A method, device and equipment for dynamically grading the geographic disaster survivability of an optical fiber communication system, and a storage medium

Abstract

The application discloses a kind of optical fiber communication system geographic disaster invulnerability dynamic grade division methods, this method includes: obtaining n The optical fiber communication system geographic disaster invulnerability evaluation index data of being graded as sample, wherein the invulnerability evaluation index data includes network invulnerability evaluation index data and service invulnerability evaluation index data;Obtain the invulnerability grading number K ;Based on invulnerability evaluation index data and invulnerability grading number, using clustering analysis method, optical fiber communication system is divided into K Grade.The application also discloses a kind of optical fiber communication system geographic disaster invulnerability dynamic grade division device.The application collects the network invulnerability index and service invulnerability index data of optical fiber communication system as the initial data of dynamic grade division, and by obtaining classification demand, using clustering analysis method, dynamically adjust invulnerability grade division interval, so that grade division mode is more scientific.

Description

Technical Field

[0001] This invention relates to the field of communication network technology, and more specifically, to a method, apparatus, equipment, and storage medium for dynamically classifying the geographical disaster resilience of an optical fiber communication system. Background Technology

[0002] The rapid construction of fiber optic communication systems has brought tremendous convenience to people's lives. However, the wide coverage area and complex operating environment of my country's fiber optic communication systems mean they are frequently damaged by geographical disasters, causing service interruptions and seriously affecting economic and national property security. To effectively reduce the destructive impact of geographical disasters on fiber optic communication systems, researchers have proposed many methods for assessing their resilience to such disasters. Among these, resilience level classification is of particular practical significance for the operation, maintenance, and protection of fiber optic communication systems.

[0003] Currently, there is no clear standard for classifying the resilience of fiber optic communication systems. However, various methods have been proposed to classify the degree of damage caused by disasters, such as the method for classifying the damage to communication base stations caused by earthquakes. The commonly used classification method is a static one, requiring extensive data training and expert scoring, especially in determining the level boundaries, which is largely a policy-driven and experience-based process. Therefore, there is an urgent need for a more accurate and objective method for classifying the geographical disaster resilience of fiber optic communication systems as a standard for evaluating their performance. Summary of the Invention

[0004] To address at least one deficiency or improvement need in the existing technology, this invention provides a method, apparatus, equipment, and storage medium for dynamic classification of geographical disaster resilience of optical fiber communication systems. Based on static classification results, it integrates dynamic classification methods to ensure that the classification is more scientific and reasonable.

[0005] To achieve the above objectives, according to a first aspect of the present invention, a method for dynamic classification of geographical disaster resilience levels of an optical fiber communication system is provided, the method comprising: S1. Obtain n Geographic disaster resilience assessment index data of a fiber optic communication system to be graded is used as a sample, wherein the resilience assessment index data includes network resilience assessment index data and service resilience assessment index data. n The number of samples in the optical fiber communication system; S2. Obtain the number of survivability ratings. K ; S3. Based on the resilience evaluation index data and the number of resilience levels, cluster analysis is used to divide the optical fiber communication system into... K class.

[0006] Furthermore, the aforementioned method for dynamically classifying the geographical disaster resilience of fiber optic communication systems also includes: The service resilience evaluation index data includes at least service resilience evaluation index data under unprotected conditions and service resilience evaluation index data under protected conditions.

[0007] Furthermore, the aforementioned method for dynamically classifying the geographical disaster resilience of fiber optic communication systems also includes: For each fiber optic communication system to be graded, obtain the information in... p The network resilience evaluation index data, the unprotected service resilience evaluation index data, and the protected service resilience evaluation index data under various earthquake risk probabilities; the above. p The index data obtained from the three evaluation indicators are used as the original geographical disaster resilience evaluation index data for the optical fiber communication system to be classified.

[0008] Furthermore, the aforementioned method for dynamically classifying the geographical disaster resilience of fiber optic communication systems also includes: S31. Standardize the damage resistance evaluation index data of the sample to obtain the grading data of the sample; S32. Adopt K - The mean clustering analysis method, based on the hierarchical data, divides the optical fiber communication system into... K class.

[0009] Furthermore, the aforementioned method for dynamically classifying the geographical disaster resilience of fiber optic communication systems also includes: S311. Obtain the survivability assessment results of the fiber optic communication system to be graded, and use them as the original sample data for the dynamic grading algorithm. ,in , n The number of samples in the optical fiber communication system; , m The number of original sample data for each fiber optic communication system to be graded; S312. Standardize the original sample data to obtain standardized data. The standardized data The calculation method is to obtain the first j Standard deviation of each evaluation indicator : ; in the formula For the first i The first of the samples j Evaluation indicator data values ​​under each evaluation indicator; For the first jThe average value of each evaluation indicator data; the original data is standardized, and the calculation method is as follows: ; S313. Calculate the grading data of the sample, using the following formula: .

[0010] According to a second aspect of the present invention, a dynamic classification device for geographical disaster resilience of an optical fiber communication system is also provided, comprising: The receiving module is configured to acquire n Data on the geographical disaster resilience assessment indicators of the desired fiber optic communication system are required, and the number of resilience levels will be obtained. K ;in, n The number of samples in the optical fiber communication system; The calculation module is configured to, based on the resilience evaluation index data and the number of resilience levels, use cluster analysis to classify the optical fiber communication system into... K class; The resilience evaluation index data includes network resilience evaluation index data and service resilience evaluation index data.

[0011] Furthermore, the aforementioned dynamic classification device for the geographical disaster resilience of optical fiber communication systems also includes: The service resilience evaluation index data includes at least service resilience evaluation index data under unprotected conditions and service resilience evaluation index data under protected conditions.

[0012] Furthermore, the aforementioned dynamic classification device for the geographical disaster resilience of optical fiber communication systems also includes: For each fiber optic communication system to be graded, obtain the information in... p The network resilience evaluation index data, the unprotected service resilience evaluation index data, and the protected service resilience evaluation index data under various earthquake risk probabilities; the above. p The index data obtained from the three evaluation indicators are used as the original geographical disaster resilience evaluation index data for the optical fiber communication system to be classified.

[0013] According to a third aspect of the present invention, a dynamic classification device for geographical disaster resilience of an optical fiber communication system is also provided, comprising at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program that, when executed by the processing unit, causes the processing unit to perform the steps of any of the methods described above.

[0014] According to a fourth aspect of the invention, a storage medium is also provided that stores a computer program executable by an access authentication device, which, when run on the access authentication device, causes the access authentication device to perform the steps of any of the methods described above.

[0015] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: (1) The dynamic classification method for geographical disaster resilience of optical fiber communication system provided by the present invention collects two objective index data of optical fiber communication system, namely network resilience index and service resilience index data, as the initial data for dynamic classification. It can effectively reflect the connection and difference between optical fiber communication system and complex network, making the classification method more scientific. (2) The dynamic classification method for geographical disaster resilience of optical fiber communication system provided by the present invention, based on the traditional static classification results, obtains classification requirements and uses cluster analysis to dynamically adjust the classification interval of resilience, so that the classification can meet different requirements and improve accuracy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a method for dynamically classifying the geographical disaster resilience of an optical fiber communication system according to an embodiment of the present invention; Figure 2 A detailed flowchart illustrating a method for dynamically classifying the geographical disaster resilience of an optical fiber communication system, as provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the dynamic classification process in a method for dynamically classifying the geographical disaster resilience of an optical fiber communication system according to an embodiment of the present invention; Figure 4 This is the original data map in a method for dynamically classifying the geographical disaster resilience of an optical fiber communication system according to an embodiment of the present invention; Figure 5 This is a standardized data map in a method for classifying the dynamic level of geographical disaster resilience of an optical fiber communication system according to an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0019] The terms "first," "second," "third," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0020] like Figures 1-2 As shown in the first embodiment, a method for dynamically classifying the geographical disaster resilience of an optical fiber communication system is provided. This method includes: S1. Obtain n Geographic disaster resilience assessment index data of a fiber optic communication system to be graded is used as a sample, wherein the resilience assessment index data includes network resilience assessment index data and service resilience assessment index data. n The number of samples in the optical fiber communication system; S2. Obtain the number of survivability ratings. K ; S3. Based on the resilience evaluation index data and the number of resilience levels, cluster analysis is used to divide the optical fiber communication system into... K class.

[0021] The present invention provides a dynamic classification method for the geographical disaster resilience of optical fiber communication systems. It collects two objective indicator data of optical fiber communication systems—network resilience index and service resilience index—as the initial data for dynamic classification. This method can effectively reflect the connection and difference between optical fiber communication systems and complex networks, making the classification method more scientific. Furthermore, by obtaining classification requirements and using cluster analysis, the resilience classification interval is dynamically adjusted, so that the classification can meet different needs and improve accuracy.

[0022] The network resilience evaluation index used in this invention InThis is a common metric used in the field of fiber optic communication to evaluate resilience, and it is a type of objective data. The service resilience metric in this invention reflects the total amount of service that the network can transmit completely after suffering earthquake damage, and it is also a type of objective data. Using the aforementioned objective data to perform cluster analysis on the resilience of fiber optic communication systems can make the classification more scientific.

[0023] Furthermore, this embodiment also includes: The service resilience evaluation index data includes at least service resilience evaluation index data under unprotected conditions and service resilience evaluation index data under protected conditions.

[0024] Based on the first embodiment, as a second embodiment of the present invention, it further includes: For each fiber optic communication system to be graded, obtain the information in... p The network resilience evaluation index data, the unprotected service resilience evaluation index data, and the protected service resilience evaluation index data under various earthquake risk probabilities; the above. p The index data obtained from the three evaluation indicators are used as the original geographical disaster resilience evaluation index data for the optical fiber communication system to be classified.

[0025] The earthquake risk probability described in this invention refers to the probability that an earthquake will occur at the location of the communication system, sufficient to damage it. A higher earthquake risk probability indicates a higher probability of an earthquake occurring; a lower earthquake risk probability indicates a lower probability of an earthquake occurring. When selected... p When considering various earthquake risk probabilities, data on network resilience evaluation indicators, unprotected service resilience evaluation indicators, and protected service resilience evaluation indicators can be obtained for each earthquake risk probability. Therefore, the total number of data obtained is... p ×3.

[0026] The service resilience index mentioned in this invention refers to an index closely related to service characteristics, including service resilience under unprotected and protected conditions, and is defined as follows: (1) In the formula, This represents the total remaining service rate of the network under both unprotected and protected conditions. This refers to the network's service rate before and after the damage; the metric reflects the total amount of service the network can transmit intact after an earthquake. The calculation method is as follows: First, traverse all shortest paths and allocate routes according to the initial service traffic imported by the user to obtain the service traffic of each link before the network is damaged.

[0027] Second, a link in the network is damaged, and the services that passed through this path before the network was damaged are recorded. Without protection, these services will not be able to be transmitted, resulting in service loss; with protection, the next shortest path is searched for these services. If a next shortest path that meets the capacity requirements exists, the service will be transmitted normally; otherwise, the service will be lost.

[0028] Based on the second embodiment, as a third embodiment of the present invention, it further includes: S31. Standardize the damage resistance evaluation index data of the sample to obtain the grading data of the sample; S32. Adopt K - The mean clustering analysis method, based on the hierarchical data, divides the optical fiber communication system into... K class.

[0029] Furthermore, this embodiment also includes: S311. Obtain the survivability assessment results of the fiber optic communication system to be graded, and use them as the original sample data for the dynamic grading algorithm. ,in , n The number of samples in the optical fiber communication system; , m The number of original sample data for each fiber optic communication system to be graded; S312. Standardize the original sample data to obtain standardized data. The standardized data The calculation method is to obtain the first j Standard deviation of each evaluation indicator : ; in the formula For the first i The first of the samples j Evaluation indicator data values ​​under each evaluation indicator; For the first j The average value of each evaluation indicator data; the original data is standardized, and the calculation method is as follows: ; S313. Calculate the grading data of the sample, using the following formula: .

[0030] This embodiment uses the following method: K - The mean clustering method is easily understood by those skilled in the art; other clustering analysis methods can also achieve the effect of dynamic hierarchical classification. K -The basic principle of the mean clustering dynamic hierarchical method is as follows: Figure 3As shown, this is a numerical classification method that uses actual quantitative indicators as a basis and employs cluster analysis principles to dynamically classify samples. If each object (sample or variable) is considered a point in the classification space, clustering is the process of grouping points that are close together according to certain principles. This invention, based on the network resilience indicators of fiber optic communication systems as the classification criterion, comprehensively considers service resilience indicator data as the initial data for dynamic classification. This effectively reflects the connection and differences between fiber optic communication systems and complex networks, making the classification method more scientific.

[0031] The determination of grading boundaries follows these steps: (1) The optical fiber communication systems to be classified are taken as the sampling population, and the sampling size is n; (2) Obtain the survivability assessment results of each optical fiber communication system as the sample raw data for the dynamic grading algorithm. ; (3) Standardize the original data to obtain standardized data. First, obtain the standard deviation of the j-th evaluation index. : (2) In the formula, X ij X is the value of the j-th evaluation index for the i-th sample; j Let j be the average value of the j-th evaluation parameter. Then, the original data is standardized. This project adopts the standard deviation method for standardization, and its calculation method is shown in formula (3): (3) (4) Determine the initial classification and assign values ​​as follows: (4) (5) (6) When all samples are divided into K classes, the initial classification of each sample can be obtained using the following formula: (7) In the formula: IFLX represents rounding the number in parentheses; N(i) represents the level number to which each sample belongs.

[0032] (5) Calculate the centroid (mean of the sample) of each level sample and use the obtained centroid as the initial grading standard.

[0033] (6) Calculate the distance of each sample to the centroid (grading standard) of each category, and classify the sample into the nearest category according to the principle of closest distance; (7) Recalculate the centers of gravity of each type as the new classification criteria; (8) Following the idea of ​​the iterative method, repeatedly adjust the category of each sample, calculate the new centroid, and check whether the centroids obtained in the previous two times are the same. If they are exactly the same, output the final classification result and give the stability level according to the sample number. (9) Calculate the distance from each sample in each level to the centroid of the level, and obtain the sample whose value is greater than the centroid and whose distance is the largest. And the sample whose value is smaller than the centroid and has the largest distance , where g represents the level number; Calculate the samples of the previous level and the next level Distance, using the median distance as the boundary between the previous and next levels, redefines the static hierarchical limits.

[0034] As a fourth embodiment of the present invention, a simulation calculation example of a method for classifying the dynamic level of geographical disaster resilience of an optical fiber communication system is provided as follows: Step 1: Take 28 samples, each containing 12 indicators. The 12 indicators for each sample simulate four different earthquake risk probabilities. Obtain network resilience evaluation index data, unprotected service resilience evaluation index data, and protected service resilience evaluation index data for each risk probability. The simulated four earthquake risk probabilities are shown in Table 1: Table 1 Earthquake Risk Probability Different earthquake risk probabilities reflect the level of seismic activity in a region. A higher earthquake risk probability indicates a higher probability of an earthquake occurring, while a lower probability indicates a lower probability of an earthquake occurring. The reason for setting different probabilities is that the level of seismic activity in networks varies across different regions. For example, the earthquake risk probability of networks in some regions is mostly below 0.2, while the earthquake risk probability of networks in other regions may be above 0.5.

[0035] Step Two: Obtain the survivability assessment results for each fiber optic communication system, which will serve as the raw sample data for the dynamic grading algorithm. This raw data is as follows: Figure 4 As shown. Figure 4 Each row represents a sample of an optical fiber communication system, resulting in a total of 28 rows and 12 columns of data.

[0036] Step 3: As described in step S312, standardize the original data to obtain standardized data. Standardized data is as follows: Figure 5 As shown in the figure. Further hierarchical data are shown in Table 2.

[0037] Table 2. Sample grading data Step 4: Use K - The mean clustering method, based on the above hierarchical data, iteratively obtains... K The levels are classified as follows: As another embodiment of the present invention, a dynamic classification device for geographical disaster resilience of an optical fiber communication system is provided, comprising: The receiving module is configured to acquire n Data on the geographical disaster resilience assessment indicators of the desired fiber optic communication system are required, and the number of resilience levels will be obtained. K ;in, n The number of samples in the optical fiber communication system; The calculation module is configured to, based on the resilience evaluation index data and the number of resilience levels, use cluster analysis to classify the optical fiber communication system into... K class; The resilience evaluation index data includes network resilience evaluation index data and service resilience evaluation index data.

[0038] Furthermore, this embodiment also includes: The service resilience evaluation index data includes at least service resilience evaluation index data under unprotected conditions and service resilience evaluation index data under protected conditions.

[0039] Furthermore, this embodiment also includes: For each fiber optic communication system to be graded, obtain the information in... p The network resilience evaluation index data, the unprotected service resilience evaluation index data, and the protected service resilience evaluation index data under various earthquake risk probabilities; the above. p The index data obtained from the three evaluation indicators are used as the original geographical disaster resilience evaluation index data for the optical fiber communication system to be classified.

[0040] As another embodiment of the present invention, a dynamic classification device for geographical disaster resilience of an optical fiber communication system is provided, which includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit performs the steps of any of the methods described above.

[0041] As another embodiment of the present invention, a storage medium is provided that stores a computer program executable by an access authentication device, which, when run on the access authentication device, causes the access authentication device to perform the steps of any of the methods described above.

[0042] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for dynamically classifying the geographical disaster resilience of an optical fiber communication system, characterized in that, include: S1. Obtain n Geographic disaster resilience assessment index data of a fiber optic communication system to be graded is used as a sample, wherein the resilience assessment index data includes network resilience assessment index data and service resilience assessment index data. n The number of samples in the optical fiber communication system; S2. Obtain the number of survivability ratings. K ; S3. Based on the resilience evaluation index data and the number of resilience levels, cluster analysis is used to divide the optical fiber communication system into... K class; Step S1 further includes: The service resilience evaluation index data includes at least service resilience evaluation index data under unprotected conditions and service resilience evaluation index data under protected conditions; For each fiber optic communication system to be graded, obtain the information in... p The network resilience evaluation index data under various earthquake risk probabilities, the service resilience evaluation index data under unprotected conditions, and the service resilience evaluation index data under protected conditions; the above. p Three evaluation index data points serve as the original geographical disaster resilience evaluation index data for the fiber optic communication system to be graded.

2. The method for dynamic classification of geographical disaster resilience of optical fiber communication systems as described in claim 1, characterized in that, Step S3 includes: S31. Standardize the damage resistance evaluation index data of the sample to obtain the grading data of the sample; S32. Adopt K - The mean clustering analysis method, based on the hierarchical data, divides the optical fiber communication system into... K class.

3. The method for dynamic classification of geographical disaster resilience of optical fiber communication systems as described in claim 2, characterized in that, Step S31 specifically includes: S311. Obtain the survivability assessment results of the fiber optic communication system to be graded, and use them as the original sample data for the dynamic grading algorithm. ,in , n The number of samples in the optical fiber communication system; , m The number of original sample data for each fiber optic communication system to be graded; S312. Standardize the original sample data to obtain standardized data. The standardized data The calculation method is to obtain the first j Standard deviation of each evaluation indicator : ； in the formula For the first i The first of the samples j Evaluation indicator data values ​​under each evaluation indicator; For the first j The average value of each evaluation indicator data; the original data is standardized, and the calculation method is as follows: ； S313. Calculate the grading data of the sample, using the following formula: 。 4. A dynamic classification device for geographical disaster resilience of an optical fiber communication system, characterized in that, include: The receiving module is configured to acquire n Data on the geographical disaster resilience assessment indicators of the desired fiber optic communication system are required, and the number of resilience levels will be obtained. K ;in, n The number of samples in the optical fiber communication system; The calculation module is configured to, based on the resilience evaluation index data and the number of resilience levels, use cluster analysis to classify the optical fiber communication system into... K class; The resilience evaluation index data includes network resilience evaluation index data and service resilience evaluation index data; Also includes: The service resilience evaluation index data includes at least service resilience evaluation index data under unprotected conditions and service resilience evaluation index data under protected conditions; For each fiber optic communication system to be graded, obtain the information in... p The network resilience evaluation index data under various earthquake risk probabilities, the service resilience evaluation index data under unprotected conditions, and the service resilience evaluation index data under protected conditions; the above. p Three evaluation index data points serve as the original geographical disaster resilience evaluation index data for the fiber optic communication system to be graded.

5. A device for dynamically classifying the geographical disaster resilience of an optical fiber communication system, characterized in that, It includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program that, when executed by the processing unit, causes the processing unit to perform the steps of the method according to any one of claims 1 to 3.

6. A storage medium, characterized in that, It stores a computer program executable by an access authentication device, which, when run on the access authentication device, causes the access authentication device to perform the steps of the method according to any one of claims 1 to 3.

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