CN117527625A - Network flow data acquisition, big data analysis and visual presentation method - Google Patents

Network flow data acquisition, big data analysis and visual presentation method Download PDF

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CN117527625A
CN117527625A CN202410021160.8A CN202410021160A CN117527625A CN 117527625 A CN117527625 A CN 117527625A CN 202410021160 A CN202410021160 A CN 202410021160A CN 117527625 A CN117527625 A CN 117527625A
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network
stability
safety
data
security
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CN117527625B (en
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朱家成
彭中莲
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Changchun Lianxinhua Information Technology Co ltd
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Changchun Lianxinhua Information Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/04—Processing captured monitoring data, e.g. for logfile generation
    • H04L43/045—Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0686—Additional information in the notification, e.g. enhancement of specific meta-data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/06—Generation of reports
    • H04L43/062—Generation of reports related to network traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0823—Errors, e.g. transmission errors
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876—Network utilisation, e.g. volume of load or congestion level
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/16—Threshold monitoring
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Environmental & Geological Engineering (AREA)
  • Data Mining & Analysis (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

The invention discloses a network traffic data acquisition, big data analysis and visual presentation method, which relates to the technical field of network traffic, and comprises the steps of acquiring network traffic data through an information acquisition unit, analyzing and processing the network traffic data through a data analysis unit, so as to judge the accuracy of network transmission and the efficiency of network operation, further judge the safety and stability degree of the network, display the evaluation coefficients of the safety and the stability of the network in real time through a control display unit, set an alarm mechanism, establish an optimization model, and carry out risk control and alarm prompt on the safety and the stability of the network, thereby carrying out corresponding fault processing in time, identifying and defending network security threats, and optimizing the performance of the network operation state.

Description

Network flow data acquisition, big data analysis and visual presentation method
Technical Field
The invention relates to the technical field of network traffic, in particular to a network traffic data acquisition, big data analysis and visual presentation method.
Background
The network traffic is the data quantity transmitted on the network, the size of the network traffic has important significance on the network architecture design, the large data analysis refers to the analysis of large-scale data, and accordingly, the utilization of data warehouse, data security, data analysis, data mining and the like around the large data gradually occurs, and the problems of network security and unstable use performance can occur in the network operation process;
however, the repairing process is generally only performed when a network has a fault problem, so that hysteresis exists in the network problem processing, real-time visual analysis and presentation of the safety and stability of the network operation cannot be performed, the dangerous degree and the fluctuation degree are difficult to judge, risk early warning is also difficult to perform, and unexpected faults are caused in the network use process, so that various losses are caused;
aiming at the technical defects, a network flow data acquisition, big data analysis and visual presentation method is provided.
Disclosure of Invention
The invention aims to provide a network traffic data acquisition, big data analysis and visual presentation method, which solves the problems.
In order to achieve the above purpose, the present invention adopts the following technical scheme: a network traffic data acquisition, big data analysis and visual presentation method comprises the following steps:
step one: the information acquisition unit acquires network flow data and sends the network flow data to the data analysis unit, wherein the network flow data comprises a safety parameter and a stability parameter;
step two: the data analysis unit analyzes and processes the network flow data and judges the network security degree and the network stability degree, wherein the data analysis unit comprises a security analysis unit and a stability analysis unit;
the security analysis unit firstly acquires the data error rate and the access error rate according to the security parameters, then acquires the transmission accuracy, judges the accuracy of network transmission, and then generates a security evaluation coefficient by combining the transmission accuracy with the access error rate to judge the network security degree;
the stability analysis unit firstly acquires the data acquisition rate according to the stability parameters, then acquires the network operation efficiency, combines the network operation efficiency with the safety evaluation coefficient to generate a stability evaluation coefficient, and judges the network stability degree;
step three: the control display unit displays the safety evaluation coefficient and the stability evaluation coefficient in real time, and respectively processes according to the network safety degree and the network stability degree:
setting an alarm mechanism according to the network security degree, and identifying and defending network security threats;
and according to the network stability degree, an optimization model is established, and the performance of the network running state is optimized.
Preferably, the safety analysis unit is processed as follows:
the security parameters comprise load data A before a transmission process, load data B after the transmission process, error access quantity Fc, user access quantity Fy and transmission packet loss rate Dc;
a1: firstly, establishing a picture comparison model, comparing load data A with load data B, and acquiring a data error rate Lsj in a data transmission process;
the picture comparison model is established by the following steps:
s1: acquiring picture information Ta of the load data A and picture information Tb of the load data B through scanning, and establishing a rectangular coordinate system of the picture information Ta and the picture information Tb by using the same base point;
s2: any position in the picture information Ta is defined as i0, and the same position of the picture information Tb is defined as i1;
s3: the color at i0 is detected as S0, the color at i1 is detected as S1, the number of detection points for sampling is set to Ni,
when s0=s1, the number of recording errors m=0; when s0+.s1, the number of recording errors m=1;
s4: obtaining a data error rate Lsj by measuring and calculating the duty ratio of the total number of errors in the sampled detection points:
a2: then, the access error rate Lfw of the network operation process is obtained by calculating the duty ratio of the error access quantity Fc in the user access quantity Fy;
a3: acquiring transmission accuracy Zcs through the data error rate Lsj and the transmission packet loss rate Dc;
the formula of the preset transmission accuracy Zcs is:；
a4: generating a security assessment coefficient Xaq by assigning a weight factor to the transmission accuracy Zcs in combination with the access error rate Lfw;
the formula of the preset security evaluation coefficient Xaq is:；
wherein, alpha 1 and alpha 2 are respectively the weight factor coefficients of the transmission accuracy Zcs combined with the access error rate Lfw, and both alpha 1 and alpha 2 are larger than 0;
a5: the transmission accuracy Zcs and the security evaluation coefficient Xaq are further analyzed to determine the accuracy of network transmission and the degree of network security.
Preferably, the further analysis of the transmission accuracy Zcs and the security assessment coefficient Xaq is as follows:
a1: the transmission accuracy Zcs is preset with a grading interval of accuracy, and the accuracy of network transmission is judged;
the method comprises the steps of comparing an actual measurement value of transmission accuracy Zcs with a preset interval to generate a corresponding accuracy prompt signal and sending the corresponding accuracy prompt signal to a control display unit;
a2: presetting a security grading interval for a security evaluation coefficient Xaq, and judging the network security degree;
the safety interval, the risk interval and the unsafe interval of the safety are preset, the actual measuring and calculating value of the safety evaluation coefficient Xaq is compared with the preset interval, and corresponding safety signals are generated and sent to the control display unit.
Preferably, the stability analysis unit is processed as follows:
the stability parameters include a data packet transmission rate Vcs, a data packet length L, and a data packet timestamp T;
b1: firstly, acquiring a data packet acquisition time period Ti through a data packet time stamp T, and acquiring a data acquisition rate Vcj through measuring and calculating the data packet length L in a unit time period;
b2: combining the data packet transmission rate Vcs with the data acquisition rate Vcj to obtain the network operation efficiency Wyx;
the formula of the preset network operation efficiency Wyx is as follows:；
b3: generating a stability evaluation coefficient Xwd by assigning a weight factor to the network operation efficiency Wyx and the security evaluation coefficient Xaq;
the formula of the preset stability evaluation coefficient Xwd is:；
wherein, beta 1 and beta 2 are respectively the weight factor coefficients of the network operation efficiency Wyx and the security evaluation coefficient Xaq, and beta 1 and beta 2 are both larger than 0;
b4: further analysis of the network operating efficiency Wyx and stability assessment coefficient Xwd determines the efficiency of network operation and the degree of network stability.
Preferably, the further analysis of the network operating efficiency Wyx and stability assessment coefficients Xwd is as follows:
b1: judging the efficiency of network operation by presetting a grading interval of the efficiency of the network operation Wyx;
comparing an actual measured value of the network operation efficiency Wyx with a preset interval to generate a corresponding efficiency prompt signal and sending the corresponding efficiency prompt signal to a control display unit;
b2: presetting a stability grading interval for a stability evaluation coefficient Xwd, and judging the network stability degree;
the stability interval, the risk interval and the instability interval of the stability are preset, the actual measuring and calculating value of the stability evaluation coefficient Xwd is compared with the preset interval, and corresponding stability signals are generated and sent to the control display unit.
Preferably, the specific process of setting the alarm mechanism is as follows:
c1: establishing a dynamic graph of the safety evaluation coefficient Xaq and the time T, substituting the dynamic graph into a curvature measuring and calculating model to obtain a safety fluctuation coefficient Jaq, and predicting the fluctuation trend of safety;
c2: setting a threshold value of a safety fluctuation coefficient Jaq, and when the safety fluctuation coefficient Jaq exceeds the threshold value, indicating that the safety fluctuation amplitude is large, generating a first early warning signal and sending the first early warning signal to a visual terminal so as to control the visual terminal to edit and display a first early warning text;
and C3: receiving an accuracy prompt signal and a safety signal, and respectively carrying out corresponding processing:
c3-1: when receiving the accuracy prompt signal, immediately editing and displaying a corresponding accuracy prompt text;
c3-2: when the safety signal is received, the corresponding safety alarm text is immediately edited for display, and the corresponding indicator lamp is controlled to flash.
Preferably, the specific process of establishing the optimization model is as follows:
d1: establishing a dynamic curve graph of the stability evaluation coefficient Xwd and the time T, substituting the dynamic curve graph into a curvature measuring and calculating model to obtain a stability fluctuation coefficient Jwd, and predicting the fluctuation trend of stability;
d2: setting a threshold value of a stability fluctuation coefficient Jwd, when the stability fluctuation coefficient Jwd exceeds the threshold value, indicating that the stability fluctuation amplitude is large, generating a second early warning signal and sending the second early warning signal to the visual terminal so as to control the visual terminal to edit and display a second early warning text;
d3: receiving the efficiency prompt signal and the stable signal, and respectively carrying out corresponding processing:
d3-1: when receiving the efficiency prompt signal, immediately editing and displaying the corresponding efficiency prompt text;
d3-2: when the stability signal is received, the corresponding stability alarm text is immediately edited for display, and the corresponding indicator lamp is controlled to flash.
In summary, due to the adoption of the technical scheme, the beneficial effects of the invention are as follows:
1. in the network traffic data acquisition, big data analysis and visual presentation method, the information acquisition unit is used for acquiring the network traffic data, and the data analysis unit is used for analyzing and processing the network traffic data, so that the accuracy of network transmission and the efficiency of network operation are judged, the degree of network safety and stability are further judged, the evaluation coefficients of the network safety and stability are displayed in real time through the control display unit, an alarm mechanism can be set, an optimized model is established, and risk control and alarm prompt are carried out on the network safety and stability, so that corresponding fault processing is timely carried out;
2. the invention realizes the visual presentation of the network operation safety and stability by collecting the network flow data and utilizing the big data analysis means, firstly judges the network safety by the network transmission accuracy, and then judges the network stability by combining the network operation efficiency with the network safety, thereby realizing the timely control of risks, the repair treatment of faults and the early warning of the safety and stability fluctuation degree, further identifying and defending the network security threat and optimizing the performance of the network operation state.
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For a clearer description of embodiments of the present application or of the solutions in the prior art, the drawings that are needed in the embodiments will be briefly described, it being obvious that the drawings in the following description are only some embodiments described in the present invention, and that other drawings may be obtained according to these drawings by a person skilled in the art;
FIG. 1 is a schematic flow chart of the present invention;
fig. 2 is a schematic block diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples:
as shown in fig. 1-2, a network traffic data acquisition, big data analysis and visual presentation method comprises the following steps:
step one: the information acquisition unit acquires network flow data and sends the network flow data to the data analysis unit, wherein the network flow data comprises a safety parameter and a stability parameter;
the security parameters comprise load data A before a transmission process, load data B after the transmission process, an error access quantity Fc, a user access quantity Fy and a transmission packet loss rate Dc;
the stability parameters include a data packet transmission rate Vcs, a data packet length L, and a data packet timestamp T;
acquiring by a network data packet analysis tool to obtain index values in network flow analysis;
step two: the data analysis unit analyzes and processes the network flow data and judges the network security degree and the network stability degree, wherein the data analysis unit comprises a security analysis unit and a stability analysis unit;
firstly, acquiring a data error rate and an access error rate according to security parameters by a security analysis unit, acquiring transmission accuracy, judging the accuracy of network transmission, generating a security evaluation coefficient by combining the transmission accuracy with the access error rate, and judging the security degree of the network;
the processing procedure of the security analysis unit is as follows:
a1: firstly, establishing a picture comparison model, comparing load data A with load data B, and acquiring a data error rate Lsj in a data transmission process;
the picture comparison model is established by the following steps:
s1: acquiring picture information Ta of the load data A and picture information Tb of the load data B through scanning, and establishing a rectangular coordinate system of the picture information Ta and the picture information Tb by using the same base point;
s2: any position in the picture information Ta is defined as i0, and the same position of the picture information Tb is defined as i1;
s3: the color at i0 is detected as S0, the color at i1 is detected as S1, the number of detection points for sampling is set to Ni,
when s0=s1, the number of recording errors m=0; when s0+.s1, the number of recording errors m=1;
s4: obtaining a data error rate Lsj by measuring and calculating the duty ratio of the total number of errors in the sampled detection points:；
a2: and then the access error rate Lfw of the network operation process is obtained by calculating the duty ratio of the error access quantity Fc in the user access quantity Fy:；
a3: acquiring transmission accuracy Zcs through the data error rate Lsj and the transmission packet loss rate Dc;
the formula of the preset transmission accuracy Zcs is:；
a4: generating a security assessment coefficient Xaq by assigning a weight factor to the transmission accuracy Zcs in combination with the access error rate Lfw;
the formula of the preset security evaluation coefficient Xaq is:；
wherein, alpha 1 and alpha 2 are respectively the weight factor coefficients of the transmission accuracy Zcs combined with the access error rate Lfw, and both alpha 1 and alpha 2 are larger than 0;
a5: further analyzing the transmission accuracy Zcs and the security evaluation coefficient Xaq to judge the accuracy of network transmission and the network security degree;
the further analysis of the transmission accuracy Zcs and the security assessment factor Xaq is as follows:
a1: the transmission accuracy Zcs is preset with a grading interval of accuracy, and the accuracy of network transmission is judged;
the method comprises the steps of comparing an actual measurement value of transmission accuracy Zcs with a preset interval to generate a corresponding accuracy prompt signal and sending the corresponding accuracy prompt signal to a control display unit;
when the transmission accuracy Zcs is positioned in a standard interval of accuracy, indicating that the transmission accuracy is excellent, and generating a first accuracy prompt signal;
when the transmission accuracy Zcs is positioned in a risk interval of accuracy, the transmission accuracy is good, and a second accuracy prompt signal is generated;
when the transmission accuracy Zcs is positioned in an inaccurate interval of accuracy, representing that the transmission accuracy is poor, generating a third accuracy prompt signal;
a2: presetting a security grading interval for a security evaluation coefficient Xaq, and judging the network security degree;
presetting a safety interval, a risk interval and an unsafe interval of safety, comparing an actual measuring value of a safety evaluation coefficient Xaq with the preset interval, generating a corresponding safety signal and sending the corresponding safety signal to a control display unit;
when the security evaluation coefficient Xaq is located in a security interval of security, indicating that the network security degree is excellent, generating a first security signal;
when the security evaluation coefficient Xaq is located in a security risk interval, representing that the network security degree is good, generating a second security signal;
when the security evaluation coefficient Xaq is located in an unsafe interval of security, which indicates that the network security degree is poor, a third security signal is generated;
the safety of the network operation state is evaluated through the safety evaluation coefficient, so that the conditions of network faults and errors can be avoided, early warning is performed in advance, risk elimination is performed, and unsafe conditions of network operation are reduced;
secondly, the stability analysis unit firstly acquires the data acquisition rate according to the stability parameters, then acquires the network operation efficiency, combines the network operation efficiency with the safety evaluation coefficient to generate a stability evaluation coefficient, and judges the network stability degree;
the processing procedure of the stability analysis unit is as follows:
b1: firstly, acquiring a data packet acquisition time period Ti through a data packet time stamp T, and acquiring a data acquisition rate Vcj through measuring and calculating the data packet length L in a unit time period:；
b2: combining the data packet transmission rate Vcs with the data acquisition rate Vcj to obtain the network operation efficiency Wyx;
the formula of the preset network operation efficiency Wyx is as follows:；
b3: generating a stability evaluation coefficient Xwd by assigning a weight factor to the network operation efficiency Wyx and the security evaluation coefficient Xaq;
the formula of the preset stability evaluation coefficient Xwd is:；
wherein, beta 1 and beta 2 are respectively the weight factor coefficients of the network operation efficiency Wyx and the security evaluation coefficient Xaq, and beta 1 and beta 2 are both larger than 0;
b4: further analyzing the network operation efficiency Wyx and the stability evaluation coefficient Xwd to judge the network operation efficiency and the network stability degree;
further analysis of the network operating efficiency Wyx and stability assessment coefficients Xwd is as follows:
b1: judging the efficiency of network operation by presetting a grading interval of the efficiency of the network operation Wyx;
comparing an actual measured value of the network operation efficiency Wyx with a preset interval to generate a corresponding efficiency prompt signal and sending the corresponding efficiency prompt signal to a control display unit;
when the network operation efficiency Wyx is located in an efficient interval of efficiency, indicating that the network operation efficiency is excellent, generating a first efficiency prompt signal;
when the network operation efficiency Wyx is positioned in the risk interval of the efficiency, the network operation efficiency is good, and a second efficiency prompt signal is generated;
when the network operation efficiency Wyx is positioned in an efficiency low-efficiency interval, representing that the network operation efficiency is poor, generating a third efficiency prompt signal;
b2: presetting a stability grading interval for a stability evaluation coefficient Xwd, and judging the network stability degree;
the method comprises the steps of presetting a stable interval, a risk interval and an unstable interval of stability, comparing an actual measuring and calculating value of a stability evaluation coefficient Xwd with the preset interval, generating a corresponding stable signal and sending the corresponding stable signal to a control display unit;
when the stability evaluation coefficient Xwd is positioned in the stability interval of stability, the network stability degree is excellent, and a first stable signal is generated;
when the stability evaluation coefficient Xwd is positioned in the risk interval of stability, representing that the network stability degree is good, generating a second stable signal;
when the stability evaluation coefficient Xwd is positioned in the unstable interval of stability, which indicates that the network stability degree is poor, a third stable signal is generated;
the network safety and the operation efficiency are comprehensively analyzed through the stability evaluation coefficient, so that the stability of the network operation performance is evaluated, the network performance can be timely optimized, and the stability of the network operation is ensured;
step three: the control display unit sends the security evaluation coefficient and the stability evaluation coefficient to the visual terminal for real-time display, and respectively carries out corresponding processing according to the network security degree and the network stability degree:
setting an alarm mechanism according to the network security degree, and identifying and defending network security threats;
according to the stability degree of the network, an optimization model is established, and the performance of the running state of the network is optimized;
the curvature measuring and calculating model is established to predict the network safety and stability fluctuation curve, when the fluctuation amplitude of the safety or stability curve is large, the safety or stability development trend is expressed to be relatively dynamic, and early warning is needed to control the corresponding performance to be in a smooth state in advance, so that the network is smooth to use;
the curvature measuring and calculating model is established as follows:
cd1: calculating the fluctuation coefficient of the curve, calculating the curvature radius R of any point on the curve, and calculating the average value R of the curvature radius of all points on the curve;
cd2: for each point, the fluctuation coefficient b of that point is calculated: b=r/R;
cd3: presetting N points, and calculating standard deviation of fluctuation coefficients b of the N points, namely, fluctuation coefficients J of a curve:；
(1) the specific process of setting the alarm mechanism is as follows:
c1: establishing a dynamic graph of the safety evaluation coefficient Xaq and the time T, substituting the dynamic graph into a curvature measuring and calculating model to obtain a safety fluctuation coefficient Jaq, and predicting the fluctuation trend of safety;
c2: setting a threshold value of a safety fluctuation coefficient Jaq, when the safety fluctuation coefficient Jaq exceeds the threshold value, indicating that the safety fluctuation amplitude is large, generating a first early warning signal and sending the first early warning signal to a visual terminal so as to control the visual terminal to edit and display a first early warning text of 'network safety fluctuation early warning';
and C3: receiving an accuracy prompt signal and a safety signal, and respectively carrying out corresponding processing:
c3-1: when receiving the accuracy prompt signal, immediately editing and displaying a corresponding accuracy prompt text;
for example, when the first accuracy prompt signal is received, editing a text with good transmission accuracy, and prompting a worker to repair the transmission accuracy;
when a second accuracy prompt signal is received, editing a text with good transmission accuracy, and prompting a worker to repair the transmission accuracy so as to improve the transmission accuracy Zcs to a standard interval and avoid continuous deterioration of the transmission accuracy;
when a third accuracy prompt signal is received, editing a text with poor transmission accuracy, and prompting a worker to perform fault processing on the transmission accuracy so as to improve the transmission accuracy Zcs to be in a standard interval;
c3-2: when a safety signal is received, immediately editing and displaying a corresponding safety alarm text, and controlling a corresponding indicator lamp to flash;
for example, when a first security signal is received, editing a text of "network security degree is good", and controlling a green indicator lamp 1 to flash, so that a worker is prompted to do not need to carry out security maintenance;
when a second safety signal is received, editing a text of 'good network safety degree', controlling a yellow indicator lamp No. 1 to flash, and prompting a worker to need safety risk maintenance so as to improve a safety evaluation coefficient Xaq to a safety interval, and avoiding continuous improvement of risks to unsafe conditions;
when a third safety signal is received, editing a text of poor network safety degree, controlling a No. 1 red indicator lamp to flash, and prompting a worker to immediately perform safety maintenance so as to improve a safety evaluation coefficient Xaq to a safety interval;
(2) the specific process for establishing the optimization model is as follows:
d1: establishing a dynamic curve graph of the stability evaluation coefficient Xwd and the time T, substituting the dynamic curve graph into a curvature measuring and calculating model to obtain a stability fluctuation coefficient Jwd, and predicting the fluctuation trend of stability;
d2: setting a threshold value of a stability fluctuation coefficient Jwd, when the stability fluctuation coefficient Jwd exceeds the threshold value, indicating that the stability fluctuation amplitude is large, generating a second early warning signal and sending the second early warning signal to the visual terminal so as to control the visual terminal to edit and display a second early warning text of 'network stability fluctuation early warning';
d3: receiving the efficiency prompt signal and the stable signal, and respectively carrying out corresponding processing:
d3-1: when receiving the efficiency prompt signal, immediately editing and displaying the corresponding efficiency prompt text;
for example, when the first efficiency prompt signal is received, editing a text of "network operation efficiency is good", and prompting a worker to repair the network operation efficiency;
when the second efficiency prompt signal is received, editing a text of 'good network operation efficiency', and prompting a worker to repair the network operation efficiency so as to improve the network operation efficiency Wyx to a high-efficiency interval and avoid continuous deterioration of the network operation efficiency;
when a third efficiency prompt signal is received, editing a text of 'poor efficiency of network operation', and prompting a worker to perform fault processing on the efficiency of network operation so as to improve the efficiency Wyx of network operation to a high-efficiency interval and avoid the poor efficiency of network operation;
d3-2: when a stable signal is received, immediately editing a corresponding stability alarm text for display, and controlling a corresponding indicator lamp to flash;
for example, when a first stable signal is received, a text of "network stability is good" is edited, and a green indicator lamp No. 2 is controlled to flash, so that staff is prompted to avoid network performance optimization;
when a second stable signal is received, editing a text with good network stability, controlling a No. 2 yellow indicator lamp to flash, and prompting a worker to repair the network stability so as to improve a stability evaluation coefficient Xwd to a stable interval and avoid the aggravation of network stability;
when a second stable signal is received, editing a text with poor network stability and controlling a No. 2 red indicator lamp to flash, prompting a worker to optimize network performance so as to improve a stability evaluation coefficient Xwd to a stable interval, and avoiding inconvenience caused by network stability deterioration;
by analyzing and processing the collected network traffic data, network attacks can be identified and defended, and trend analysis is performed on network traffic distribution, so that network performance optimization is realized.
According to the network traffic data acquisition, big data analysis and visual presentation method, the information acquisition unit is used for acquiring the network traffic data, and the data analysis unit is used for analyzing and processing the network traffic data, so that the accuracy of network transmission and the efficiency of network operation are judged, the degree of network safety and stability are further judged, the evaluation coefficients of the network safety and stability are displayed in real time through the control display unit, an alarm mechanism can be set, an optimization model is built, and risk control and alarm prompt are carried out on the network safety and stability, so that corresponding fault processing is timely carried out;
according to the invention, network traffic data are collected, the visual presentation is carried out on the network operation safety and stability in real time by utilizing a big data analysis means, the network safety is judged through the network transmission accuracy, the network stability is judged by utilizing the network safety in combination with the network operation efficiency, the data utilization rate is high, the timely control of risks and the repair treatment of faults are realized, so that the network safety threat is identified and defended, and the performance of the network operation state is optimized.
The formulas are all formulas with dimensions removed and numerical calculation, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by a person skilled in the art according to the actual situation; the size of the threshold is set for ease of comparison, and regarding the size of the threshold, the number of cardinalities is set for each set of sample data depending on how many sample data are and the person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.

Claims (7)

1. A network traffic data acquisition, big data analysis and visual presentation method is characterized in that: the method comprises the following steps:
step one: the information acquisition unit acquires network flow data and sends the network flow data to the data analysis unit, wherein the network flow data comprises a safety parameter and a stability parameter;
step two: the data analysis unit analyzes and processes the network flow data and judges the network security degree and the network stability degree, wherein the data analysis unit comprises a security analysis unit and a stability analysis unit;
the security analysis unit firstly acquires the data error rate and the access error rate according to the security parameters, then acquires the transmission accuracy, judges the accuracy of network transmission, and then generates a security evaluation coefficient by combining the transmission accuracy with the access error rate to judge the network security degree;
the stability analysis unit firstly acquires the data acquisition rate according to the stability parameters, then acquires the network operation efficiency, combines the network operation efficiency with the safety evaluation coefficient to generate a stability evaluation coefficient, and judges the network stability degree;
step three: the control display unit displays the safety evaluation coefficient and the stability evaluation coefficient in real time, and respectively processes according to the network safety degree and the network stability degree:
setting an alarm mechanism according to the network security degree, and identifying and defending network security threats;
and according to the network stability degree, an optimization model is established, and the performance of the network running state is optimized.
2. The method for collecting, analyzing and visually presenting network traffic data according to claim 1, wherein the method comprises the steps of: the processing procedure of the security analysis unit is as follows:
the security parameters comprise load data A before a transmission process, load data B after the transmission process, error access quantity Fc, user access quantity Fy and transmission packet loss rate Dc;
a1: firstly, establishing a picture comparison model, comparing load data A with load data B, and acquiring a data error rate Lsj in a data transmission process;
the picture comparison model is established by the following steps:
s1: acquiring picture information Ta of the load data A and picture information Tb of the load data B through scanning, and establishing a rectangular coordinate system of the picture information Ta and the picture information Tb by using the same base point;
s2: any position in the picture information Ta is defined as i0, and the same position of the picture information Tb is defined as i1;
s3: the color at i0 is detected as S0, the color at i1 is detected as S1, the number of detection points for sampling is set to Ni,
when s0=s1, the number of recording errors m=0; when s0+.s1, the number of recording errors m=1;
s4: obtaining a data error rate Lsj by measuring and calculating the duty ratio of the total number of errors in the sampled detection points:
a2: then, the access error rate Lfw of the network operation process is obtained by calculating the duty ratio of the error access quantity Fc in the user access quantity Fy;
a3: acquiring transmission accuracy Zcs through the data error rate Lsj and the transmission packet loss rate Dc;
the formula of the preset transmission accuracy Zcs is:；
a4: generating a security assessment coefficient Xaq by assigning a weight factor to the transmission accuracy Zcs in combination with the access error rate Lfw;
the formula of the preset security evaluation coefficient Xaq is:；
wherein, alpha 1 and alpha 2 are respectively the weight factor coefficients of the transmission accuracy Zcs combined with the access error rate Lfw, and both alpha 1 and alpha 2 are larger than 0;
a5: the transmission accuracy Zcs and the security evaluation coefficient Xaq are further analyzed to determine the accuracy of network transmission and the degree of network security.
3. The method for collecting, analyzing and visually presenting network traffic data according to claim 2, wherein the method comprises the steps of: the further analysis of the transmission accuracy Zcs and the security assessment factor Xaq is as follows:
a1: the transmission accuracy Zcs is preset with a grading interval of accuracy, and the accuracy of network transmission is judged;
the method comprises the steps of comparing an actual measurement value of transmission accuracy Zcs with a preset interval to generate a corresponding accuracy prompt signal and sending the corresponding accuracy prompt signal to a control display unit;
a2: presetting a security grading interval for a security evaluation coefficient Xaq, and judging the network security degree;
the safety interval, the risk interval and the unsafe interval of the safety are preset, the actual measuring and calculating value of the safety evaluation coefficient Xaq is compared with the preset interval, and corresponding safety signals are generated and sent to the control display unit.
4. The method for collecting, analyzing and visually presenting network traffic data according to claim 2, wherein the method comprises the steps of: the processing procedure of the stability analysis unit is as follows:
the stability parameters include a data packet transmission rate Vcs, a data packet length L, and a data packet timestamp T;
b1: firstly, acquiring a data packet acquisition time period Ti through a data packet time stamp T, and acquiring a data acquisition rate Vcj through measuring and calculating the data packet length L in a unit time period;
b2: combining the data packet transmission rate Vcs with the data acquisition rate Vcj to obtain the network operation efficiency Wyx;
the formula of the preset network operation efficiency Wyx is as follows:；
b3: generating a stability evaluation coefficient Xwd by assigning a weight factor to the network operation efficiency Wyx and the security evaluation coefficient Xaq;
the formula of the preset stability evaluation coefficient Xwd is:；
wherein, beta 1 and beta 2 are respectively the weight factor coefficients of the network operation efficiency Wyx and the security evaluation coefficient Xaq, and beta 1 and beta 2 are both larger than 0;
b4: further analysis of the network operating efficiency Wyx and stability assessment coefficient Xwd determines the efficiency of network operation and the degree of network stability.
5. The method for collecting, analyzing and visually presenting network traffic data according to claim 4, wherein the method comprises the steps of: further analysis of the network operating efficiency Wyx and stability assessment coefficients Xwd is as follows:
b1: judging the efficiency of network operation by presetting a grading interval of the efficiency of the network operation Wyx;
comparing an actual measured value of the network operation efficiency Wyx with a preset interval to generate a corresponding efficiency prompt signal and sending the corresponding efficiency prompt signal to a control display unit;
b2: presetting a stability grading interval for a stability evaluation coefficient Xwd, and judging the network stability degree;
the stability interval, the risk interval and the instability interval of the stability are preset, the actual measuring and calculating value of the stability evaluation coefficient Xwd is compared with the preset interval, and corresponding stability signals are generated and sent to the control display unit.
6. The method for collecting, analyzing and visually presenting network traffic data according to claim 1, wherein the method comprises the steps of: the specific process of setting the alarm mechanism is as follows:
c1: establishing a dynamic graph of the safety evaluation coefficient Xaq and the time T, substituting the dynamic graph into a curvature measuring and calculating model to obtain a safety fluctuation coefficient Jaq, and predicting the fluctuation trend of safety;
c2: setting a threshold value of a safety fluctuation coefficient Jaq, and when the safety fluctuation coefficient Jaq exceeds the threshold value, indicating that the safety fluctuation amplitude is large, generating a first early warning signal and sending the first early warning signal to a visual terminal so as to control the visual terminal to edit and display a first early warning text;
and C3: receiving an accuracy prompt signal and a safety signal, and respectively carrying out corresponding processing:
c3-1: when receiving the accuracy prompt signal, immediately editing and displaying a corresponding accuracy prompt text;
c3-2: when the safety signal is received, the corresponding safety alarm text is immediately edited for display, and the corresponding indicator lamp is controlled to flash.
7. The method for collecting, analyzing and visually presenting network traffic data according to claim 1, wherein the method comprises the steps of: the specific process for establishing the optimization model is as follows:
d1: establishing a dynamic curve graph of the stability evaluation coefficient Xwd and the time T, substituting the dynamic curve graph into a curvature measuring and calculating model to obtain a stability fluctuation coefficient Jwd, and predicting the fluctuation trend of stability;
d2: setting a threshold value of a stability fluctuation coefficient Jwd, when the stability fluctuation coefficient Jwd exceeds the threshold value, indicating that the stability fluctuation amplitude is large, generating a second early warning signal and sending the second early warning signal to the visual terminal so as to control the visual terminal to edit and display a second early warning text;
d3: receiving the efficiency prompt signal and the stable signal, and respectively carrying out corresponding processing:
d3-1: when receiving the efficiency prompt signal, immediately editing and displaying the corresponding efficiency prompt text;
d3-2: when the stability signal is received, the corresponding stability alarm text is immediately edited for display, and the corresponding indicator lamp is controlled to flash.
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