A method and apparatus for evaluating flexibility of network structure

Abstract

This application relates to a method and apparatus for evaluating the flexibility of a network structure, and pertains to the field of network technology. The method includes: calculating the physical cross-linking degree of the network structure based on a first metric used to evaluate the physical cross-linking of the network structure; calculating the information cross-linking degree of the network structure based on a second metric used to evaluate the information sharing of the network structure; and evaluating the flexibility of the network structure based on the physical cross-linking degree and the information cross-linking degree. This achieves the evaluation of the flexibility of the network structure.

Description

Technical Field

[0001] This invention belongs to the field of network technology, and specifically relates to a method and apparatus for evaluating the flexibility of network structures. Background Technology

[0002] With the widespread application of network technology, network structures are increasingly exhibiting complex nonlinear characteristics, leading to higher demands on their flexibility. Flexibility refers to a network system's ability to effectively respond to changing environments through self-adjustment and to leverage environmental uncertainties and changes to improve its own efficiency. As a crucial indicator for evaluating network structure, flexibility significantly impacts system performance and directly reflects the network topology's operational status and patterns of change. Higher flexibility indicates a stronger ability to adapt to external changes, and vice versa. Therefore, assessing the flexibility of network structures is a critical issue. Summary of the Invention

[0003] In view of this, it is necessary to provide a method and apparatus for evaluating the flexibility of network structures in order to address the above-mentioned technical problems.

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

[0005] The physical cross-linking degree of the network structure is calculated based on a first metric used to evaluate the physical cross-linking of the network structure.

[0006] The information cross-linking degree of the network structure is calculated based on a second metric used to evaluate the information sharing of the network structure.

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

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

[0009] In one embodiment, the physical cross-linking degree of the network structure is calculated based on a first metric used to evaluate the physical cross-linking of the network structure, including:

[0010] Based on the varying connectivity between the first node and the second node in the network structure, calculate the connectivity entropy between the first node and the second node, where the first node and the second node are any two nodes in the network structure.

[0011] Based on the calculated connectivity entropy, determine the total connectivity entropy and maximum connectivity entropy of the network structure;

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

[0013] In one embodiment, the connection entropy between the first node and the second node is calculated based on the varying connectivity between the first node and the second node in the network structure, including:

[0014] Based on the varying number of connections between the first node and the second node in the network structure and the total number of connections in the network structure, calculate the connection probability between the first node and the second node.

[0015] Calculate the connectivity entropy between the first node and the second node using the following formula:

[0016]

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

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

[0019] In one embodiment, the varying connectivity between the first node and the second node in the network structure is determined according to the following method:

[0020] The number of physical links from the first node to the second node in the network structure is counted and used as the connectivity of the first node.

[0021] The number of physical links traversed from the first node to the next hop node in the network structure is counted and used as the active connectivity number of the first node.

[0022] The difference between the connectivity number of the first node and the active connectivity number is determined as the connectivity number that changes between the first node and the second node;

[0023] Based on the varying connectivity between the first node and the second node in the network structure and the total number of connections in the network structure, the connectivity probability between the first node and the second node is calculated, including:

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

[0025]

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

[0027] F ij Used to represent the connection 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 based on the maximum connectivity entropy and the total connectivity entropy includes:

[0029] Determine the 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 embodiment, the second metric includes information sharing entropy; wherein the degree of information cross-linking is inversely correlated with the information sharing entropy; and the flexibility of the network structure is positively correlated with the degree of information cross-linking.

[0032] In one embodiment, the information crosslinking degree of the network structure is calculated based on a second metric used to evaluate the information sharing of the network structure, including:

[0033] Calculate the information sharing entropy of the multiple sub-network structures of the network structure.

[0034] The information cross-linking degree of the network structure is calculated based on 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 represents the total number of information-sharing nodes in the network structure;

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

[0039] n ij Used to represent the number of times the i-th node in the j-th sub-network structure shares information;

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

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

[0042] In one embodiment, the information cross-linking degree of the network structure is calculated based on the information sharing entropy of the plurality of sub-network structures, including:

[0043] The information sharing entropy of the multiple sub-networks is averaged to obtain the average sharing entropy; the difference between the second set value and the average sharing 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; the information sharing entropy of each sub-network is weighted and summed to obtain the weighted information sharing entropy; the difference between the second set value and the weighted information sharing entropy is determined as the information crosslinking 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 crosslinking degree and the information crosslinking degree, including:

[0047] The flexibility of the network structure is calculated based on 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.

[0048] Secondly, an apparatus for evaluating the flexibility of a network structure is provided, the apparatus comprising:

[0049] The first calculation unit is used to calculate the physical cross-linking degree of the network structure based on a first metric used to evaluate the physical cross-linking of the network structure.

[0050] The second calculation unit is used to calculate the information crosslinking degree of the network structure according to a second metric used to evaluate the information sharing of the network structure;

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

[0052] In the aforementioned method and apparatus for evaluating the flexibility of a network structure, the physical cross-linking degree of the network structure is calculated based on a first metric used to evaluate the physical cross-linking of the network structure; the information cross-linking degree of the network structure is calculated based on 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 cross-linking degree and the information cross-linking degree. Thus, by providing the above-mentioned flexibility evaluation method, the physical cross-linking and information sharing of the network structure are evaluated, thereby obtaining the aforementioned physical cross-linking degree and information cross-linking degree, and then the flexibility of the network structure is evaluated based on these two metrics, thus realizing the evaluation of the flexibility of the network structure. Attached Figure Description

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

[0054] Figure 2 This is a schematic diagram illustrating the relationships between nodes in a network structure in one embodiment;

[0055] Figure 3 This is a schematic diagram illustrating the relationships between sub-network structures included in a network structure in one embodiment.

[0056] Figure 4 This is a schematic diagram illustrating the calculation logic of the network structure's flexibility in one embodiment;

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

[0058] Figure 6 This is an internal structural diagram of a computing device in one embodiment. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] Before introducing this application, let's first explain the technical terms involved:

[0061] 1. Operations research is a discipline that uses mathematical and modern computer science methods to study various activities and provides theories and methods for the quantitative analysis and optimization of system architecture.

[0062] 2. A mathematical model is a description of a system using mathematical concepts and language. Using mathematical models to solve problems in various business and other operations is an important part of operations research. Mathematical models facilitate the description of real-world phenomena; for quantifiable components, they can be accurately expressed using mathematical equations or computer languages, solving problems related to phenomena that are too large or too small, too complex, or invisible and intangible.

[0063] Based on this, this application provides a method for evaluating the flexibility of a network structure. The method calculates the physical interconnectivity of the network structure according to a first metric used to evaluate the physical interconnectivity; calculates the information interconnectivity of the network structure according to a second metric used to evaluate the information sharing of the network structure; and evaluates the flexibility of the network structure based on the physical interconnectivity and the information interconnectivity. By analyzing the physical connectivity and information sharing interconnectivity of the network structure, a mathematical method for measuring network structure is provided.

[0064] In one embodiment, such as Figure 1 As shown, a method for evaluating the flexibility of a network structure is provided. Taking the application of this method to an electronic device as an example, the electronic device can be, but is not limited to, a server or similar device. When implementing the above method, the electronic device may include the following steps:

[0065] S11. Calculate the physical cross-linking degree of the network structure based on a first metric used to evaluate the physical cross-linking of the network structure.

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

[0067] The physical interconnections of a network structure refer to the system's composition and topology, which are fundamental to the effective connection and coordinated operation of the system with other elements. The flexibility of physical interconnections refers to the network structure's ability to adjust and rapidly reorganize its topology according to user needs and environmental changes. Even under the influence of uncertainties, the various components of the network structure can autonomously coordinate to maintain the stable operation of the entire system, reflecting the network structure's ability to adapt to changing circumstances. A highly flexible network structure must provide accurate physical interconnections for each network node. Using physical interconnections as an evaluation index of network structure flexibility can measure the reliability of network connectivity, the flexibility of module reorganization, and the flexibility of the network topology. By continuously optimizing and improving the network structure, it is possible to ensure the maximum aggregation of various network nodes and maximize the system's efficiency.

[0068] Based on this, in this step, a metric for evaluating the physical cross-linking status (physical cross-linking flexibility) of the network structure can be obtained first. In order to distinguish it from other subsequent metric indicators, this metric is marked as the first metric indicator, and then the physical cross-linking degree of the network structure is calculated based on the first metric 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 based on a second metric used to evaluate the information sharing of the network structure.

[0071] In practical implementation, the flexibility of network structure information interconnection is mainly reflected in the timely sharing of various types of information resources among different links in the network structure, achieving the goal of rapid processing, dissemination, and application of information. Information sharing is a crucial manifestation of the advantages of information interconnection and a reliable way to improve the flexibility of the network structure. By sharing information throughout the network, the uncertainty of the network structure can be effectively reduced, enabling each network node to fully grasp various types of information, continuously perceive environmental changes, promptly judge changing trends, and select appropriate routes. Furthermore, information sharing will promote the integration and aggregation of various resources in the network structure, reducing costs while improving resource utilization, enabling the entire network to achieve orderly vertical and horizontal interconnection, and achieving a flexible sharing effect of readily accessible network access.

[0072] In this step, since the information cross-linking of the network structure can also characterize the flexibility of the network structure, we can first obtain a metric for evaluating the information cross-linking (information cross-linking flexibility) of the network structure, namely the second metric mentioned above; and then use the second metric to evaluate and calculate the degree of information cross-linking of the network structure.

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

[0074] Specifically, the physical connectivity of a network reflects the flexible topology and resilience of the network structure, while the information sharing of a network reflects the interconnection of information within the network. Both connectivity and sharing bring added value to the flexible performance of the network structure.

[0075] Based on this, after obtaining the physical crosslinking degree and the information crosslinking degree of the network structure, we obtain metrics for characterizing the flexibility of physical crosslinking and metrics for characterizing the flexibility of information crosslinking. Since the flexibility of the network structure includes both the physical crosslinking flexibility and the information crosslinking flexibility, we can evaluate the flexibility of the network structure based on these two degrees, thus achieving the evaluation of the network structure's flexibility.

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

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

[0078] Specifically, due to the complexity of network structures, information is often subject to interference and impact from uncertain external factors during its flow. 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 connectivity stability of a network structure, referring to the network's ability to maintain connectivity under internal and external environments. Connectivity entropy, on the other hand, measures the uncertainty of physical cross-linking in a network structure, reflecting the interrelationships and influence between nodes. It is a key indicator of the quality of physical connections in a network structure and is determined by the number of connected nodes. Using connectivity entropy to measure the degree of physical cross-linking in a network structure, the lower the connectivity entropy, the greater the degree of physical cross-linking and the stronger the network structure's flexibility; conversely, the higher the connectivity entropy, the lower the degree of physical cross-linking and the weaker the network structure's flexibility.

[0080] Based on this, in this embodiment, step S11 can be performed according to the following process: calculate the connection entropy between the first node and the second node based on the varying connectivity 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 connection entropy and the maximum connection entropy of the network structure based on the calculated connection entropy; and determine the physical crosslinking degree of the network structure based on the maximum connection entropy and the total connection entropy.

[0081] Optionally, in one embodiment, the step of calculating the connection entropy between the first node and the second node based on the varying connectivity between the first node and the second node in the network structure can be performed according to the following process: calculating the connection probability between the first node and the second node based on the varying connectivity between the first node and the second node in the network structure and the total number of connections in the network structure; calculating the connection 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] This is used to represent the connectivity probability between the first node i and the second node j.

[0085] Based on this, the connection entropy of any two nodes in the network structure can be calculated using the aforementioned formula for calculating connection entropy.

[0086] Optionally, in one embodiment, the variable connectivity between the first node and the second node in the network structure can be determined by the following method: counting the number of physical links traversed from the first node to the second node in the network structure, as the connectivity of the first node; counting the number of physical links traversed from the first node to the next-hop node in the network structure, as the active connectivity of the first node; and determining the difference between the connectivity of the first node and the active connectivity as the variable connectivity 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 total number of physical links from the first node i to the second node j is called the connectivity of the first node i, denoted as f1; the total number of physical links from the first node i to the next hop node, that is, the total connectivity of the first step from the first node i, is called the effective active connectivity of the first node i, f2, and the rest are the variable connectivity, denoted as f1-f2.

[0088] To better understand this embodiment, Figure 2Taking the example shown, there are 6 physical links from the first node i to the second node j: 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. Therefore, the connectivity of the first node i is f1 = 6.

[0089] Also combined Figure 2 The next-hop nodes reached from the first node i are nodes 7, 1, and 4, which includes three physical links: physical link 1: first node i to node 7, physical link 2: first node i to node 1, and physical link 3: first node i to node 4. Therefore, the active connectivity number f2 of the first node i is 3.

[0090] After obtaining the connectivity number f1 and active connectivity number f2 of the first node i, we can obtain the variable connectivity number between the first node i and the second node j, i.e., f1-f2=6-3=3.

[0091] Furthermore, the following procedure can be followed to calculate the connection probability between the first node and the second node based on the varying number of connections between the first node and the second node in the network structure and the total number of connections in the network structure: the ratio between the varying number of connections and the total number of connections in 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. 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 in the network structure can be calculated using the following formula:

[0093]

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

[0095] F ij Used to represent the connection 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 in the network structure, and the value of j is also between 1 and the total number of nodes in the network structure. The total number of nodes in the network can be determined according to the actual situation, and different network structures can have the same or different total number of nodes.

[0097] Specifically, the shortest connection between two nodes within a network structure is defined as the connectivity length between the two nodes. Furthermore... Figure 2 To illustrate, the number of connections between the first node i and the second node j can be determined based on the physical links between them. Referring to the previous description of the physical links from the first node i to the second node j, taking the number of nodes traversed by the first node i to the second node j as an example, the number of connections for physical link 1 is 2, for physical link 2 it is 2, for physical link 3 it is 3, for physical link 4 it is 3, for physical link 5 it is 2, and for physical link 6 it is 3. Therefore, the shortest connection between the first node i and the second node j is 2, and the connection length between the first node i and the second node j is 2. Of course, the above number of connections can be defined in other ways, and can be set according to the actual situation. This embodiment does not limit this.

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

[0099] Maximum connected entropy of network structure The calculation formula is: Where W represents the total number of connected components mentioned above.

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

[0101]

[0102] In this formula, N can 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 aforementioned first set value can 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 can be expressed according to the following formula:

[0105]

[0106] Therefore, based on the calculation process provided above, the physical cross-linking degree of the network structure can be obtained.

[0107] The following describes the calculation process for the information cross-linking degree of the network structure:

[0108] Specifically, various types of information flow between different layers and links in any network structure. Information itself is inherently uncertain, and the network structure is a dynamic pattern of topological changes, influenced by geographical environment, electromagnetic spectrum, and other factors. Therefore, information sharing between nodes also exhibits significant uncertainty. Thus, in the mathematical description of related concepts, based on information entropy theory, an information sharing evaluation model is established, starting from the uncertainty of information sharing and the state probabilities of nodes.

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

[0110] Specifically, due to the complexity of network structures, information is often subject to interference and impact from uncertain external factors during its flow. To reflect the degree of information cross-linking in the network structure, information sharing entropy is used as a measure of the degree of information cross-linking, and an evaluation of the flexibility of information cross-linking in the network structure is given.

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

[0112] Based on this, in this embodiment, step S12 can be performed according to the following process: calculate the information sharing entropy of the multiple sub-network structures of the network structure; calculate the information cross-linking degree of the network structure based on the information sharing entropy of the multiple sub-network structures.

[0113] Specifically, the network structure can be divided into several sub-network structures. Then, the degree of information cross-linking between these sub-network structures is analyzed and solved. Based on this, the degree of information cross-linking among multiple sub-network structures within the network structure is described. Finally, based on the degree of information cross-linking among multiple sub-network structures, the information cross-linking degree of the network structure is calculated. The degree of information cross-linking of each sub-network structure can be characterized by its information sharing entropy. Therefore, assuming that the network structure N consists 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] Based on this, let's take the j-th sub-network structure as an example. The j-th 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, we can count the number of times any i-th node in the j-th sub-network structure shares information, denoted as n. ij Then it can be expressed as: Nj = (n j1 ,n j2 ,…n jm To better understand this embodiment, it can be seen that... Figure 3 The network structure shown is used as an example for illustration. Figure 3 The network structure includes three sub-network structures. Figure 3 The subnetwork structure shown by the dashed circle is: Subnetwork 1, Subnetwork 2, and Subnetwork 3. When j = 1, Subnetwork 1 includes 4 nodes: node 1, node 2, node 4, and node 7. Therefore, Subnetwork 1 can be represented as N1 = (n... 11 ,n 12 ,n 13, n 14 ),from Figure 3 It can be seen that node 7 belongs to subnetwork 1, subnetwork 2, and subnetwork 3. Therefore, the number of times node 7 shares information is 3, or n. 14 =3. Since node 4 also belongs to subnetworks 1 through 3, we can conclude that node 4 shares information 3 times, or n. 13 =3; Since node 1 and node 2 belong only to subnetwork 1, the number of times node 1 and node 2 share information is 1 each, i.e., n. 11 n 12 =1, therefore 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 can be calculated according to the following formula:

[0117]

[0118] in, Y represents the total number of information-sharing nodes in the network structure;

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

[0120] n ij Used to represent the number of times the i-th node in the j-th sub-network structure shares information;

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

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

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

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

[0125]

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

[0127] In the above method for calculating the information crosslinking degree of the network structure, the average value of the information sharing entropy of multiple sub-network structures is calculated so that the average sharing entropy can characterize the degree of information sharing of the network structure to a certain extent, that is, to a certain extent, indicate the crosslinking of the network structure. Then, by subtracting the average sharing entropy from 1, the information crosslinking degree of the network structure can be obtained.

[0128] In another embodiment, the step of calculating the information crosslinking degree of the network structure based on the information sharing entropy of the plurality of 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 a weighted summation of 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 crosslinking 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 mentioned above can be 1. Based on this, the information cross-linking degree E of the network structure can also be characterized according to the following formula:

[0130] Where, β j The weights used to represent the information sharing entropy of the j-th sub-network structure; if the information sharing entropy of the j-th sub-network structure is relatively large, then 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 information sharing entropy value, the more nodes in the corresponding sub-network structure are shared, which indicates that the corresponding sub-network structure is more important and better represents the interconnection of the entire network structure.

[0131] Therefore, the degree of information cross-linking between nodes is not simply the sum of the information content of each node, but is also closely related to the degree of information sharing between them. 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, and is well used to analyze the degree of information cross-linking in the network structure.

[0132] Based on any of the above embodiments, in this embodiment, step S13 can be performed according to the following process: calculate the flexibility of the network structure based on 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 interconnections and information sharing effects of the network, calculates the network structure flexibility using appropriate weights, and provides a mathematical method for deriving the network structure flexibility measure from physical and information interconnections. (See reference...) Figure 4 As shown.

[0134] Specifically, network connectivity reflects the flexible topology and resilience of the network structure, while information sharing among nodes reflects the interconnectivity of information within the network. Both connectivity and sharing contribute to the value of the network structure's flexibility. Combining the physical interconnections and information sharing effects of the network, we can obtain the expression for the network structure's flexibility F, as shown below:

[0135]

[0136] In the formula φ, The weighting coefficients for physical crosslinking degree L and information crosslinking degree E in the network structure can be configured according to the actual situation.

[0137] Therefore, this application's evaluation of network structure flexibility not only qualitatively measures relevant factors but also quantitatively calculates the degree of influence of these factors on the effectiveness of the network structure and grasps the changing characteristics of the network structure. This evaluation method, combining qualitative and quantitative approaches, is a prediction and assessment of the network structure's adaptability to the environment, a comprehensive estimation and identification of the network structure, and the foundation for network structure optimization and improvement.

[0138] The method for evaluating the flexibility of network structures provided in this application starts by analyzing the flexibility of the network. It mathematically models two key variables supporting network flexibility: physical cross-linking and information cross-linking. This study investigates the connectivity and information sharing capabilities of the network structure and presents a mathematical method for deriving a measure of network structure flexibility from physical and information cross-linking. The mathematical formulas show that the flexibility of the network structure is not only related to the topology but also to the degree of information sharing between links and nodes. Therefore, by utilizing network structure flexibility analysis, we can optimize and improve the network structure from the perspective of rational resource allocation and increased network reliability, enabling the network structure to have better flexible topology capabilities and rapidly move towards a direction of "link connectivity, information compatibility, and structural reconfigurability."

[0139] Furthermore, this application uses mathematical modeling to describe the physical and information cross-linking flexibility of the network and its changing processes, thereby transforming the network structure problem into a measurable problem and laying the foundation for applying mathematical methods to solve the network structure flexibility problem.

[0140] This completes the design of a method for evaluating the flexibility of network structures.

[0141] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed 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 some of the sub-steps or stages of other steps.

[0142] Based on the same technical concept, and referencing Figure 5 The schematic diagram shown illustrates that this application also provides an apparatus for evaluating the flexibility of a network structure, the apparatus comprising:

[0143] The first calculation unit 51 is used to calculate the physical cross-linking degree of the network structure based on a first metric used to evaluate the physical cross-linking of the network structure.

[0144] The second calculation unit 5 is used to calculate the information cross-linking degree of the network structure according to a second metric used to evaluate the information sharing of the network structure;

[0145] Evaluation unit 53 is used to evaluate the flexibility of the network structure based on the physical crosslinking degree and the information crosslinking degree.

[0146] Thus, by providing the aforementioned apparatus for evaluating the flexibility of a network structure, the physical cross-linking and information sharing of the network structure are evaluated, thereby obtaining the aforementioned physical cross-linking degree and information cross-linking degree. Based on these two indicators, the flexibility of the network structure is evaluated, thus realizing the evaluation of the flexibility of the network structure.

[0147] In one embodiment, a computing device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a method for evaluating the flexibility of a network structure.

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

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

[0150] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, 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. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0151] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for evaluating the flexibility of a network structure, characterized in that, The method includes: The physical cross-linking degree of the network structure is calculated based on a first metric used to evaluate the physical cross-linking of the network structure. The information cross-linking degree of the network structure is calculated based on a second metric used to evaluate the information sharing of the network structure; wherein: The second metric includes information sharing entropy; the information cross-linking degree is inversely correlated with the information sharing entropy; the flexibility of the network structure is positively correlated with the information cross-linking degree; calculating the information cross-linking degree of the network structure includes: calculating the information sharing entropy of multiple sub-network structures divided by the network structure respectively; calculating the information cross-linking degree of the network structure based on the information sharing entropy of the multiple sub-network structures; and calculating the information sharing entropy of each sub-network structure according to the following formula: in, , Used to represent the total number of information-sharing nodes in the network structure; The information sharing entropy used to represent the structure of the j-th sub-network; Used to represent the number of times the i-th node in the j-th sub-network structure shares information; , The probability used to represent the information sharing entropy of the j-th sub-network structure; The weight used to represent the influence of the information sharing degree of the i-th node on the structure of the j-th sub-network; The flexibility of the network structure is evaluated based on the physical cross-linking degree and the information cross-linking degree.

2. The method according to claim 1, characterized in that, The first metric includes connectivity entropy, wherein the physical cross-linking degree is inversely 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, The physical cross-linking degree of the network structure is calculated based on a first metric used to evaluate the physical cross-linking of the network structure, including: Based on the varying connectivity between the first node and the second node in the network structure, calculate the connectivity entropy between the first node and the second node, where the first node and the second node are any two nodes in the network structure. Based on the calculated connectivity entropy, determine the total connectivity entropy and maximum connectivity entropy of the network structure; The physical cross-linking degree of the network structure is determined based on the maximum connectivity entropy and the total connectivity entropy.

4. The method according to claim 3, characterized in that, Based on the varying connectivity between the first and second nodes in the network structure, the connectivity entropy between the first and second nodes is calculated, including: Based on the varying number of connections between the first node and the second node in the network structure and the total number of connections in the network structure, calculate the connection probability between the first node and the second node. Calculate the connectivity entropy between the first node and the second node using the following formula: in, Used to represent the connectivity entropy between the first node i and the second node j; This is 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 varying connectivity between the first and second nodes in the network structure is determined using the following method: The number of physical links from the first node to the second node in the network structure is counted and used as the connectivity of the first node. The number of physical links traversed from the first node to the next hop node in the network structure is counted and used as the active connectivity number of the first node. The difference between the connectivity number of the first node and the active connectivity number is determined as the connectivity number that changes between the first node and the second node; Based on the varying connectivity between the first node and the second node in the network structure and the total number of connections in the network structure, the connectivity probability between the first node and the second node is calculated, including: The ratio between the variable number of connections and the total number of connections in the network structure is determined as the connectivity probability. The total number of connections in the network structure is calculated according to the following formula: ； Used to represent the total number of connections; Used to represent the connection length between the first node i and the second node j.

6. The method according to claim 3, characterized in that, The physical cross-linking degree of the network structure is determined based on the maximum connectivity entropy and the total connectivity entropy, including: Determine the 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. An apparatus for evaluating the flexibility of a network structure, characterized in that, The device includes: The first calculation unit is used to calculate the physical cross-linking degree of the network structure based on a first metric used to evaluate the physical cross-linking of the network structure. The second calculation unit is used to calculate the information crosslinking degree of the network structure based on a second metric used to evaluate the information sharing of the network structure; wherein: The second metric includes information sharing entropy; the information cross-linking degree is inversely correlated with the information sharing entropy; the flexibility of the network structure is positively correlated with the information cross-linking degree; calculating the information cross-linking degree of the network structure includes: calculating the information sharing entropy of multiple sub-network structures divided by the network structure respectively; calculating the information cross-linking degree of the network structure based on the information sharing entropy of the multiple sub-network structures; and calculating the information sharing entropy of each sub-network structure according to the following formula: in, , Used to represent the total number of information-sharing nodes in the network structure; The information sharing entropy used to represent the structure of the j-th sub-network; Used to represent the number of times the i-th node in the j-th sub-network structure shares information; , The probability used to represent the information sharing entropy of the j-th sub-network structure; The weight used to represent the influence of the information sharing degree of the i-th node on the structure of the j-th sub-network; An evaluation unit is used to evaluate the flexibility of the network structure based on the physical crosslinking degree and the information crosslinking degree.

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