CN116150257B - Visual analysis method, system and storage medium for electric power communication optical cable resources - Google Patents
Visual analysis method, system and storage medium for electric power communication optical cable resources Download PDFInfo
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Abstract
The application relates to a visual analysis method, a visual analysis system and a visual analysis storage medium for electric power communication optical cable resources, wherein the visual analysis method comprises the following specific steps: optical cable resource information data set arrangement and matrix construction; visualizing the optical cable resource information; carrying out data analysis on optical cable resource information based on a complex network theory, carrying out statistical analysis on global distribution conditions of various optical cable resource information, and identifying key optical cables; the optical cable resource information visualization unit interactively operates. The method and the system realize visualization and analysis of various optical cable resource information, provide multi-angle efficient cognition for operators to excavate various optical cable resource information, improve intuitiveness and readability of the optical cable resource information, ensure effective acquisition of the optical cable resource information by related operators, and improve operation and maintenance management working efficiency of the optical cable.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method, a system, and a storage medium for visual analysis of power communication optical cable resources.
Background
As a main mode of the power communication network, the optical cable network is a main carrier of the power dispatching data network and the power comprehensive data network, and the optical cable network runs through six links of power generation, power transmission, power transformation, power distribution, power consumption and dispatching of the power system, thereby powerfully guaranteeing the communication needs of the services such as power production, construction, administration, dispatching, relay protection, safety automatic devices and the like, and becomes an important means for ensuring the safe, stable, economic and reliable operation of a power grid, and is an important infrastructure of the power system. Meanwhile, with the development of a novel power system, the importance of an optical cable network is increasingly highlighted, and the operation and maintenance management work is an important problem of the safe production of a power grid. The basis of the operation and maintenance management work of the optical cable network is various optical cable information. In actual work, service personnel need to constantly search various optical cable resource information data and analyze the data to acquire effective knowledge.
In recent years, with the increase of the power communication demands of the construction of a novel power system, the optical cable network is increasingly large in scale, and various optical cable resource information is increasingly complicated. The large-scale and complicated information data and knowledge of the optical cable resources make the acquisition of the effective information of various optical cable resources difficult, influence the evaluation and judgment of service personnel on the running state of the optical cable network, lead to lower working efficiency of the operation and maintenance management of the current optical cable, and can not meet the requirements of safety, reliability, economy, high efficiency and real-time performance of the electric power communication network. How to help business personnel to intuitively, timely and effectively acquire various optical fiber resource information becomes an important problem to be solved in the operation and maintenance management work of the current optical cable. However, the related research of the problem is relatively lacking.
Disclosure of Invention
The embodiment of the application aims to provide a visual analysis method, a visual analysis system and a visual analysis storage medium for power communication optical cable resources, so that the intuitiveness and the availability of large-scale and complicated optical cable resource information are improved, and the quality and the efficiency of optical cable operation and maintenance management work are improved.
In order to achieve the above purpose, the present application provides the following technical solutions:
in a first aspect, an embodiment of the present application provides a method for visualizing optical cable resource information, including the following specific steps:
optical cable resource information data set arrangement and matrix construction;
visualizing the optical cable resource information;
carrying out data analysis on optical cable resource information based on a complex network theory, carrying out statistical analysis on global distribution conditions of various optical cable resource information, and identifying key optical cables;
the optical cable resource information visualization unit interactively operates.
The optical cable resource information data set comprises an optical cable network topology data set, a fiber core service data set, a fiber core availability degree data set and a fiber core quality data set, wherein the optical cable network topology data set refers to a data set described by the connection relation of an optical cable to a communication site, the fiber core service data set refers to a data set of services carried by each fiber core in the optical cable and scheduling grades thereof, the fiber core availability degree refers to a data set of usable fiber cores in the current optical cable, and the fiber core quality data set refers to a data set described by the abnormal quality condition in the current optical cable.
The optical cable resource information matrix structure is specifically an optical cable network topology matrix A= { a ij } N*N ，a ij Representing the connection relation between the communication station node i and the communication station node j in the network, wherein N is the total number of the communication station nodes, and a is when an optical cable is directly connected between the node i and the node j ij =1; otherwise, a ij =0, core traffic distribution matrix D (k) ={d (k) ij And (d) representing the distribution of the traffic quantity of different scheduling levels on different optical cables (k) ij Representing the number of services with a load scheduling level k on an optical cable connecting a communication station node i and a communication station node j, and the core availability degree matrix is E= { E ij -a matrix of cores q= { Q, wherein eij represents the number of cores available on the cable connecting the communication station node i and the communication station node j ij -characterizing the distribution of the number of faulty cores on different cables, where q ij Representing the number of failed cores on the fiber optic cable connecting communication station node i and communication station node j.
The optical cable resource information visualization specifically includes generating an optical cable network based on an optical cable network topology matrix A
Network topology, using nodes to characterize communication sites, when a ij When=1, generating an edge connecting the communication station node i and the communication station node j; when a is ij When=0, there is no edge between the communication station node i and the communication station node j;
fiber core based service distribution matrix D (k) Generating a fiber core service distribution diagram, and distinguishing services with different scheduling levels through different colors; then, the thickness of the edge is equal to d (k) ij The positive correlation is that the larger the numerical value is, the more the number of the traffic of the bearing scheduling level x is, and the thicker the edge is;
generating a fiber core availability degree graph based on the fiber core availability degree matrix E, and distinguishing the available fiber core quantity in the optical cable by the thickness of the edge, namely the thickness of the edge and E ij The larger the number, the thicker the line, the more cores are available;
and generating a fiber core quality diagram based on the fiber core quality matrix Q, and based on the optical cable network topology diagram, performing numerical marking on the edges of the topology diagram to realize visualization of the number of fiber core faults on the optical cable.
The analysis of the optical cable resource information data based on the complex network theory carries out the statistical analysis of the global distribution condition of various optical cable resource information and identifies the key optical cable specifically,
a fiber optic cable network topology analysis, comprising: analyzing the degree distribution characteristics, the community structure and the homography characteristics and identifying key bridge optical cables;
an optical cable network traffic distribution analysis comprising: the statistical characteristic analysis of the distribution of the service scheduling level and the key optical cable identification based on the comprehensive service weight;
an analysis of the availability of fiber cores of a fiber optic cable network, comprising: the fiber core availability geographic distribution statistical feature analysis and fiber core resource tension key optical cable identification;
an optical cable network core quality condition analysis comprising: and (5) carrying out geographical distribution statistical feature analysis on the number of the failed fiber cores and identifying the high-failure-rate key optical cable.
The interactive operation of the optical cable resource information visualization unit comprises zoom adjustment, node dragging and multi-graph comparison.
Second aspect embodiments of the present application provide a system for visualizing information about optical cable resources, comprising,
the optical cable resource information data set arrangement module is used for arranging an optical cable network topology data set, a fiber core service data set, a fiber core availability data set and a fiber core quality data set and sending the optical cable network topology data set, the fiber core service data set, the fiber core availability data set and the fiber core quality data set to the optical cable resource information matrix construction module;
the optical cable resource information matrix construction module is used for constructing the optical cable network topology data set, the fiber core service data set, the fiber core availability data set and the fiber core quality data set which are sent by the optical cable resource information data set arrangement module into an optical cable network topology matrix, a fiber core service distribution matrix, a fiber core availability matrix and a fiber core quality matrix;
the optical cable resource information visualization module is used for respectively generating an optical cable network topology map, a fiber core service distribution map, a fiber core availability map and a fiber core quality map from the optical cable network topology matrix, the fiber core service distribution matrix, the fiber core availability map and the fiber core quality matrix which are constructed by the optical cable resource information matrix construction module;
the optical cable resource information data analysis module is used for analyzing the optical cable network topological graph, the fiber core service distribution graph, the fiber core availability degree graph and the fiber core quality graph which are generated by the optical cable resource information visualization module;
the visualization unit interactive operation module is used for performing scaling adjustment, node dragging and multi-graph comparison operations on the optical cable network topological graph, the fiber core service distribution graph, the fiber core availability degree graph and the fiber core quality graph which are generated by the optical cable resource information visualization module.
In a third aspect, embodiments of the present application provide a computer readable storage medium storing program code which, when executed by a processor, implements the steps of the method for visualizing information about optical cable resources as described above.
Compared with the prior art, the invention has the beneficial effects that:
1) Aiming at the problem of insufficient analysis of optical cable resource information data in the existing research, the method of the invention uses a matrix mathematical model to carry out mathematical modeling on multi-dimensional optical cable resource information such as optical cable-station connection relation, fiber core bearing service, fiber core availability, fiber core quality and the like, and simultaneously carries out analysis on macroscopic and local layers, thereby being capable of assisting an optical cable operation and maintenance manager to establish overall understanding of optical cable network resource characteristics and mining potential modes possibly contained.
2) Aiming at the problem of lack of visual research on optical cable resource information data, the invention fuses multi-source data such as optical cable network topology fiber core bearing service, fiber core availability, fiber core quality and the like, utilizes a complex network diagram model to visualize the optical cable resource information data in multiple dimensions, improves the readability and the observability of the optical cable resource information data, and improves the analysis efficiency.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of a cable network topology visualization of the present invention;
FIG. 3 is a schematic view of a traffic distribution visualization of the present invention;
FIG. 4 is a schematic view of a visual representation of the core availability of the present invention;
FIG. 5 is a schematic view of a visualization of the core quality condition of the present invention;
fig. 6 is a system diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The terms "first," "second," and the like, are used merely to distinguish one entity or action from another entity or action, and are not to be construed as indicating or implying any actual such relationship or order between such entities or actions.
Referring to fig. 1, an embodiment of the present application provides a method for visualizing optical cable resource information, including the following specific steps:
optical cable resource information data set arrangement and matrix construction;
visualizing the optical cable resource information;
carrying out data analysis on optical cable resource information based on a complex network theory, carrying out statistical analysis on global distribution conditions of various optical cable resource information, and identifying key optical cables;
the optical cable resource information visualization unit interactively operates.
Optical cable resource information modeling, comprising: optical cable network topology modeling, optical cable service distribution modeling, fiber core availability modeling and fiber core quality modeling.
The optical cable network topology modeling mainly comprises the following steps:
step one: and combing to obtain a topology related data set, namely the connection relation between the optical cable and the communication site, aiming at the optical cable network in a certain area.
Step two: from the topology dataset, the topology relationship is described as a matrix a= { a ij } N*N ，a ij Representing the connection relation between the communication station node i and the communication station node j in the network, and N is the total number of the communication station nodes. A when there is a direct connection of the optical cable between node i and node j ij =1; otherwise, a ij =0。
The optical cable service distribution modeling mainly comprises the following steps:
step one: and combing to obtain a fiber core service data set, namely a data set of the service carried by each fiber core in the optical cable and the scheduling grade thereof, aiming at each optical cable in the optical cable network.
Step two: constructing a fiber core service distribution matrix D according to the fiber core service distribution data set (k) ={d (k) ij And the system is used for representing the distribution condition of the service quantity of different dispatching grades on different optical cables. Wherein d (k) ij Indicating the number of traffic with a scheduling level k carried on the cable connecting communication station node i and communication station node j.
The modeling of the fiber core availability mainly comprises the following steps:
step one: the fiber core availability data set is obtained by carding for each optical cable in the optical cable network, namely the data set of the number of the fiber cores which can be used in each optical cable in the current optical cable network.
Step two: generating a fiber core availability degree matrix E= { E according to the optical cable service distribution data set ij And (d) characterizing the distribution of the number of cores available on the different cables. Where eij represents the number of cores available on the fiber optic cable connecting communication station node i and communication station node j.
Modeling fiber core quality abnormality information, mainly comprising the following steps:
step one: and combing to obtain a fiber core quality abnormal data set aiming at each optical cable in the optical cable network, wherein the fiber core quality abnormal data set refers to a data set described by the current quality abnormal condition in the optical cable.
Step two: core mass profile matrix q= { Q ij And (3) the distribution situation of the number of the failed fiber cores on different optical cables is represented. Wherein q ij Representing the number of failed cores on the fiber optic cable connecting communication station node i and communication station node j.
Fiber optic cable resource information data visualization, comprising: optical cable network topology visualization, optical cable service distribution visualization, fiber core availability visualization and fiber core quality visualization.
Optical cable network topology visualization, generating an optical cable network topology graph based on an optical cable network topology matrix A, representing a communication site by using nodes, and generating edges for connecting the nodes i and j when aij=1; when aij=0, there is no edge between nodes i and j.
An example of a cable network topology visualization is shown in fig. 2.
Fiber core service distribution matrix D based on optical cable service distribution visualization (k) Generating a fiber core service distribution diagram. The method mainly comprises the following two steps:
step one: different scheduling level services are distinguished through different colors;
step two: edge thickness and d (k) ij The more positive correlation, i.e. the larger the value, the more the number of bearer scheduling class k trafficThe more, the thicker the edges.
An example of traffic distribution visualization is shown in fig. 3.
The core availability is visualized and a core availability map is generated based on the core availability matrix E. The number of the available fiber cores in the optical cable is distinguished by the thickness of the edges, namely, the thickness of the edges is positively correlated with eij, and the larger the numerical value is, the thicker the line is, and the larger the number of the available fiber cores is.
Fig. 4 shows an example of a visualization of the core availability.
And (3) visualizing the fiber core quality condition, generating a fiber core quality diagram based on the fiber core quality condition matrix Q, and realizing the visualization of the fiber core fault number on the optical cable by carrying out numerical marking on the edge of the topology diagram based on the optical cable network topology diagram.
Fig. 5 shows an example of a visualization of the core quality.
1. Optical cable resource information data analysis, comprising:
the optical cable network topology analysis mainly comprises the following steps:
step one: the network topology global feature analysis mainly comprises degree distribution, community structure features and homography. Degree is one of the simplest and most important measures of importance of nodes in a network. In the network, the degree of one node is described as the total number of edges directly connected thereto, and the expression thereof is shown in formula (1).
Wherein a is ij For the elements on the j-th column of the i-th row in the optical cable network topology matrix a, |v| represents the total number of nodes in the network.
The degree distribution represents the distribution of the degree of tightness of the connection of the nodes in the network, and is described by a degree distribution function P (k). The distribution function P (k) represents the probability of randomly selecting a node in the network whose degree value is k, which can be expressed by the ratio of the number of nodes in the network whose degree value is k to the total number of nodes in the network.
The community structure is that nodes in the network can be grouped, the connection relationship among the nodes in the same group is relatively tight, and the connection among the nodes in different groups is relatively sparse. Such a differential feature of node set connection closeness in a network is referred to as a community structure. The significance of the network community structure is measured by modularity. The modularity is defined as the ratio of the total edge number in the community to the total edge number in the network minus an expected value, wherein the expected value is the ratio of the total edge number in the community to the total edge number in the network when the network is converted into a random network according to the same community division, and the expression is shown in the formula (2).
Wherein c i And c j Respectively represent node v i And v j The label of the community. When c i ＝c j When representing node v i And node v j Is located in the same community; when c i ≠c j When representing node v i And node v j Located in different communities. I E is the total number of edges in the network, k i Representing node v i Is a degree value of (2). Q' has a value of 0, 1]And when the value of Q is close to 1, the community structure characteristics of the network are more obvious.
Homography refers to a network that is considered heterography if a large degree node is intended to connect with other large degree nodes and if a large degree node is intended to connect with a small degree node. In order to describe the homography characteristic of the network, the definition of the average degree of the adjacent nodes is introduced, and the expression is shown as the formula (4)
Wherein the conditional probability P (k ' |k ' ') represents a degree value of k ' 'Probability of a node being connected to a node having a degree value of k'. It can be seen that if k nn (k ") increases with increasing degree value k", indicating that as the degree of the node itself increases, the average degree of the neighboring nodes connected thereto increases, and the network is a homoleptic network; if k is nn (k ') decreases with increasing k '), indicating that as the node's own degree increases, the average degree of the neighboring nodes connected thereto decreases, and the network is a heterogeneous network.
Wherein the conditional probability P (k ' |k ") represents the probability that a node of degree k ' is connected to a node of degree k '.
Step two: network topology oriented key bridge optical cable identification. A bridge fiber optic cable is defined as a fiber optic cable that connects communication nodes belonging to different communities. As a key optical cable bridging different communities, interruption of the bridge optical cable may cause the network to be divided into sub-networks that are not connected to each other, which is of great importance for identification thereof.
The analysis of the optical cable service distribution data mainly comprises the following steps:
step one: and (5) carrying out statistical feature analysis on the distribution of the service scheduling levels.
Wherein D is x Represents the total number of core services with the overall network scheduling level of x, and Dtotal is the total number of the overall network core services.
Step two: and (5) key optical cable identification based on comprehensive service weight. The definition of the comprehensive service weight is shown as a formula (6), and is a weighted sum of the service numbers of different scheduling grades. The fiber optic cable with the integrated service weight greater than the given threshold is defined as the integrated service weight critical fiber optic cable.
Wherein e ij For the cable connecting communication stations i and j, dx (eij) is the number of traffic of cable eij carrying schedule class x, wx represents the weight, w x ∈[0,1]And (2) and
。
the fiber core availability data analysis mainly comprises the following steps:
step one: and (5) carrying out statistical feature analysis on the geographical distribution of the availability degree of the fiber core.
Step two: the core resources are strained for critical cable identification. A core resource-intense critical cable is defined as a cable in which the number of usable cores is less than a given threshold.
The analysis of abnormal fiber core quality data mainly comprises the following steps:
step one: analyzing the geographical distribution statistical characteristics of the number of the fault fiber cores;
step two: high fault critical cable identification. A high failure rate critical fiber optic cable is defined as a fiber optic cable having a number of failed cores greater than a given threshold.
The optical cable resource information graph visualizes visual element interactivity operations. Mainly comprises the following steps: scaling adjustment, node dragging, multi-graph comparison, and the like.
As shown in fig. 6, embodiments of the present application provide a system for visualizing information about fiber optic cable resources, comprising,
the optical cable resource information data set arrangement module 1 is used for arranging an optical cable network topology data set, a fiber core service data set, a fiber core availability data set and a fiber core quality data set and sending the optical cable resource information data sets to the optical cable resource information matrix construction module;
the optical cable resource information matrix construction module 2 is configured to construct the optical cable network topology data set, the fiber core service data set, the fiber core availability data set and the fiber core quality data set sent by the optical cable resource information data set arrangement module into an optical cable network topology matrix, a fiber core service distribution matrix, a fiber core availability matrix and a fiber core quality matrix;
the optical cable resource information visualization module 3 is used for respectively generating an optical cable network topology map, a fiber core service distribution map, a fiber core availability map and a fiber core quality map from the optical cable network topology matrix, the fiber core service distribution matrix, the fiber core availability map and the fiber core quality matrix which are constructed by the optical cable resource information matrix construction module;
the optical cable resource information data analysis module 4 is used for analyzing the optical cable network topological graph, the fiber core service distribution graph, the fiber core availability degree graph and the fiber core quality graph generated by the optical cable resource information visualization module;
and the visualization unit interactive operation module 5 is used for performing scaling adjustment, node dragging and multi-graph comparison operation on the optical cable network topological graph, the fiber core service distribution graph, the fiber core availability degree graph and the fiber core quality graph which are generated by the optical cable resource information visualization module.
Embodiments of the present application provide a computer readable storage medium storing program code which, when executed by a processor, implements the steps of the optical cable resource information visualization method as described above.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
The foregoing is merely exemplary embodiments of the present application and is not intended to limit the scope of the present application, and various modifications and variations may be suggested to one skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (3)
1. The visual analysis method for the power communication optical cable resources is characterized by comprising the following specific steps of:
optical cable resource information data set arrangement and optical cable resource information matrix construction;
visualizing the optical cable resource information;
carrying out data analysis on optical cable resource information based on a complex network theory, carrying out statistical analysis on global distribution conditions of various optical cable resource information, and identifying key optical cables;
the optical cable resource information visualization unit performs interactive operation;
the optical cable resource information data set comprises an optical cable network topology data set, a fiber core service data set, a fiber core availability data set and a fiber core quality data set, wherein the optical cable network topology data set refers to a data set described by the connection relation of an optical cable to a communication site, the fiber core service data set refers to a data set of services carried by each fiber core in the optical cable and scheduling grades thereof, the fiber core availability data set refers to a data set of usable fiber cores in the current optical cable, and the fiber core quality data set refers to a data set described by the abnormal quality condition in the current optical cable;
the optical cable resource information matrix structure is specifically an optical cable network topology matrixA={a ij } N*N ，a ij Representing a node of a communication station in a networkiAnd a communication station nodejIs used for the connection of the two terminals,Nfor the total number of communication station nodes, when the nodeiSum nodejWhen the optical cable is directly connected in the middle,a ij =1; otherwise the first set of parameters is selected,a ij =0, core traffic distribution matrixD k() ={d k() ij And used for representing the distribution condition of the traffic quantity of different dispatching grades on different optical cables, wherein,d k() ij representing a node connecting communication stationsiAnd a communication station nodejThe load dispatch level on the optical cable is as followskIs the number of services, the core availability matrix isE={e ij And used to characterize the distribution of the number of cores available on different fiber optic cables, wherein,e ij representing a node connecting communication stationsiAnd a communication station nodejThe number of cores available on the cable of (a) a core quality matrixQ={q ij And used for representing the distribution situation of the number of failed fiber cores on different optical cables, wherein,q ij representing a node connecting communication stationsiAnd a communication station nodejThe number of failed cores on the cable;
the optical cable resource information visualization is specifically that an optical cable network topology diagram is generated based on an optical cable network topology matrix A, nodes are used for representing communication sites, and whena ij When=1, a node for connecting communication stations is generatediAnd a communication station nodejIs a side of (2); when (when)a ij When=0, communication station nodeiAnd a communication station nodejNo edge exists between the two;
fiber core based service distribution matrixD k() Generating core traffic segmentsFirstly, differentiating different scheduling level services by different colors; then, the thickness of the edge andd k() ij with positive correlation, i.e. the larger the value, the bearer scheduling levelkThe more the number of services, the thicker the edges;
based on a matrix of core availabilityEGenerating a usable level graph of the fiber cores, and distinguishing the usable fiber core quantity in the optical cable by the thickness of the edge, namely the thickness of the edge and the thickness of the edgee ij The larger the number, the thicker the line, the more cores are available;
based on a core quality matrixQGenerating a fiber core quality diagram, and based on the optical cable network topology diagram, performing numerical marking on the edge of the topology diagram to realize visualization of the number of fiber core faults on the optical cable;
the analysis of the optical cable resource information data based on the complex network theory carries out the statistical analysis of the global distribution condition of various optical cable resource information and identifies the key optical cable specifically,
a fiber optic cable network topology analysis, comprising: analyzing the degree distribution characteristics, the community structure and the homography characteristics and identifying key bridge optical cables;
an optical cable network traffic distribution analysis comprising: the statistical characteristic analysis of the distribution of the service scheduling level and the key optical cable identification based on the comprehensive service weight;
an analysis of the availability of fiber cores of a fiber optic cable network, comprising: the fiber core availability geographic distribution statistical feature analysis and fiber core resource tension key optical cable identification;
an optical cable network core quality condition analysis comprising: and (5) carrying out geographical distribution statistical feature analysis on the number of the failed fiber cores and identifying the high-failure-rate key optical cable.
2. The method for visualizing analysis of a power communication cable resource according to claim 1, wherein said cable resource information visualization unit interactive operation comprises scaling adjustment, node dragging, multi-graph comparison.
3. A computer readable storage medium, characterized in that the computer readable storage medium stores a program code which, when executed by a processor, implements the steps of the power communication cable resource visualization analysis method of any one of claims 1-2.
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