SDN (Software Defined Network) controller deployment optimization method and system for electric power communication network

Abstract

The invention belongs to the technical field of electric power communication networks, and relates to an electric power communication network-oriented SDN controller deployment optimization method and system, and the method comprises the steps: constructing a data communication network cloud platform, obtaining the deployment topology data of an electric power communication network, forming a data communication network graph model, monitoring the connection of equipment in a communication network, and carrying out the real-time updating. The method comprises the following steps: accessing an SDN controller in an electric power communication network, collecting operation data of the SDN controller, analyzing communication performance of each device, and generating a communication network data matrix; analyzing the communication network data matrix, and judging whether the deployment of each SDN controller has an optimization requirement or not; marking the SDN controllers meeting the optimization demand discrimination conditions, and generating a deployment optimization list; and analyzing SDN controller optimization requirements in the deployment optimization list, and initiating feedback to related personnel. Therefore, stable operation of the power system is guaranteed, and complexity and low efficiency caused by decentralized management are avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power communication networks, and in particular relates to an SDN controller deployment optimization method and system for electric power communication networks. Background Art

[0002] With the development of the network, the traditional network architecture can no longer meet the current communication needs, and the SDN of the network has become an inevitable trend. The SDN controller is the core of the SDN architecture. It communicates with the data plane through the network programming interface and can control the network traffic.

[0003] Existing technologies usually deploy SDN controllers in clusters to improve processing capabilities. Each node in the cluster can take on a portion of the computing tasks and jointly process the communication network.

[0004] As an important part of the power system, the power communication network undertakes important tasks such as power dispatching, automatic control, and information exchange. However, due to the large scale of the power system and the diverse business needs, how to deploy SDN controllers in the power communication network, ensure the stable operation of the power communication network, and fully consider the scalability of the controller and optimize the SDN controller deployed in the cluster are the current problems that need to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide a SDN controller deployment optimization system and method for a power communication network to solve the problems raised in the above background technology.

[0006] In order to achieve the purpose of the present invention, the present invention will be implemented by adopting the following technical solutions. The SDN controller deployment optimization method for power communication network includes the following steps:

[0007] Step S100: construct a data communication network cloud platform, coordinate all devices in the communication network, obtain deployment topology data of the power communication network, form a data communication network graph model, monitor the connection of devices in the communication network, and update the data communication network graph model in real time;

[0008] Step S200: Access the SDN controller in the power communication network, collect the operation data of the SDN controller, collect the instructions received by each device through the data communication network cloud platform during each control execution, and generate a communication list according to the instructions; randomly select an SDN controller, analyze the communication performance of each device based on the communication list, and generate a communication network data matrix;

[0009] Step S300: Analyze the communication network data matrix based on cloud computing to determine whether there is an optimization requirement for the deployment of each SDN controller; mark the SDN controller that meets the optimization requirement judgment condition, and generate a deployment optimization list;

[0010] Step S400: Analyze the SDN controller optimization requirements in the deployment optimization list based on the data communication network graph model, and feedback the deployment optimization requirements in the power communication network to relevant personnel.

[0011] As a preferred solution of the present invention, the implementation process of step S100 includes the following steps:

[0012] Step S101: Build a data communication network cloud platform, coordinate all devices in the communication network, assign coding prefixes according to device types, and uniformly code each device; identify the connection mode between each device in the communication network, and obtain the deployment topology data of the power communication network; when any SDN controller performs control communication on any device, collect the northbound interface protocol and southbound interface protocol of the control communication, mark the connection line with the same intermediate layer service processing request when the same SDN controller performs control communication on the device as the Qth control communication, and connect the i-th SDN controller with device A. j The connection line is recorded as SDN i →Q→B; among them, SDN i represents the code of the i-th SDN controller, Q represents the Q-th intermediate layer service processing request, B={A j |j∈[1,m]},A j represents the code of the jth device, and m represents the total number of devices that process requests through the Qth intermediate layer service when the i-th SDN controller performs control communication;

[0013] Step S102: Based on the control communication records, a data communication network graph model is formed, and the data communication network graph model includes connection lines between each SDN controller and the device; the connection of the devices in the communication network is monitored, and when a new device is added to the communication network, step S101 is repeated to update the connection line of the SDN controller. When the new device does not belong to the existing connection line, a new connection line is generated and the data communication network graph model is expanded; when the interface protocol of the original device in the communication network is changed or the coding is deleted, the connection line of the SDN controller and the data communication network graph model are refreshed.

[0014] According to the above method, the connection lines in the power communication network are divided based on the communication protocol and the content of the middle-layer service processing, and the deployment characteristics of the SDN controller are reflected in the vertical dimension of the network architecture, providing a data source for subsequent data analysis.

[0015] As a preferred solution of the present invention, the implementation process of step S200 includes the following steps:

[0016] Step S201: Access the SDN controller in the power communication network based on the communication cycle; in the Tth communication cycle, collect the operation data of the SDN controller, and collect the instructions received by each device through the data communication network cloud platform during each control execution; wherein, the instructions sent by the same SDN controller to the device corresponding to the same connection line are integrated into an instruction cluster, and the data communication network cloud platform coordinates all the collected instruction clusters to generate a communication list of the kth communication cycle; the communication list is accompanied by a connection line label of each instruction cluster, and any instruction cluster is recorded as ZC(iQB), wherein ZC(iQB)={[L z (A j ), L t (A j )]|j∈[1,m]},L z (A j ) indicates device A j The corresponding latest instruction content, L t (A j ) indicates device A j The corresponding latest instruction reception time, the communication list of the kth communication cycle is recorded as LZC k and sort the command clusters in the communication list according to the time when the latest command of the device is received;

[0017] Step S202: There are multiple SDN controllers working together in the power communication network, and each controller manages an area or subnet; a SDN controller is randomly selected, and a communication list of the SDN controller is obtained. The communication performance of each device is analyzed based on the communication list corresponding to each communication cycle, and the communication performance score of the selected SDN controller and the device in the power communication network is calculated according to the following formula:

[0018]

[0019] Among them, X ij represents the communication performance score of the jth device in the communication list of the i-th SDN controller, W represents the total number of communication cycles recorded for the i-th SDN controller, if[(F(LZC k+1 )∩F(LZC k )] represents the discriminant function, F(LZC k+1 ) indicates that the communication list of the k+1th communication cycle contains the instruction cluster of the instruction sent to the jth device; F(LZC k ) represents the instruction cluster containing the instruction sent to the jth device in the communication list of the kth communication cycle; when (F(LZCk+1 )∩F(LZC k ) is empty, if[(F(LZC k+1 )∩F(LZC k )]=0; when (F(LZC k+1 )∩F(LZC k ) is not empty, if[(F(LZC k+1 )∩F(LZC k )]=1;

[0020] Step S203: Generate a communication network data matrix based on the communication performance scores of each SDN controller and the devices connected to the SDN controller in the power communication network, where the rows of the matrix represent different SDN controllers, the columns of the matrix represent different devices, and the value of the i-th row and j-th column in the matrix is ​​X ij .

[0021] According to the above method, the devices in the power communication network are monitored for receiving instructions, and the communication performance of each SDN controller in the power communication network and the devices connected to the SDN controller in the power communication network are mapped into a matrix. Based on the network architecture, the areas managed by each SDN controller are analyzed, which can reflect the communication frequency and communication volume of each area, so as to facilitate the subsequent further analysis of the capabilities of each SDN controller.

[0022] As a preferred solution of the present invention, the implementation process of step S300 includes the following steps:

[0023] Step S301: Analyze the communication network data matrix based on cloud computing, define the network status of each SDN controller according to the communication network data matrix, check whether the values ​​in the matrix are evenly distributed, and calculate the optimization index of the SDN controller corresponding to the i-th row of the matrix according to the following formula:

[0024]

[0025] Where N is the total number of SDN controllers, M is the total number of devices connected to the SDN controllers in the power communication network, and μ i represents the average value of all elements in the i-th row of the matrix, and μ represents the average value of all elements in the matrix;

[0026] Step S302: When the optimization index of the SDN controller corresponding to the i-th row of the matrix exceeds a preset threshold, it is considered that there is a need for optimization in the deployment of the i-th SDN controller in the power communication network; the SDN controller with the need for optimization is marked, and a deployment optimization list is generated.

[0027] According to the above method, the control status of the SDN controller over each device in its management area can be reflected. The higher the optimization index of the SDN controller, the more control operations are performed in its management area. In order to avoid excessive load on the controller and reduced network stability, and to prevent the configuration complexity of the controller from becoming more complicated, the SDN controller whose optimization index exceeds the preset threshold is marked as an SDN controller with optimization needs.

[0028] As a preferred solution of the present invention, the implementation process of step S400 includes the following steps:

[0029] Step S401: The deployment optimization list includes several SDN controller codes that have optimization requirements. The optimization requirements of the SDN controllers in the deployment optimization list are analyzed based on the data communication network graph model, and the abnormality of the device represented by the pth row of the matrix corresponding to any SDN controller in the deployment optimization list is calculated according to the following formula:

[0030]

[0031] Among them, X gp represents the value of the gth row and pth column of the matrix, μ p represents the average value of the pth column of the matrix, X gj represents the value of the g-th row and j-th column of the matrix, μ j Represents the average value of all elements in the jth column of the matrix;

[0032] Step S402: When the abnormality of the device represented by the pth row of the matrix corresponding to any SDN controller in the deployment optimization list exceeds a preset threshold, it is considered that the device has an impact on the currently connected SDN controller; based on the optimization demand analysis results of each SDN controller in the deployment optimization list, the deployment optimization demand in the power communication network is fed back to relevant personnel, and the relevant personnel manage the equipment that affects the SDN controller.

[0033] According to the above method, the abnormality of the devices connected to the SDN controller with optimization needs is analyzed to help relevant personnel locate the location of the devices that affect the capabilities of the SDN controller, so that relevant personnel can re-manage the deployment and management area of ​​the SDN controller for specific devices.

[0034] The SDN controller deployment optimization system for power communication networks includes: communication data acquisition module, controller performance analysis module, optimization demand identification module and deployment feedback module;

[0035] The communication data acquisition module is used to obtain the deployment topology data of the power communication network, form a data communication network graph model, monitor the connection of devices in the communication network, and update the data communication network graph model in real time;

[0036] The controller performance analysis module is used to access the SDN controller in the power communication network, collect the operation data of the SDN controller, and analyze the communication performance of each device;

[0037] The optimization requirement identification module is used to analyze the communication network data matrix to determine whether there is an optimization requirement for the deployment of each SDN controller; mark the SDN controller that meets the optimization requirement identification conditions and generate a deployment optimization list;

[0038] The deployment feedback module is used to analyze the SDN controller optimization requirements in the deployment optimization list and feedback the deployment optimization requirements in the power communication network to relevant personnel.

[0039] Further, the controller performance analysis module includes an instruction acquisition unit, a list generation unit and a matrix generation unit;

[0040] The instruction collection unit accesses the SDN controller in the power communication network based on the communication cycle; in the Tth communication cycle, the operation data of the SDN controller is collected, and the instructions received by each device are collected through the data communication network cloud platform during each control execution; wherein the instructions sent by the same SDN controller to the device corresponding to the same connection line are integrated into one instruction cluster;

[0041] The list generation unit coordinates all the collected instruction clusters through the data communication network cloud platform to generate a communication list of the kth communication cycle; the communication list is accompanied by a connection line label of each instruction cluster, and any instruction cluster is recorded as ZC(iQB), where ZC(iQB)={[L z (A j ), L t (A j )]|j∈[1,m]},L z (A j ) indicates device A j The corresponding latest instruction content, L t (A j ) indicates device A j The corresponding latest instruction reception time, the communication list of the kth communication cycle is recorded as LZC k , ZC(iQB)∈LZC k ; And sort the command clusters in the communication list according to the latest command reception time of the device involved;

[0042] The matrix generation unit analyzes the communication performance of each device based on the communication list corresponding to each communication cycle, and generates a communication network data matrix according to the communication performance scores of each SDN controller and the devices connected to the SDN controller in the power communication network, wherein the rows of the matrix represent different SDN controllers, the columns of the matrix represent different devices, and the value of the i-th row and j-th column in the matrix is ​​X ij ; said X ij Calculated according to the following formula:

[0043]

[0044] Among them, X ij represents the communication performance score of the jth device in the communication list of the i-th SDN controller, W represents the total number of communication cycles recorded for the i-th SDN controller, if[(F(LZC k+1 )∩F(LZC k )] represents the discriminant function, F(LZC k+1 ) indicates that the communication list of the k+1th communication cycle contains the instruction cluster of the instruction sent to the jth device; F(LZC k ) represents the instruction cluster containing the instruction sent to the jth device in the communication list of the kth communication cycle; when (F(LZC k+1 )∩F(LZC k ) is empty, if[(F(LZC k+1 )∩F(LZC k )]=0; when (F(LZC k+1 )∩F(LZC k ) is not empty, if[(F(LZC k+1 )∩F(LZC k )]=1.

[0046] Further, the optimization demand identification module includes a matrix analysis unit and a demand analysis unit;

[0047] The matrix analysis unit analyzes the communication network data matrix based on cloud computing, defines the network status of each SDN controller according to the communication network data matrix, checks whether the values ​​in the matrix are evenly distributed, and calculates the optimization index of the SDN controller corresponding to the i-th row of the matrix according to the following formula:

[0048]

[0049] Where N is the total number of SDN controllers, M is the total number of devices connected to the SDN controllers in the power communication network, and μ i represents the average value of all elements in the i-th row of the matrix, and μ represents the average value of all elements in the matrix;

[0050] The demand analysis unit is used to determine whether there is an optimization demand for the deployment of the SDN controller according to the optimization index of the SDN controller, mark the SDN controller with the optimization demand, and generate a deployment optimization list.

[0051] Beneficial effects:

[0052] (1) The present invention manages all devices through a data communication network cloud platform to achieve centralized management and monitoring of the network, pays attention to changes in network topology, and can cope with the uncontrollable disaster recovery problems caused by the expansion of business needs. It provides an abnormal autonomous perception method for an SDN controller, which can analyze the operating status of the communication network in real time, avoiding the complexity and inefficiency caused by decentralized management.

[0053] (2) The present invention adopts a distributed controller architecture and combines it with a centralized control concept to ensure the reliability and stability of each subnet. At the same time, it can dynamically adjust and optimize the judgment strategy according to the actual needs of the network, effectively avoiding the limitations brought by static configuration. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of the SDN controller deployment optimization method for power communication network of the present invention. DETAILED DESCRIPTION

[0055] The technical solution of the present invention will be clearly and completely described below in combination with the embodiments of the present invention and the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] As an embodiment of the present invention, Figure 1 As shown, the present invention provides an SDN controller deployment optimization method for a power communication network, comprising the following steps:

[0057] Step S100: construct a data communication network cloud platform, coordinate all devices in the communication network, obtain deployment topology data of the power communication network, form a data communication network graph model, monitor the connection of devices in the communication network, and update the data communication network graph model in real time;

[0058] Step S101: Build a data communication network cloud platform, coordinate all devices in the communication network, assign coding prefixes according to device types, and uniformly code each device; obtain interface information and connection status from network devices through the SNMP protocol; automatically discover the connection relationship between devices through the LLDP protocol; obtain device status and connection information through the API interface; identify the connection mode between each device in the communication network, and obtain the deployment topology data of the power communication network; when any SDN controller regulates and communicates with any device, collect the northbound interface protocol and southbound interface protocol of the regulation and control communication, mark the connection line with the same intermediate layer service processing request when the same SDN controller regulates and communicates with the device as the Qth regulation and control communication, and connect the i-th SDN controller with the device A j The connection line is recorded as SDN i →Q→B; among them, SDN i represents the code of the i-th SDN controller, Q represents the Q-th intermediate layer service processing request, B={A j |j∈[1,m]},A j represents the code of the jth device, and m represents the total number of devices that process requests through the Qth intermediate layer service when the i-th SDN controller performs control communication;

[0059] Step S102: Based on the control communication records, a data communication network graph model is formed, and the data communication network graph model includes connection lines between each SDN controller and the device; the connection of the devices in the communication network is monitored, and when a new device is added to the communication network, step S101 is repeated to update the connection line of the SDN controller. When the new device does not belong to the existing connection line, a new connection line is generated and the data communication network graph model is expanded; when the interface protocol of the original device in the communication network is changed or the coding is deleted, the connection line of the SDN controller and the data communication network graph model are refreshed.

[0060] According to the above method, the connection lines in the power communication network are divided based on the communication protocol and the content of the middle-layer service processing, and the deployment characteristics of the SDN controller are reflected in the vertical dimension of the network architecture, providing a data source for subsequent data analysis.

[0061] Step S200: Access the SDN controller in the power communication network, collect the operation data of the SDN controller, collect the instructions received by each device through the data communication network cloud platform during each control execution, and generate a communication list according to the instructions; randomly select an SDN controller, analyze the communication performance of each device based on the communication list, and generate a communication network data matrix;

[0062] Step S201: Access the SDN controller in the power communication network based on the communication cycle; in the Tth communication cycle, collect the operation data of the SDN controller, and collect the instructions received by each device through the data communication network cloud platform during each control execution; wherein, the instructions sent by the same SDN controller to the device corresponding to the same connection line are integrated into an instruction cluster, and the data communication network cloud platform coordinates all the collected instruction clusters to generate a communication list of the kth communication cycle; the communication list is accompanied by a connection line label of each instruction cluster, and any instruction cluster is recorded as ZC(iQB), wherein ZC(iQB)={[L z (A j ), L t (A j )]|j∈[1,m]},L z (A j ) indicates device A j The corresponding latest instruction content, L t (A j ) indicates device A j The corresponding latest instruction reception time, the communication list of the kth communication cycle is recorded as LZC k , ZC(iQB)∈LZC k ; And sort the command clusters in the communication list according to the latest command reception time of the device involved;

[0063] Step S202: There are multiple SDN controllers working together in the power communication network, and each controller manages an area or subnet; a SDN controller is randomly selected, and a communication list of the SDN controller is obtained. The communication performance of each device is analyzed based on the communication list corresponding to each communication cycle, and the communication performance score of the selected SDN controller and the device in the power communication network is calculated according to the following formula:

[0064]

[0065] Among them, X ij represents the communication performance score of the jth device in the communication list of the i-th SDN controller, W represents the total number of communication cycles recorded for the i-th SDN controller, if[(F(LZC k+1 )∩F(LZC k )] represents the discriminant function, F(LZC k+1 ) indicates that the communication list of the k+1th communication cycle contains the instruction cluster of the instruction sent to the jth device; F(LZC k ) represents the instruction cluster containing the instruction sent to the jth device in the communication list of the kth communication cycle; when (F(LZC k+1 )∩F(LZC k) is empty, if[(F(LZC k+1 )∩F(LZC k )]=0; when (F(LZC k+1 )∩F(LZC k ) is not empty, if[(F(LZC k+1 )∩F(LZC k )]=1;

[0066] Step S203: Generate a communication network data matrix based on the communication performance scores of each SDN controller and the devices connected to the SDN controller in the power communication network, where the rows of the matrix represent different SDN controllers, the columns of the matrix represent different devices, and the value of the i-th row and j-th column in the matrix is ​​X ij .

[0067] According to the above method, the devices in the power communication network are monitored for receiving instructions, and the communication performance of each SDN controller in the power communication network and the devices connected to the SDN controller in the power communication network are mapped into a matrix. Based on the network architecture, the areas managed by each SDN controller are analyzed, which can reflect the communication frequency and communication volume of each area, so as to facilitate the subsequent further analysis of the capabilities of each SDN controller.

[0068] Step S300: Analyze the communication network data matrix based on cloud computing to determine whether there is an optimization requirement for the deployment of each SDN controller; mark the SDN controller that meets the optimization requirement judgment condition, and generate a deployment optimization list;

[0069] Step S301: Analyze the communication network data matrix based on cloud computing, define the network status of each SDN controller according to the communication network data matrix, check whether the values ​​in the matrix are evenly distributed, and calculate the optimization index of the SDN controller corresponding to the i-th row of the matrix according to the following formula:

[0070]

[0071] Where N is the total number of SDN controllers, M is the total number of devices connected to the SDN controllers in the power communication network, and μ i represents the average value of all elements in the i-th row of the matrix, and μ represents the average value of all elements in the matrix;

[0072] Step S302: When the optimization index of the SDN controller corresponding to the i-th row of the matrix exceeds a preset threshold, it is considered that there is a need for optimization in the deployment of the i-th SDN controller in the power communication network; the SDN controller with the need for optimization is marked, and a deployment optimization list is generated.

[0073] According to the above method, the control status of each device in its management area by the SDN controller can be reflected, and the elastic and agile control of large-scale business can be supported, and a decentralized management mode is provided to facilitate system business operations; the higher the optimization index of the SDN controller, the more control operations are performed in its management area. In order to avoid excessive load on the controller and reduced stability of the network, so that the configuration complexity of the controller does not become more complicated, the SDN controller whose optimization index exceeds the preset threshold is marked as an SDN controller with optimization needs.

[0074] Step S400: Analyze the SDN controller optimization requirements in the deployment optimization list based on the data communication network graph model, and feedback the deployment optimization requirements in the power communication network to relevant personnel;

[0075] Step S401: The deployment optimization list includes several SDN controller codes that have optimization requirements. The optimization requirements of the SDN controllers in the deployment optimization list are analyzed based on the data communication network graph model, and the abnormality of the device represented by the pth row of the matrix corresponding to any SDN controller in the deployment optimization list is calculated according to the following formula:

[0076]

[0077] Among them, X gp represents the value of the gth row and pth column of the matrix, μ p represents the average value of the pth column of the matrix, X gj represents the value of the g-th row and j-th column of the matrix, μ j Represents the average value of all elements in the jth column of the matrix;

[0078] Step S402: When the abnormality of the device represented by the pth row of the matrix corresponding to any SDN controller in the deployment optimization list exceeds a preset threshold, it is considered that the device has an impact on the currently connected SDN controller; based on the optimization demand analysis results of each SDN controller in the deployment optimization list, the deployment optimization demand in the power communication network is fed back to relevant personnel, and the relevant personnel manage the equipment that affects the SDN controller.

[0079] According to the above method, the abnormality of the devices connected to the SDN controller with optimization needs is analyzed to help relevant personnel locate the location of the devices that affect the capabilities of the SDN controller, so that relevant personnel can re-manage the deployment and management area of ​​the SDN controller for specific devices.

[0080] The technical solution of the present invention is described in detail above in conjunction with the embodiments / drawings, but the present invention is not limited to the above technical solution. For ordinary technicians in this technical field, after knowing the contents recorded in the present invention, they can make several equivalent changes and substitutions without departing from the principle of the present invention. These equivalent changes and substitutions should also be regarded as belonging to the protection scope of the present invention.

Claims

1. An SDN controller deployment optimization method for power communication networks, characterized in that: The following steps are involved: Step S100: construct a data communication network cloud platform, coordinate all devices in the communication network, obtain deployment topology data of the power communication network, form a data communication network graph model, monitor the connection of devices in the communication network, and update the data communication network graph model in real time; Step S200: Access the SDN controller in the power communication network, collect the operation data of the SDN controller, collect the instructions received by each device through the data communication network cloud platform during each control execution, and generate a communication list according to the instructions; randomly select an SDN controller, analyze the communication performance of each device based on the communication list, and generate a communication network data matrix; Step S300: Analyze the communication network data matrix based on cloud computing to determine whether there is a need for optimization in the deployment of each SDN controller; Mark the SDN controllers that meet the optimization requirement judgment criteria and generate a deployment optimization list; Step S400: Analyze the SDN controller optimization requirements in the deployment optimization list based on the data communication network graph model, and feedback the deployment optimization requirements in the power communication network to relevant personnel.

2. The SDN controller deployment optimization method for power communication network according to claim 1 is characterized in that: The implementation process of step S100 includes the following steps: Step S101: construct a data communication network cloud platform, coordinate all devices in the communication network, assign coding prefixes according to device types, and uniformly code each device; identify the connection mode between each device in the communication network, and obtain the deployment topology data of the power communication network; When any SDN controller regulates and communicates with any device, the connection line with the same intermediate layer service processing request when the same SDN controller regulates and communicates with the device is marked as the Qth regulation communication, and the i-th SDN controller and device A are j The connection line is recorded as SDN i →Q→B; among them, SDN i represents the code of the i-th SDN controller, Q represents the Q-th intermediate layer service processing request, B={A j |j∈[1,m]},A j represents the code of the jth device, and m represents the total number of devices that process requests through the Qth intermediate layer service when the i-th SDN controller performs control communication; Step S102: Based on the control communication records, a data communication network graph model is formed, and the data communication network graph model includes connection lines between each SDN controller and the device; the connection of the devices in the communication network is monitored, and when a new device is added to the communication network, step S101 is repeated to update the connection line of the SDN controller. When the new device does not belong to the existing connection line, a new connection line is generated and the data communication network graph model is expanded; when the interface protocol of the original device in the communication network is changed or the coding is deleted, the connection line of the SDN controller and the data communication network graph model are refreshed.

3. The SDN controller deployment optimization method for electric power communication network according to claim 1 is characterized in that: The implementation process of step S200 includes the following steps: Step S201: Access the SDN controller in the power communication network based on the communication cycle; in the Tth communication cycle, collect the operation data of the SDN controller, and collect the instructions received by each device through the data communication network cloud platform during each control execution; wherein, the instructions sent by the same SDN controller to the device corresponding to the same connection line are integrated into an instruction cluster, and the data communication network cloud platform coordinates all the collected instruction clusters to generate a communication list of the kth communication cycle; the communication list is accompanied by a connection line label of each instruction cluster, and any instruction cluster is recorded as ZC(iQB), wherein ZC(iQB)={[L z (A j ), L t (A j )]|j∈[1,m]},L z (A j ) indicates device A j The corresponding latest instruction content, L t (A j ) indicates device A j The corresponding latest instruction reception time, the communication list of the kth communication cycle is recorded as LZC k and sort the command clusters in the communication list according to the time when the latest command of the device is received; Step S202: randomly select an SDN controller, obtain the communication list of the SDN controller, analyze the communication performance of each device based on the communication list corresponding to each communication cycle, and calculate the communication performance score between the selected SDN controller and the device in the power communication network according to the following formula: Among them, X ij represents the communication performance score of the jth device in the communication list of the i-th SDN controller, W represents the total number of recorded communication cycles of the i-th SDN controller, if[(F(LZC k+1 )∩F(LZC k )] represents the discriminant function, F(LZC k+1 ) indicates that the communication list of the k+1th communication cycle contains the instruction cluster of the instruction sent to the jth device; F(LZC k ) represents the instruction cluster containing the instruction sent to the jth device in the communication list of the kth communication cycle; when (F(LZC k+1 )∩F(LZC k ) is empty, if[(F(LZC k+1 )∩F(LZC k )]=0; when (F(LZC k+1 )∩F(LZC k ) is not empty, if[(F(LZC k+1 )∩F(LZC k )]=1; Step S203: Generate a communication network data matrix based on the communication performance scores of each SDN controller and the devices connected to the SDN controller in the power communication network, where the rows of the matrix represent different SDN controllers, the columns of the matrix represent different devices, and the value of the i-th row and j-th column in the matrix is ​​X ij .

4. The SDN controller deployment optimization method for electric power communication network according to claim 1 is characterized in that: The implementation process of step S300 includes the following steps: Step S301: Analyze the communication network data matrix based on cloud computing, define the network status of each SDN controller according to the communication network data matrix, and calculate the optimization index of the SDN controller corresponding to the i-th row of the matrix according to the following formula: Where N is the total number of SDN controllers, M is the total number of devices connected to the SDN controllers in the power communication network, and μ i represents the average value of all elements in the i-th row of the matrix, and μ represents the average value of all elements in the matrix; Step S302: When the optimization index of the SDN controller corresponding to the i-th row of the matrix exceeds a preset threshold, it is considered that there is a need for optimization in the deployment of the i-th SDN controller in the power communication network; the SDN controller with the need for optimization is marked, and a deployment optimization list is generated.

5. The SDN controller deployment optimization method for electric power communication network according to claim 4 is characterized in that: The implementation process of step S400 includes the following steps: Step S401: The deployment optimization list includes several SDN controller codes that have optimization requirements. The optimization requirements of the SDN controllers in the deployment optimization list are analyzed based on the data communication network graph model, and the abnormality of the device represented by the pth row of the matrix corresponding to any SDN controller in the deployment optimization list is calculated according to the following formula: Among them, X gp represents the value of the gth row and pth column of the matrix, μ p represents the average value of the pth column of the matrix, X gj represents the value of the g-th row and j-th column of the matrix, μ j Represents the average value of all elements in the jth column of the matrix; Step S402: When the abnormality of the device represented by the pth row of the matrix corresponding to any SDN controller in the deployment optimization list exceeds a preset threshold, it is considered that the device has an impact on the currently connected SDN controller; based on the optimization requirement analysis results of each SDN controller in the deployment optimization list, the deployment optimization requirements in the power communication network are fed back to relevant personnel.

6. An SDN controller deployment optimization system for power communication networks, characterized in that: include: Communication data acquisition module, controller performance analysis module, optimization demand identification module and deployment feedback module; The communication data acquisition module is used to obtain the deployment topology data of the power communication network, form a data communication network graph model, monitor the connection of devices in the communication network, and update the data communication network graph model in real time; The controller performance analysis module is used to access the SDN controller in the power communication network, collect the operation data of the SDN controller, and analyze the communication performance of each device; The optimization requirement identification module is used to analyze the communication network data matrix to determine whether there is an optimization requirement for the deployment of each SDN controller; mark the SDN controller that meets the optimization requirement identification conditions and generate a deployment optimization list; The deployment feedback module is used to analyze the SDN controller optimization requirements in the deployment optimization list and feedback the deployment optimization requirements in the power communication network to relevant personnel.

7. The SDN controller deployment optimization system for electric power communication network according to claim 6 is characterized in that: The controller performance analysis module includes an instruction acquisition unit, a list generation unit and a matrix generation unit; The instruction collection unit accesses the SDN controller in the power communication network based on the communication cycle; in the Tth communication cycle, the operation data of the SDN controller is collected, and the instructions received by each device are collected through the data communication network cloud platform during each control execution; wherein the instructions sent by the same SDN controller to the device corresponding to the same connection line are integrated into one instruction cluster; The list generation unit coordinates all the collected instruction clusters through the data communication network cloud platform to generate a communication list of the kth communication cycle; the communication list is accompanied by a connection line label of each instruction cluster, and any instruction cluster is recorded as ZC(iQB), where ZC(iQB)={[L z (A j ), L t (A j )]|j∈[1,m]},L z (A j ) indicates device A j The corresponding latest instruction content, L t (A j ) indicates device A j The corresponding latest instruction reception time, the communication list of the kth communication cycle is recorded as LZC k and sort the command clusters in the communication list according to the time when the latest command of the device is received; The matrix generation unit analyzes the communication performance of each device based on the communication list corresponding to each communication cycle, and generates a communication network data matrix according to the communication performance scores of each SDN controller and the devices connected to the SDN controller in the power communication network, wherein the rows of the matrix represent different SDN controllers, the columns of the matrix represent different devices, and the value of the i-th row and j-th column in the matrix is ​​X ij ; said X ij Calculated according to the following formula: Among them, X ij represents the communication performance score of the jth device in the communication list of the i-th SDN controller, W represents the total number of recorded communication cycles of the i-th SDN controller, if[(F(LZC k+1 )∩F(LZC k )] represents the discriminant function, F(LZC k+1 ) indicates that the communication list of the k+1th communication cycle contains the instruction cluster of the instruction sent to the jth device; F(LZC k ) represents the instruction cluster containing the instruction sent to the jth device in the communication list of the kth communication cycle; when (F(LZC k+1 )∩F(LZC k ) is empty, if[(F(LZC k+1 )∩F(LZC k )]=0; when (F(LZC k+1 )∩F(LZC k ) is not empty, if[(F(LZC k+1 )∩F(LZC k )]=1.

8. The SDN controller deployment optimization system for electric power communication network according to claim 6, characterized in that: The optimization demand identification module includes a matrix analysis unit and a demand analysis unit; The matrix analysis unit analyzes the communication network data matrix based on cloud computing, defines the network status of each SDN controller according to the communication network data matrix, checks whether the values ​​in the matrix are evenly distributed, and calculates the optimization index of the SDN controller corresponding to the i-th row of the matrix according to the following formula: Where N is the total number of SDN controllers, M is the total number of devices connected to the SDN controllers in the power communication network, and μ i represents the average value of all elements in the i-th row of the matrix, and μ represents the average value of all elements in the matrix; The demand analysis unit is used to determine whether there is an optimization demand for the deployment of the SDN controller according to the optimization index of the SDN controller, mark the SDN controller with the optimization demand, and generate a deployment optimization list.

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