Network planning system and method based on big data analysis

Abstract

The present invention relates to the field of network planning technology, and is used to solve the problem that in the existing network planning method, it is impossible to accurately determine the state of network business requirements, resulting in the inability to provide accurate guidance in network construction; it is also difficult to accurately analyze the transmission performance and security level of network planning, and thus the security and stability of the later network cannot be guaranteed. Specifically, it is a network planning system and method based on big data analysis, including a data acquisition module, a network business demand analysis module, a network topology analysis module, a network transmission performance analysis module, a network security status analysis module, a cloud storage library and a display terminal. The present invention, through data analysis, performs a comprehensive auxiliary determination of the state of network planning from the business demand level, the topology construction level, and the transmission performance and security performance level, and provides strong data support for building a reasonable network environment.

Description

Technical Field

[0001] The present invention relates to the technical field of network planning, and in particular to a network planning system and method based on big data analysis. Background Art

[0002] Network planning refers to the process of designing and deploying a network system based on factors such as network topology, hardware equipment, software applications, and security protection in order to meet specific business needs and goals.

[0003] With the rapid development of network technology, network planning has become an indispensable step in network engineering construction. The quality of network planning determines whether the network is available. Therefore, it is very important to clarify the status of network planning.

[0004] However, the existing network planning methods cannot accurately determine the status of network service demand, resulting in the inability to provide accurate guidance during network construction;

[0005] It is also difficult to accurately analyze the transmission performance and security level of network planning, and thus it is impossible to guarantee the security and stability of the subsequent network. Summary of the invention

[0006] The purpose of the present invention is to solve the problem that in the existing network planning method, it is impossible to accurately determine the status of network business needs, resulting in the inability to provide accurate guidance in network construction; it is also difficult to accurately analyze the transmission performance and security level of network planning, and thus the security and stability of the subsequent network cannot be guaranteed. Through data analysis, the status of network planning is comprehensively auxiliary determined from the business demand level, topology structure construction level, transmission performance and security performance level, and strong data support is provided for building a reasonable network environment, and a network planning system and method based on big data analysis are proposed.

[0007] The object of the present invention can be achieved by the following technical solutions: a network planning system based on big data analysis, including a data acquisition module, a network service demand analysis module, a network topology structure analysis module, a network transmission performance analysis module, a network security status analysis module, a cloud storage library and a display terminal;

[0008] The data acquisition module is used to collect the business demand information, topology information, transmission performance information, and security status information of the target network in the network planning process, and send them to the network business demand analysis module, the network topology analysis module, the network transmission performance analysis module, and the network security status analysis module respectively;

[0009] The network service demand analysis module is used to monitor the service demand information of the target network, thereby analyzing the demand status of the target network;

[0010] The network topology analysis module is used to monitor the network topology information of the target network, thereby analyzing the topology state of the target network;

[0011] The network transmission performance analysis module is used to monitor the transmission performance information of the target network, thereby analyzing the transmission performance status of the target network;

[0012] The network security status analysis module is used to monitor the security status information of the target network, thereby analyzing the security status of the target network;

[0013] The cloud storage repository is used to store a topology type table of the target network, a transmission performance level classification table of the target network, and a security performance level classification table of the target network.

[0014] Preferably, the monitoring and analysis of the service demand information of the target network is performed in the following specific process:

[0015] Obtain the bandwidth requirement value, delay requirement value and service data volume in the service demand information of the target network, and mark them as dk, sy and sl respectively, and perform formula analysis on them. Obtain the service demand coefficient bdc of the target network, where λ1, λ2 and λ3 are weight factor coefficients of bandwidth demand value, delay requirement value and service data volume, respectively, and λ1, λ2 and λ3 are all natural numbers greater than 0;

[0016] It should be noted that the bandwidth requirement value refers to the data value of the bandwidth required by the network service when the service is running, and the delay requirement value is used to represent the data value of the maximum delay limit allowed in the target network operation;

[0017] Setting a first demand comparison interval, a second demand comparison interval, and a third demand comparison interval for the service demand coefficient of the target network, and substituting the service demand coefficient of the target network into the preset first demand comparison interval, the second demand comparison interval, and the third demand comparison interval for comparative analysis;

[0018] When the service demand coefficient of the target network is within a preset first demand comparison interval, a low-demand service signal is generated; when the service demand coefficient of the target network is within a preset second demand comparison interval, a medium-demand service signal is generated; and when the service demand coefficient of the target network is within a preset third demand comparison interval, a high-demand service signal is generated.

[0019] Preferably, the topological structure information of the target network is monitored, and the specific monitoring process is as follows:

[0020] The number of devices and the total number of cables to be connected to the target network are obtained, and they are marked as i and dl respectively, and then normalized and analyzed. According to the set formula td=μ1*i+μ2*dl, the structural coefficient td of the target network is obtained, where μ1 and μ2 are the normalization factor coefficients of the number of devices and the total number of cables respectively, and both μ1 and μ2 are natural numbers greater than 0;

[0021] Based on the number of devices to be connected to the target network, the bandwidth value, delay value, throughput and encryption level of the performance parameters of each target device are obtained and marked as bv i 、dv i 、tc i and sg i , and conduct a formal analysis based on the set formula The performance feedback coefficient fkx of each target device is obtained i , where i = 1, 2, 3 ... n, and i represents the number of target devices, γ1, γ2, γ3 and γ4 are correction factor coefficients of bandwidth value, delay value, throughput and encryption level respectively, and γ1, γ2, γ3 and γ4 are all natural numbers greater than 0;

[0022] The performance feedback coefficients of each target device are analyzed by the mean value, according to the formula Get the average performance feedback coefficient fkx of all devices corresponding to the target network topology * .

[0023] Preferably, the network topology state of the target network is analyzed, and the specific analysis steps are as follows:

[0024] Obtain the structural coefficient, average performance feedback coefficient, number of nodes and construction cost value in the topological structure information of the target network, and analyze them in a formula according to the set formula tpx=ρ1×td+ρ2×fkx * +ρ3×ps+ρ4×cb, the topological structure discrimination coefficient tpx of the target network is obtained, where ps represents the number of nodes, cb represents the construction cost value, ρ1, ρ2, ρ3 and ρ4 are the error factor coefficients of the structure coefficient, average performance feedback coefficient, number of nodes and construction cost value respectively, and ρ1, ρ2, ρ3 and ρ4 are all natural numbers greater than 0;

[0025] The topological structure discrimination coefficient of the target network is compared and matched with the topological structure type table stored in the database to obtain the corresponding network topological structure, and each topological structure discrimination coefficient of the target network corresponds to a network topological structure.

[0026] Preferably, the transmission performance information of the target network is monitored, and the specific monitoring process is as follows:

[0027] Divide a period of time into j equal time points, where j = 1, 2, 3, ... m;

[0028] Capture the transmission rate of the target network for a period of time and calculate the standard deviation according to the formula Get the transmission rate fluctuation value σ of the target network, where csl j represents the jth time data point, csl * is the average value of all data, that is, the average value of the transmission rate over a period of time, and m is the size of all data sets;

[0029] Record the amount of data packets sent and received by the target network respectively, and record them as fmb and smb respectively, and analyze the two data by formula. Thus, the data transmission packet loss rate ut of the target network is obtained, where t represents the transmission time.

[0030] Preferably, the transmission performance status of the target network is analyzed, and the specific analysis steps are as follows:

[0031] Obtain the transmission rate fluctuation value, data transmission packet loss rate and data transmission rate from the transmission performance information of the target network, and analyze the three data in a formula. The transmission performance index Nc of the target network is obtained, where lv represents the data transmission rate of the target network, δ1, δ2 and δ3 are the transmission rate fluctuation value, data transmission packet loss rate and data transmission rate weighting factor coefficient respectively;

[0032] The transmission performance index of the target network is compared and matched with the transmission performance level classification table stored in the database, thereby obtaining the corresponding transmission performance level of the target network, and each transmission performance index of the target network corresponds to a transmission performance level.

[0033] Preferably, the monitoring of the target network's security status information and the analysis of the security status are performed in the following specific processes:

[0034] Obtain the user identity authentication mode value, emergency response alternative plan value and encryption key length value in the security status information of the target network, and mark them as s1, s2 and s3 respectively, and perform a comprehensive analysis on them. According to the set formula sty=s1+s2+zhy×s3, the security performance coefficient sty of the target network is obtained, where zhy is the conversion factor coefficient of the encryption key length value, and zhy is a natural number greater than 0;

[0035] The safety performance coefficient of the target network is compared and matched with the safety performance level classification table stored in the database to obtain the corresponding safety performance level of the target network, and the safety performance coefficient of each target network corresponds to a safety performance level.

[0036] The network planning method based on big data analysis includes the following steps:

[0037] Step 1: Collect the target network's business demand information, topology information, transmission performance information, and security status information during the network planning process;

[0038] Step 2: Monitor the service demand information of the target network, analyze the demand status of the target network, and send the obtained service demand status determination result to the display terminal for feedback explanation;

[0039] Step 3: Monitor the topological structure information of the target network, analyze the topological structure state of the target network, and send the obtained network topological structure determination result to the display terminal for feedback explanation;

[0040] Step 4: monitoring the transmission performance information of the target network, thereby analyzing the transmission performance status of the target network, and sending the obtained transmission performance level determination result to the display terminal for feedback explanation;

[0041] Step 5: Monitor the security status information of the target network, analyze the security status of the target network, and send the obtained security performance level determination result to the display terminal for feedback.

[0042] Beneficial effects of the present invention:

[0043] Through data calibration, formula calculation and gradient interval substitution analysis, the service demand level of the target network is clarified, laying the foundation for achieving reasonable network planning;

[0044] The network topology information of the target network is clarified through normalization analysis and mean analysis, and the topology status of the target network is analyzed. The planning status of the target network is determined and analyzed from the topology level through formula analysis and database comparison and matching analysis.

[0045] By using the time equalization setting, standard deviation calculation and data proportion analysis, the transmission performance information of the target network is clarified. Based on this, the transmission performance status of the target network is clearly determined and analyzed by using comprehensive analysis and data substitution comparison analysis.

[0046] Through data physical quantity conversion and data superposition, the planning method of the target network is analyzed from the perspective of network security performance, laying the foundation for the reasonable planning and construction of the network.

[0047] It provides comprehensive auxiliary judgment on the status of network planning from the perspectives of business needs, topology construction, transmission performance, and security performance, and provides strong data support for building a reasonable network environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will be further described below in conjunction with the accompanying drawings.

[0049] Figure 1 is a system block diagram of the present invention;

[0050] Figure 2 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0052] Embodiment 1:

[0053] See also Figure 1 As shown, the present invention is a network planning system based on big data analysis, including: a data acquisition module, a network business demand analysis module, a network topology structure analysis module, a network transmission performance analysis module, a network security status analysis module, a cloud storage library and a display terminal.

[0054] It should be noted that the data acquisition module, network business demand analysis module, network topology analysis module, network transmission performance analysis module, and network security status analysis module are respectively connected to the cloud storage repository, and the network business demand analysis module, network topology analysis module, network transmission performance analysis module, and network security status analysis module are respectively connected to the display terminal.

[0055] The data acquisition module is used to collect the business demand information, topology information, transmission performance information, and security status information of the target network in the network planning process, and send them to the network business demand analysis module, network topology analysis module, network transmission performance analysis module, and network security status analysis module respectively.

[0056] The cloud storage repository is used to store the topology type table of the target network, the transmission performance level classification table of the target network, and the security performance level classification table of the target network.

[0057] The network service demand analysis module is used to monitor the service demand information of the target network and analyze the demand status of the target network. The specific process is as follows:

[0058] Obtain the bandwidth requirement value, delay requirement value and service data volume in the service demand information of the target network, and mark them as dk, sy and sl respectively, and perform formula analysis on them. Obtain the service demand coefficient bdc of the target network, where λ1, λ2 and λ3 are weight factor coefficients of bandwidth demand value, delay requirement value and service data volume, respectively, and λ1, λ2 and λ3 are all natural numbers greater than 0, and the weight factor coefficient is used to balance the weight of each data in the formula calculation, thereby promoting the accuracy of the calculation result;

[0059] It should be noted that the bandwidth requirement value refers to the data value of the bandwidth required by the network service when the service is running, and the delay requirement value is used to represent the data value of the maximum delay limit allowed in the target network operation;

[0060] Set the first demand comparison interval, the second demand comparison interval, and the third demand comparison interval of the service demand coefficient of the target network, and substitute the service demand coefficient of the target network into the preset first demand comparison interval, the second demand comparison interval, and the third demand comparison interval for comparative analysis. It should be noted that the interval values ​​of the first demand comparison interval, the second demand comparison interval, and the third demand comparison interval increase in a gradient;

[0061] When the service demand coefficient of the target network is within the preset first demand comparison interval, a low-demand service signal is generated; when the service demand coefficient of the target network is within the preset second demand comparison interval, a medium-demand service signal is generated; when the service demand coefficient of the target network is within the preset third demand comparison interval, a high-demand service signal is generated, and the obtained service demand status determination result is sent to the display terminal for feedback.

[0062] The network topology analysis module is used to monitor the network topology information of the target network. The specific monitoring process is as follows:

[0063] The number of devices and the total number of cables to be connected to the target network are obtained, and they are marked as i and dl respectively, and then normalized and analyzed. According to the set formula td=μ1*i+μ2*dl, the structural coefficient td of the target network is obtained, where μ1 and μ2 are the normalization factor coefficients of the number of devices and the total number of cables respectively, and μ1 and μ2 are natural numbers greater than 0, and the normalization factor coefficient is used to represent the coefficient for converting the data of the number of devices and the total number of cables into dimensionless form;

[0064] Based on the number of devices to be connected to the target network, the bandwidth value, delay value, throughput and encryption level of the performance parameters of each target device are obtained and marked as bv i 、dv i 、tc i and sg i , and conduct a formal analysis based on the set formula The performance feedback coefficient fkx of each target device is obtained i , where i = 1, 2, 3 ... n, and i represents the number of target devices, γ1, γ2, γ3 and γ4 are correction factor coefficients of bandwidth value, delay value, throughput and encryption level respectively, and γ1, γ2, γ3 and γ4 are all natural numbers greater than 0. The correction factor coefficient is used to correct the deviation of various parameters in the process of formula calculation, so as to calculate more accurate parameter data;

[0065] It should be noted that the bandwidth value refers to the data transmission rate supported by the target device, the throughput represents the effective data flow that the target device can process and transmit, and the encryption level represents the strength level of the encryption algorithms and protocols supported by the target device;

[0066] The performance feedback coefficients of each target device are analyzed by the mean value, according to the formula Get the average performance feedback coefficient fkx of all devices corresponding to the target network topology * ;

[0067] The topological structure status of the target network is analyzed. The specific analysis steps are as follows:

[0068] Obtain the structural coefficient, average performance feedback coefficient, number of nodes and construction cost value in the topological structure information of the target network, and analyze them in a formula according to the set formula tpx=ρ1×td+ρ2×fkx *+ρ3×ps+ρ4×cb, the topological structure discrimination coefficient tpx of the target network is obtained, where ps represents the number of nodes, cb represents the construction cost value, ρ1, ρ2, ρ3 and ρ4 are the error factor coefficients of the structure coefficient, average performance feedback coefficient, number of nodes and construction cost value respectively, and ρ1, ρ2, ρ3 and ρ4 are all natural numbers greater than 0, and the error factor coefficient is used to adjust the errors in the calculation process of the structure coefficient, average performance feedback coefficient, number of nodes and construction cost value to reduce the error of the calculation result;

[0069] The topology structure discrimination coefficient of the target network is compared and matched with the topology structure type table stored in the database to obtain the corresponding network topology structure. Each topology structure discrimination coefficient of the target network corresponds to a network topology structure, and the obtained network topology structure judgment result is sent to the display terminal for feedback.

[0070] The network transmission performance analysis module is used to monitor the transmission performance information of the target network. The specific monitoring process is as follows:

[0071] Divide a period of time into j equal time points, where j = 1, 2, 3, ... m;

[0072] Capture the transmission rate of the target network for a period of time and calculate the standard deviation according to the formula Get the transmission rate fluctuation value σ of the target network, where cs l j represents the jth time data point, cs l * is the average value of all data, that is, the average value of the transmission rate over a period of time, and m is the size of all data sets;

[0073] Record the amount of data packets sent and received by the target network respectively, and record them as fmb and smb respectively, and analyze the two data by formula. Thus, the data transmission packet loss rate ut of the target network is obtained, where t represents the transmission time;

[0074] The transmission performance status of the target network is analyzed. The specific analysis steps are as follows:

[0075] Obtain the transmission rate fluctuation value, data transmission packet loss rate and data transmission rate from the transmission performance information of the target network, and analyze the three data in a formula. The transmission performance index Nc of the target network is obtained, where lv represents the data transmission rate of the target network, δ1, δ2 and δ3 are the transmission rate fluctuation value, data transmission packet loss rate and data transmission rate weighting factor coefficient respectively, and the weighting factor coefficient is used to reduce the error of the calculation result;

[0076] The transmission performance index of the target network is compared and matched with the transmission performance level grading table stored in the database to obtain the corresponding transmission performance level of the target network. Each transmission performance index of the target network corresponds to a transmission performance level, and the obtained transmission performance level determination result is sent to the display terminal for feedback.

[0077] The network security status analysis module is used to monitor the security status information of the target network and analyze the security status of the target network. The specific process is as follows:

[0078] Obtain the user identity authentication mode value, emergency response alternative plan value and encryption key length value in the security status information of the target network, and mark them as s1, s2 and s3 respectively, and perform comprehensive analysis on them, and obtain the security performance coefficient sty of the target network according to the set formula sty=s1+s2+zhy×s3, wherein zhy is the conversion factor coefficient of the encryption key length value, and zhy is a natural number greater than 0, and the conversion factor coefficient is used to convert the physical quantity of the encryption key length value into a data coefficient of the same physical quantity as the user identity authentication mode value and the emergency response alternative plan value;

[0079] It should be noted that the user authentication method value is used to indicate the type of authentication method that the target network can use, and the authentication methods include password authentication, SMS verification code authentication, fingerprint authentication, etc. Assuming that the target network can use both password authentication and SMS verification code authentication, the user authentication method value is 2; the emergency response alternative plan value is used to indicate the number of alternative plans for the emergency response plan formulated by the target network during planning. The emergency response plan is a response plan for various network security incidents. Assuming that three emergency response plans are formulated for the target network, the emergency response alternative plan value is 3; the encryption key length value is used to measure the security level of the target network planning. The longer the key length, the higher the security of the target network planning.

[0080] The safety performance coefficient of the target network is compared and matched with the safety performance level classification table stored in the database to obtain the corresponding safety performance level of the target network. The safety performance coefficient of each target network corresponds to a safety performance level, and the obtained safety performance level determination result is sent to the display terminal for feedback.

[0081] Embodiment 2:

[0082] See also Figure 2 As shown, the present invention is a network planning method based on big data analysis, comprising the following steps:

[0083] Step 1: Collect the target network's business demand information, topology information, transmission performance information, and security status information during the network planning process;

[0084] Step 2: Monitor the service demand information of the target network, analyze the demand status of the target network, and send the obtained service demand status determination result to the display terminal for feedback explanation;

[0085] Step 3: Monitor the topological structure information of the target network, analyze the topological structure state of the target network, and send the obtained network topological structure determination result to the display terminal for feedback explanation;

[0086] Step 4: monitoring the transmission performance information of the target network, thereby analyzing the transmission performance status of the target network, and sending the obtained transmission performance level determination result to the display terminal for feedback explanation;

[0087] Step 5: Monitor the security status information of the target network, analyze the security status of the target network, and send the obtained security performance level determination result to the display terminal for feedback.

[0088] When the present invention is used, the service demand level of the target network is clarified by monitoring the service demand information of the target network and analyzing the demand status, and adopting the methods of data calibration, formula calculation and gradient interval substitution analysis, thereby laying a foundation for realizing reasonable network planning;

[0089] By monitoring the network topology information of the target network, the network topology information of the target network is clarified by using normalization analysis and mean analysis, and the topology status of the target network is analyzed accordingly. By using formula analysis and database comparison and matching analysis, the planning status of the target network is determined and analyzed from the topology level.

[0090] By monitoring the transmission performance information of the target network, the transmission performance information of the target network is clarified by using the time equalization setting, standard deviation calculation and data proportion analysis. Based on this, the transmission performance status of the target network is clearly determined and analyzed by using comprehensive analysis and data substitution comparison analysis.

[0091] By monitoring and analyzing the security status of the target network, using data physical quantity conversion and data superposition, the planning method of the target network is analyzed from the perspective of network security performance, laying the foundation for the reasonable planning and construction of the network.

[0092] It provides comprehensive auxiliary judgment on the status of network planning from the perspectives of business needs, topology construction, transmission performance, and security performance, and provides strong data support for building a reasonable network environment.

[0093] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A network planning system based on big data analysis, characterized in that: include: The data collection module is used to collect the business demand information, topology information, transmission performance information, and security status information of the target network in the network planning process; The network service demand analysis module is used to monitor the service demand information of the target network and analyze the demand status of the target network; A network topology analysis module is used to monitor the network topology information of the target network, thereby analyzing the topology state of the target network; The network transmission performance analysis module is used to monitor the transmission performance information of the target network, thereby analyzing the transmission performance status of the target network; A network security status analysis module is used to monitor the security status information of the target network, thereby analyzing the security status of the target network; A cloud storage repository, used to store a topology type table of a target network, a transmission performance level classification table of a target network, and a security performance level classification table of a target network; The specific process of monitoring and analyzing the service demand information of the target network is as follows: Obtain the bandwidth requirement value, delay requirement value and service data volume in the service requirement information of the target network, and perform formula analysis on them to obtain the service requirement coefficient of the target network; Setting a first demand comparison interval, a second demand comparison interval, and a third demand comparison interval for the service demand coefficient of the target network, and substituting the service demand coefficient of the target network into the preset first demand comparison interval, the second demand comparison interval, and the third demand comparison interval for comparative analysis; When the service demand coefficient of the target network is within a preset first demand comparison interval, a low demand service signal is generated; when the service demand coefficient of the target network is within a preset second demand comparison interval, a medium demand service signal is generated; when the service demand coefficient of the target network is within a preset third demand comparison interval, a high demand service signal is generated; The topological structure information of the target network is monitored, and the specific monitoring process is as follows: The number of devices and the total number of cables to be connected to the target network are obtained, and they are marked as i and dl respectively, and then normalized and analyzed. According to the set formula td=μ1*i+μ2*dl, the structural coefficient td of the target network is obtained, where μ1 and μ2 are the normalization factor coefficients of the number of devices and the total number of cables respectively, and both μ1 and μ2 are natural numbers greater than 0; Based on the number of devices to be connected to the target network, the bandwidth value, delay value, throughput and encryption level of the performance parameters of each target device are obtained, and the performance feedback coefficient of each target device is obtained by formulating and analyzing the performance parameters; Perform mean analysis on the performance feedback coefficient of each target device to obtain the average performance feedback coefficient of all devices corresponding to the target network topology; The network topology state of the target network is analyzed, and the specific analysis steps are as follows: Obtain the structure coefficient, average performance feedback coefficient, number of nodes and construction cost value in the topological structure information of the target network, and perform a formula analysis on them to obtain the topological structure discrimination coefficient of the target network; The topological structure discrimination coefficient of the target network is compared and matched with the topological structure type table stored in the database, thereby obtaining the corresponding network topological structure, and each topological structure discrimination coefficient of the target network corresponds to a network topological structure; The transmission performance information of the target network is monitored, and the specific monitoring process is as follows: Divide a period of time into j equal time points, where j = 1, 2, 3, ... m; Capture the transmission rate of the target network for a period of time and calculate the standard deviation according to the formula Get the transmission rate fluctuation value σ of the target network, where csl j represents the jth time data point, csl * is the average value of all data, that is, the average value of the transmission rate over a period of time, and m is the size of all data sets; Record the amount of data packets sent and received by the target network respectively, and record them as fmb and smb respectively, and analyze the two data by formula. Thus, the data transmission packet loss rate ut of the target network is obtained, where t represents the transmission time; The transmission performance status of the target network is analyzed, and the specific analysis steps are as follows: Obtain the transmission rate fluctuation value, data transmission packet loss rate and data transmission rate from the transmission performance information of the target network, and analyze the three data in a formula. The transmission performance index Nc of the target network is obtained, where lv represents the data transmission rate of the target network, δ1, δ2 and δ3 are the transmission rate fluctuation value, data transmission packet loss rate and data transmission rate weighting factor coefficient respectively; er represents the transmission rate fluctuation value of the target network; The transmission performance index of the target network is compared and matched with the transmission performance level classification table stored in the database, thereby obtaining the corresponding transmission performance level of the target network, and each transmission performance index of the target network corresponds to a transmission performance level; The specific process of monitoring the security status information of the target network and analyzing the security status is as follows: Obtain the user identity authentication mode value, emergency response alternative plan value and encryption key length value in the security status information of the target network, and mark them as s1, s2 and s3 respectively, and perform a comprehensive analysis on them. According to the set formula sty=s1+s2+zhy×s3, the security performance coefficient sty of the target network is obtained, where zhy is the conversion factor coefficient of the encryption key length value, and zhy is a natural number greater than 0; The safety performance coefficient of the target network is compared and matched with the safety performance level classification table stored in the database, thereby obtaining the corresponding safety performance level of the target network, and each safety performance coefficient of the target network corresponds to a safety performance level; 2. The network planning system based on big data analysis according to claim 1, characterized in that: The method based on the network planning system comprises the following steps: Step 1: Collect the target network's business demand information, topology information, transmission performance information, and security status information during the network planning process; Step 2: Monitor the service demand information of the target network, analyze the demand status of the target network, and send the obtained service demand status determination result to the display terminal for feedback explanation; Step 3: Monitor the topological structure information of the target network, analyze the topological structure state of the target network, and send the obtained network topological structure determination result to the display terminal for feedback explanation; Step 4: monitoring the transmission performance information of the target network, thereby analyzing the transmission performance status of the target network, and sending the obtained transmission performance level determination result to the display terminal for feedback explanation; Step 5: Monitor the security status information of the target network, analyze the security status of the target network, and send the obtained security performance level determination result to the display terminal for feedback.

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