Network traffic information management platform based on Internet of Things

Abstract

The invention discloses a network flow information management platform based on the Internet of Things, and belongs to the technical field of network information management. The method and device are used for solving the technical problems that in an existing scheme, when network flow information supervision analysis is abnormal, abnormal influence evaluation in different aspects cannot be carried out, and network flow management and control cannot be adaptively and dynamically implemented according to an evaluation result. Data analysis is carried out on the overall bandwidth usage rate and the local bandwidth usage rate which are obtained through monitoring, tracing analysis and marking are carried out on a single exception type corresponding to an overall instantaneous bandwidth usage state exception or a local instantaneous bandwidth usage state exception, and an overall bandwidth usage control necessary state corresponding to a platform server is processed and analyzed. And dynamically implementing an overall bandwidth use control scheme and a local bandwidth use control scheme generated by the platform server by different hot spot information items according to a local bandwidth use control necessary state generated by the platform server by different hot spot information items.

Description

Technical Field

[0001] The present invention relates to the technical field of network information management, and particularly to a network traffic information management platform based on the Internet of Things. Background Art

[0002] A network traffic information management platform is a system specifically used for monitoring, analyzing, and optimizing network traffic. It provides enterprises or organizations with a comprehensive perspective to understand their network usage, helps identify potential problems, and takes measures to improve network performance and security.

[0003] After retrieval, a Chinese invention with the application number 2022108682041 and the name of "A Network Traffic Control Method Based on an Information Management Platform" discloses the problem that the existing server controls data traffic according to a fixed traffic threshold and cannot make the most of network resources. It includes: monitoring the overall bandwidth utilization rate of the platform server and the local bandwidth utilization rate caused by monitoring hot information items on the platform server; if the overall bandwidth utilization rate exceeds the overall bandwidth threshold and the local bandwidth utilization rate does not exceed the local bandwidth threshold, then start the overall traffic control method; if the overall bandwidth utilization rate does not exceed the overall bandwidth threshold and the local bandwidth utilization rate exceeds the local bandwidth threshold, then start the local traffic control method; if the overall bandwidth utilization rate exceeds the overall bandwidth threshold and at the same time the local bandwidth utilization rate exceeds the local bandwidth threshold, then start both the overall traffic control method and the local traffic control method. This invention is used for network traffic control.

[0004] However, the existing network traffic information management platforms still have certain defects in implementation. For network traffic control, they only stay on the supervision, evaluation, and control of overall traffic usage and local traffic usage, without conducting multi-dimensional supervision and analysis on the impacts of different abnormal traffic usages, and evaluating whether to adjust the overall traffic usage and local traffic usage according to the analysis results to avoid poor usage effects corresponding to the overall traffic usage and local traffic usage after adjustment. There is a situation where when there are abnormalities in network traffic information supervision and analysis, abnormal impact evaluations in different aspects cannot be carried out, and network traffic control cannot be dynamically implemented adaptively according to the evaluation results. Summary of the Invention

[0005] The purpose of the present invention is to provide a network traffic information management platform based on the Internet of Things, which is used to solve the technical problem that when there are abnormalities in network traffic information supervision and analysis in the existing solutions, abnormal impact evaluations in different aspects cannot be carried out, and network traffic control cannot be dynamically implemented adaptively according to the evaluation results.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A network traffic information management platform based on the Internet of Things includes:

[0008] A network traffic supervision and processing analysis module is used to monitor the overall bandwidth utilization rate of the platform server and the local bandwidth utilization rate caused by monitoring hot information items on the platform server, perform data analysis on the overall bandwidth utilization rate and local bandwidth utilization rate obtained by monitoring, determine the corresponding overall instantaneous bandwidth usage status and local instantaneous bandwidth usage status, and conduct traceability analysis and marking on the single anomaly types corresponding to the abnormal overall instantaneous bandwidth usage status or abnormal local instantaneous bandwidth usage status;

[0009] A network traffic supervision integration management module is used to respectively perform integration processing and analysis of the single anomaly impacts on the overall bandwidth usage supervision data of the platform server and the local bandwidth usage supervision data caused by monitoring hot information items on the platform server, and determine the necessary overall bandwidth usage control status corresponding to the platform server and the necessary local bandwidth usage control status caused by different hot information items on the platform server according to the analysis results, so as to dynamically implement the overall bandwidth usage control scheme and the local bandwidth usage control scheme caused by different hot information items on the platform server.

[0010] Preferably, the overall bandwidth utilization rate of the monitoring platform server and the local bandwidth utilization rate caused by monitoring hot information items on the platform server are subjected to data analysis through a bandwidth usage identification model, and the corresponding bandwidth usage status value KSk is output; k is 1, 2; respectively representing the overall bandwidth usage of the platform server and the local bandwidth usage caused by hot information items on the platform server;

[0011] Among them, the expression of the bandwidth usage identification model is In the formula, LSk is LS1, LS2, which are respectively the overall bandwidth utilization rate of the platform server and the local bandwidth utilization rate caused by hot information items on the platform server; LS0k is LS01, LS02, which are respectively the overall bandwidth standard utilization rate of the platform server and the local bandwidth standard utilization rate caused by hot information items on the platform server.

[0012] Preferably, according to the bandwidth usage status value with a value of 1, the corresponding overall instantaneous broadband usage traceability instruction or local instantaneous broadband usage traceability instruction is generated, and according to the overall instantaneous broadband usage traceability instruction, the first anomaly duration and the first anomaly broadband usage total corresponding to the abnormal overall instantaneous broadband usage status are monitored and statistically analyzed, and according to the local instantaneous broadband usage traceability instruction, the second anomaly duration and the second anomaly broadband usage total corresponding to the abnormal local instantaneous broadband usage status are monitored and statistically analyzed, through the formula Calculate to obtain the corresponding first broadband anomaly status value YZ1k; in the formula, YZ1k is YZ11 and YZ12, which are respectively the first broadband anomaly status value corresponding to the overall instantaneous broadband usage status anomaly and the first broadband anomaly status value corresponding to the local instantaneous broadband usage status anomaly; TYk is TY1 and TY2, which are respectively the first anomaly duration and the second anomaly duration; TY0k is TY01 and TY02, which are respectively the first anomaly standard duration and the second anomaly standard duration.

[0013] Preferably, through the formula Calculate to obtain the corresponding second broadband anomaly status value YZ2k; in the formula, YZ2k is YZ21 and YZ22, which are respectively the second broadband anomaly status value corresponding to the overall instantaneous broadband usage status anomaly and the second broadband anomaly status value corresponding to the local instantaneous broadband usage status anomaly; LYk is LY1 and LY2, which are respectively the first anomaly broadband usage total and the second anomaly broadband usage total; LY0k is LY01 and LY02, which are respectively the first anomaly standard broadband usage total and the second anomaly standard broadband usage total.

[0014] Preferably, perform data analysis on the calculated first broadband anomaly status value and the second broadband anomaly status value to determine the single anomaly type corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly to which they belong;

[0015] If YZ1k > 0 and YZ2k > 0 do not exist simultaneously, then prompt that the single anomaly type corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly to which they belong is a mild anomaly type;

[0016] If YZ1k > 0 and YZ2k > 0 exist simultaneously, then prompt that the single anomaly type corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly to which they belong is a severe anomaly type.

[0017] Preferably, sort and combine the several first anomaly durations and the first anomaly broadband usage totals obtained by processing and analyzing the overall bandwidth usage rate of the monitoring platform server respectively, and sort and combine the several second anomaly durations and the second anomaly broadband usage totals obtained by processing and analyzing the local bandwidth usage rate caused by the hotspot information item of the platform server respectively, to obtain the corresponding anomaly duration sorting sequence and anomaly broadband usage total sorting sequence, and mark the elements with the largest values in the anomaly duration sorting sequence and the anomaly broadband usage total sorting sequence as the first anomaly selected value and the second anomaly selected value respectively.

[0018] Preferably, obtain the median values of all elements in the anomaly duration sorting sequence and the anomaly broadband usage total sorting sequence respectively and mark them as the third anomaly selected value and the fourth anomaly selected value.

[0019] Preferably, the different abnormal selection values obtained by corresponding processing of different bandwidth usage rates are subjected to data analysis through a traffic usage recognition model, and corresponding control necessary identifiers are output;

[0020] The control necessary identifier includes a numerical value of 0, 1, or 2;

[0021] According to the control necessary identifier with a numerical value of 0, maintain the existing overall traffic control scheme and the corresponding hotspot information items to enable the local traffic control scheme occurring in the platform server.

[0022] Preferably, according to the control necessary identifier with a numerical value of 1, implement the overall traffic local optimization control scheme and the corresponding hotspot information items to enable the local traffic local optimization control scheme occurring in the platform server;

[0023] According to the control necessary identifier with a numerical value of 2, label the target-related traffic usage with a severe anomaly, and implement the overall traffic overall optimization control scheme and the corresponding hotspot information items to enable the local traffic overall optimization control scheme occurring in the platform server.

[0024] Preferably, the expression of the traffic usage recognition model is In the formula, YX1k, YX2k, YX3k, and YX4k are respectively the first abnormal selection value, the second abnormal selection value, the third abnormal selection value, and the fourth abnormal selection value obtained by corresponding processing of different bandwidth usage rates; ak, bk, ck, and dk are respectively the first abnormal standard value, the second abnormal standard value, the third abnormal standard value, and the fourth abnormal standard value corresponding to different bandwidth usage rates.

[0025] Compared with the existing solution, the beneficial effects achieved by the present invention are:

[0026] The present invention analyzes the overall bandwidth usage rate and local bandwidth usage rate obtained by monitoring, determines the corresponding overall instantaneous bandwidth usage status and local instantaneous bandwidth usage status, and conducts retrospective analysis and marking on the single abnormal type corresponding to the abnormal overall instantaneous bandwidth usage status or local instantaneous bandwidth usage status, realizing digital processing and screening classification of the abnormal overall instantaneous bandwidth usage status or local instantaneous bandwidth usage status, and can also provide reliable local abnormal processing analysis data support for the dynamic implementation analysis of subsequent different bandwidth usage control schemes.

[0027] The present invention processes and analyzes the overall bandwidth usage control necessary state corresponding to the platform server, as well as the local bandwidth usage control necessary state caused by different hotspot information items on the platform server, and dynamically implements the overall bandwidth usage control scheme and the local bandwidth usage control scheme caused by different hotspot information items on the platform server, realizing the autonomous evaluation of abnormal impacts in different aspects when the network traffic information supervision and analysis is abnormal, and adaptively and dynamically implementing network traffic control according to the evaluation results, improving the diversity and reliability of network traffic anomaly information management. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described below in conjunction with the accompanying drawings.

[0029] Figure 1 It is a step block diagram of the operation of the network traffic information management platform based on the Internet of Things of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0031] As Figure 1 shown, the present invention is a network traffic information management platform based on the Internet of Things, including a network traffic supervision and processing analysis module and a network traffic supervision and integration management module;

[0032] The network traffic supervision and processing analysis module is used to monitor the overall bandwidth utilization rate of the platform server and the local bandwidth utilization rate caused by monitoring hotspot information items on the platform server, perform data analysis on the overall bandwidth utilization rate and the local bandwidth utilization rate obtained by monitoring, determine the corresponding overall instantaneous bandwidth usage state and local instantaneous bandwidth usage state, and perform trace analysis and marking on the single anomaly type corresponding to the abnormal overall instantaneous bandwidth usage state or the abnormal local instantaneous bandwidth usage state; including:

[0033] Perform data analysis on the overall bandwidth utilization rate of the monitored platform server and the local bandwidth utilization rate caused by monitoring hotspot information items on the platform server through a bandwidth usage identification model, and output the corresponding bandwidth usage state value KSk; k is 1, 2; respectively representing the overall bandwidth usage of the platform server and the local bandwidth usage caused by hotspot information items on the platform server;

[0034] Among them, the expression of the bandwidth usage identification model is In the formula, LSk is LS1 and LS2, which are respectively the overall bandwidth utilization rate of the platform server and the local bandwidth utilization rate caused by the hot-spot information item on the platform server; LS0k is LS01 and LS02, which are respectively the overall standard bandwidth utilization rate of the platform server and the local standard bandwidth utilization rate caused by the hot-spot information item on the platform server, and can be determined according to the existing bandwidth usage design requirement data;

[0035] The bandwidth usage status value includes a numerical value of 0 or 1;

[0036] A bandwidth usage status value of 0 indicates that the overall instantaneous bandwidth usage status of the belonging part is normal or the local instantaneous bandwidth usage status is normal;

[0037] A bandwidth usage status value of 1 indicates that the overall instantaneous bandwidth usage status of the belonging part is abnormal or the local instantaneous bandwidth usage status is abnormal;

[0038] In the embodiment of the present invention, by supervising, processing and analyzing the overall bandwidth utilization rate of the platform server and the local bandwidth utilization rate caused by monitoring the hot-spot information item on the platform server, the corresponding overall instantaneous bandwidth usage status and local instantaneous bandwidth usage status can be obtained, and reliable abnormal supervision data support can be provided for the subsequent traceability evaluation of the overall instantaneous bandwidth usage status abnormality and / or local instantaneous bandwidth usage status abnormality.

[0039] Generate a corresponding overall instantaneous broadband usage traceback instruction or local instantaneous broadband usage traceback instruction according to the bandwidth usage status value of 1, and monitor and count the first abnormal duration and the first total abnormal broadband usage corresponding to the overall instantaneous broadband usage status abnormality according to the overall instantaneous broadband usage traceback instruction, and monitor and count the second abnormal duration and the second total abnormal broadband usage corresponding to the local instantaneous broadband usage status abnormality according to the local instantaneous broadband usage traceback instruction. The first total abnormal broadband usage and the second total abnormal broadband usage are obtained by calculating the differences between the overall bandwidth utilization rate and the overall standard bandwidth utilization rate, and between the local bandwidth utilization rate and the local standard bandwidth utilization rate respectively and then summing them up. Through the formula Calculate and obtain the corresponding first broadband abnormal status value YZ1k; in the formula, YZ1k is YZ11 and YZ12, which are respectively the first broadband abnormal status value corresponding to the overall instantaneous broadband usage status abnormality and the first broadband abnormal status value corresponding to the local instantaneous broadband usage status abnormality; TYk is TY1 and TY2, which are respectively the first abnormal duration and the second abnormal duration; TY0k is TY01 and TY02, which are respectively the first abnormal standard duration and the second abnormal standard duration, and can all be determined according to the existing bandwidth usage design requirement data, or determined according to the previous trial operation test data;

[0040] And, through the formula calculate the corresponding second broadband anomaly status value YZ2k; in the formula, YZ2k is YZ21, YZ22, which are respectively the second broadband anomaly status value corresponding to the overall instantaneous broadband usage status anomaly and the second broadband anomaly status value corresponding to the local instantaneous broadband usage status anomaly; LYk is LY1, LY2, which are respectively the first anomalous broadband usage total amount and the second anomalous broadband usage total amount; LY0k is LY01, LY02, which are respectively the first anomalous standard broadband usage total amount and the second anomalous standard broadband usage total amount, and all can be determined according to the existing bandwidth usage design requirement data or according to the previous trial operation test data;

[0041] It should be noted that the first broadband anomaly status value and the second broadband anomaly status value are used to calculate the anomaly data corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly from different aspects, so as to digitally represent the corresponding single anomaly type;

[0042] Perform data analysis on the calculated first broadband anomaly status value and second broadband anomaly status value to determine the single anomaly type corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly to which it belongs;

[0043] If YZ1k>0 and YZ2k>0 do not exist simultaneously, it is prompted that the single anomaly type corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly to which it belongs is a mild anomaly type;

[0044] If YZ1k>0 and YZ2k>0 exist simultaneously, it is prompted that the single anomaly type corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly to which it belongs is a severe anomaly type;

[0045] In the embodiment of the present invention, by performing data analysis on the monitored overall bandwidth usage rate and local bandwidth usage rate, the corresponding overall instantaneous bandwidth usage status and local instantaneous bandwidth usage status are determined, and the single anomaly type corresponding to the overall instantaneous bandwidth usage status anomaly or the local instantaneous bandwidth usage status anomaly is traced and analyzed and marked, realizing the digital processing and screening classification of the abnormal overall instantaneous bandwidth usage status anomaly or local instantaneous bandwidth usage status anomaly, and can also provide reliable local anomaly processing analysis data support for the dynamic implementation analysis of subsequent different bandwidth usage control schemes.

[0046] The network traffic supervision integration management module is used to separately perform integrated processing and analysis of single abnormal impacts on the overall bandwidth usage supervision data of the platform server and the local bandwidth usage supervision data caused by monitoring hot-spot information items on the platform server, and determine the necessary state of overall bandwidth usage control corresponding to the platform server and the necessary state of local bandwidth usage control caused by different hot-spot information items on the platform server according to the analysis results, so as to dynamically implement the overall bandwidth usage control scheme and the local bandwidth usage control scheme caused by different hot-spot information items on the platform server; including:

[0047] Sort and combine several first abnormal duration times and the total amount of first abnormal broadband usage obtained by processing and analyzing the overall bandwidth usage rate of the monitored platform server, and sort and combine several second abnormal duration times and the total amount of second abnormal broadband usage obtained by processing and analyzing the local bandwidth usage rate caused by the hot-spot information item on the platform server, to obtain corresponding abnormal duration time sorting sequences and abnormal broadband usage total amount sorting sequences, and mark the elements with the largest values in the abnormal duration time sorting sequence and the abnormal broadband usage total amount sorting sequence as the first abnormal selected value and the second abnormal selected value respectively;

[0048] And, obtain the median values of all elements in the abnormal duration time sorting sequence and the abnormal broadband usage total amount sorting sequence respectively and mark them as the third abnormal selected value and the fourth abnormal selected value;

[0049] Different from the prior art solution which only implements the corresponding traffic control scheme when staying at the analysis of a single monitoring item for abnormality and does not perform diversified supervision and processing analysis on the impacts corresponding to the existing traffic analysis abnormalities, there are deficiencies in the necessity and reliability of the implementation of the traffic control scheme regulation. In the embodiments of the present invention, by obtaining the corresponding monitoring item data from different aspects and performing integrated processing and analysis, the diversity and reliability of the analysis of corresponding traffic usage abnormalities can be effectively improved.

[0050] Perform data analysis on different abnormal selected values obtained by corresponding processing of different bandwidth usage rates through a traffic usage recognition model, and output the corresponding control necessary identifier CBk;

[0051] Among them, the expression of the traffic usage recognition model is In the formula, YX1k, YX2k, YX3k, and YX4k are respectively the first abnormal selected value, the second abnormal selected value, the third abnormal selected value, and the fourth abnormal selected value obtained by corresponding processing of different bandwidth usage rates; ak, bk, ck, and dk are respectively the first abnormal standard value, the second abnormal standard value, the third abnormal standard value, and the fourth abnormal standard value corresponding to different bandwidth usage rates, which can all be determined according to the existing bandwidth usage design requirement data or according to the previous trial operation test data;

[0052] The control necessary identifier includes a numerical value of 0, 1, or 2;

[0053] According to the control necessary identifier with a numerical value of 0, use the normal label for the associated traffic of the target, and maintain the existing overall traffic control scheme and the corresponding hotspot information items to make the local traffic control scheme occurring in the platform server;

[0054] According to the control necessary identifier with a numerical value of 1, use the mild anomaly label for the associated traffic of the target, and implement the overall traffic local optimization control scheme and the corresponding hotspot information items to make the local traffic local optimization control scheme occurring in the platform server;

[0055] According to the control necessary identifier with a numerical value of 2, use the severe anomaly label for the associated traffic of the target, and implement the overall traffic overall optimization control scheme and the corresponding hotspot information items to make the local traffic overall optimization control scheme occurring in the platform server;

[0056] Among them, the overall traffic local optimization control scheme and the local traffic local optimization control scheme can specifically be to adjust the corresponding broadband threshold according to the first adjustment ratio on the basis of the corresponding existing overall traffic control scheme and local traffic control scheme;

[0057] The overall traffic overall optimization control scheme and the local traffic overall optimization control scheme can specifically be to adjust the corresponding broadband threshold according to the second adjustment ratio on the basis of the corresponding existing overall traffic control scheme and local traffic control scheme; both the first adjustment ratio and the second adjustment ratio are real numbers greater than 1, and the first adjustment ratio is less than the second adjustment ratio; and the specific values of the first adjustment ratio and the second adjustment ratio are not selected as fixed values, and can be dynamically adjusted according to the actual situation, or can be determined according to the preliminary trial operation test data to meet the real-time requirements of different network congestion states.

[0058] In the embodiments of the present invention, by processing and analyzing the overall bandwidth usage control necessary state corresponding to the platform server, and the local bandwidth usage control necessary state occurring in the platform server due to different hotspot information items, and dynamically implementing the overall bandwidth usage control scheme and the local bandwidth usage control scheme occurring in the platform server due to different hotspot information items, it realizes the autonomous evaluation of abnormal impacts in different aspects when the network traffic information supervision and analysis are abnormal, and adaptively and dynamically implements network traffic control according to the evaluation results, improving the diversity and reliability of network traffic abnormal information management.

[0059] In addition, the formulas involved above are all calculated by removing the dimension and taking their numerical values, and are obtained by a software through simulating a large amount of data to get a formula closest to the real situation.

[0060] In several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described invention embodiments are merely illustrative. For example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0061] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical modules. They can be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0062] In addition, in each embodiment of the present invention, the functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of a combination of hardware and software functional modules.

[0063] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and without departing from the basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. The network traffic information management platform based on the Internet of Things is characterized by: include: The network traffic monitoring processing and analysis module is used to monitor the overall bandwidth usage rate of the platform server and the local bandwidth usage rate of the platform server caused by the hot information project, and to perform data analysis on the overall bandwidth usage rate and local bandwidth usage rate obtained through monitoring, determine the corresponding overall instantaneous bandwidth usage status and local instantaneous bandwidth usage status, and to perform retrospective analysis and marking of the single abnormal type corresponding to the abnormal overall instantaneous bandwidth usage status or the abnormal local instantaneous bandwidth usage status; The network traffic supervision integration management module is used to integrate and analyze the impact of single abnormalities on the overall bandwidth usage supervision data of the platform server and the local bandwidth usage supervision data caused by monitoring hotspot information items on the platform server, and determine the necessary status of the overall bandwidth usage control corresponding to the platform server and the necessary status of the local bandwidth usage control caused by different hotspot information items on the platform server based on the analysis results, so as to dynamically implement the overall bandwidth usage control plan and the local bandwidth usage control plan caused by different hotspot information items on the platform server.

2. The network traffic information management platform based on the Internet of Things according to claim 1 is characterized in that: The overall bandwidth usage rate of the monitoring platform server and the local bandwidth usage rate of the monitoring hotspot information project on the platform server are analyzed through the bandwidth usage identification model, and the corresponding bandwidth usage status value KSk is output; k is 1 and 2; representing the overall bandwidth usage of the platform server and the local bandwidth usage of the platform server caused by the hotspot information project, respectively; Among them, the expression of bandwidth usage identification model is: Wherein, LSk is LS1 and LS2, which are respectively the overall bandwidth utilization rate of the platform server and the local bandwidth utilization rate caused by the hot information project on the platform server; LS0k is LS01 and LS02, which are respectively the overall standard bandwidth utilization rate of the platform server and the local standard bandwidth utilization rate caused by the hot information project on the platform server.

3. The network traffic information management platform based on the Internet of Things according to claim 2 is characterized in that: According to the bandwidth usage status value of 1, the corresponding overall instantaneous broadband usage tracing instruction or local instantaneous broadband usage tracing instruction is generated, and the first abnormal duration and the total amount of first abnormal broadband usage corresponding to the abnormal overall instantaneous broadband usage status are monitored and counted according to the overall instantaneous broadband usage tracing instruction, and the second abnormal duration and the total amount of second abnormal broadband usage corresponding to the abnormal local instantaneous broadband usage status are monitored and counted according to the local instantaneous broadband usage tracing instruction, and the formula is used to calculate the duration of the second abnormality and the total amount of second abnormal broadband usage corresponding to the abnormal local instantaneous broadband usage status. Calculate and obtain the corresponding first broadband abnormal state value YZ1k; where YZ1k is YZ11 and YZ12, which are the first broadband abnormal state value corresponding to the overall instantaneous broadband usage state abnormality and the first broadband abnormal state value corresponding to the local instantaneous broadband usage state abnormality, respectively; TYk is TY1 and TY2, which are the first abnormality duration and the second abnormality duration, respectively; TY0k is TY01 and TY02, which are the duration of the first abnormal standard and the duration of the second abnormal standard respectively.

4. The network traffic information management platform based on the Internet of Things according to claim 3 is characterized in that: By formula Calculate and obtain the corresponding second broadband abnormal state value YZ2k; where YZ2k is YZ21 and YZ22, which are respectively the second broadband abnormal state value corresponding to the overall instantaneous broadband usage state abnormality and the second broadband abnormal state value corresponding to the local instantaneous broadband usage state abnormality; LYk is LY1 and LY2, which are respectively the first abnormal broadband usage total amount and the second abnormal broadband usage total amount; LY0k is LY01 and LY02, which are respectively the first abnormal standard broadband usage total amount and the second abnormal standard broadband usage total amount.

5. The network traffic information management platform based on the Internet of Things according to claim 4 is characterized in that: Performing data analysis on the first broadband abnormal state value and the second broadband abnormal state value obtained by calculation to determine a single abnormality type corresponding to the overall instantaneous bandwidth usage state abnormality or the local instantaneous bandwidth usage state abnormality; If YZ1k>0 and YZ2k>0 do not exist at the same time, it indicates that the overall instantaneous bandwidth usage status is abnormal or the single abnormality type corresponding to the local instantaneous bandwidth usage status is a mild abnormality type; If YZ1k>0 and YZ2k>0 exist at the same time, it indicates that the overall instantaneous bandwidth usage state is abnormal or the single abnormality type corresponding to the local instantaneous bandwidth usage state is abnormal is a severe abnormality type.

6. The network traffic information management platform based on the Internet of Things according to claim 5 is characterized in that: Several first abnormal durations and first abnormal total bandwidth usage obtained through analysis and processing of the overall bandwidth usage of the monitoring platform server are sorted and combined respectively, and several second abnormal durations and second abnormal total bandwidth usage obtained through analysis and processing of the local bandwidth usage caused by the hot information project to the platform server are sorted and combined respectively to obtain corresponding abnormal duration sorting sequences and abnormal broadband usage total sorting sequences, and the elements with the largest values ​​in the abnormal duration sorting sequences and the abnormal broadband usage total sorting sequences are marked as the first abnormal selected value and the second abnormal selected value, respectively.

7. The network traffic information management platform based on the Internet of Things according to claim 6 is characterized in that: The medians of all elements in the abnormal duration sorting sequence and the abnormal bandwidth usage total sorting sequence are obtained respectively and marked as the third abnormal selected value and the fourth abnormal selected value respectively.

8. The network traffic information management platform based on the Internet of Things according to claim 7 is characterized in that: The different abnormal selected values ​​obtained by processing the corresponding different bandwidth usage rates are analyzed through the traffic usage identification model, and the corresponding control necessary identification is output; The control required flag contains a value of 0, 1, or 2; According to the control necessity identifier with a value of 0, the existing overall flow control plan and the local flow control plan generated by the platform server corresponding to the hot information item are maintained.

9. The network traffic information management platform based on the Internet of Things according to claim 8, characterized in that: Implement the overall traffic local optimization control plan and the local traffic local optimization control plan generated by the platform server corresponding to the hot information project according to the control necessary flag with a value of 1; According to the control necessary identifier with a value of 2, the target-related traffic is labeled with a severe anomaly, and the overall traffic optimization control plan and the local traffic optimization control plan generated by the platform server corresponding to the hot information project are implemented.

10. The network traffic information management platform based on the Internet of Things according to claim 9, characterized in that: The expression of the traffic usage identification model is: Wherein, YX1k, YX2k, YX3k, and YX4k are respectively the first abnormal selected value, the second abnormal selected value, the third abnormal selected value, and the fourth abnormal selected value obtained by processing corresponding to different bandwidth usage rates; ak, bk, ck, and dk are respectively the first abnormal standard value, the second abnormal standard value, the third abnormal standard value, and the fourth abnormal standard value corresponding to different bandwidth usage rates.

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