Method and device for evaluating flexibility of network structure

Abstract

The invention relates to a method and device for evaluating the flexibility of a network structure, and relates to the technical field of networks. The method comprises the following steps: calculating the physical crosslinking degree of a network structure according to a first measurement index used for evaluating the physical crosslinking condition of the network structure; calculating the information cross-linking degree of the network structure according to a second measurement index used for evaluating the information sharing condition of the network structure; and evaluating the flexibility of the network structure based on the physical crosslinking degree and the information crosslinking degree. Therefore, the flexibility of the network structure is evaluated.

Description

Technical Field

[0001] The invention belongs to the field of network technology, and in particular relates to a method and a device for evaluating the flexibility of a network structure. Background Art

[0002] With the widespread use of network technology, network structures are increasingly showing complex nonlinear characteristics, and the requirements for the flexibility of network structures are becoming higher and higher. Flexibility is the ability of a network system to effectively respond to a changing environment through self-adjustment, and to use the uncertainty and changes in the environment to improve the efficiency of the system itself. Flexibility is an important indicator for evaluating network structure. Its size affects the performance of the system and is an intuitive reflection of the operation status and change mode of the network topology. The higher the flexibility, the stronger the ability of the network structure to adapt to external changes, and vice versa. Therefore, how to evaluate the flexibility of the network structure is one of the most important topics. Summary of the invention

[0003] In view of this, it is necessary to provide a method and device for evaluating the flexibility of a network structure in order to address the above technical issues, so as to achieve the evaluation of the flexibility of the network structure.

[0004] A method for evaluating the flexibility of a network structure, the method comprising:

[0005] Calculating the degree of physical crosslinking of the network structure according to a first metric for evaluating the physical crosslinking of the network structure;

[0006] Calculating the information cross-linking degree of the network structure according to a second metric used to evaluate the information sharing status of the network structure;

[0007] Based on the physical cross-linking degree and the information cross-linking degree, the flexibility of the network structure is evaluated.

[0008] In one embodiment, the first metric includes connectivity entropy, wherein the physical cross-linking degree is negatively correlated with the connectivity entropy; and the flexibility of the network structure is positively correlated with the physical cross-linking degree.

[0009] In one embodiment, calculating the degree of physical crosslinking of the network structure according to a first metric for evaluating the physical crosslinking of the network structure includes:

[0010] Calculating the connectivity entropy between a first node and a second node according to the number of connections that vary between the first node and the second node in the network structure, where the first node and the second node are any two nodes in the network structure;

[0011] Determine the total connectivity entropy and the maximum connectivity entropy of the network structure according to the calculated connectivity entropies;

[0012] The physical cross-linking degree of the network structure is determined according to the maximum connectivity entropy and the total connectivity entropy.

[0013] In one embodiment, according to the number of connections between the first node and the second node that vary in the network structure, calculating the connectivity entropy between the first node and the second node includes:

[0014] Calculating a connection probability between the first node and the second node according to the number of connections with changes between the first node and the second node in the network structure and the total number of connections in the network structure;

[0015] The connectivity entropy between the first node and the second node is calculated according to the following formula:

[0016]

[0017] in, Used to represent the connectivity entropy between the first node i and the second node j;

[0018] Used to represent the connectivity probability between the first node i and the second node j.

[0019] In one embodiment, the number of connections between the first node and the second node in the network structure that have changed is determined according to the following method:

[0020] Counting the number of physical links from the first node to the second node in the network structure as the connectivity number of the first node;

[0021] Counting the number of physical links from the first node to the next hop node in the network structure as the active connectivity number of the first node;

[0022] Determine the difference between the connectivity number of the first node and the active connectivity number as the connectivity number with changes between the first node and the second node;

[0023] Calculating the connection probability between the first node and the second node according to the number of connections with changes between the first node and the second node in the network structure and the total number of connections of the network structure includes:

[0024] The ratio between the changed number of connections and the total number of connections of the network structure is determined as the connection probability; wherein the total number of connections of the network structure is calculated according to the following formula:

[0025]

[0026] W is used to represent the total number of connections;

[0027] F ij Used to represent the connectivity length between the first node i and the second node j.

[0028] In one embodiment, determining the physical cross-linking degree of the network structure according to the maximum connectivity entropy and the total connectivity entropy includes:

[0029] Determining a ratio between the maximum connectivity entropy and the total connectivity entropy;

[0030] The difference between the first set value and the ratio is determined as the physical cross-linking degree of the network structure.

[0031] In one of the embodiments, the second metric includes information sharing entropy; wherein the information cross-linking degree is negatively correlated with the information sharing entropy; and the flexibility of the network structure is positively correlated with the information cross-linking degree.

[0032] In one embodiment, calculating the information cross-linking degree of the network structure according to a second metric for evaluating the information sharing status of the network structure includes:

[0033] Calculating the information sharing entropy of multiple sub-network structures divided by the network structure respectively;

[0034] The information cross-linking degree of the network structure is calculated according to the information sharing entropy of the multiple sub-network structures.

[0035] In one embodiment, the information sharing entropy of each sub-network structure is calculated according to the following formula:

[0036]

[0037] in, Y is used to represent the total number of information sharing nodes in the network structure;

[0038] Information sharing entropy used to represent the j-th sub-network structure;

[0039] n ij Used to indicate the amount of information shared by the i-th node in the j-th sub-network structure;

[0040] The probability of information sharing entropy used to represent the j-th sub-network structure;

[0041] w i It is used to represent the influence weight of the information sharing degree of the i-th node on the j-th sub-network structure.

[0042] In one embodiment, calculating the information cross-linking degree of the network structure according to the information sharing entropy of the multiple sub-network structures includes:

[0043] The information sharing entropies of the plurality of sub-networks are averaged to obtain an average shared entropy; the difference between the second set value and the average shared entropy is determined as the information cross-linking degree of the network structure;

[0044] or,

[0045] A weight is assigned to the information sharing entropy of each sub-network; a weighted summation is performed on the information sharing entropy of each sub-network to obtain a weighted information sharing entropy; and a difference between the second set value and the weighted information sharing entropy is determined as the information cross-linking degree of the network structure, wherein the value of the assigned weight is positively correlated with the value of the information sharing entropy.

[0046] In one embodiment, the flexibility of the network structure is evaluated based on the physical cross-linking degree and the information cross-linking degree, including:

[0047] The flexibility of the network structure is calculated according to the physical cross-linking degree, the first weight of the physical cross-linking degree, the information cross-linking degree and the second weight of the information cross-linking degree.

[0048] In a second aspect, a device for evaluating the flexibility of a network structure is provided, the device comprising:

[0049] A first calculation unit, used to calculate the physical cross-linking degree of the network structure according to a first metric used to evaluate the physical cross-linking condition of the network structure;

[0050] A second calculation unit, used for calculating the information cross-linking degree of the network structure according to a second metric used for evaluating the information sharing situation of the network structure;

[0051] An evaluation unit is used to evaluate the flexibility of the network structure based on the physical cross-linking degree and the information cross-linking degree.

[0052] In the above method and device for evaluating the flexibility of a network structure, the physical crosslinking degree of the network structure is calculated according to a first metric used to evaluate the physical crosslinking of the network structure; the information crosslinking degree of the network structure is calculated according to a second metric used to evaluate the information sharing of the network structure; and the flexibility of the network structure is evaluated based on the physical crosslinking degree and the information crosslinking degree. Thus, by providing the above flexibility evaluation method, the physical crosslinking and information sharing of the network structure are evaluated, thereby obtaining the above physical crosslinking degree and information crosslinking degree, and then the flexibility of the network structure is evaluated based on these two indicators, thereby achieving the evaluation of the flexibility of the network structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 The figure is a flowchart of a method for evaluating the flexibility of a network structure in one embodiment.

[0054] Figure 2 A schematic diagram of the relationship between nodes in a certain network structure in an embodiment;

[0055] Figure 3 A schematic diagram of the relationship between sub-network structures included in a certain network structure in an embodiment;

[0056] Figure 4 A schematic diagram of the calculation logic of the flexibility of a network structure in one embodiment;

[0057] Figure 5 is a schematic structural diagram of a device for evaluating the flexibility of a network structure in one embodiment;

[0058] Figure 6 FIG. 4 is a diagram showing the internal structure of a computing device in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0060] Before introducing this application, the technical terms involved are explained first:

[0061] 1. Operations research is a discipline that applies scientific and technological methods such as mathematics and modern computers to study various activities and provide theories and methods for quantitative analysis and optimization of system architecture.

[0062] 2. Mathematical model is the description of the system using mathematical concepts and language. Using mathematical models to solve problems in various operations such as business is an important part of the field of operations research. Mathematical models are convenient for describing real things. For the quantifiable parts, mathematical equations or computer languages ​​can be used to accurately express them, solving the problems that real things are too big or too small, real affairs are too complicated, and real affairs are invisible and intangible.

[0063] Based on this, the present application provides a method for evaluating the flexibility of a network structure, wherein the physical crosslinking degree of the network structure is calculated according to a first metric used to evaluate the physical crosslinking of the network structure; the information crosslinking degree of the network structure is calculated according to a second metric used to evaluate the information sharing of the network structure; and the flexibility of the network structure is evaluated based on the physical crosslinking degree and the information crosslinking degree. By analyzing the physical connectivity and information sharing crosslinking degree of the network structure, a mathematical method for measuring the network structure is provided.

[0064] In one embodiment, Figure 1 As shown, a method for evaluating the flexibility of a network structure is provided, and the method is applied to an electronic device as an example for explanation. The electronic device may be, but is not limited to, a server or other device. When the above electronic device implements the above method, the following steps may be included:

[0065] S11. Calculate the degree of physical crosslinking of the network structure according to a first metric for evaluating the physical crosslinking of the network structure.

[0066] In specific implementation, the flexibility of the network structure is not only reflected in the dynamic topological performance of the network structure that actively adapts to changes, but also more profoundly reflects the sustainable self-adjustment and self-renewal capabilities of the network structure to utilize and control changes. The flexibility of the network structure is divided into physical cross-linking flexibility and information cross-linking flexibility. The degree of cross-linking of these two indicators is measured to measure the flexibility of the network structure.

[0067] The physical cross-linking of the network structure is the composition structure and topology of the system itself, and is the basis for the effective connection and coordinated operation of the system with other elements. The flexibility of physical cross-linking refers to the network structure's timely adjustment and rapid reorganization of the network topology according to user needs and environmental changes. Even under the influence of uncertain factors, each link of the network structure can still autonomously coordinate to maintain the stable operation of the entire system, reflecting the network structure's ability to "adapt to changes". A network structure with high flexibility will inevitably provide accurate physical cross-linking for each network node in the network structure. Using physical cross-linking as an evaluation indicator of network structure flexibility can measure the reliability of network connectivity, the flexibility of module reorganization, and the tension and relaxation of network topology. By continuously optimizing and improving the network structure, it can ensure the maximum aggregation of various network nodes and multiply the system efficiency.

[0068] Based on this, in this step, a measurement indicator for evaluating the physical crosslinking condition (physical crosslinking flexibility) of the network structure can be first obtained. In order to distinguish it from other subsequent measurement indicators, the measurement indicator is marked as the first measurement indicator, and then the physical crosslinking degree of the network structure is calculated based on the first measurement indicator.

[0069] It is worth noting that the above network structure can be any network structure.

[0070] S12. Calculate the information cross-linking degree of the network structure according to a second metric used to evaluate the information sharing situation of the network structure.

[0071] In specific implementation, the flexibility of network structure information cross-linking is mainly reflected in the timely sharing of various types of information resources in various links of the network structure, so as to achieve the purpose of quick processing, pushing and applying information. Information sharing is an important manifestation of realizing the advantages of information cross-linking, and it is also a reliable way to improve the flexibility of network structure. By sharing information throughout the network, the uncertainty of the network structure can be effectively reduced, so that each network node in the network structure can fully grasp various types of information, continuously perceive environmental changes, timely judge the trend of changes and select appropriate routes. In addition, information sharing will also promote the integration and aggregation of various resources in the network structure, while reducing costs, it also improves the utilization rate of resources, so that the entire network can be interconnected vertically and horizontally in an orderly manner, and achieve a flexible sharing effect of accessing the network at any time.

[0072] In this step, since the information cross-linking of the network structure can also characterize the flexibility of the network structure, based on this, in this step, a measurement indicator for evaluating the information cross-linking of the network structure (information cross-linking flexibility) can be first obtained, that is, the above-mentioned second measurement indicator; and then the second measurement indicator is used to evaluate the information cross-linking degree of the network structure.

[0073] S13. Based on the physical cross-linking degree and the information cross-linking degree, the flexibility of the network structure is evaluated.

[0074] Specifically, the physical connectivity of the network reflects the flexible topology and anti-destruction capability of the network structure, and the information sharing of the network reflects the interconnection of information in the network. Both connectivity and sharing bring value gains to the flexible performance of the network structure.

[0075] Based on this, after obtaining the physical crosslinking degree and information crosslinking degree of the network structure, we also obtain the measurement index for characterizing the physical crosslinking flexibility and the measurement index for characterizing the information crosslinking flexibility. The flexibility of the network structure includes the above-mentioned physical crosslinking flexibility and the above-mentioned information crosslinking flexibility. Therefore, the flexibility of the network structure can be evaluated based on the above-mentioned physical crosslinking degree and the above-mentioned information crosslinking degree, that is, the evaluation of the flexibility of the network structure is realized.

[0076] In the above method for evaluating the flexibility of a network structure, the physical crosslinking degree of the network structure is calculated according to a first metric used to evaluate the physical crosslinking of the network structure; the information crosslinking degree of the network structure is calculated according to a second metric used to evaluate the information sharing of the network structure; and the flexibility of the network structure is evaluated based on the physical crosslinking degree and the information crosslinking degree. Thus, by providing the above flexibility evaluation method, the physical crosslinking and information sharing of the network structure are evaluated, thereby obtaining the above physical crosslinking degree and information crosslinking degree, and then the flexibility of the network structure is evaluated based on these two metrics, thereby achieving the evaluation of the flexibility of the network structure.

[0077] Optionally, in one embodiment, the first metric includes connectivity entropy, wherein the physical cross-linking degree is negatively correlated with the connectivity entropy; and the flexibility of the network structure is positively correlated with the physical cross-linking degree.

[0078] Specifically, due to the complexity of network structure, information is often disturbed and impacted by external uncertain factors during its circulation. In order to reflect the degree of physical cross-linking of information flow in the network structure, connectivity entropy is used as a measure of the degree of physical cross-linking, and an evaluation of the physical cross-linking flexibility of the network structure is given.

[0079] Specifically, physical cross-linking is a measure of the stability of the connectivity of the network structure, which refers to the ability of the network to remain connected under internal and external environments. Connectivity entropy is a measure of the uncertainty of the physical cross-linking of the network structure, reflecting the relationship and influence between the nodes of the network structure. It is a key measure of the quality of the physical connection of the network structure and is determined by the number of connections of the network. Connectivity entropy is used to measure the degree of physical cross-linking of the network structure. The smaller the connectivity entropy, the greater the degree of physical cross-linking and the more flexible the network structure; the larger the connectivity entropy, the smaller the degree of physical cross-linking and the less flexible the network structure.

[0080] On this basis, in this embodiment, step S11 can be performed according to the following process: based on the changing number of connections between the first node and the second node in the network structure, the connectivity entropy between the first node and the second node is calculated, and the first node and the second node are any two nodes in the network structure; based on the calculated connectivity entropies, the total connectivity entropy and the maximum connectivity entropy of the network structure are determined; based on the maximum connectivity entropy and the total connectivity entropy, the physical cross-linking degree of the network structure is determined.

[0081] Optionally, in one embodiment, the step of calculating the connectivity entropy between the first node and the second node according to the number of connectivity changes between the first node and the second node in the network structure may be performed according to the following process: calculating the connectivity probability between the first node and the second node according to the number of connectivity changes between the first node and the second node in the network structure and the total number of connectivity of the network structure; calculating the connectivity entropy between the first node and the second node according to the following formula:

[0082]

[0083] in, Used to represent the connectivity entropy between the first node i and the second node j;

[0084] Used to represent the connectivity probability between the first node i and the second node j.

[0085] Based on this, the connectivity entropy between any two nodes in the network structure can be calculated according to the aforementioned connectivity entropy calculation formula.

[0086] Optionally, in one embodiment, the number of connections that change between the first node and the second node in the network structure may be determined according to the following method: the number of physical links passed from the first node to the second node in the network structure is counted as the number of connections of the first node; the number of physical links passed from the first node to the next hop node in the network structure is counted as the number of active connections of the first node; the difference between the number of connections of the first node and the number of active connections is determined as the number of connections that change between the first node and the second node;

[0087] Specifically, taking any first node i and any second node j in the network structure as an example, the number of all physical links from the first node i to the second node j is called the connectivity number of the first node i, denoted by f1; the number of physical links from the first node i to the next hop node, that is, the number of all first-step connectivity from the first node i is called the effective active connectivity number f2 of the first node i, and the rest are changing connectivity numbers, denoted by f1-f2.

[0088] In order to better understand this embodiment, Figure 2As shown in the figure, there are 6 physical links from the first node i to the second node j, which are physical link 1: first node i--node 7--node 8--second node j, physical link 2: first node i--node 1--node 2--second node j, physical link 3: first node i--node 1--node 2--node 3--second node j, physical link 4: first node i--node 4--node 2--node 3--second node j, physical link 5: first node i--node 4--node 2--second node j, physical link 6: first node i--node 4--node 5--node 6--second node j. It can be obtained that the connectivity number f1 of the first node i is 6.

[0089] Also combined Figure 2 , the next hop nodes reached from the first node i are node 7, node 1, and node 4, that is, there are three physical links, namely: physical link 1: first node i--node 7, physical link 2: first node i--node 1, physical link 3: first node i--node 4. It can be seen that the active connectivity number f2 of the first node i is 3.

[0090] After obtaining the connectivity number f1 and the active connectivity number f2 of the first node i, the variable connectivity number between the first node i and the second node j can be obtained, that is, f1-f2=6-3=3.

[0091] Further, the step of calculating the connection probability between the first node and the second node according to the number of connections that have changed between the first node and the second node in the network structure and the total number of connections of the network structure can be performed according to the following process: the ratio between the number of connections that have changed and the total number of connections of the network structure is determined as the connection probability, which can be expressed by the following formula: That is, the connection probability between the first node i and the second node j is It can be expressed as the ratio of the difference between the number of connections f1 of the first node i and the number of effective active connections f2 to the total number of network connections.

[0092] The total number of connections of the network structure can be calculated according to the following formula:

[0093]

[0094] W is used to represent the total number of connections;

[0095] F ij Used to represent the connectivity length between the first node i and the second node j.

[0096] In the above formula, the value of i is between 1 and the total number of nodes included in the network structure, and the value of j is also between 1 and the total number of nodes included in the network structure. The value of the total number of nodes included in the network node can be determined according to actual conditions, and the total number of nodes included in different network structures can be the same or different.

[0097] Specifically, the shortest number of connections between two nodes in the network structure is defined as the connection length between the two nodes. Figure 2 For explanation, the connection number between the first node i and the second node j can be determined based on each physical link between the first node i and the second node j. Referring to the description of the physical link from the first node i to the second node j, the number of nodes passed by the first node i to the second node j is used as the connection number for explanation. The connection number corresponding to physical link 1 is 2, the connection number corresponding to physical link 2 is 2, the connection number corresponding to physical link 3 is 3, the connection number corresponding to physical link 4 is 3, the connection number corresponding to physical link 5 is 2, and the connection number corresponding to physical link 6 is 3. Then, the shortest connection number between the first node i and the second node j is 2, and then the connection length between the first node i and the second node j can be determined to be 2. Of course, the above connection number can also be defined in other ways, which can be set according to actual conditions, and this embodiment does not limit this.

[0098] Furthermore, after obtaining the connectivity entropy of any two nodes in the network structure, the maximum connectivity entropy and the total connectivity entropy of the network structure can be obtained respectively, which can be represented by the following formulas:

[0099] Maximum connectivity entropy of network structure The calculation formula is: Where W is used to represent the total number of connections mentioned above.

[0100] The total connectivity entropy of the network structure H L The calculation formula is:

[0101]

[0102] In this formula, N may be the total number of nodes included in the network structure.

[0103] Furthermore, the step of determining the physical cross-linking degree of the network structure based on the maximum connectivity entropy and the total connectivity entropy can be performed according to the following process: determining the ratio between the maximum connectivity entropy and the total connectivity entropy; and determining the difference between the first set value and the ratio as the physical cross-linking degree of the network structure.

[0104] Specifically, the first set value may be 1. Based on this, when the physical cross-linking degree of the network structure is represented by L, the physical cross-linking degree of the network structure may be represented by the following formula:

[0105]

[0106] As a result, the physical cross-linking degree of the network structure is obtained based on the calculation process provided above.

[0107] Next, we will introduce the calculation process of the information cross-linking degree of the network structure:

[0108] Specifically, various types of information flow between the various layers and links of any network structure. Information itself is uncertain. In addition, the network structure is a dynamic topological change mode. Affected by the geographical environment, electromagnetic spectrum, etc., information sharing between nodes also presents a large uncertainty. Therefore, when mathematically describing related concepts, based on the information entropy theory, starting from the uncertainty of information sharing and the state probability of nodes, an information sharing evaluation model is established.

[0109] In view of this, in one embodiment, the second metric includes information sharing entropy; wherein the information cross-linking degree is negatively correlated with the information sharing entropy; and the flexibility of the network structure is positively correlated with the information cross-linking degree.

[0110] Specifically, due to the complexity of network structure, information is often disturbed and impacted by external uncertain factors during its circulation. In order to reflect the degree of information cross-linking in the network structure, information sharing entropy is used as a measure of information cross-linking degree to give an evaluation of the information cross-linking flexibility of the network structure.

[0111] Specifically, information sharing entropy is a measure of uncertainty when information is shared between nodes. The smaller the sharing entropy, the tighter the information cross-linking between nodes, and the higher the degree of information cross-linking, the more obvious the information flexibility rules of the network structure are.

[0112] On this basis, in this embodiment, step S12 can be performed according to the following process: respectively calculating the information sharing entropy of the multiple sub-network structures divided by the network structure; and calculating the information cross-linking degree of the network structure according to the information sharing entropy of the multiple sub-network structures.

[0113] Specifically, the network structure can be divided into several sub-network structures, and then the information cross-linking degree between the sub-network structures is analyzed and solved, and based on this, the information cross-linking degree of multiple sub-network structures in the network structure is described, and then based on the information cross-linking degree of multiple sub-network structures, the information cross-linking degree of the network structure is calculated. The information cross-linking degree of each sub-network structure can be characterized by the information sharing entropy of the sub-network structure. Based on this, it is assumed that the network structure N is composed of h sub-network structures, N = (N1, N2, ... Nj, Nt ..., Nh), where the value of h can be configured according to the actual situation.

[0114] On this basis, the jth sub-network structure is taken as an example for explanation. The jth sub-network structure includes m nodes, where the value of m can be configured according to the actual situation. Since the sub-network structures in the network structure may share the same node, the number of information shared by any i-th node included in the jth sub-network structure can be counted, which is recorded as n ij , it can be expressed as: Nj = (n j1 ,n j2 ,…n jm ). In order to better understand this embodiment, Figure 3 The network structure shown in the figure is used as an example to illustrate. Figure 3 The network structure in includes three sub-network structures. Figure 3 The subnetwork structure shown by the dotted circle: subnetwork 1, subnetwork 2 and subnetwork 3. When j = 1, subnetwork 1 includes 4 nodes, namely node 1, node 2, node 4 and node 7. Then subnetwork 1 can be expressed as N1 = (n 11 ,n 12 ,n 13, n 14 ),from Figure 3 It can be seen that node 7 belongs to sub-network 1, sub-network 2, and sub-network 3. Therefore, the number of information shared by node 7 is 3, that is, n 14 =3. Node 4 also belongs to subnetworks 1 to 3. Therefore, it can be concluded that the number of information shared by node 4 is 3, that is, n 13 =3; since nodes 1 and 2 only belong to subnetwork 1, the number of information shared by nodes 1 and 2 is 1, that is, n 11 、n 12 =1, so N1=(1,1,3,3).

[0115] Similarly, the amount of information shared by each node in subnetwork 2 and subnetwork 3 can be obtained respectively.

[0116] Furthermore, in one embodiment, the information sharing entropy of each sub-network structure may be calculated according to the following formula:

[0117]

[0118] in, Y is used to represent the total number of information sharing nodes in the network structure;

[0119] Information sharing entropy used to represent the j-th sub-network structure;

[0120] n ij Used to indicate the amount of information shared by the i-th node in the j-th sub-network structure;

[0121] The probability of information sharing entropy used to represent the j-th sub-network structure;

[0122] w i It is used to represent the influence weight of the information sharing degree of the i-th node on the j-th sub-network structure, and

[0123] Furthermore, in one embodiment, the step of calculating the information cross-linking degree of the network structure based on the information sharing entropy of the multiple sub-network structures can be performed according to the following process: averaging the information sharing entropy of the multiple sub-networks to obtain an average shared entropy; and determining the difference between the second set value and the average shared entropy as the information cross-linking degree of the network structure.

[0124] Specifically, the second set value may be 1. Based on this, the information cross-linking degree E of the network structure may be characterized according to the following formula:

[0125]

[0126] Among them, h is used to represent the number of sub-network structures included in the network structure. is the average shared entropy. E∈[0,1], the larger the E(N), the better the information cross-linking flexibility of the network.

[0127] In the above-mentioned method for calculating the information cross-linking degree of the network structure, the information sharing entropy of multiple sub-network structures is averaged so that the obtained average shared entropy can characterize the information sharing degree of the network structure to a certain extent, that is, it can indicate the cross-linking status of the network structure to a certain extent, and then the information cross-linking degree of the network structure can be obtained by subtracting the average shared entropy from 1.

[0128] In addition, in another embodiment, the step of calculating the information cross-linking degree of the network structure based on the information sharing entropy of the multiple sub-networks can also be performed according to the following process: assigning a weight to the information sharing entropy of each sub-network structure; performing weighted summation calculation on the information sharing entropy of each sub-network structure to obtain a weighted information sharing entropy; and determining the difference between the second set value and the weighted information sharing entropy as the information cross-linking degree of the network structure, wherein the value of the assigned weight is positively correlated with the value of the information sharing entropy.

[0129] Specifically, the second set value may be 1. Based on this, the information cross-linking degree E of the network structure may also be characterized according to the following formula:

[0130] Among them, β j Used to represent the weight of the information sharing entropy of the j-th sub-network structure; if the value of the information sharing entropy of the j-th sub-network structure is relatively large, a larger weight can be assigned to the j-th sub-network structure, and β j ∈[0,1]. It should be noted that the larger the value of information sharing entropy is, the more nodes in the corresponding sub-network structure are shared, which means that the corresponding sub-network structure is more important and can better represent the cross-linking of the entire network structure.

[0131] Therefore, the degree of information cross-linking between nodes is not a simple addition of the information volume of each node, but is also closely related to the information sharing measure between the two. The network information cross-linking degree model represents the functional relationship between information sharing entropy, information sharing probability, information cross-linking and node state probability in the network structure, so as to better analyze the degree of information cross-linking of the network structure.

[0132] Based on any of the above embodiments, in this embodiment, step S13 may be performed according to the following process: calculating the flexibility of the network structure according to the physical crosslinking degree, the first weight of the physical crosslinking degree, the information crosslinking degree and the second weight of the information crosslinking degree.

[0133] Specifically, the network structure flexibility algorithm combines the physical cross-linking and information sharing effects of the network, calculates the network structure flexibility with appropriate weight matching, and gives a mathematical method for deriving the network structure flexibility measure from physical cross-linking and information cross-linking. Figure 4 shown.

[0134] Specifically, the connectivity of the network reflects the flexible topology and anti-destruction capability of the network structure, and the information sharing of nodes reflects the interconnection of information in the network. Both connectivity and sharing bring value gains to the flexible performance of the network structure. Combining the physical cross-linking and information sharing effects of the network, we can get the expression of the flexibility F of the network structure, as shown below:

[0135]

[0136] Where φ, is the weight coefficient of the physical cross-linking degree L and the information cross-linking degree E in the network structure, and the specific value can be configured according to the actual situation.

[0137] Therefore, the evaluation of the flexibility of the network structure in this application should not only qualitatively measure the standards of relevant factors, but also quantitatively calculate the degree of influence of relevant factors on the performance of the system structure, and grasp the changing characteristics of the network structure. This evaluation method combining qualitative and quantitative methods is a prediction and evaluation of the flexibility of the network structure to adapt to the environment, a comprehensive assessment and identification of the network structure, and the basis for the optimization and improvement of the network structure.

[0138] In the method for evaluating the flexibility of a network structure provided in the present application, starting from analyzing the flexibility of the network, mathematical modeling is performed on the two key variables supporting the flexibility of the network, namely, the physical cross-linking degree and the information cross-linking degree, to study the connectivity and information sharing capabilities of the network structure, and a mathematical method for deriving the flexibility measurement of the network structure from the physical cross-linking and the information cross-linking is given. It can be seen from the mathematical formula that the flexibility of the network structure is not only related to the topological structure, but also to the degree of information sharing between links and nodes. Therefore, by analyzing the flexibility of the network structure, the network structure can be optimized and improved from the perspective of rationally allocating resources and increasing network reliability, so that the network structure has better flexible topological capabilities and moves rapidly towards the direction of "links are connected, information is compatible, and structures are reorganizable."

[0139] In addition, this application uses mathematical modeling to describe the physical cross-linking flexibility and information cross-linking flexibility of the network and the changing process, thereby converting the network structure problem into a quantifiable problem, laying the foundation for applying mathematical methods to solve the problem of network structure flexibility.

[0140] At this point, a method for evaluating the flexibility of a network structure has been designed.

[0141] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0142] Based on the same technical concept, Figure 5 As shown in the structural schematic diagram, the present application also provides a device for evaluating the flexibility of a network structure, the device comprising:

[0143] A first calculation unit 51 is used to calculate the physical cross-linking degree of the network structure according to a first metric used to evaluate the physical cross-linking condition of the network structure;

[0144] A second calculation unit 5, used for calculating the information cross-linking degree of the network structure according to a second measurement index used for evaluating the information sharing situation of the network structure;

[0145] The evaluation unit 53 is used to evaluate the flexibility of the network structure based on the physical cross-linking degree and the information cross-linking degree.

[0146] Therefore, by providing the above-mentioned device for evaluating the flexibility of the network structure, the physical cross-linking and information sharing of the network structure are evaluated, thereby obtaining the above-mentioned physical cross-linking degree and information cross-linking degree, and then evaluating the flexibility of the network structure based on these two indicators, thereby realizing the evaluation of the flexibility of the network structure.

[0147] In one embodiment, a computing device is provided. The computing device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile 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 the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for evaluating the flexibility of a network structure is implemented.

[0148] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0149] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for evaluating the flexibility of a network structure provided in any of the above embodiments are implemented.

[0150] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. 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. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0151] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0152] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for evaluating the flexibility of a network structure, characterized in that: The method comprises: Calculating the degree of physical crosslinking of the network structure according to a first metric for evaluating the physical crosslinking of the network structure; Calculating the information cross-linking degree of the network structure according to a second metric used to evaluate the information sharing status of the network structure; Based on the physical cross-linking degree and the information cross-linking degree, the flexibility of the network structure is evaluated.

2. The method according to claim 1, characterized in that: The first metric includes connectivity entropy, wherein the physical cross-linking degree is negatively correlated with the connectivity entropy; and the flexibility of the network structure is positively correlated with the physical cross-linking degree.

3. The method according to claim 2, characterized in that Calculating the degree of physical crosslinking of the network structure according to a first metric for evaluating the physical crosslinking of the network structure includes: Calculating the connectivity entropy between a first node and a second node according to the number of connections that vary between the first node and the second node in the network structure, where the first node and the second node are any two nodes in the network structure; Determine the total connectivity entropy and the maximum connectivity entropy of the network structure according to the calculated connectivity entropies; The physical cross-linking degree of the network structure is determined according to the maximum connectivity entropy and the total connectivity entropy.

4. The method according to claim 3, characterized in that: Calculating the connectivity entropy between the first node and the second node according to the number of connections between the first node and the second node in the network structure that have changed, including: Calculating a connection probability between the first node and the second node according to the number of connections with changes between the first node and the second node in the network structure and the total number of connections in the network structure; The connectivity entropy between the first node and the second node is calculated according to the following formula: in, Used to represent the connectivity entropy between the first node i and the second node j; Used to represent the connectivity probability between the first node i and the second node j.

5. The method according to claim 3, characterized in that: The number of connections between the first node and the second node in the network structure that have changed is determined according to the following method: Counting the number of physical links from the first node to the second node in the network structure as the connectivity number of the first node; Counting the number of physical links from the first node to the next hop node in the network structure as the active connectivity number of the first node; Determine the difference between the connectivity number of the first node and the active connectivity number as the connectivity number with changes between the first node and the second node; Calculating the connection probability between the first node and the second node according to the number of connections with changes between the first node and the second node in the network structure and the total number of connections of the network structure includes: Determine the ratio between the number of connections with changes and the total number of connections of the network structure as the connection probability; The total number of connections of the network structure is calculated according to the following formula: W is used to represent the total number of connections; F ij Used to represent the connectivity length between the first node i and the second node j.

6. The method according to claim 3, characterized in that Determining the physical cross-linking degree of the network structure according to the maximum connectivity entropy and the total connectivity entropy includes: Determining a ratio between the maximum connectivity entropy and the total connectivity entropy; The difference between the first set value and the ratio is determined as the physical cross-linking degree of the network structure.

7. The method according to claim 1, characterized in that The second metric includes information sharing entropy; wherein the information cross-linking degree is negatively correlated with the information sharing entropy; and the flexibility of the network structure is positively correlated with the information cross-linking degree.

8. The method according to claim 7, characterized in that Calculating the information cross-linking degree of the network structure according to a second metric for evaluating the information sharing status of the network structure includes: Calculating the information sharing entropy of multiple sub-network structures divided by the network structure respectively; The information cross-linking degree of the network structure is calculated according to the information sharing entropy of the multiple sub-network structures.

9. The method according to claim 1, characterized in that: The information sharing entropy of each sub-network structure is calculated according to the following formula: in, Y is used to represent the total number of information sharing nodes in the network structure; Information sharing entropy used to represent the j-th sub-network structure; n ij Used to indicate the amount of information shared by the i-th node in the j-th sub-network structure; The probability of information sharing entropy used to represent the j-th sub-network structure; w i It is used to represent the influence weight of the information sharing degree of the i-th node on the j-th sub-network structure.

10. A device for evaluating the flexibility of a network structure, characterized in that: The device comprises: A first calculation unit, used to calculate the physical cross-linking degree of the network structure according to a first metric used to evaluate the physical cross-linking condition of the network structure; A second calculation unit, used for calculating the information cross-linking degree of the network structure according to a second metric used for evaluating the information sharing situation of the network structure; An evaluation unit is used to evaluate the flexibility of the network structure based on the physical cross-linking degree and the information cross-linking degree.

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