Dynamic attribution processing method and device of network node, equipment and medium

Abstract

The embodiment of the invention provides a dynamic affiliation processing method and device for a network node, equipment and a medium, and the method can accurately affiliate the network node to a corresponding segmented network through a segmented network center node of at least one segmented network and first index information of a plurality of network nodes. Network resources can be distributed and managed more effectively, so that the operation efficiency of the whole network system is improved, and accurate network node affiliation is realized; according to the invention, the segmented network center node of the segmented network is used as a reference for attributing the network node to the segmented network, and the first index information of the network node can be used as a basis for dividing the network node to be attributed to the segmented network, so that the network node can be attributed to the appropriate segmented network more accurately.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device, equipment and medium for processing dynamic attribution of network nodes. Background Art

[0002] In order to meet the growing communication needs, mobile ad hoc networks are generally used to achieve communication between multiple devices. In mobile ad hoc networks, the dynamic change of network topology caused by the movement of network nodes is the main factor for performance degradation and limited scale expansion; the existing segmented routing method cannot accurately allocate network nodes, which reduces the operating efficiency of the mobile network. Summary of the invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide a method, apparatus, device and medium for dynamic attribution processing of network nodes that overcome the above problems or at least partially solve the above problems.

[0004] In order to solve the above problem, an embodiment of the present invention discloses a method for processing dynamic attribution of a network node, the method comprising:

[0005] Obtaining first indicator information of multiple network nodes;

[0006] According to the first indicator information, the multiple network nodes are respectively matched with the segmented network center node of at least one segmented network, and the segmented networks to which the multiple network nodes belong are respectively determined according to the matching results.

[0007] Optionally, matching the multiple network nodes with the segmented network center node of at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the multiple network nodes belong respectively according to the matching results, includes:

[0008] Determine first spatial coordinates of the plurality of network nodes in the multi-dimensional virtual space, where the first spatial coordinates are obtained by mapping first indicator information of the network nodes to the multi-dimensional virtual space;

[0009] respectively determining distances between first spatial coordinates of the plurality of network nodes and second spatial coordinates of a segmented network center node of at least one segmented network in a multi-dimensional virtual space;

[0010] Determine a network node matching the segment network center node according to the distance, and determine the matching network node as a segment network node of the at least one segment network;

[0011] The network nodes other than the segment network node among the plurality of network nodes are regarded as mobile network nodes, and the segment network to which the mobile network node belongs is determined.

[0012] Optionally, determining a network node matching the segmented network center node according to the distance includes:

[0013] The network node whose distance does not exceed a set threshold is determined as a network node matching the segment network center node.

[0014] Optionally, the first indicator information includes at least one of initial capability information and actual capability information.

[0015] Optionally, the initial capability information includes at least one of a physical distance and a moving frequency, the actual capability information includes at least one of a number of hops, delay information, an energy consumption value, and a signal strength, and the determining the first spatial coordinates of the plurality of network nodes in the multidimensional virtual space includes:

[0016] Mapping at least one of the physical distance, the moving frequency, the number of hops, the delay information, the energy consumption value, and the signal strength into a dimension of a multi-dimensional virtual space;

[0017] Determine the coordinate values ​​of the multiple network nodes mapped to corresponding dimensions in the multidimensional virtual space based on at least one of the physical distance, the moving frequency, the number of hops, the delay information, the energy consumption value, and the signal strength, and obtain the first spatial coordinates of the multiple network nodes in the multidimensional virtual space.

[0018] Optionally, determining the coordinate values ​​of the plurality of network nodes mapped to corresponding dimensions in the multi-dimensional virtual space according to at least one of the physical distance, the moving frequency, the number of hops, the delay information, the energy consumption value, and the signal strength, respectively, includes:

[0019] Determining coordinate values ​​of the plurality of network nodes mapped to a first dimension in a multi-dimensional virtual space according to the hop count;

[0020] Determine, based on the delay information, coordinate values ​​of a plurality of network nodes mapped to a second dimension in the multi-dimensional virtual space;

[0021] Determining coordinate values ​​of the plurality of network nodes mapped to a third dimension in the multi-dimensional virtual space according to the physical distance;

[0022] Determining coordinate values ​​of the plurality of network nodes mapped to a fourth dimension in the multi-dimensional virtual space according to the energy consumption value;

[0023] According to the movement frequency, coordinate values ​​of the plurality of network nodes mapped to a fifth dimension in the multi-dimensional virtual space are determined.

[0024] Optionally, determining, according to the hop count, coordinate values ​​of the plurality of network nodes mapped to a first dimension in the multi-dimensional virtual space includes:

[0025] Determining a hop count average and a hop count standard deviation of the hop count;

[0026] Determine coordinate values ​​of the plurality of network nodes mapped to a first dimension in a multidimensional space according to the hop count, the hop count average, and the hop count standard deviation;

[0027] Determining, according to the delay information, coordinate values ​​of the plurality of network nodes mapped to a second dimension in the multi-dimensional virtual space, comprising:

[0028] Determine a delay information average value and a delay information standard deviation of the delay information;

[0029] Determining coordinate values ​​of the plurality of network nodes mapped to a second dimension in the multidimensional space according to the delay information, the average value of the delay information and the standard deviation of the delay information;

[0030] The determining, according to the physical distance, a coordinate value of the mobile network node mapped to a third dimension in the multi-dimensional virtual space includes:

[0031] determining a physical distance mean and a physical distance standard deviation of the physical distances;

[0032] Determine coordinate values ​​of the plurality of network nodes mapped to a third dimension in the multidimensional space according to the physical distance, the average physical distance, and the standard deviation of the physical distance;

[0033] The step of determining, according to the energy consumption value, a coordinate value of the mobile network node mapped to a fourth dimension in the multi-dimensional virtual space includes:

[0034] Determine an energy consumption value average and an energy consumption value standard deviation of the energy consumption values;

[0035] Determining coordinate values ​​of the plurality of network nodes mapped to a fourth dimension in the multi-dimensional virtual space according to the energy consumption value, the average value of the energy consumption value and the standard deviation of the energy consumption value;

[0036] The step of determining, according to the movement frequency, a coordinate value of the mobile network node mapped to a fifth dimension in the multi-dimensional virtual space includes:

[0037] determining a moving frequency mean and a moving frequency standard deviation of the moving frequency;

[0038] According to the movement frequency, the movement frequency average value and the movement frequency standard deviation, the coordinate values ​​of the plurality of network nodes mapped to the fifth dimension in the multi-dimensional virtual space are determined.

[0039] Optionally, it also includes:

[0040] After determining the segmented networks to which the multiple network nodes belong, re-determine the segmented network center node of the at least one segmented network based on the network nodes in the at least one segmented network, and return to the step of matching the multiple network nodes with the segmented network center node of the at least one segmented network according to the first indicator information, and determining the segmented networks to which the multiple network nodes belong according to the matching results, until the preset conditions are met.

[0041] Optionally, after determining the segmented networks to which the multiple network nodes belong, re-determining the segmented network center node of the at least one segmented network according to the network nodes in the at least one segmented network includes:

[0042] After determining the segmented networks to which the multiple network nodes belong, the average values ​​of the first spatial coordinates of each network node in the at least one segmented network in the multi-dimensional virtual space are determined respectively to obtain the segmented network center node of the at least one segmented network.

[0043] Optionally, matching the multiple network nodes with the segmented network center node of at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the multiple network nodes belong respectively according to the matching results, includes:

[0044] Obtaining an initial segmented network center node of at least one segmented network;

[0045] According to the first indicator information, the multiple network nodes are matched with an initial segmented network center node of at least one segmented network respectively, and the segmented networks to which the multiple network nodes belong are determined respectively according to the matching results.

[0046] Optionally, obtaining an initial segmented network center node of at least one segmented network includes:

[0047] Acquire first spatial coordinates of the plurality of network nodes in the multi-dimensional virtual space;

[0048] The first spatial coordinate corresponding to at least one network node among the multiple network nodes is used as an initial segmented network center node of at least one segmented network.

[0049] Optionally, matching the multiple network nodes with an initial segmented network center node of at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the multiple network nodes belong respectively according to the matching results, includes:

[0050] Determining at least one segmented network based on distances of the plurality of network nodes to the at least one initial segmented network center node;

[0051] According to the at least one segmented network, respectively determine the segmented networks to which the plurality of network nodes belong;

[0052] The segmented networks correspond one-to-one to the central nodes of the initial segmented network, and the distance between the network nodes included in at least one segmented network and the corresponding central node of the initial segmented network is less than a preset distance threshold.

[0053] Optionally, the preset condition includes that the distance between the segmented network center node determined last time and the segmented network center node determined this time is less than a preset threshold.

[0054] The present invention also discloses a dynamic attribution processing device for a network node, the device comprising:

[0055] An acquisition module, used to acquire first indicator information of multiple network nodes;

[0056] A determination module is used to match the multiple network nodes with the segmented network center node of at least one segmented network according to the first indicator information, and determine the segmented networks to which the multiple network nodes belong according to the matching results.

[0057] The present invention also discloses an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of the dynamic attribution processing method of the network node as described above are implemented.

[0058] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the dynamic attribution processing method of the network node as described above are implemented.

[0059] The embodiments of the present invention include the following advantages:

[0060] The present invention can accurately attribute network nodes to corresponding segmented networks through the first indicator information of the segmented network center node and multiple network nodes of at least one segmented network, and can more effectively allocate and manage network resources, thereby improving the operating efficiency of the entire network system. Through accurate network node attribution, the traffic and load in the network can be better predicted and controlled, which helps to improve the stability and reliability of the network. In the present invention, the segmented network center node of the segmented network is used as a reference for attributing network nodes to the segmented network, and the first indicator information of the network node can be used as a basis for dividing the network nodes into segmented networks, so that the network nodes can be more accurately attributed to the appropriate segmented network. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 is a flowchart of the steps of a method for assigning a network node to a network provided by an embodiment of the present invention;

[0062] Figure 2 It is a structural block diagram of a home device of a network node provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0064] One of the core concepts of the embodiments of the present invention is that the present invention can accurately attribute network nodes to corresponding segmented networks through the segmented network center node of at least one segmented network and the first indicator information of multiple network nodes, and can more effectively allocate and manage network resources, thereby improving the operating efficiency of the entire network system. Through accurate network node attribution, the traffic and load in the network can be better predicted and controlled, which helps to improve the stability and reliability of the network. In the present invention, the segmented network center node of the segmented network is used as a reference for attributing network nodes to the segmented network, and the first indicator information of the network node can be used as a basis for dividing the network nodes into segmented networks, so that the network nodes can be more accurately attributed to the appropriate segmented network.

[0065] Reference Figure 1 , shows a flowchart of a method for assigning a network node to a network provided by an embodiment of the present invention. The method may specifically include the following steps:

[0066] Step 101: Obtain first indicator information of multiple network nodes.

[0067] In an embodiment of the present invention, the first indicator information is used to indicate a series of parameters set by the network node in a mobile ad hoc network or other dynamic network environment, which may include the following aspects, such as connection quality indicators: such as signal strength, link stability, data transmission rate, etc.; security indicators: such as encryption strength, authentication mechanism, intrusion detection; service quality indicators: such as delay, jitter, packet loss rate; mobility indicators: such as network node speed, direction, predicted path, etc.; network load indicators: current network bandwidth usage, traffic distribution between network nodes, etc., and no specific one is limited here.

[0068] Step 102: According to the first indicator information, the plurality of network nodes are matched with the segmented network center node of at least one segmented network respectively, and the segmented networks to which the plurality of network nodes belong are determined respectively according to the matching results.

[0069] In an embodiment of the present invention, the segmented network center node is determined by the network centroid of the segmented network, that is, the network node closest to the network centroid among each network node. After obtaining the first indicator information of multiple network nodes, the multiple network nodes can be matched with the segmented network center node of at least one segmented network respectively to obtain matching results, and then the segmented networks to which the multiple network nodes belong are determined respectively according to the matching results.

[0070] In one embodiment of the present invention, multiple network nodes are matched with a segmented network center node of at least one segmented network according to first indicator information, and the segmented networks to which the multiple network nodes belong are determined according to the matching results, including: determining the first spatial coordinates of the multiple network nodes in a multidimensional virtual space, the first spatial coordinates being obtained by mapping the first indicator information of the network nodes to the multidimensional virtual space; respectively determining the distances between the first spatial coordinates of the multiple network nodes and the second spatial coordinates of the segmented network center node of at least one segmented network in the multidimensional virtual space; determining a network node that matches the segmented network center node according to the distance, and determining the matched network node as a segmented network node of at least one segmented network; treating network nodes other than the segmented network nodes among the multiple network nodes as mobile network nodes, and determining the segmented network to which the mobile network nodes belong.

[0071] In an embodiment of the present invention, each network node can define a multi-dimensional virtual space, in which each dimension corresponds to a preset indicator, and then map the first indicator information of the network node to each dimension of the multi-dimensional virtual space, so as to determine the specific position of the network node in the space. The position of the network node in the multi-dimensional virtual space can intuitively represent its current network status and performance. Network administrators or automation systems can use these spatial coordinates to optimize the network, for example, by adjusting the position of the network node to improve the network topology, or by analyzing the distribution of the network nodes in space to predict and avoid network congestion.

[0072] The first spatial coordinates of the plurality of network nodes in the multi-dimensional virtual space may be determined according to the first indicator information of the plurality of network nodes, and then the distances between the plurality of network nodes and the segmented network center node of the segmented network in the multi-dimensional virtual space may be calculated according to the first spatial coordinates of the plurality of network nodes and the second spatial coordinates of the segmented network center node in the multi-dimensional virtual space, as shown in formula (1):

[0073]

[0074] Among them, w j is the weight coefficient of the jth feature parameter, x ij is the jth characteristic parameter of the ith network node, C j is the value of the jth characteristic parameter of the segmented network center node coordinate.

[0075] In one example, there are 10 network nodes and 3 segmented network center nodes. That is, the weighted distance from each network node to the segmented network center node can be calculated according to formula (1), and then the network nodes are sorted from small to large according to the weighted distance, and then the network nodes with lower movement frequency are selected from the sorted list as segmented network nodes.

[0076] Further, after determining the segmented network nodes, network nodes other than the segmented network nodes among the multiple network nodes may be determined as mobile nodes, and then the mobile nodes may be allocated to the respective segmented network nodes according to the distances between the mobile nodes and the segmented network nodes.

[0077] In an embodiment of the present invention, determining a network node that matches a segmented network center node based on a distance includes: determining a network node whose distance does not exceed a set threshold as a network node that matches the segmented network center node.

[0078] In an embodiment of the present invention, after calculating the distances between multiple network nodes and the central node of the segmented network respectively, the network nodes whose distances do not exceed a set threshold among the multiple distances can be determined as network nodes matching the central node of the segmented network, that is, segmented network nodes of at least one segmented network.

[0079] In an embodiment of the present invention, the first indicator information includes at least one of initial capability information and actual capability information.

[0080] In the embodiment of the present invention, the initial capability information of the network node generally refers to the inherent performance or function of the network node when the network is deployed or started, and the actual capability information refers to the performance or function exhibited by the network node during actual operation.

[0081] In one embodiment of the present invention, the initial capability information includes at least one of physical distance and moving frequency, the actual capability information includes at least one of number of hops, delay information, energy consumption value, and signal strength, and the first spatial coordinates of multiple network nodes in the multi-dimensional virtual space are determined, including: mapping at least one of the physical distance, moving frequency, number of hops, delay information, energy consumption value, and signal strength to a dimension of the multi-dimensional virtual space; determining the coordinate values ​​of multiple network nodes mapped to corresponding dimensions in the multi-dimensional virtual space based on at least one of the physical distance, moving frequency, number of hops, delay information, energy consumption value, and signal strength, to obtain the first spatial coordinates of the multiple network nodes in the multi-dimensional virtual space.

[0082] In the embodiment of the present invention, the number of hops refers to the number of intermediate network nodes that a mobile network node needs to pass through to reach a segmented network node. In a multi-dimensional virtual space, the number of hops can be used as the first dimension. The fewer the number of hops, the shorter the path.

[0083] Delay information refers to the time required for a data packet to be transmitted from a mobile network node to a segmented network node. In a multi-dimensional virtual space, delay information can be used as the second dimension to represent the communication delay between network nodes. The lower the delay, the higher the communication efficiency.

[0084] Physical distance refers to the actual geographical distance between a mobile network node and a segmented network node. In a multi-dimensional virtual space, physical distance can be used as the third dimension to represent the actual spatial position relationship between network nodes. The shorter the physical distance, the closer the network nodes are in actual space.

[0085] Energy consumption value refers to the energy consumed by mobile network nodes during the communication process. In the multi-dimensional virtual space, energy consumption can be used as the fourth dimension to represent the energy efficiency of network nodes. The lower the energy consumption, the more economical the energy use of network nodes.

[0086] Mobile frequency refers to the number of times or speed that a mobile network node moves in a unit of time. In a multi-dimensional virtual space, mobile frequency can be used as the fifth dimension to represent the mobility of network nodes. The higher the mobile frequency, the stronger the mobility of the network node.

[0087] Signal strength refers to the power level of the wireless signal transmitted or received by a mobile network node.

[0088] When determining the first spatial coordinates of multiple network nodes in a multidimensional virtual space, at least one of the physical distance, moving frequency, number of hops, delay information, energy consumption value, and signal strength can be first mapped to a dimension of the multidimensional virtual space, thereby forming multiple dimensions. Taking physical distance, moving frequency, number of hops, delay information, and energy consumption value as an example, physical distance, moving frequency, number of hops, delay information, and energy consumption value can be mapped to five dimensions of the multidimensional virtual space, and then the coordinate values ​​of multiple network nodes mapped to the corresponding dimensions in the multidimensional virtual space are determined respectively to obtain the first spatial coordinates of the multiple network nodes in the multidimensional virtual space.

[0089] In one embodiment of the present invention, the coordinate values ​​of multiple network nodes mapped to corresponding dimensions in a multidimensional virtual space are determined based on at least one of physical distance, moving frequency, number of hops, delay information, energy consumption value, and signal strength, including: determining the coordinate values ​​of multiple network nodes mapped to a first dimension in the multidimensional virtual space based on the number of hops; determining the coordinate values ​​of multiple network nodes mapped to a second dimension in the multidimensional virtual space based on the delay information; determining the coordinate values ​​of multiple network nodes mapped to a third dimension in the multidimensional virtual space based on the physical distance; determining the coordinate values ​​of multiple network nodes mapped to a fourth dimension in the multidimensional virtual space based on the energy consumption value; and determining the coordinate values ​​of multiple network nodes mapped to a fifth dimension in the multidimensional virtual space based on the moving frequency.

[0090] In an embodiment of the present invention, the coordinate values ​​of multiple network nodes mapped to the first dimension in the multidimensional virtual space can be determined based on the number of hops, the coordinate values ​​of multiple network nodes mapped to the second dimension in the multidimensional virtual space can be determined based on the delay information, the coordinate values ​​of multiple network nodes mapped to the third dimension in the multidimensional virtual space can be determined based on the physical distance, the coordinate values ​​of multiple network nodes mapped to the fifth dimension in the multidimensional virtual space can be determined based on the energy consumption value, and the coordinate values ​​of multiple network nodes mapped to the fifth dimension in the multidimensional virtual space can be determined based on the movement frequency.

[0091] In one embodiment mode of the present invention, determining coordinate values ​​of a plurality of network nodes mapped to a first dimension in a multidimensional virtual space according to the hop count includes: determining a hop count average and a hop count standard deviation of the hop count; determining coordinate values ​​of a plurality of network nodes mapped to a first dimension in a multidimensional space according to the hop count, the hop count average and the hop count standard deviation;

[0092] In the embodiment of the present invention, for example, there are network nodes a, b, and c, the hop count of network node a is h1, the hop count of network node b is h2, and the hop count of network node c is h3. The average hop count of the network nodes can be calculated as Calculate the standard deviation of the hop count Where hi is the hop count of the i-th network node. After calculating the average hop count and the standard deviation of the hop count, the coordinate values ​​of the first dimension of the network nodes a, b, and c in the multidimensional virtual space can be calculated by formula (2):

[0093]

[0094] Among them, z 1 Refers to the coordinate value of the first dimension.

[0095] Determining coordinate values ​​of a plurality of network nodes mapped to a second dimension in a multidimensional virtual space based on the delay information, including: determining a delay information average value and a delay information standard deviation of the delay information; determining coordinate values ​​of a plurality of network nodes mapped to a second dimension in a multidimensional space based on the delay information, the delay information average value and the delay information standard deviation;

[0096] In the embodiment of the present invention, the delay of network node a is t1, the delay of network node b is t2, and the delay of network node c is t3. The average delay of the network nodes can be calculated as Calculate the delay standard deviation Where ti is the delay from the network node to the i-th network node. After calculating the average delay and the standard deviation of the delay, the coordinate values ​​of the network nodes a, b, and c mapped to the second dimension in the multidimensional virtual space can be calculated by formula (3):

[0097]

[0098] Among them, z 2 Refers to the coordinate value of the second dimension.

[0099] Determining coordinate values ​​of a mobile network node mapped to a third dimension in a multi-dimensional virtual space according to the physical distance, including: determining a physical distance average and a physical distance standard deviation of the physical distance; determining coordinate values ​​of a plurality of network nodes mapped to a third dimension in a multi-dimensional space according to the physical distance, the physical distance average and the physical distance standard deviation;

[0100] In the embodiment of the present invention, the physical distance of network node a is d1, the physical distance of network node b is d2, and the physical distance of network node c is d3. The average value of the physical distances of the network nodes can be calculated as Calculate the standard deviation of physical distance Where di is the physical distance of the i-th segment network node. After calculating the average value and standard deviation of the physical distance, the coordinate values ​​of the network nodes a, b, and c mapped to the third dimension in the multidimensional virtual space can be calculated by formula (4):

[0101]

[0102] Among them, z 3 Refers to the coordinate value of the third dimension.

[0103] According to the energy consumption value, the coordinate value of the mobile network node mapped to the fourth dimension in the multidimensional virtual space is determined, including: determining the average energy consumption value and the standard deviation of the energy consumption value; according to the energy consumption value, the average energy consumption value and the standard deviation of the energy consumption value, determining the coordinate values ​​of multiple network nodes mapped to the fourth dimension in the multidimensional virtual space.

[0104] In the embodiment of the present invention, the energy consumption of network node a is e1, the energy consumption of network node b is e2, and the energy consumption of network node c is e3. The average energy consumption of the network nodes can be calculated as Calculate the standard deviation of energy consumption Where ei is the energy consumption of the i-th segment network node. After calculating the average energy consumption and the standard deviation of energy consumption, the coordinate values ​​of network nodes a, b, and c mapped to the fourth dimension in the multidimensional virtual space can be calculated by formula (5):

[0105]

[0106] Among them, z 4 Refers to the coordinate value of the fourth dimension.

[0107] According to the moving frequency, the coordinate value of the mobile network node mapped to the fifth dimension in the multi-dimensional virtual space is determined, including: determining the moving frequency average and the moving frequency standard deviation of the moving frequency; according to the moving frequency, the moving frequency average and the moving frequency standard deviation, determining the coordinate values ​​of multiple network nodes mapped to the fifth dimension in the multi-dimensional virtual space.

[0108] In the embodiment of the present invention, the frequency of network node a is f1, the frequency of network node b is f2, and the frequency of network node c is f3. The average frequency of the network nodes can be calculated as Calculate the frequency standard deviation Where fi is the frequency of the i-th segment network node. After calculating the frequency mean and frequency standard deviation, the coordinate values ​​of network nodes a, b, and c mapped to the fifth dimension in the multidimensional virtual space can be calculated by formula (6):

[0109]

[0110] Among them, z 5 Refers to the coordinate value of the fifth dimension.

[0111] In one embodiment of the present invention, it also includes: after determining the segmented networks to which multiple network nodes belong, re-determining the segmented network center node of at least one segmented network based on the network nodes in at least one segmented network, and returning to the step of matching the multiple network nodes with the segmented network center node of at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the multiple network nodes belong respectively according to the matching results, until the preset conditions are met.

[0112] In an embodiment of the present invention, after determining the segmented network to which multiple network nodes belong, the segmented network center node of at least one segmented network can be re-determined based on the network nodes in at least one segmented network, and then the segmented network to which the multiple network nodes belong can be determined based on the re-determined segmented network center node and the first indicator information of the multiple network nodes until a preset condition is met. The preset condition can be set according to preset requirements. In one instance, the preset condition can be that the distance between the current segmented network center node and the last determined segmented network center node is less than a preset distance. The present invention can achieve efficient management and optimization of the network by continuously adjusting the segmented network center node and the network node affiliation.

[0113] In one embodiment of the present invention, after determining the segmented network to which multiple network nodes belong, the segmented network center node of at least one segmented network is re-determined based on the network nodes in at least one segmented network, including: after determining the segmented network to which multiple network nodes belong, respectively determining the average value of the first spatial coordinates of each network node in at least one segmented network in the multidimensional virtual space to obtain the segmented network center node of at least one segmented network.

[0114] In an embodiment of the present invention, as shown in Table 1, the first indicator information of multiple network nodes shown in the embodiment of the present invention is shown. The first indicator information may include the number of hops, delay, physical distance, energy consumption value, and mobile frequency. The multiple network nodes are node A, node B, node C, node D, node E, node F, node G, node H, node I, and node J. The specific indicator information of the multiple nodes is shown in Table 1.

[0115]

[0116] Table 1

[0117] After calculation, it can be calculated that the first spatial coordinates of the 10 network nodes mapped to the multi-dimensional virtual space are:

[0118] 'A': [-0.95, -1.19, -1.04, -1.06, 0.14], 'B': [0.32, -0.06, 0.54, 0.51, -1.29], 'C': [-0.32, -0.34 , 0.01, -0.27, 0.86], 'D': [-0.95, -1.37, -1.33, -0.90, 0.58], 'E': [-1.45, -1.48, -1.30, -1.45, 1.5 8], 'F': [-0.32, -0.48, -0.25, -0.66, 0.14], 'G': [1.58, 1.07, 1.06, 0.67, -0.58], 'H': [-0.95, -0. 77, -0.65, -0.86, 0.14], 'I': [0.95, 1.65, 1.59, 1.29, -1.29], 'J': [0.32, 0.23, 0.29, 0.12, 0.86]}.

[0119] Further, after determining the segmented networks to which the multiple network nodes belong, the segmented network center node of at least one segmented network can be obtained according to the average value of the first spatial coordinates of each network node in each segmented network in the multi-dimensional virtual space, for example, segmented network 1 (segmented network center node A): A, E, H, segmented network 2 (segmented network center node D): D, B, I; segmented network 3 (segmented network center node G): G, C, F, J. The segmented network center node can be calculated according to the coordinates of each network node, and the calculation can be performed using formula (7):

[0120]

[0121] Among them, χ i is the first dimension coordinate, α i is the second dimension coordinate, β i is the third dimension coordinate, δ i is the fourth dimension coordinate, γ i is the fifth dimension coordinate.

[0122] Specifically: Segment network center node of segment network 1:

[0123]

[0124] Segment network center node of segment network 2:

[0125]

[0126] Segment network center node of segment network 3:

[0127]

[0128] In one embodiment of the present invention, according to first indicator information, multiple network nodes are respectively matched with a segmented network center node of at least one segmented network, and the segmented networks to which the multiple network nodes belong are respectively determined according to the matching results, including: obtaining an initial segmented network center node of at least one segmented network; according to the first indicator information, multiple network nodes are respectively matched with an initial segmented network center node of at least one segmented network, and the segmented networks to which the multiple network nodes belong are respectively determined according to the matching results.

[0129] In an embodiment of the present invention, for example, there are 10 network nodes. The initial segmented network center node of at least one segmented network can be first obtained from the 10 network nodes, and then the segmented networks to which the multiple network nodes belong can be determined respectively based on the initial segmented network center node of at least one segmented network and the first indicator information of the multiple network nodes.

[0130] In one embodiment of the present invention, obtaining an initial segmented network center node of at least one segmented network includes: obtaining first spatial coordinates of multiple network nodes in a multi-dimensional virtual space; and using the first spatial coordinate corresponding to at least one network node among the multiple network nodes as the initial segmented network center node of at least one segmented network.

[0131] In the embodiment of the present invention, for example, the first spatial coordinates of 10 network nodes mapped to the multi-dimensional virtual space are calculated as follows:

[0132] 'A': [-0.95, -1.19, -1.04, -1.06, 0.14], 'B': [0.32, -0.06, 0.54, 0.51, -1.29], 'C': [-0.32, -0.34 , 0.01, -0.27, 0.86], 'D': [-0.95, -1.37, -1.33, -0.90, 0.58], 'E': [-1.45, -1.48, -1.30, -1.45, 1.5 8], 'F': [-0.32, -0.48, -0.25, -0.66, 0.14], 'G': [1.58, 1.07, 1.06, 0.67, -0.58], 'H': [-0.95, -0. 77, -0.65, -0.86, 0.14], 'I': [0.95, 1.65, 1.59, 1.29, -1.29], 'J': [0.32, 0.23, 0.29, 0.12, 0.86]}.

[0133] You can select any three of the 10 coordinates as the initial segment network center nodes:

[0134] The coordinates of the central node of the segmented network are =

[0135] {'A':[-0.95,-1.19,-1.04,-1.06,0.14],'D':[-0.95,-1.37,-1.33,-0.90,0.58],'G':[1.58,1.07,1.06,0.67,-0.58]}.

[0136] In one embodiment of the present invention, multiple network nodes are matched with an initial segmented network center node of at least one segmented network according to first indicator information, and the segmented networks to which the multiple network nodes belong are determined according to the matching results, including: determining at least one segmented network according to the distances from the multiple network nodes to at least one initial segmented network center node; determining the segmented networks to which the multiple network nodes belong according to at least one segmented network; the segmented networks correspond one-to-one to the initial segmented network center node, and the distance between the network nodes included in at least one segmented network and the corresponding initial segmented network center node is less than a preset distance threshold.

[0137] In an embodiment of the present invention, after determining the initial segmented network center node, the distances from multiple network nodes to at least one initial segmented network center node can be calculated, and then the network nodes among the multiple network nodes whose distances from the initial segmented network center node A are less than a preset distance threshold are divided into the segmented network corresponding to the initial segmented network center node A, the network nodes among the multiple network nodes whose distances from the initial segmented network center node D are less than the preset distance threshold are divided into the segmented network corresponding to the initial segmented network center node D, and the network nodes among the multiple network nodes whose distances from the initial segmented network center node G are less than the preset distance threshold are divided into the segmented network corresponding to the initial segmented network center node G.

[0138] Furthermore, a new segmented network center node can be calculated based on the segmented networks corresponding to the three initial segmented network center nodes until the distance between the new segmented network center node and the previous segmented network center node is less than a preset threshold, and then the segmented network nodes among the multiple network nodes are determined, and the network nodes except the segmented network nodes among the multiple network nodes are used as mobile network nodes, and finally the mobile network nodes are divided into the segmented networks corresponding to each segmented network node.

[0139] The present invention discloses a method for attributing network nodes. The network nodes can be accurately attributed to corresponding segmented networks through the first indicator information of a segmented network center node and multiple network nodes of at least one segmented network. The network resources can be allocated and managed more effectively, thereby improving the operation efficiency of the entire network system. Through accurate network node attribution, the traffic and load in the network can be better predicted and controlled, which helps to improve the stability and reliability of the network. In the present invention, the segmented network center node of the segmented network is used as a reference for attributing the network nodes to the segmented networks, and the first indicator information of the network nodes can be used as a basis for dividing the network nodes into segmented networks, so that the network nodes can be more accurately attributed to appropriate segmented networks.

[0140] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0141] Reference Figure 2 , shows a structural block diagram of a dynamic affiliation processing device for a network node provided by an embodiment of the present invention, and the device may specifically include the following modules:

[0142] An acquisition module 201 is used to acquire first indicator information of multiple network nodes;

[0143] The determination module 202 is used to match the multiple network nodes with the segmented network center node of at least one segmented network according to the first indicator information, and determine the segmented networks to which the multiple network nodes belong according to the matching results.

[0144] The present invention discloses an attribution device for network nodes, which can accurately attribute network nodes to corresponding segmented networks through a segmented network center node of at least one segmented network and first indicator information of multiple network nodes, and can more effectively allocate and manage network resources, thereby improving the operating efficiency of the entire network system. Through accurate network node attribution, the traffic and load in the network can be better predicted and controlled, which helps to improve the stability and reliability of the network. In the present invention, the segmented network center node of the segmented network is used as a reference for attributing network nodes to the segmented network, and the first indicator information of the network node can be used as a basis for dividing the network nodes into segmented networks, so that the network nodes can be more accurately attributed to appropriate segmented networks.

[0145] In an embodiment of the present invention, the determination module 202 may include:

[0146] A first determination submodule is used to determine first spatial coordinates of multiple network nodes in the multi-dimensional virtual space, where the first spatial coordinates are obtained by mapping first indicator information of the network nodes to the multi-dimensional virtual space;

[0147] A second determination submodule, used to respectively determine the distances between the first spatial coordinates of the plurality of network nodes and the second spatial coordinates of the segmented network center node of at least one segmented network in the multi-dimensional virtual space;

[0148] A third determination submodule, configured to determine a network node matching the segmented network center node according to the distance, and determine the matching network node as a segmented network node of at least one segmented network;

[0149] The fourth determining submodule is used to take the network nodes other than the segmented network nodes among the multiple network nodes as mobile network nodes, and determine the segmented network to which the mobile network node belongs.

[0150] In one embodiment of the present invention, the third determining submodule includes:

[0151] The first determining unit is used to determine a network node whose distance does not exceed a set threshold as a network node matching the segment network center node.

[0152] In an embodiment of the present invention, the first indicator information includes at least one of initial capability information and actual capability information.

[0153] In an embodiment of the present invention, the initial capability information includes at least one of a physical distance and a mobile frequency, the actual capability information includes at least one of a number of hops, delay information, an energy consumption value, and a signal strength, and the first determination submodule includes:

[0154] A first mapping unit, configured to map at least one of the physical distance, the moving frequency, the number of hops, the delay information, the energy consumption value, and the signal strength into a dimension of the multi-dimensional virtual space;

[0155] The second mapping unit is used to determine the coordinate values ​​of multiple network nodes mapped to corresponding dimensions in the multi-dimensional virtual space based on at least one of the physical distance, moving frequency, number of hops, delay information, energy consumption value, and signal strength, and obtain the first spatial coordinates of the multiple network nodes in the multi-dimensional virtual space.

[0156] In one embodiment of the present invention, the second mapping unit includes:

[0157] A first mapping subunit, used to determine the coordinate values ​​of the first dimension of the multi-dimensional virtual space mapped to the plurality of network nodes according to the hop count;

[0158] A second mapping subunit, used to determine the coordinate values ​​of the plurality of network nodes mapped to the second dimension in the multi-dimensional virtual space according to the delay information;

[0159] A third mapping subunit, used to determine the coordinate values ​​of the plurality of network nodes mapped to the third dimension in the multi-dimensional virtual space according to the physical distance;

[0160] A fourth mapping subunit, used to determine the coordinate values ​​of the plurality of network nodes mapped to the fourth dimension in the multi-dimensional virtual space according to the energy consumption values;

[0161] The fifth mapping subunit is used to determine the coordinate values ​​of the fifth dimension of the multi-dimensional virtual space mapped to the multiple network nodes according to the movement frequency.

[0162] In one embodiment of the present invention, the first mapping subunit includes:

[0163] A first subunit is used to determine a hop count average and a hop count standard deviation of the hop count;

[0164] A second subunit is used to determine the coordinate values ​​of the first dimension of the multidimensional space mapped to the plurality of network nodes according to the hop count, the hop count average value and the hop count standard deviation;

[0165] The second mapping subunit includes:

[0166] The third unit is used to determine the delay information average value and the delay information standard deviation of the delay information;

[0167] A fourth unit is used to determine the coordinate values ​​of the plurality of network nodes mapped to the second dimension in the multidimensional space according to the delay information, the average value of the delay information and the standard deviation of the delay information;

[0168] The third mapping subunit includes:

[0169] Unit 5, physical distance mean and physical distance standard deviation for determining physical distance;

[0170] A sixth unit is used to determine coordinate values ​​of a plurality of network nodes mapped to a third dimension in the multidimensional space according to the physical distance, the average value of the physical distance and the standard deviation of the physical distance;

[0171] The fourth mapping subunit includes:

[0172] Unit 7, for determining an energy consumption value mean value and an energy consumption value standard deviation;

[0173] An eighth unit is used to determine coordinate values ​​of a plurality of network nodes mapped to a fourth dimension in the multi-dimensional virtual space according to the energy consumption value, the average value of the energy consumption value and the standard deviation of the energy consumption value;

[0174] The fifth mapping subunit includes:

[0175] Unit 9, for determining the moving frequency mean and moving frequency standard deviation;

[0176] The tenth unit is used to determine the coordinate values ​​of the fifth dimension of the multi-dimensional virtual space mapped to the multiple network nodes according to the moving frequency, the moving frequency average value and the moving frequency standard deviation.

[0177] In one embodiment of the present invention, it also includes:

[0178] A loop module is used to, after determining the segmented networks to which multiple network nodes belong, re-determine the segmented network center node of at least one segmented network according to the network nodes in at least one segmented network, and return to the step of matching the multiple network nodes with the segmented network center node of at least one segmented network according to the first indicator information, and determining the segmented networks to which the multiple network nodes belong according to the matching results, until a preset condition is met.

[0179] In one embodiment of the present invention, the circulation module includes:

[0180] The fifth determination submodule is used to determine the average value of the first spatial coordinates of each network node in at least one segmented network in the multi-dimensional virtual space after determining the segmented networks to which multiple network nodes belong, so as to obtain the segmented network center node of at least one segmented network.

[0181] In one embodiment of the present invention, the determining module includes:

[0182] A first acquisition submodule, used to acquire an initial segmented network center node of at least one segmented network;

[0183] The first matching submodule is used to match the multiple network nodes with the initial segmented network center node of at least one segmented network according to the first indicator information, and determine the segmented networks to which the multiple network nodes belong according to the matching results.

[0184] In one embodiment of the present invention, the first acquisition submodule includes:

[0185] A first acquisition unit, used to acquire first spatial coordinates of multiple network nodes in the multi-dimensional virtual space;

[0186] The second determining unit is used to use the first spatial coordinates corresponding to at least one network node among the multiple network nodes as an initial segmented network center node of at least one segmented network.

[0187] In one embodiment of the present invention, the first matching submodule includes:

[0188] A third determining unit, configured to determine at least one segmented network according to distances from a plurality of network nodes to at least one initial segmented network center node;

[0189] The fourth determination unit is used to determine the segmented networks to which multiple network nodes belong based on at least one segmented network; the segmented networks correspond one-to-one to the central nodes of the initial segmented network, and the distance between the network nodes included in at least one segmented network and the corresponding central node of the initial segmented network is less than a preset distance threshold.

[0190] In an embodiment of the present invention, the preset condition includes that the distance between the segment network center node determined last time and the segment network center node determined this time is less than a preset threshold.

[0191] The present invention discloses an attribution device for network nodes, which can accurately attribute network nodes to corresponding segmented networks through a segmented network center node of at least one segmented network and first indicator information of multiple network nodes, and can more effectively allocate and manage network resources, thereby improving the operating efficiency of the entire network system. Through accurate network node attribution, the traffic and load in the network can be better predicted and controlled, which helps to improve the stability and reliability of the network. In the present invention, the segmented network center node of the segmented network is used as a reference for attributing network nodes to the segmented network, and the first indicator information of the network node can be used as a basis for dividing the network nodes into segmented networks, so that the network nodes can be more accurately attributed to appropriate segmented networks.

[0192] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0193] An embodiment of the present invention further provides an electronic device, including:

[0194] It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, each process of the above-mentioned dynamic attribution processing method embodiment of the network node is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0195] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned dynamic affiliation processing method embodiment of the network node are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0196] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0197] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0198] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0199] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0200] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0201] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0202] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0203] The above is a detailed introduction to the dynamic attribution processing method, device, equipment and storage medium of a network node provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for processing dynamic attribution of network nodes, characterized in that: The method comprises: Obtaining first indicator information of multiple network nodes; According to the first indicator information, the multiple network nodes are respectively matched with the segmented network center node of at least one segmented network, and the segmented networks to which the multiple network nodes belong are respectively determined according to the matching results.

2. The method according to claim 1, characterized in that: The step of matching the plurality of network nodes with a segmented network center node of at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the plurality of network nodes belong respectively according to the matching results, includes: Determine first spatial coordinates of the plurality of network nodes in the multi-dimensional virtual space, where the first spatial coordinates are obtained by mapping first indicator information of the network nodes to the multi-dimensional virtual space; respectively determining distances between first spatial coordinates of the plurality of network nodes and second spatial coordinates of a segmented network center node of at least one segmented network in a multi-dimensional virtual space; Determine a network node matching the segment network center node according to the distance, and determine the matching network node as a segment network node of the at least one segment network; The network nodes other than the segment network node among the plurality of network nodes are regarded as mobile network nodes, and the segment network to which the mobile network node belongs is determined.

3. The method according to claim 2, characterized in that The determining, according to the distance, a network node matching the segmented network center node comprises: The network node whose distance does not exceed a set threshold is determined as a network node matching the segment network center node.

4. The method according to any one of claims 1 to 3, characterized in that The first indicator information includes at least one of initial capability information and actual capability information.

5. The method according to claim 4, characterized in that The initial capability information includes at least one of a physical distance and a moving frequency, the actual capability information includes at least one of a number of hops, delay information, an energy consumption value, and a signal strength, and the determining of first spatial coordinates of the plurality of network nodes in the multi-dimensional virtual space includes: Mapping at least one of the physical distance, the moving frequency, the number of hops, the delay information, the energy consumption value, and the signal strength into a dimension of a multi-dimensional virtual space; Determine the coordinate values ​​of the multiple network nodes mapped to corresponding dimensions in the multidimensional virtual space based on at least one of the physical distance, the moving frequency, the number of hops, the delay information, the energy consumption value, and the signal strength, and obtain the first spatial coordinates of the multiple network nodes in the multidimensional virtual space.

6. The method according to claim 5, characterized in that The determining, based on at least one of the physical distance, the moving frequency, the number of hops, the delay information, the energy consumption value, and the signal strength, coordinate values ​​of the plurality of network nodes mapped to corresponding dimensions in the multi-dimensional virtual space comprises: Determining coordinate values ​​of the plurality of network nodes mapped to a first dimension in a multi-dimensional virtual space according to the hop count; Determine, based on the delay information, coordinate values ​​of a plurality of network nodes mapped to a second dimension in the multi-dimensional virtual space; Determining coordinate values ​​of the plurality of network nodes mapped to a third dimension in the multi-dimensional virtual space according to the physical distance; Determining coordinate values ​​of the plurality of network nodes mapped to a fourth dimension in the multi-dimensional virtual space according to the energy consumption values; According to the movement frequency, coordinate values ​​of the plurality of network nodes mapped to a fifth dimension in the multi-dimensional virtual space are determined.

7. The method according to claim 6, characterized in that The step of determining, according to the hop count, coordinate values ​​of the plurality of network nodes mapped to a first dimension in the multi-dimensional virtual space includes: Determining a hop count average and a hop count standard deviation of the hop count; Determine coordinate values ​​of the plurality of network nodes mapped to a first dimension in a multidimensional space according to the hop count, the hop count average, and the hop count standard deviation; Determining, according to the delay information, coordinate values ​​of the plurality of network nodes mapped to a second dimension in the multi-dimensional virtual space, comprising: Determine a delay information average value and a delay information standard deviation of the delay information; Determining coordinate values ​​of the plurality of network nodes mapped to a second dimension in the multidimensional space according to the delay information, the average value of the delay information and the standard deviation of the delay information; The determining, according to the physical distance, a coordinate value of the mobile network node mapped to a third dimension in the multi-dimensional virtual space includes: determining a physical distance mean and a physical distance standard deviation of the physical distances; Determine coordinate values ​​of the plurality of network nodes mapped to a third dimension in the multidimensional space according to the physical distance, the average physical distance, and the standard deviation of the physical distance; The step of determining, according to the energy consumption value, a coordinate value of the mobile network node mapped to a fourth dimension in the multi-dimensional virtual space includes: Determine an energy consumption value average and an energy consumption value standard deviation of the energy consumption values; Determine, according to the energy consumption value, the average value of the energy consumption value and the standard deviation of the energy consumption value, the coordinate values ​​of the plurality of network nodes mapped to the fourth dimension in the multi-dimensional virtual space; The step of determining, according to the movement frequency, a coordinate value of the mobile network node mapped to a fifth dimension in the multi-dimensional virtual space includes: determining a moving frequency mean and a moving frequency standard deviation of the moving frequency; According to the movement frequency, the movement frequency average value and the movement frequency standard deviation, the coordinate values ​​of the plurality of network nodes mapped to the fifth dimension in the multi-dimensional virtual space are determined.

8. The method according to claim 2, characterized in that: Also includes: After determining the segmented networks to which the multiple network nodes belong, re-determine the segmented network center node of the at least one segmented network based on the network nodes in the at least one segmented network, and return to the step of matching the multiple network nodes with the segmented network center node of the at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the multiple network nodes belong respectively according to the matching results, until the preset conditions are met.

9. The method according to claim 8, characterized in that After determining the segmented networks to which the plurality of network nodes belong, re-determining the segmented network center node of the at least one segmented network according to the network nodes in the at least one segmented network includes: After determining the segmented networks to which the multiple network nodes belong, the average values ​​of the first spatial coordinates of each network node in the at least one segmented network in the multi-dimensional virtual space are determined respectively to obtain the segmented network center node of the at least one segmented network.

10. The method according to claim 1, characterized in that The step of matching the plurality of network nodes with a segmented network center node of at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the plurality of network nodes belong respectively according to the matching results, includes: Obtaining an initial segmented network center node of at least one segmented network; According to the first indicator information, the multiple network nodes are matched with an initial segmented network center node of at least one segmented network respectively, and the segmented networks to which the multiple network nodes belong are determined respectively according to the matching results.

11. The method according to claim 10, characterized in that The obtaining of at least one initial segment network center node of the segment network comprises: Acquire first spatial coordinates of the plurality of network nodes in the multi-dimensional virtual space; The first spatial coordinate corresponding to at least one network node among the multiple network nodes is used as an initial segmented network center node of at least one segmented network.

12. The method according to claim 10, characterized in that The step of matching the plurality of network nodes with an initial segmented network center node of at least one segmented network respectively according to the first indicator information, and determining the segmented networks to which the plurality of network nodes belong respectively according to the matching results, comprises: Determining at least one segmented network based on distances of the plurality of network nodes to the at least one initial segmented network center node; According to the at least one segmented network, respectively determine the segmented networks to which the plurality of network nodes belong; The segmented networks correspond one-to-one to the central nodes of the initial segmented network, and the distance between the network nodes included in at least one segmented network and the corresponding central node of the initial segmented network is less than a preset distance threshold.

13. The method according to claim 10, characterized in that The preset condition includes that the distance between the segment network center node determined last time and the segment network center node determined this time is less than a preset threshold.

14. A dynamic attribution processing device for a network node, characterized in that: The device comprises: An acquisition module, used to acquire first indicator information of multiple network nodes; A determination module is used to match the multiple network nodes with the segmented network center node of at least one segmented network according to the first indicator information, and determine the segmented networks to which the multiple network nodes belong according to the matching results.

15. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of the dynamic attribution processing method for a network node as described in any one of claims 1 to 13 are implemented.

16. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for dynamic affiliation processing of a network node according to any one of claims 1 to 13 are implemented.

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