CN113079058B - Key infrastructure network elasticity strengthening method and system - Google Patents
Key infrastructure network elasticity strengthening method and system Download PDFInfo
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Abstract
The invention relates to a method and a system for strengthening the elasticity of a key infrastructure network. The method comprises the following steps: acquiring network parameters of a key infrastructure network; the network parameters comprise a node set and a connecting edge set; obtaining the operation parameters of the key infrastructure network at the current moment; the operation parameters comprise structural parameters and load data, the structural parameters are network structures of the key infrastructure network, and the load data comprise load values of each node in the key infrastructure network; determining a reinforced node identification sequencing index of each node in the key infrastructure network at the current moment according to the operation parameters of the key infrastructure network; determining a plurality of nodes with the highest identification and sequencing indexes of the strengthening nodes as nodes to be strengthened to obtain a node set to be strengthened; sequentially strengthening each node to be strengthened in the node set to be strengthened; the tolerance value of each node to be strengthened after being strengthened is infinite. The invention can improve the elasticity strengthening effect of the key infrastructure network.
Description
Technical Field
The invention relates to the field of facility network strengthening, in particular to a method and a system for strengthening the elasticity of a key infrastructure network.
Background
The key infrastructure network is the 'nerve center' of social economy and national defense safety and is also an important link of network safety, the coverage is wide, and the functions are also characterized by diversification and diversity. With the development of a new technical revolution and an industrial revolution, the key infrastructure network effectively integrates and utilizes the existing resources by coupling the information domain and the physical domain, and the operating efficiency of different networks is greatly improved. However, the technical progress also makes people face challenges brought by a plurality of uncertain factors, for example, due to the coupling effect, the network has the characteristic of multi-network fusion, the node has large scale, complex structure and hierarchical cross-linking, the occurrence of faults is easy to evolve and propagate, the serious fault chain reaction is caused, the catastrophic results are generated, and the key infrastructure network is easy to become the attack target, so effective measures must be taken, and the safety protection work is really done.
In order to effectively protect the critical infrastructure, many countries have promoted the work of protecting the critical infrastructure into national strategy, issued relevant laws and regulations, and clearly required different emergency management measures to maintain the normal operation of the critical infrastructure. The huge damage caused by natural disasters not only can easily become an attack target, but also local faults can easily evolve to cause the global paralysis of the system, so that on one hand, the economic serious loss can be caused, on the other hand, the safety of related industries and countries can even be seriously threatened, and the great destructive power is realized. For this reason, many countries attach high importance to the protection of the critical infrastructure, and have detailed relevant policies and plans to improve the risk prevention and evaluation capability of the critical infrastructure.
Disclosure of Invention
The invention aims to provide a method and a system for strengthening the elasticity of a key infrastructure network so as to improve the elasticity strengthening effect of the key infrastructure network.
In order to achieve the purpose, the invention provides the following scheme:
a method for elastic reinforcement of a key infrastructure network comprises the following steps:
acquiring network parameters of a key infrastructure network; the network parameters comprise a node set and a connecting edge set;
obtaining the operation parameters of the key infrastructure network at the current moment; the operational parameters include structural parameters and load data, the structural parameters are network structures of the key infrastructure network, and the load data includes a load value of each node in the key infrastructure network;
using a formula based on the operational parameters of the key infrastructure network
Determining a reinforced node identification sequencing index of each node in the key infrastructure network at the current moment; wherein D isi(t) identifying a ranking index for a reinforcement node of an ith node in the key infrastructure network at the current moment; y isi(t) represents a load capacity margin proportion of an ith node in the critical infrastructure network at the current time,
Yj(t) represents a load capacity margin proportion of a jth node in the critical infrastructure network at the current moment; gamma-shapediA neighbor node representing an ith node in the critical infrastructure network; l isi(t) represents a load value of an ith node in the critical infrastructure network at the current time; l isj(t) represents a load value of a jth node in the critical infrastructure network at the current time; β represents a tolerance parameter;
determining a plurality of nodes with the highest identification and sequencing indexes of the strengthening nodes as nodes to be strengthened to obtain a node set to be strengthened;
sequentially strengthening each node to be strengthened in the node set to be strengthened; the tolerance value of each node to be strengthened after strengthening is infinite.
Optionally, the obtaining of the operation parameters of the key infrastructure network at the current time specifically includes:
acquiring fault data of the key infrastructure network at the current moment;
determining node information and connection side information of the key infrastructure network at the current moment according to the network parameters of the key infrastructure network and the fault data to obtain the structural parameters;
and acquiring the load value of each node in the key infrastructure network at the current moment according to the structural parameters to obtain the load data.
Optionally, the determining, according to the network parameter of the key infrastructure network and the fault data, node information and connection side information of the key infrastructure network at the current time to obtain the structural parameter further includes:
and constructing an adjacency matrix of the key infrastructure network based on the structural parameters to obtain a key infrastructure network model.
Optionally, the sequentially strengthening each node to be strengthened in the set of nodes to be strengthened, and then further includes:
when the end time of the monitoring time period is reached, evaluating the elasticity strengthening effect of the key infrastructure network in the monitoring time period based on an elasticity evaluation index; the elasticity evaluation indexes are as follows:
wherein, R (T)*) The method comprises the following steps of (1) obtaining an elasticity evaluation result of the key infrastructure network after a monitoring time period is ended; g1(t) is the relative size of the maximum connected sub-cluster of the key infrastructure network at time t in the monitoring time period in practical cases, G0(t) is the relative size of the maximum connected sub-cluster of the critical infrastructure network at time t within the monitoring period under ideal no-fault conditions, t0Is the initial time of the monitoring period, T*Is the end time of the monitoring time period.
The invention also provides a system for strengthening the elasticity of the key infrastructure network, which comprises:
the network parameter acquisition module is used for acquiring network parameters of the key infrastructure network; the network parameters comprise a node set and a connecting edge set;
the operation parameter acquisition module is used for acquiring the operation parameters of the key infrastructure network at the current moment; the operational parameters include structural parameters and load data, the structural parameters are network structures of the key infrastructure network, and the load data includes a load value of each node in the key infrastructure network;
a determination module for identifying and sequencing index of the enhanced node, which is used for utilizing a formula according to the operation parameters of the key infrastructure network
Determining a reinforced node identification sequencing index of each node in the key infrastructure network at the current moment; wherein D isi(t) identifying a ranking index for a reinforcement node of an ith node in the key infrastructure network at the current moment; y isi(t) represents a load capacity margin proportion of an ith node in the critical infrastructure network at the current time,
Yj(t) represents a load capacity margin proportion of a jth node in the critical infrastructure network at the current moment; gamma-shapediA neighbor node representing an ith node in the critical infrastructure network; l isi(t) represents a load value of an ith node in the critical infrastructure network at the current time; l isj(t) represents a load value of a jth node in the critical infrastructure network at the current time; β represents a tolerance parameter;
the node to be strengthened determining module is used for determining a plurality of nodes with the highest recognition and sequencing indexes of the strengthening nodes as nodes to be strengthened to obtain a node set to be strengthened;
the strengthening module is used for sequentially strengthening each node to be strengthened in the node set to be strengthened; the tolerance value of each node to be strengthened after being strengthened is infinite.
Optionally, the operation parameter obtaining module specifically includes:
the fault data acquisition unit is used for acquiring the fault data of the key infrastructure network at the current moment;
a parameter structure determining unit, configured to determine node information and connection side information of the key infrastructure network at the current time according to the network parameter of the key infrastructure network and the fault data, to obtain the structure parameter;
and the load data acquisition unit is used for acquiring the load value of each node in the key infrastructure network at the current moment according to the structural parameters to obtain the load data.
Optionally, the method further includes:
and the key infrastructure network model building module is used for determining node information and connection side information of the key infrastructure network at the current moment according to the network parameters and the fault data of the key infrastructure network to obtain the structural parameters, and then building an adjacency matrix of the key infrastructure network based on the structural parameters to obtain a key infrastructure network model.
Optionally, the method further includes:
the elastic evaluation module is used for evaluating the elastic strengthening effect of the key infrastructure network in the monitoring time period based on an elastic evaluation index after sequentially strengthening each node to be strengthened in the node set to be strengthened and when the end time of the monitoring time period is reached; the elasticity evaluation indexes are as follows:
wherein, R (T)*) The method comprises the following steps of (1) obtaining an elasticity evaluation result of the key infrastructure network after a monitoring time period is ended; g1(t) is the relative size of the maximum connected sub-cluster of the key infrastructure network at time t in the monitoring time period in practical cases, G0(t) is the relative size of the maximum connected sub-cluster of the critical infrastructure network at time t within the monitoring period under ideal no-fault conditions, t0Is the initial time of the monitoring period, T*Is the end time of the monitoring time period.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
(1) the invention has wide application range. The method is applicable to complex systems with objects covering key infrastructures in multiple fields of communication, traffic, energy and the like, and all related systems which can be abstracted into network models can be used for elastic reinforcement.
(2) The strengthening effect is excellent. The reinforcement method provided by the invention has excellent reinforcement effect, and can obtain better elastic reinforcement effect under given resource constraint.
(3) The computational complexity is low. The reinforcement method provided by the invention only needs to calculate the structure information of the neighborhood nodes and the load capacity margin information, has low calculation complexity, is beneficial to quickly identifying and screening the reinforcement nodes in the key infrastructure network, and is also beneficial to expanding the elastic reinforcement calculation of a large-scale network.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a method for enhancing network elasticity of a key infrastructure network according to the present invention;
FIG. 2 is a schematic diagram of a key infrastructure network resiliency enforcement system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
FIG. 1 is a flow chart of a method for enhancing network elasticity of a key infrastructure network according to the present invention. As shown in fig. 1, the method for enhancing network elasticity of a key infrastructure of the present invention comprises the following steps:
step 100: network parameters of a key infrastructure network are obtained. The network parameters include a node set and a connecting edge set. During a monitoring period of time t e [ t ]0,T*]In terms of key groupsEvaluating area range of infrastructure network, and acquiring node set and connecting edge set of key infrastructure network, wherein t0Denotes the starting time, T*Indicating the termination time.
Step 200: and obtaining the operation parameters of the key infrastructure network at the current moment. The operational parameters include structural parameters that are network structures of the critical infrastructure network and load data that includes a load value for each node in the critical infrastructure network. The invention collects the fault information at the current moment to obtain the fault node set. In the operation process, when a node fails, the connection condition of the node is changed, namely the network structure is changed. Therefore, the key infrastructure network node information and the connecting edge information can be counted according to the fault node set, then the key infrastructure network node numbers and the connecting edge numbers are distributed, the N nodes are sequentially numbered from 1 to N, and the M connecting edges are sequentially numbered from 1 to M. And further, constructing a key infrastructure network adjacency matrix according to the node information and the connection edge information, and defining that a if any node i and node j (i ≠ j) of the network adjacency matrix A (t) have connection edgesij(t) is 1, otherwise aij(t) is 0. Wherein A (t) represents a adjacency matrix of t times; a is aij(t) represents the value of the element adjacent to the ith row and jth column of the matrix at time t. The adjacency matrix obtained is as follows:
from the adjacency matrix, a key infrastructure network model can be derived.
According to the network structure of the key infrastructure network model, the load value L of any node i can be acquired in real timeiAnd (t) obtaining load data of the whole network.
Step 300: and determining a reinforced node identification sequencing index of each node in the key infrastructure network at the current moment according to the operation parameters of the key infrastructure network. In order to effectively identify the enhanced nodes in the key infrastructure network and comprehensively consider the load capacity margin proportion of the nodes and the local neighborhood, the invention adopts the following identification and sequencing indexes of the enhanced nodes:
wherein D isi(t) identifying a ranking index for a reinforcement node of an ith node in the key infrastructure network at the current moment; y isi(t) represents a load capacity margin proportion of an ith node in the critical infrastructure network at the current time,
Yj(t) represents a load capacity margin proportion of a jth node in the critical infrastructure network at the current moment; gamma-shapediA neighbor node representing an ith node in the critical infrastructure network; l is a radical of an alcoholi(t) represents a load value of an ith node in the critical infrastructure network at the current time; l isj(t) represents a load value of a jth node in the critical infrastructure network at a current time; beta represents a tolerance parameter.
Step 400: and determining a plurality of nodes with the highest identification and sequencing indexes of the strengthening nodes as nodes to be strengthened to obtain a node set to be strengthened. According to the reinforced node identification sorting indexes corresponding to each node at the current moment, the reinforced node identification sorting indexes of all the nodes are sorted in a descending order, and the obtained node sequence S meets the condition that S is equal to { D ═ Di(t)≥Dj(t)≥Dk(t)≥......≥Dl(t) }, where i, j, k, l are node numbers. Under the resource constraint of given quantity m of strengthening nodes, screening the first m nodes as nodes to be strengthened according to the arrangement sequence of the node sequence S.
Step 500: and sequentially strengthening each node to be strengthened in the node set to be strengthened. The tolerance value of each node to be strengthened after being strengthened is infinite. And reinforcing the first m nodes to obtain m reinforced nodes, wherein the tolerance value of the reinforced nodes is infinite. In an actual system, the nodes can be reinforced by using extra resources to achieve the effect of strengthening the tolerance of the nodes, for example, measures such as increasing manpower in a traffic network to dredge traffic, cleaning road occupation and increasing capacity are added, and the measures taken by different systems are inconsistent.
In the above manner, the key infrastructure network at each moment can be elastically strengthened in the monitoring time period until the monitoring time is over.
After the monitoring time period is finished, the elasticity enhancing effect of the key infrastructure network in the monitoring time period can be further evaluated. The elasticity enhancement effect evaluation of the invention is based on network connectivity performance indexes, and the specific formula is as follows:
wherein, R (T)*) The method comprises the following steps of (1) obtaining an elasticity evaluation result of the key infrastructure network after a monitoring time period is ended; g1(t) is the connectivity index of the key infrastructure network at time t in the monitoring time period in practical cases, G0(t) is a connectivity index of the key infrastructure network at time t within a monitoring time period under an ideal fault-free condition, t0Is the initial time of the monitoring period, T*Is the end time of the monitoring time period. The connectivity of the key infrastructure network at the time t is the relative size of the maximum connected sub-cluster at the time t, and the relative size G of the maximum connected sub-cluster at the time t is max { G { (G)1,G2,...,Gn}，G1,G2,...,GnRepresenting the relative size G of the connected sub-groups in the key infrastructure network at time t, which are decomposed due to node failure and have no interconnectioni＝gi/g0,i＝1,2,…,n，giRepresents the total number of nodes, g, of the ith connected clique0N represents the total number of connected sub-cliques for the total number of nodes of the critical infrastructure network in an ideal fault-free state.
FIG. 2 is a schematic diagram of a key infrastructure network resiliency strengthening system according to the present invention. As shown in fig. 2, the system for enhancing network elasticity of a key infrastructure network of the present invention comprises the following structures:
a network parameter obtaining module 201, configured to obtain a network parameter of a key infrastructure network; the network parameters include a node set and a connecting edge set.
An operation parameter obtaining module 202, configured to obtain an operation parameter of the key infrastructure network at the current time; the operational parameters include structural parameters that are network structures of the critical infrastructure network and load data that includes a load value for each node in the critical infrastructure network.
A determination module 203 for identifying and ranking the index of the enhanced node, configured to utilize a formula according to the operation parameters of the key infrastructure network
Determining a reinforced node identification sequencing index of each node in the key infrastructure network at the current moment; wherein D isi(t) identifying a ranking index for a reinforcement node of an ith node in the key infrastructure network at the current moment; y isi(t) represents a load capacity margin proportion of an ith node in the critical infrastructure network at the current time,
Yj(t) represents a load capacity margin proportion of a jth node in the critical infrastructure network at the current moment; gamma-shapediA neighbor node representing an ith node in the critical infrastructure network; l isi(t) represents a load value of an ith node in the critical infrastructure network at the current time; l isj(t) represents a load value of a jth node in the critical infrastructure network at the current time; beta represents a tolerance parameter.
The node to be strengthened determining module 204 is configured to determine a plurality of nodes with the highest recognition and ranking index of the strengthening nodes as nodes to be strengthened, so as to obtain a node set to be strengthened.
A strengthening module 205, configured to sequentially strengthen each node to be strengthened in the set of nodes to be strengthened; the tolerance value of each node to be strengthened after being strengthened is infinite.
As a specific embodiment, in the system for enhancing network elasticity of a key infrastructure network according to the present invention, the operation parameter obtaining module 202 specifically includes:
and the fault data acquisition unit is used for acquiring the fault data of the key infrastructure network at the current moment.
And the parameter structure determining unit is used for determining the node information and the connection side information of the key infrastructure network at the current moment according to the network parameters of the key infrastructure network and the fault data to obtain the structure parameters.
And the load data acquisition unit is used for acquiring the load value of each node in the key infrastructure network at the current moment according to the structural parameters to obtain the load data.
As a specific embodiment, the system for enhancing network elasticity of a key infrastructure of the present invention further comprises:
and the key infrastructure network model building module is used for determining node information and connection side information of the key infrastructure network at the current moment according to the network parameters and the fault data of the key infrastructure network to obtain the structural parameters, and then building an adjacency matrix of the key infrastructure network based on the structural parameters to obtain a key infrastructure network model.
As a specific embodiment, the system for enhancing network elasticity of a key infrastructure of the present invention further includes:
the elasticity evaluation module is used for evaluating the elasticity strengthening effect of the key infrastructure network in the monitoring time period based on an elasticity evaluation index after strengthening each node to be strengthened in the node set to be strengthened in sequence and when the end time of the monitoring time period is reached; the elasticity evaluation indexes are as follows:
wherein, R (T)*) The elasticity evaluation result of the key infrastructure network after the monitoring time period is finished; g1(t) in practice, the maximum connected sub-cluster of the key infrastructure network at t time in the monitoring time periodRelative size of (1), G0(t) is the relative size of the maximum connected sub-cluster of the critical infrastructure network at time t within the monitoring period under ideal fault-free conditions, t0Is the initial time of the monitoring period, T*Is the end time of the monitoring time period.
In specific application, different strengthening methods can be adopted for comparison, and the strengthening method with the optimal strengthening effect is obtained for carrying out elastic strengthening on the key infrastructure network. Specifically, disturbance is applied to the key infrastructure network according to historical fault data, a cascade failure process is triggered, different methods are adopted for elastic reinforcement in the cascade failure process, when the cascade failure process is finished, the key infrastructure network connectivity performance indexes are counted, and the key infrastructure network elasticity is obtained through calculation. The method comprises the following steps:
(1) setting five node strengthening methods as comparison verification, wherein the five node strengthening methods respectively comprise degree centrality, randomness, k core centrality, betweenness centrality and aggregation coefficient, and strengthening the identified nodes by adopting different strengthening methods under the constraint of the same resource;
(2) applying disturbance to the network according to the collected historical fault node set, and in t epsilon [ t ∈ [ ]0,T*]Sequentially removing nodes of the fault node set at different times t in the range, and counting and recording corresponding parameters of the network, including G0(t)、G1(t)、n(t)、Li(t) and Ci(t0) Five parameters until the cascade failure process is ended, and the time T is T*；
(3) According to the elasticity evaluation index formula, calculating the time T as T*After the cascade failure process is finished, comparing the elasticity strengthening results of different strengthening methods after strengthening the network, and further screening out the strengthening method with the highest elasticity evaluating result, namely the best strengthening effect, as the elasticity strengthening method of the key infrastructure network.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principle and the embodiment of the present invention are explained by applying specific examples, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A method for elastic reinforcement of a key infrastructure network is characterized by comprising the following steps:
acquiring network parameters of a key infrastructure network; the network parameters comprise a node set and a connecting edge set;
obtaining the operation parameters of the key infrastructure network at the current moment; the operational parameters include structural parameters and load data, the structural parameters are network structures of the key infrastructure network, and the load data includes a load value of each node in the key infrastructure network;
using a formula based on the operational parameters of the key infrastructure network
Determining a reinforced node identification sequencing index of each node in the key infrastructure network at the current moment; wherein D isi(t) identifying a ranking index for a reinforcement node of an ith node in the key infrastructure network at the current moment; y isi(t) represents a load capacity margin proportion of an ith node in the critical infrastructure network at the current time,
Yj(t) represents a load capacity margin proportion of a jth node in the critical infrastructure network at the current moment;Γia neighbor node representing an ith node in the critical infrastructure network; l isi(t) represents a load value of an ith node in the critical infrastructure network at the current time; l isj(t) represents a load value of a jth node in the critical infrastructure network at a current time; β represents a tolerance parameter;
determining a plurality of nodes with the highest identification and sequencing indexes of the strengthening nodes as nodes to be strengthened to obtain a node set to be strengthened;
and sequentially strengthening each node to be strengthened in the node set to be strengthened.
2. The method for elastic reinforcement of a key infrastructure network according to claim 1, wherein the obtaining of the operation parameters of the key infrastructure network at the current time specifically includes:
acquiring fault data of the key infrastructure network at the current moment;
determining node information and connection side information of the key infrastructure network at the current moment according to the network parameters of the key infrastructure network and the fault data to obtain the structural parameters;
and acquiring the load value of each node in the key infrastructure network at the current moment according to the structural parameters to obtain the load data.
3. The method for elastic reinforcement of a key infrastructure network according to claim 2, wherein the determining node information and side information of the key infrastructure network at the current time according to the network parameters of the key infrastructure network and the fault data to obtain the structural parameters further comprises:
and constructing an adjacency matrix of the key infrastructure network based on the structural parameters to obtain a key infrastructure network model.
4. The method according to claim 1, wherein the strengthening of each node to be strengthened in the set of nodes to be strengthened is performed in sequence, and then further comprising:
when the end time of the monitoring time period is reached, evaluating the elasticity strengthening effect of the key infrastructure network in the monitoring time period based on an elasticity evaluation index; the elasticity evaluation indexes are as follows:
wherein, R (T)*) The method comprises the following steps of (1) obtaining an elasticity evaluation result of the key infrastructure network after a monitoring time period is ended; g1(t) is the relative size of the maximum connected sub-cluster of the key infrastructure network at time t in the monitoring time period in practical cases, G0(t) is the relative size of the maximum connected sub-cluster of the critical infrastructure network at time t within the monitoring period under ideal no-fault conditions, t0Is the initial time of the monitoring period, T*Is the end time of the monitoring time period.
5. A system for resilient reinforcement of a critical infrastructure network, comprising:
the network parameter acquisition module is used for acquiring network parameters of the key infrastructure network; the network parameters comprise a node set and a connecting edge set;
the operation parameter acquisition module is used for acquiring the operation parameters of the key infrastructure network at the current moment; the operational parameters include structural parameters that are network structures of the critical infrastructure network and load data that includes a load value for each node in the critical infrastructure network;
a determination module for identifying and sequencing index of the enhanced node, which is used for utilizing a formula according to the operation parameters of the key infrastructure network
Determining a reinforced node identification sequencing index of each node in the key infrastructure network at the current moment; wherein D isi(t) is the key base at the current momentIdentifying and sequencing indexes of the strengthened nodes of the ith node in the infrastructure network; y isi(t) represents a load capacity margin proportion of an ith node in the critical infrastructure network at the current time,
Yj(t) represents a load capacity margin proportion of a jth node in the critical infrastructure network at the current moment; gamma-shapediA neighbor node representing an ith node in the critical infrastructure network; l isi(t) represents a load value of an ith node in the critical infrastructure network at the current time; l isj(t) represents a load value of a jth node in the critical infrastructure network at the current time; β represents a tolerance parameter;
the node to be strengthened determining module is used for determining a plurality of nodes with the highest recognition and sequencing indexes of the strengthening nodes as nodes to be strengthened to obtain a node set to be strengthened;
and the strengthening module is used for sequentially strengthening each node to be strengthened in the node set to be strengthened.
6. The system for elastic reinforcement of a key infrastructure network according to claim 5, wherein the operation parameter obtaining module specifically comprises:
the fault data acquisition unit is used for acquiring the fault data of the key infrastructure network at the current moment;
a parameter structure determining unit, configured to determine node information and connection side information of the key infrastructure network at the current time according to the network parameter of the key infrastructure network and the fault data, to obtain the structure parameter;
and the load data acquisition unit is used for acquiring the load value of each node in the key infrastructure network at the current moment according to the structural parameters to obtain the load data.
7. The key infrastructure network resiliency strengthening system of claim 6, further comprising:
and the key infrastructure network model building module is used for determining node information and connection side information of the key infrastructure network at the current moment according to the network parameters and the fault data of the key infrastructure network to obtain the structural parameters, and then building an adjacency matrix of the key infrastructure network based on the structural parameters to obtain a key infrastructure network model.
8. The key infrastructure network resiliency strengthening system of claim 5, further comprising:
the elastic evaluation module is used for evaluating the elastic strengthening effect of the key infrastructure network in the monitoring time period based on an elastic evaluation index after sequentially strengthening each node to be strengthened in the node set to be strengthened and when the end time of the monitoring time period is reached; the elasticity evaluation indexes are as follows:
wherein, R (T)*) The method comprises the following steps of (1) obtaining an elasticity evaluation result of the key infrastructure network after a monitoring time period is ended; g1(t) is the relative size of the maximum connected sub-cluster of the key infrastructure network at time t within the monitoring period of time under practical conditions, G0(t) is the relative size of the maximum connected sub-cluster of the critical infrastructure network at time t within the monitoring period under ideal no-fault conditions, t0Is the initial time of the monitoring period, T*Is the end time of the monitoring time period.
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| WO2013144950A1 (en) * | 2012-03-25 | 2013-10-03 | Intucell Ltd. | System and method for optimizing performance of a communication network |
| WO2015199591A1 (en) * | 2014-06-26 | 2015-12-30 | Telefonaktiebolaget L M Ericsson (Publ) | Methods, nodes and system for enabling redistribution of cell load |
| CN108601047A (en) * | 2018-08-02 | 2018-09-28 | 南昌航空大学 | The measurement method of opportunistic network key node |
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| WO2013144950A1 (en) * | 2012-03-25 | 2013-10-03 | Intucell Ltd. | System and method for optimizing performance of a communication network |
| WO2015199591A1 (en) * | 2014-06-26 | 2015-12-30 | Telefonaktiebolaget L M Ericsson (Publ) | Methods, nodes and system for enabling redistribution of cell load |
| CN108601047A (en) * | 2018-08-02 | 2018-09-28 | 南昌航空大学 | The measurement method of opportunistic network key node |
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