) * 2017-03-24 2017-05-31 大连大学 Charge cascade failure model construction method with hierarchical structure

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070143442A1 (en) * 2005-12-20 2007-06-21 Nec Laboratories America, Inc. Scalable Publish/Subscribe Broker Network Using Active Load Balancing
CN102270388A (en) * 2011-06-03 2011-12-07 王正武 Method for measuring and calculating importance of traffic network nodes with consideration of cascading failure
CN103957032A (en) * 2014-04-17 2014-07-30 华北电力大学 Load redistribution method for electric power coupling network to resist cascade failure
CN104811397A (en) * 2015-03-24 2015-07-29 中国人民解放军国防科学技术大学 Method for estimating node significance of complex network based on node state evolution
CN104766141A (en) * 2015-04-20 2015-07-08 国家电网公司 Power grid risk prevention and control system based on cascading failure sequence
CN105656198A (en) * 2015-12-29 2016-06-08 中国电力科学研究院 Electric power communication network redundant path strategy acquiring method
CN106789376A (en) * 2017-03-24 2017-05-31 大连大学 Charge cascade failure model construction method with hierarchical structure

Cited By (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN108683448A (en) * 2018-04-24 2018-10-19 中国民航大学 Influence power node recognition methods suitable for air net and system
CN108683448B (en) * 2018-04-24 2020-10-09 中国民航大学 Influence node identification method and system suitable for aviation network
CN108898300A (en) * 2018-06-21 2018-11-27 南京邮电大学 The construction method of supply chain network risk cascade model
CN108965127A (en) * 2018-07-19 2018-12-07 中国人民解放军战略支援部队信息工程大学 A kind of method and device identifying inter-domain routing system key node
CN108965127B (en) * 2018-07-19 2021-10-15 中国人民解放军战略支援部队信息工程大学 Method and device for identifying key nodes of inter-domain routing system
CN109543960A (en) * 2018-11-02 2019-03-29 北京电子工程总体研究所 A kind of the reliability critical product analysis method and system of complex large system
CN110224930A (en) * 2019-05-30 2019-09-10 国网福建省电力有限公司 A kind of power telecom network service restoration method of logic-based cascading failure model
CN110224930B (en) * 2019-05-30 2021-10-29 国网福建省电力有限公司 Power communication network service recovery method based on logic cascade failure model
CN111008311A (en) * 2019-12-25 2020-04-14 中国人民解放军国防科技大学 Complex network node importance evaluation method and device based on neighborhood weak connection
CN111008311B (en) * 2019-12-25 2023-07-21 中国人民解放军国防科技大学 Complex network node importance assessment method and device based on neighborhood weak connection
CN111327484A (en) * 2020-04-09 2020-06-23 东北大学秦皇岛分校 Improved load redistribution method based on maximum residual capacity of node
CN111327484B (en) * 2020-04-09 2022-03-22 东北大学秦皇岛分校 Improved load redistribution method based on maximum residual capacity of node
CN111881545A (en) * 2020-06-11 2020-11-03 杭州师范大学 Node importance identification method based on complex network dependent seepage model
CN111881545B (en) * 2020-06-11 2023-12-08 杭州师范大学 Node importance identification method based on complex network dependent seepage model
CN112087328A (en) * 2020-08-27 2020-12-15 西安理工大学 Complex time-lag network synchronization and identification method based on optimal node selection strategy
CN114120643B (en) * 2021-11-23 2022-10-28 燕山大学 Method for relieving cascade failure of urban road traffic network
CN114120643A (en) * 2021-11-23 2022-03-01 燕山大学 Method for relieving cascade failure of urban road traffic network
CN114928546A (en) * 2022-04-06 2022-08-19 杭州电子科技大学 Method for identifying key recovery node based on spatial network
CN114928546B (en) * 2022-04-06 2024-04-09 杭州电子科技大学 Method for identifying key recovery nodes based on space network
CN114938338A (en) * 2022-05-18 2022-08-23 南京理工大学 Resource protection allocation method under limited resource condition in rail transit network
CN114938338B (en) * 2022-05-18 2024-04-12 南京理工大学 Protection resource allocation method under limited resource condition in rail transit network
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