CN112104515A - Network reconstruction method and device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to a network reconstruction method, a network reconstruction device, computer equipment and a storage medium. The method comprises the following steps: acquiring an initial binary data matrix in a preset IP node network, wherein elements in the matrix represent the data receiving state of whether the IP node receives data; determining the common data quantity of any two nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity; elements in the common data matrix represent the common data quantity of any two IP nodes; determining a binary data subgraph corresponding to each data according to the data receiving state; obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraphs; and (5) carrying out network reconstruction on the subgraph common data matrix corresponding to each datum. By adopting the method, the difficulty of acquiring data by the network is reduced, the accuracy of network topology reconstruction is improved, and the calculation complexity is low.
Description
Technical Field
The present application relates to the field of network technologies, and in particular, to a network reconfiguration method and apparatus, a computer device, and a storage medium.
Background
Networks have been widely present in the real world as abstractions of complex systems, from the food network of the biological world to brain networks in the brain, power networks in modern society, the Internet, social networks, and so on. The nodes in the network represent entity elements in the system, and the connecting edges among the nodes in the network represent interaction relations among the entities in the system. However, people generally have little knowledge about the complex system in reality, and how to reconstruct the network with unknown structure according to the relevant data observable on the network is an important and research-worthy problem without knowing the relevant structure inside the system.
A computer network is generally divided into five layers, namely a physical layer (physical layer), a data link layer (data link layer), a network layer (network layer), a transport layer (transport layer) and an application layer (application layer) from low to high. The physical layer refers primarily to the physical transmission medium used to transmit information, such as twisted pair, coaxial cable, and optical fiber. The data link layer is used for transmitting data between adjacent nodes, and smooth transmission of network data between different nodes is guaranteed. The network layer mainly provides communication service for different hosts on the packet switching network, and ensures the mutual communication between the hosts. The function of the transport layer is to provide a generic data transfer service for communication between processes in two hosts. The application layer is the highest layer in the five-layer structure, and the task is to complete a specific network application through interaction among application processes.
The IP node network is referred to as a computer network layer. The interaction of the datagrams among the nodes on the IP node network reflects the dynamic process on the network, and the datagram interaction among the nodes can reflect the connection relation among the network nodes, so that the topology of the network can be reconstructed through the IP network datagrams. The traditional IP node network reconstruction method is mainly obtained by measurement, and the main measurement methods are divided into two types: based on the SNMP protocol and on the ICMP protocol. However, both methods have respective defects, and the first method is suitable for measurement in a network range with jurisdiction, so that the method is difficult to popularize and apply; the second method is implemented by Tracert, and can be used for large-scale network measurement on the Internet, but cannot perform measurement when firewall software is installed on the network.
The number of IP node network nodes is huge, the interaction relation among the nodes is complex, and the traditional method cannot meet the requirements of network topology structure reconstruction of different network types and larger network scale.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device and a storage medium for simple and fast network reconfiguration, which can be applied to different network types and large network sizes.
A method of network reconfiguration, the method comprising:
acquiring an initial binary data matrix in a preset IP node network; and the elements in the initial binary data matrix represent the data receiving state of whether the IP node receives the data or not.
Determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity; the elements in the common data matrix represent the common data quantity of any two IP nodes.
And determining a binary data subgraph corresponding to each data according to the data receiving state.
And obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraph.
And reconstructing a network by using the subgraph common data matrix corresponding to each datum.
In one embodiment, the method further comprises the following steps: acquiring discrete data in a preset IP node network, and constructing an initial binary data matrix according to the discrete data.
In one embodiment, the method further comprises the following steps: the receiving state comprises 1 and 0, when the receiving state is 1, the receiving state indicates that data is received, and when the receiving state is 0, the receiving state indicates that data is not received; the row number of the binary data matrix represents the number of data, and the column number represents the number of nodes in the IP node network.
And determining the binary data subgraph according to the column number corresponding to the position with the receiving state of 1 in each row in the binary data matrix.
In one embodiment, the method further comprises the following steps: and extracting data from the common data matrix by taking the column numbers as row and column basis according to the column numbers corresponding to the elements in the binary data subgraph corresponding to each data to obtain a subgraph common data matrix corresponding to each data.
In one embodiment, the method further comprises the following steps: and searching the maximum common data for each row of the subgraph common data matrix corresponding to each data.
And when the maximum common data is one, connecting edges of the two IP nodes corresponding to the maximum common data position to obtain a reconstructed sub-graph.
And when the maximum common data is more than one, sequentially connecting edges of two IP nodes corresponding to each maximum common data position to obtain subgraphs with the same quantity as the maximum common data, performing degree variance calculation on the subgraphs, and determining the subgraphs with small degree variance values as the reconstructed subgraphs.
And superposing the reconstruction subgraph obtained by each datum to obtain a reconstruction network.
In one embodiment, the method further comprises the following steps: and respectively carrying out logical union operation on the connecting edge set and the node set of the reconstruction subgraph corresponding to each datum to obtain the network topology of the reconstruction network.
A network reconfiguration device, the device comprising:
the data acquisition module is used for acquiring an initial binary data matrix in a preset IP node network; and the elements in the initial binary data matrix represent the data receiving state of whether the IP node receives the data or not.
A common data matrix determining module, configured to determine, according to the data receiving state, a common data quantity of any two IP nodes in the IP node network, and determine, according to the common data quantity, a common data matrix; the elements in the common data matrix represent the common data quantity of any two IP nodes.
And the binary data subgraph determining module is used for determining a binary data subgraph corresponding to each data according to the data receiving state.
And the subgraph common data matrix determining module is used for obtaining a subgraph common data matrix corresponding to each datum according to the common data matrix and the binary data subgraphs.
And the network reconstruction module is used for reconstructing a network by using the subgraph common data matrix corresponding to each datum.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring an initial binary data matrix in a preset IP node network; and the elements in the initial binary data matrix represent the data receiving state of whether the IP node receives the data or not.
Determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity; the elements in the common data matrix represent the common data quantity of any two IP nodes.
And determining a binary data subgraph corresponding to each data according to the data receiving state.
And obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraph.
And reconstructing a network by using the subgraph common data matrix corresponding to each datum.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring an initial binary data matrix in a preset IP node network; and the elements in the initial binary data matrix represent the data receiving state of whether the IP node receives the data or not.
Determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity; the elements in the common data matrix represent the common data quantity of any two IP nodes.
And determining a binary data subgraph corresponding to each data according to the data receiving state.
And obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraph.
And reconstructing a network by using the subgraph common data matrix corresponding to each datum.
According to the network reconstruction method, the network reconstruction device, the computer equipment and the storage medium, the topology of the IP node network is reconstructed from local to global by fully utilizing the correlation among the nodes, the difficulty of acquiring data is greatly reduced, in addition, the influence of each piece of data on the network structure is fully utilized, the accuracy of network topology reconstruction is improved, and the calculation complexity is low.
Drawings
FIG. 1 is a flow diagram illustrating a network reconfiguration method in one embodiment;
FIG. 2 is a schematic diagram of an embodiment of a sub-graph reconstruction process;
FIG. 3 is a diagram illustrating a sub-graph reconstruction process in one embodiment;
FIG. 4 is a diagram illustrating a sub-graph overlay process in one embodiment;
FIG. 5 and FIG. 6 are diagrams illustrating the WS network reconfiguration effect in one embodiment;
fig. 7 and 8 are diagrams illustrating the reconfiguration effect of the BA network in one embodiment;
FIG. 9 is a diagram illustrating the effects of ER network reconfiguration in one embodiment;
FIG. 10 is a graph of comparative experiments comparing the number of identical nodes in the WS, BA and ER networks in one embodiment;
FIG. 11 is a diagram illustrating the reconstruction effect of WS networks with different averaging values in one embodiment;
FIG. 12 is a diagram illustrating the effectiveness of BA network reconstruction for different averaging values in one embodiment;
FIG. 13 is a graph of ER network reconstruction effects for different averaging values in one embodiment;
FIG. 14 is a block diagram showing the structure of a network reconfiguration device according to an embodiment;
FIG. 15 is a diagram showing an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In the network reconstruction method provided by the application, the computer network topology refers to the topology configuration of a communication subnet, and the network structure is represented by the geometric relationship between the nodes and the communication lines in the network, so that the structural relationship of each entity in the network is reflected. There are two types of nodes of the network: one is a transit node for converting and exchanging information, including node switch, hub and terminal controller, and the other is an access node, including computer host and terminal.
In one embodiment, as shown in fig. 1, there is provided a network reconfiguration method, including:
and 102, acquiring an initial binary data matrix in a preset IP node network.
An IP node network refers to a network layer in a computer network for finding a suitable path for a datagram to be sent for transmission in a complex network environment.
The binary matrix is a logical matrix and is composed of 0 and 1.
The elements in the initial binary data matrix represent the data reception status of whether the IP node receives data.
The initial binary data matrix is a state matrix of whether the IP node receives data, and is defined to reduce the influence of interference data on network topology reconstruction. The initial binary data matrix in an IP node network is created by "tracking" different data and recording the different nodes through which the data passes. According to the state of whether the node receives the data.
And step 104, determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity.
The elements in the common data matrix represent the amount of common data for any two IP nodes.
The data reception state includes 1 and 0, and when the reception state is 1, it indicates that data is received, and when the reception state is 0, it indicates that data is not received.
The element on the diagonal of the common data matrix is defined as 0, and the elements at other positions are equal to the common data amount of any two IP nodes.
The element on the diagonal line of the common data matrix is defined as 0, the elements at other positions are data extracted from the common data matrix according to the binary data subgraph, and the elements in the common data matrix represent the common data quantity of any two IP nodes.
And step 106, determining a binary data subgraph corresponding to each data according to the data receiving state.
A binary data subgraph is any set of nodes that data can receive.
And step 108, obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraphs.
The element on the diagonal line of the subgraph common data matrix corresponding to each data is defined as 0, and the elements at other positions are data extracted from the common data matrix according to the binary data subgraphs.
And step 110, carrying out network reconstruction on the subgraph common data matrix corresponding to each datum.
The network reconstruction method comprises the steps of determining the common data quantity of any two IP nodes in the IP node network by obtaining an initial binary data matrix in the IP node network, determining the common data matrix according to the common data quantity, then determining a binary data subgraph corresponding to each data according to the initial binary data matrix, obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraph, and reconstructing the network by using the subgraph common data matrix corresponding to each data. In the network reconstruction method, the topology of the IP node network is reconstructed from local to global by fully utilizing the correlation among the nodes, the difficulty of acquiring data is greatly reduced, in addition, the influence of each piece of data on the network structure is fully utilized, the accuracy of network topology reconstruction is improved, and the calculation complexity is lower.
For step 102, in one embodiment, discrete data in a preset IP node network is obtained, and an initial binary data matrix is constructed according to the discrete data.
Discrete data is network data in which there is only a correlation between IP nodes, but there is no correlation between data in time.
For example, an initial binary data matrix for a network of 16 data 8 nodes
The following were used:
wherein:
line number: is the amount of data in the IP node network.
The number of columns: is the number of nodes in the IP node network.
For step 106, in one embodiment. And determining a binary data subgraph according to the column number corresponding to the position with the receiving state of 1 in each row in the binary data matrix.
A binary data subgraph: the IP node set is a set of IP nodes that receive data, that is, a set of nodes whose data receiving status is 1 when the IP node receives the data.
For example, based on an initial binary data matrix
Determining a binary data subgraph of first data:
wherein
Is an IP node.
For step 108, in one example. And extracting data from the common data matrix by taking the column number as row and column data according to the column number corresponding to the element in the binary data subgraph corresponding to each data to obtain a subgraph common data matrix corresponding to each data.
The elements in the common data matrix represent the amount of common data for any two IP nodes in the IP node network.
The subgraph common data matrix is a matrix formed by data extracted from the common data matrix according to the binary data subgraph and is a submatrix of the common data matrix.
The column number of the binary data matrix corresponding to the element in the binary data subgraph is the number of the IP node, the data at the corresponding position is extracted from the common data matrix by taking the number as the row number and the column number respectively, and the data are taken as the element to form the common data matrix of the subgraph.
For example, given a binary data map
(wherein:
a collection of nodes in the diagram is represented,
representing a set of states for each node in the graph) and a graph data matrix
The common data matrix is:
for example, the subgraph common data matrix corresponding to data 1 is as follows:
for step 110, in one example. And searching the maximum common data for each row of the subgraph common data matrix corresponding to each data.
And when the maximum common data is one, connecting edges of the two IP nodes corresponding to the maximum common data position to obtain a reconstructed subgraph.
And when the maximum common data is more than one, sequentially connecting edges of the two IP nodes corresponding to each maximum common data position to obtain subgraphs with the same quantity as the maximum common data, performing degree variance calculation on the subgraphs, and taking the subgraphs with small degree variance values as reconstructed subgraphs.
And superposing the reconstruction subgraphs obtained by each datum to obtain a reconstruction network.
In the embodiment, the influence of each piece of data on the network structure is fully utilized through the structure reconstruction method from the local part to the global part, the accuracy of network topology reconstruction is improved, and the calculation complexity is low.
For example, the sub-graph reconstruction process corresponding to data 1 is shown in fig. 3:
in a specific embodiment, when the network is reconstructed, the connection edge set and the node set of the reconstructed subgraph corresponding to each piece of data are respectively subjected to logical union operation to obtain the network topology of the reconstructed network.
For example, a reconstructed subgraph corresponding to data 1 and data 2
、
And performing superposition, wherein the subgraph superposition process is as shown in FIG. 4. The subgraph superposition mathematical computation process is as follows:
wherein:
the set of nodes of the reconstructed subgraph corresponds to signal 1.
In another embodiment, when obtaining the subgraph common matrix, the specific steps are as follows:
acquiring discrete data in a preset IP node network, and constructing an initial binary data matrix according to the state of receiving the discrete data by nodes in the IP node network.
The node receiving state in the IP node network comprises 1 and 0, when the receiving state is 1, the data is received, and when the receiving state is 0, the data is not received.
The row number of the binary data matrix represents the number of data, and the column number represents the node number in the IP node network.
And determining a binary data subgraph according to the column number corresponding to the position with the receiving state of 1 in each row in the binary data matrix.
And extracting data from the subgraph common data matrix by taking the column numbers as row and column data according to the column numbers corresponding to the elements in the binary data subgraph corresponding to each data to obtain the subgraph common data matrix corresponding to each data.
In the embodiment, the network data is represented by the receiving states of the discrete data at different nodes, so that the influence of interference data on network topology reconstruction is reduced.
The following description is given of the advantageous effects of the present invention with reference to a specific example:
the Positive Rate (TPR: True Positive Rate) and the False Positive Rate (FPR: False Positive Rate) will be used to measure the accuracy and error of the network reconstruction. The higher the TPR value, the smaller the FPR value, and the higher the accuracy of the network reconstruction. TPR = TP/(TP + FN), FPR = FP/(FP + TN), where TP, FN, FP and TN represent true positive, false negative, false positive and true negative, respectively.
The network reconfiguration experiments are carried out on the WS network, the BA network and the ER network with different node numbers by using the proposed network reconfiguration algorithm, and the specific information of the networks is shown in Table 1. Fig. 5 and 6 are simulation experiment results of the WS network, fig. 7 and 8 are simulation experiment results of the WS network, and fig. 9 is simulation experiment results of the ER network. As can be seen from fig. 5 to 9, as the amount of data increases, the TPR of the network reconstruction gradually increases and finally reaches 1, and the FPR of the network reconstruction is substantially maintained around 0. Experiments in three different structure networks can prove that the proposed algorithm can accurately reconstruct the topological structure of the network.
Watch (A)
Basic topological characteristics of three types of networks
It is also found that as the number of network nodes increases, the amount of data required to achieve a TPR index of 1 also increases, since the number of network edges increases as the number of nodes increases. In order to compare the reconstruction of different types of networks with the same data volume, we performed corresponding experimental comparisons, and the results are shown in fig. 10.
As can be seen from fig. 10, the reconstruction results of the WS network and the BA network with the same number of nodes have higher similarity, while the reconstruction results of the ER network with the same number of nodes have larger difference from the WS network and the BA network, as can be seen from table 1, the WS network and the BA network with the same number of nodes have similar number of edges, and the number of edges of the ER network corresponding to the same number of nodes is greatly different from the WS network and the BA network. It can thus be seen that the algorithm herein has a similar effect on networks with similar numbers of edges and nodes.
As can be seen from fig. 11, in the WS network, when the number of network nodes is small (100-. As can be seen from fig. 12, in the BA network, under the same data amount, the network reconstruction effect gradually decreases as the network average value increases, and the reconstruction effects of the three average values are less similar. As can be seen from fig. 13, in ER networks with different node sizes, the difference of network reconstruction effects is small.
It should be understood that although the various steps in the flow charts of fig. 1-2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 14, there is provided a network reconfiguration device including: the device comprises a data acquisition module, a subgraph common data matrix determination module, a binary data subgraph determination module, a subgraph common data matrix determination module and a network reconstruction module, wherein:
the data acquisition module is used for acquiring an initial binary data matrix in a preset IP node network; the elements in the initial binary data matrix represent the data reception status of whether the IP node receives data.
The subgraph common data matrix determining module is used for determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state and determining a common data matrix according to the common data quantity; the elements in the subgraph common data matrix represent the common data quantity of any two IP nodes.
And the binary data subgraph determining module is used for determining a binary data subgraph corresponding to each data according to the data receiving state.
And the subgraph common data matrix determining module is used for obtaining a subgraph common data matrix corresponding to each datum according to the subgraph common data matrix and the binary data subgraphs.
And the network reconstruction module is used for reconstructing a network by using the subgraph common data matrix corresponding to each datum.
In one embodiment, the data obtaining module is further configured to obtain discrete data in a preset IP node network, and construct an initial binary data matrix according to the discrete data.
In one embodiment, the binary data subgraph determining module is further configured to, through a preset receiving state, indicate that data is received when the receiving state is 1, and indicate that data is not received when the receiving state is 0; the row number of the binary data matrix represents the number of data, and the column number represents the node number in the IP node network; and determining a binary data subgraph according to the column number corresponding to the position with the receiving state of 1 in each row in the binary data matrix.
In one embodiment, the subgraph common data matrix determining module is further configured to extract data from the subgraph common data matrix to obtain the subgraph common data matrix corresponding to each data, with the column numbers as row and column data, according to the column numbers corresponding to the elements in the binary data subgraph corresponding to each data.
In one embodiment, the network reconfiguration module is further configured to search for the maximum common data for each row of the sub-graph common data matrix corresponding to each data; when the maximum common data is one, connecting edges of two IP nodes corresponding to the maximum common data position to obtain a reconstructed sub-graph; when the maximum common data is larger than one, sequentially connecting edges of two IP nodes corresponding to each maximum common data position to obtain subgraphs with the same quantity as the maximum common data, performing degree variance calculation on the subgraphs, and taking the subgraphs with small degree variance values as reconstructed subgraphs; and superposing the reconstruction subgraphs obtained by each datum to obtain a reconstruction network.
In one embodiment, the network reconstruction module is further configured to perform logical and operation on the edge set and the node set of the reconstruction subgraph corresponding to each piece of data to obtain a network topology of the reconstruction network.
For specific limitations of the network reconfiguration device, reference may be made to the above limitations of the network reconfiguration method, which is not described herein again. The modules in the network reconfiguration device described above may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 15. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store network topology data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a network reconfiguration method.
Those skilled in the art will appreciate that the architecture shown in fig. 15 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, there is provided a computer device comprising a memory storing a computer program and a processor implementing the following steps when the processor executes the computer program:
102, acquiring an initial binary data matrix in a preset IP node network; elements in the initial binary data matrix represent the data receiving state of whether the IP node receives the data;
104, determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity; the elements in the subgraph common data matrix represent the common data quantity of any two IP nodes.
And step 106, determining a binary data subgraph corresponding to each data according to the data receiving state.
And step 108, obtaining a subgraph common data matrix corresponding to each datum according to the subgraph common data matrix and the binary data subgraphs.
And step 110, carrying out network reconstruction on the subgraph common data matrix corresponding to each datum.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
in one embodiment, discrete data in a preset IP node network are obtained, and an initial binary data matrix is constructed according to the discrete data.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and determining a binary data subgraph according to the column number corresponding to the position with the receiving state of 1 in each row in the binary data matrix.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and extracting data from the common data matrix by taking the column number as row and column data according to the column number corresponding to the element in the binary data subgraph corresponding to each data to obtain a subgraph common data matrix corresponding to each data.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and searching the maximum common data for each row of the subgraph common data matrix corresponding to each data.
And when the maximum common data is one, connecting edges of the two IP nodes corresponding to the maximum common data position to obtain a reconstructed subgraph.
And when the maximum common data is more than one, sequentially connecting edges of the two IP nodes corresponding to each maximum common data position to obtain subgraphs with the same quantity as the maximum common data, performing degree variance calculation on the subgraphs, and taking the subgraphs with small degree variance values as reconstructed subgraphs.
And superposing the reconstruction subgraphs obtained by each datum to obtain a reconstruction network.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and respectively carrying out logical union operation on the connecting edge set and the node set of the reconstruction subgraph corresponding to each datum to obtain the network topology of the reconstruction network.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
102, acquiring an initial binary data matrix in a preset IP node network; the elements in the initial binary data matrix represent the data reception status of whether the IP node receives data.
104, determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity; the elements in the subgraph common data matrix represent the common data quantity of any two IP nodes.
And step 106, determining a binary data subgraph corresponding to each data according to the data receiving state.
And step 108, obtaining a subgraph common data matrix corresponding to each datum according to the subgraph common data matrix and the binary data subgraphs.
And step 110, carrying out network reconstruction on the subgraph common data matrix corresponding to each datum.
In one embodiment, the computer program when executed by the processor further performs the steps of:
in one embodiment, discrete data in a preset IP node network are obtained, and an initial binary data matrix is constructed according to the discrete data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and determining a binary data subgraph according to the column number corresponding to the position with the receiving state of 1 in each row in the binary data matrix.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and extracting data from the common data matrix by taking the column number as row and column data according to the column number corresponding to the element in the binary data subgraph corresponding to each data to obtain a subgraph common data matrix corresponding to each data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and searching the maximum common data for each row of the subgraph common data matrix corresponding to each data.
And when the maximum common data is one, connecting edges of the two IP nodes corresponding to the maximum common data position to obtain a reconstructed subgraph.
And when the maximum common data is more than one, sequentially connecting edges of the two IP nodes corresponding to each maximum common data position to obtain subgraphs with the same quantity as the maximum common data, performing degree variance calculation on the subgraphs, and taking the subgraphs with small degree variance values as reconstructed subgraphs.
And superposing the reconstruction subgraphs obtained by each datum to obtain a reconstruction network.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and respectively carrying out logical union operation on the connecting edge set and the node set of the reconstruction subgraph corresponding to each datum to obtain the network topology of the reconstruction network.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (9)
1. A method for network reconfiguration, the method comprising:
acquiring an initial binary data matrix in a preset IP node network; elements in the initial binary data matrix represent a data receiving state whether the IP node receives data or not;
determining the common data quantity of any two IP nodes in the IP node network according to the data receiving state, and determining a common data matrix according to the common data quantity; elements in the common data matrix represent the common data quantity of any two IP nodes;
determining a binary data subgraph corresponding to each data according to the data receiving state;
obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraph;
and reconstructing a network by using the subgraph common data matrix corresponding to each datum.
2. The method of claim 1, wherein obtaining an initial binary data matrix in a network of preset IP nodes comprises:
acquiring discrete data in a preset IP node network, and constructing an initial binary data matrix according to the discrete data.
3. The method of claim 1, wherein the receiving status comprises 1 and 0, and wherein the receiving status is 1 to indicate that data is received, and the receiving status is 0 to indicate that data is not received; the row number of the binary data matrix represents the number of data, and the column number represents the node number in the IP node network;
determining a binary data subgraph corresponding to each data according to the data receiving state, wherein the determination comprises the following steps:
and determining the binary data subgraph according to the column number corresponding to the position with the receiving state of 1 in each row in the binary data matrix.
4. The method of claim 3, wherein obtaining a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraph comprises:
and extracting data from the common data matrix by taking the column numbers as row and column basis according to the column numbers corresponding to the elements in the binary data subgraph corresponding to each data to obtain a subgraph common data matrix corresponding to each data.
5. The method of claim 1, wherein reconstructing the network from the subgraph common data matrix corresponding to each piece of data comprises:
searching the maximum common data for each row of the subgraph common data matrix corresponding to each data;
when the maximum common data is one, connecting edges of two IP nodes corresponding to the maximum common data position to obtain a reconstructed sub-graph;
when the maximum common data is larger than one, sequentially connecting edges of two IP nodes corresponding to each maximum common data position to obtain subgraphs with the same number as the maximum common data, performing degree variance calculation on the subgraphs, and determining the subgraphs with small degree variance values as the reconstructed subgraphs;
and superposing the reconstruction subgraph obtained by each datum to obtain a reconstruction network.
6. The method of claim 5, wherein superimposing the reconstructed subgraph from each data to obtain the reconstructed network comprises:
and respectively carrying out logical union operation on the connecting edge set and the node set of the reconstruction subgraph corresponding to each datum to obtain the network topology of the reconstruction network.
7. An apparatus for network reconfiguration, the apparatus comprising:
the data acquisition module is used for acquiring an initial binary data matrix in a preset IP node network; elements in the initial binary data matrix represent a data receiving state whether the IP node receives data or not;
a common data matrix determining module, configured to determine, according to the data receiving state, a common data quantity of any two IP nodes in the IP node network, and determine, according to the common data quantity, a common data matrix; elements in the common data matrix represent the common data quantity of any two IP nodes;
a binary data subgraph determining module, configured to determine a binary data subgraph corresponding to each data according to the data receiving state;
a subgraph common data matrix determining module, configured to obtain a subgraph common data matrix corresponding to each data according to the common data matrix and the binary data subgraph;
and the network reconstruction module is used for reconstructing a network by using the subgraph common data matrix corresponding to each datum.
8. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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