Method and system for evaluating self-healing capability of communication network, and electronic equipment

Abstract

The invention provides a communication network self-healing capability evaluation method and system and electronic equipment, and the method comprises the steps: constructing a power communication network self-healing evaluation system which comprises a self-healing capability evaluation value, a plurality of business indexes corresponding to the self-healing capability evaluation value, and a plurality of influence factors corresponding to each business index; performing pairwise comparison on the influence factors under the same business index to construct a judgment matrix; obtaining a relative weight of each factor in each business index through the judgment matrix, and calculating a combined weight coefficient of each influence factor according to the relative weight of each factor in each business index; and calculating according to the combined weight of each influence factor to obtain a self-healing ability evaluation value. According to the method and the device, the self-healing capability of the communication network can be comprehensively evaluated, so that technical reference is provided for subsequent planning of the self-healing communication network.

Description

Technical Field

[0001] The present invention relates to the technical field of communication network self-healing evaluation, and in particular to a communication network self-healing capability evaluation method, system and electronic equipment. Background Art

[0002] With the development of power communication network, a large number of power system services need to be transmitted through the power communication network. The risks and failures of the power communication network have an increasingly serious impact on the power system, and the power system production departments have higher and higher requirements for the reliability of the power communication network.

[0003] Due to the continuous development of network technology, more business volume is concentrated on fewer network elements. While enjoying the convenience and huge benefits brought by the network, the harm caused by network failures is also attracting more and more attention. In the current era, due to the increasing speed and large capacity of the network, the consequences of network failures will be much more serious than before. Once such a network fails and the failure cannot be eliminated in a short time, the severity of the result can be imagined. For example, the failure of a 40-wavelength WDM system transmitting 2.5Gbit / s SDH signal can affect 12 million telephone calls. Therefore, a network failure will affect many communication services, which will inevitably cause huge economic losses, and in severe cases may cause social and economic turmoil. After the development of highly integrated communications, people gradually shifted their attention to automatic recovery technology, that is, self-healing technology.

[0004] Self-healing means that the network can automatically restore service transmission capacity from failure in a very short time without human intervention. Alternative routes can use backup equipment or utilize the redundancy in existing equipment to meet end-to-end service recovery or specify that priority services are not affected. During the self-healing process, various services will not be interrupted, and users will not feel that the network has been reorganized. The role of power communication networks in power production and power dispatching is becoming more and more important, and the recovery technology after power communication network failures is becoming more and more important. However, the application of self-healing technology in power communication transmission networks and even ordinary networks is not yet mature. Therefore, a method for evaluating the self-healing capacity of communication networks is urgently needed to provide an important reference for self-healing network planning. Summary of the invention

[0005] Based on this, the purpose of the present invention is to propose a method, system and electronic equipment for evaluating the self-healing capability of a communication network, so as to construct an evaluation system for the self-healing capability index of a power communication network, thereby being able to comprehensively evaluate the self-healing capability of the communication network and provide a technical reference for the subsequent planning of the self-healing communication network.

[0006] On the one hand, the present invention provides a method for evaluating the self-healing capability of a communication network, the method comprising: Constructing a self-healing evaluation system for a power communication network, the self-healing evaluation system for a power communication network comprising a self-healing capability evaluation value, a plurality of business indicators corresponding to the self-healing capability evaluation value, and a plurality of influencing factors corresponding to each of the business indicators; Compare the influencing factors of the same business indicator in pairs to build a judgment matrix; The relative weight of each factor in each business indicator is obtained from the judgment matrix, and the combined weight coefficient of each influencing factor is calculated based on the relative weight of each factor in each business indicator; The self-healing ability evaluation value is calculated based on the combined weights of various influencing factors.

[0007] In summary, according to the above-mentioned communication network self-healing capability evaluation method, by constructing a power communication network self-healing evaluation system, the self-healing capability of the communication network can be comprehensively evaluated, thereby providing a technical reference for the subsequent planning of the self-healing communication network.

[0008] Furthermore, the step of comparing the influencing factors under the same business indicator in pairs to construct a judgment matrix includes: Obtaining the number of influencing factors under the same business indicator, and obtaining the number of rows and columns of the judgment matrix according to the number of influencing factors under the same business indicator; Each influencing factor is numbered in turn, and the comparison results of the influencing factors are obtained according to the numbering results, and the comparison results of the influencing factors are filled into the judgment matrix one by one.

[0009] Furthermore, the step of obtaining the relative weight of each factor in each business indicator from the judgment matrix, and calculating the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator includes: The nine-point scaling model is used to quantify the relative weights of the influencing factors. The initial weight coefficient of each influencing factor is calculated according to the following formula: Among them, s i represents the initial weight coefficient of the i-th influencing factor, b im It represents the relative weight between the ith influencing factor and the mth influencing factor, and m represents the total number of influencing factors under the current business indicator.

[0010] Furthermore, the step of obtaining the relative weight of each factor in each business indicator from the judgment matrix, and calculating the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator includes: The combined weight coefficient of each influencing factor is calculated according to the following formula: Among them, w i Represents the combined weight coefficient of the i-th influencing factor.

[0011] Furthermore, the step of calculating the self-healing ability evaluation value according to the combined weights of various influencing factors includes: calculating the self-healing ability evaluation value according to the following formula: Among them, Q represents the self-healing ability evaluation value, q i represents the evaluation value of the i-th influencing factor, j represents the j-th business indicator, and n represents the total number of business indicators.

[0012] On the other hand, an embodiment of the present invention further provides a self-healing capability evaluation system for a communication network, the system comprising: an evaluation system construction module, used to construct a self-healing evaluation system for a power communication network, the self-healing evaluation system for a power communication network comprising a self-healing capability evaluation value, a plurality of business indicators corresponding to the self-healing capability evaluation value, and a plurality of influencing factors corresponding to each of the business indicators; The judgment matrix construction module is used to compare the influencing factors under the same business indicator in pairs to construct the judgment matrix; the weight calculation module is used to obtain the relative weight of each factor in each business indicator from the judgment matrix, and calculate the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator; The evaluation value output module is used to calculate the self-healing ability evaluation value according to the combined weight of each influencing factor.

[0013] Another aspect of the present invention provides a storage medium, including one or more programs stored in the storage medium, which, when executed, implements the above-mentioned method for evaluating the self-healing capability of a communication network.

[0014] Another aspect of the present invention further provides an electronic device, the electronic device comprising a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, the above-mentioned method for evaluating the self-healing capability of the communication network is implemented.

[0015] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description or will be learned through embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flowchart of a method for evaluating the self-healing capability of a communication network proposed in a first embodiment of the present invention; Figure 2 is a schematic diagram of a power communication network self-healing evaluation system in a first embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a communication network self-healing capability evaluation system proposed in the second embodiment of the present invention.

[0017] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0018] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0020] See also Figure 1 , which is a flow chart of a method for evaluating the self-healing capability of a communication network in a first embodiment of the present invention, the method comprises steps S01 to S04, wherein: Step S01: construct a power communication network self-healing evaluation system, wherein the power communication network self-healing evaluation system includes a self-healing capability evaluation value, a plurality of business indicators corresponding to the self-healing capability evaluation value, and a plurality of influencing factors corresponding to each of the business indicators; it should be noted that, please refer to Figure 2 , study and establish a risk assessment index system for power communication networks, and divide the self-healing assessment index system of power communication networks into three parts: business support indicators, communication network operation quality indicators, and communication network operation and maintenance quality indicators; specifically, first, the business support indicators are evaluated according to specific types of business; secondly, the communication network operation quality indicators are evaluated according to different network types of power communication networks, including optical cable networks, transmission networks, dispatching data networks, integrated data networks, administrative exchange networks, dispatching exchange networks, video conferencing systems and other different network types; finally, the communication network operation and maintenance quality indicators are divided into six parts: system construction environment and material allocation, human resources allocation, capital allocation, communication maintenance and repair level, and communication professional level.

[0021] In addition, the communication services of the power system are mainly divided into power grid operation and enterprise management services according to their functions and characteristics. Power grid operation services are further divided into operation control services and operation information services; enterprise management services are further divided into information services and office services. These services all rely on the support of communication networks, but the requirements for communication are not consistent. As a link in power grid control, the operation control service is directly related to the safety of the power grid. Since such services have extremely high requirements for communication transmission delay and channel reliability, the power communication private network, namely the optical cable transmission network, is currently mainly used. This type of service mainly includes three categories: line protection service, stability service, and dispatching automation service, and seven categories: dispatching telephone service, video conferencing service, administrative telephone service, and information service. The risks of a specific type of service are analyzed through four parts: business scale, business guarantee capability, business reliability, and business quality. First, the risk of a certain type of service in the network is proportional to its scale. The larger the scale of the service, the greater the probability of risk. Second, the stronger the service guarantee capability, the smaller the probability of risk. The service guarantee capability is related to the network protection measures for the transmission service, including dual-channel lines, optical fiber, emergency channels and routing protection. In addition, the interruption and alarm of the service channel that reflects the reliability of the service, and the bit error of the service that reflects the quality of the service are all used as indicators for assessing service risks.

[0022] In addition, the power communication network is mainly based on the development of optical communication, and on this basis, data network, exchange network, clock synchronization network, video conferencing system and power carrier unique to the power system are developed as the main communication methods. The communication network operation quality indicators are divided into seven categories according to the type of communication network: optical cable network indicators, transmission network indicators, dispatching data network indicators, comprehensive data network indicators, administrative exchange network, dispatching exchange network, and video conferencing system indicators. Different types of networks are further divided into scale indicators, coverage indicators, technical compliance indicators, network reliability indicators and network quality indicators. First, the risk of various types of networks is proportional to their size. Generally speaking, the larger the scale, the greater the probability of risk; secondly, different coverage indicators of different networks have a great impact on the risk of the network. Taking the optical cable network as an example, the higher the optical cable coverage of the network, the smaller the probability of risk in the network; thirdly, different networks will adopt specific technologies to improve the performance of the network, so technical compliance can also be used as an indicator to measure network risk; in addition, network reliability and network quality indicators are also important indicators to measure network risk.

[0023] In addition, the power communication network operation and maintenance quality indicators mainly consider the communication network maintenance plan completion rate and maintenance plan accuracy. The maintenance plan completion rate refers to the proportion of planned maintenance plans that have been completed, reflecting the level of communication maintenance and is a positive correlation indicator. The maintenance plan accuracy rate refers to the proportion of planned maintenance plans that have been completed accurately, reflecting the level of communication maintenance and is a positive correlation indicator.

[0024] Step S02: Compare the influencing factors under the same business indicator in pairs to construct a judgment matrix; In this step, firstly, the number of influencing factors under the same business indicator needs to be obtained, and the number of rows and columns of the judgment matrix is ​​obtained according to the number of influencing factors under the same business indicator; Each influencing factor is numbered in turn, and the comparison results of the influencing factors are obtained according to the numbering results, and the comparison results of the influencing factors are filled into the judgment matrix one by one.

[0025] For example, a judgment matrix is ​​constructed as follows: Step S03: Obtain the relative weight of each factor in each business indicator from the judgment matrix, and calculate the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator; In this step, the method for solving the weight coefficient of each layer of indicators is generally to first find the initial weight coefficient, and then use multiplication to find the combined weight coefficient, so as to find the weight coefficient of each layer of indicators, as follows: Firstly, the nine-point scaling model is used to quantify the relative weights of the influencing factors. Then the initial weight coefficient of each influencing factor is calculated according to the following formula: Among them, s i represents the initial weight coefficient of the i-th influencing factor, b im It represents the relative weight between the ith influencing factor and the mth influencing factor, and m represents the total number of influencing factors under the current business indicator.

[0026] Then calculate the combined weight coefficient of each influencing factor according to the following formula: Among them, w i Represents the combined weight coefficient of the i-th influencing factor.

[0027] Step S04: Calculate the self-healing ability evaluation value according to the combined weights of various influencing factors.

[0028] In this step, the self-healing ability evaluation value is calculated according to the following formula: Among them, Q represents the self-healing ability evaluation value, q i represents the evaluation value of the i-th influencing factor, j represents the j-th business indicator, and n represents the total number of business indicators.

[0029] By constructing an accurate self-healing capability evaluation function, various business indicators and the specific influencing factors under each business indicator are integrated together, thus achieving a comprehensive and accurate evaluation of the communication network.

[0030] In summary, according to the above-mentioned communication network self-healing capability evaluation method, by constructing a power communication network self-healing evaluation system, the self-healing capability of the communication network can be comprehensively evaluated, thereby providing a technical reference for the subsequent planning of the self-healing communication network.

[0031] See also Figure 3 , which is a schematic diagram of the structure of a self-healing capability evaluation system for a communication network in a second embodiment of the present invention, the system comprises: An evaluation system construction module 10 is used to construct a power communication network self-healing evaluation system, wherein the power communication network self-healing evaluation system includes a self-healing capability evaluation value, a plurality of business indicators corresponding to the self-healing capability evaluation value, and a plurality of influencing factors corresponding to each of the business indicators; The judgment matrix construction module 20 is used to compare the influencing factors under the same business indicator in pairs to construct a judgment matrix; the weight calculation module 30 is used to obtain the relative weight of each factor in each business indicator from the judgment matrix, and calculate the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator; The evaluation value output module 40 is used to calculate the self-healing ability evaluation value according to the combined weights of various influencing factors.

[0032] Further, in some optional embodiments, the judgment matrix construction module 20 is further used to: obtain the number of influencing factors under the same business indicator, and obtain the number of rows and columns of the judgment matrix according to the number of influencing factors under the same business indicator; Each influencing factor is numbered in turn, and the comparison results of the influencing factors are obtained according to the numbering results, and the comparison results of the influencing factors are filled into the judgment matrix one by one.

[0033] Furthermore, in some optional embodiments, the weight calculation module 30 is further used for: The nine-point scaling model is used to quantify the relative weights of the influencing factors. The initial weight coefficient of each influencing factor is calculated according to the following formula: Among them, s i represents the initial weight coefficient of the i-th influencing factor, b im Indicates the relative weight of the i-th influencing factor and the m-th influencing factor, and m represents the total number of influencing factors under the current business indicator; The combined weight coefficient of each influencing factor is calculated according to the following formula: Among them, w i Represents the combined weight coefficient of the i-th influencing factor.

[0034] Further, in some optional embodiments, the evaluation value output module 40 is further used for: The self-healing ability evaluation value is calculated according to the following formula: Among them, Q represents the self-healing ability evaluation value, q i represents the evaluation value of the i-th influencing factor, j represents the j-th business indicator, and n represents the total number of business indicators.

[0035] Another aspect of the present invention further provides a computer storage medium on which one or more programs are stored, and when the programs are executed by a processor, the above-mentioned method for evaluating the self-healing capability of a communication network is implemented.

[0036] Another aspect of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the above-mentioned method for evaluating the self-healing capability of a communication network.

[0037] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0038] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0039] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0040] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0041] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A method for evaluating the self-healing capability of a communication network, characterized in that: The method comprises: Constructing a self-healing evaluation system for a power communication network, the self-healing evaluation system for a power communication network comprising a self-healing capability evaluation value, a plurality of business indicators corresponding to the self-healing capability evaluation value, and a plurality of influencing factors corresponding to each of the business indicators; Compare the influencing factors of the same business indicator in pairs to build a judgment matrix; The relative weight of each factor in each business indicator is obtained from the judgment matrix, and the combined weight coefficient of each influencing factor is calculated based on the relative weight of each factor in each business indicator; The self-healing ability evaluation value is calculated based on the combined weights of various influencing factors.

2. The method for evaluating the self-healing capability of a communication network according to claim 1, characterized in that: The step of comparing the influencing factors under the same business indicator in pairs to construct a judgment matrix includes: Obtaining the number of influencing factors under the same business indicator, and obtaining the number of rows and columns of the judgment matrix according to the number of influencing factors under the same business indicator; Each influencing factor is numbered in turn, and the comparison results of the influencing factors are obtained according to the numbering results, and the comparison results of the influencing factors are filled into the judgment matrix one by one.

3. The method for evaluating the self-healing capability of a communication network according to claim 2, characterized in that: The step of obtaining the relative weight of each factor in each business indicator from the judgment matrix, and calculating the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator includes: The nine-point scaling model is used to quantify the relative weights of the influencing factors. The initial weight coefficient of each influencing factor is calculated according to the following formula: Among them, s i represents the initial weight coefficient of the i-th influencing factor, b im It represents the relative weight between the ith influencing factor and the mth influencing factor, and m represents the total number of influencing factors under the current business indicator.

4. The method for evaluating the self-healing capability of a communication network according to claim 3, characterized in that: The step of obtaining the relative weight of each factor in each business indicator from the judgment matrix, and calculating the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator includes: The combined weight coefficient of each influencing factor is calculated according to the following formula: Among them, w i Represents the combined weight coefficient of the i-th influencing factor.

5. The method for evaluating the self-healing capability of a communication network according to claim 4, characterized in that: The step of calculating the self-healing ability evaluation value according to the combined weights of various influencing factors comprises: The self-healing ability evaluation value is calculated according to the following formula: Among them, Q represents the self-healing ability evaluation value, q i represents the evaluation value of the i-th influencing factor, j represents the j-th business indicator, and n represents the total number of business indicators.

6. A communication network self-healing capability evaluation system, characterized in that: The system comprises: An evaluation system construction module, used to construct a power communication network self-healing evaluation system, wherein the power communication network self-healing evaluation system includes a self-healing capability evaluation value, a plurality of business indicators corresponding to the self-healing capability evaluation value, and a plurality of influencing factors corresponding to each of the business indicators; The judgment matrix construction module is used to compare the influencing factors under the same business indicator in pairs to construct a judgment matrix; The weight calculation module is used to obtain the relative weight of each factor in each business indicator from the judgment matrix, and calculate the combined weight coefficient of each influencing factor according to the relative weight of each factor in each business indicator; The evaluation value output module is used to calculate the self-healing ability evaluation value according to the combined weights of various influencing factors.

7. The self-healing capability evaluation system of a communication network according to claim 6, characterized in that: The judgment matrix building module is also used for: Obtaining the number of influencing factors under the same business indicator, and obtaining the number of rows and columns of the judgment matrix according to the number of influencing factors under the same business indicator; Each influencing factor is numbered in turn, and the comparison results of the influencing factors are obtained according to the numbering results, and the comparison results of the influencing factors are filled into the judgment matrix one by one.

8. The self-healing capability evaluation system of a communication network according to claim 7, characterized in that: The weight calculation module is also used for: The nine-point scaling model is used to quantify the relative weights of the influencing factors. The initial weight coefficient of each influencing factor is calculated according to the following formula: Among them, s i represents the initial weight coefficient of the i-th influencing factor, b im It represents the relative weight between the ith influencing factor and the mth influencing factor, and m represents the total number of influencing factors under the current business indicator.

9. A storage medium, characterized in that: include: The storage medium stores one or more programs, which, when executed by a processor, implement the method for evaluating the self-healing capability of a communication network as described in any one of claims 1 to 5.

10. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, the method for evaluating the self-healing capability of a communication network described in any one of claims 1 to 5 is implemented.

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