CN117857373A - Multi-platform information data optimization transmission method and system - Google Patents
Multi-platform information data optimization transmission method and system Download PDFInfo
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Abstract
The present invention relates to the field of communications technologies, and in particular, to a method and a system for optimizing transmission of multi-platform information data. The method comprises the following steps: acquiring and processing network data of different network transmission platforms to obtain information data to be transmitted of multiple platforms and network environment information data of multiple platforms; acquiring multi-platform network equipment type information data, and performing network characteristic influence analysis on the multi-platform network environment information data to acquire network characteristic influence factor data of the network equipment; acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform network to acquire a multi-platform network transmission strategy; and acquiring network transmission load influence factor data, and dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data of the network equipment and the network transmission load influence factor data to obtain the multi-platform network transmission optimization strategy. The invention can realize high efficiency and low delay of data transmission between different platforms.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method and a system for optimizing transmission of multi-platform information data.
Background
With the development of mobile communication technology, the demand for cross-platform information data transmission is increasing, including but not limited to traditional wired network platforms, mobile communication network platforms (such as 4G and 5G), and internet of things platforms. However, data transmission between different network transmission platforms is affected by network conditions, transmission protocols, network loads and other factors, so that the problems of low information data transmission efficiency and high delay are caused.
Disclosure of Invention
Accordingly, the present invention is directed to a method and system for optimized transmission of multi-platform information data, which solve at least one of the above-mentioned problems.
In order to achieve the above purpose, a multi-platform information data optimization transmission method comprises the following steps:
step S1: acquiring and processing network data of different network transmission platforms to obtain information data to be transmitted of multiple platforms and network environment information data of multiple platforms; detecting the device types of different network transmission platforms to obtain multi-platform network device type information data; analyzing network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data to obtain network characteristic influence factor data of the network equipment;
Step S2: acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform based on the multi-platform network transmission demand data to obtain a multi-platform network transmission strategy; analyzing a network transmission path of the multi-platform network transmission strategy to obtain multi-platform network transmission path information data;
step S3: network load analysis is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data; carrying out load influence analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms to obtain network transmission load influence factor data;
step S4: and dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data and the network transmission load influence factor data of the network equipment to obtain the multi-platform network transmission optimization strategy.
The invention firstly acquires the abundant multi-platform information data to be transmitted and the network environment information data by carrying out network data acquisition processing on different network transmission platforms, which comprises the data information to be transmitted and various parameters and characteristics of the network environment. Meanwhile, by detecting the device types of different network transmission platforms, the device types and technical specifications adopted by each network transmission platform can be accurately identified, so that the capability and limitation of network devices can be understood, and basic information is provided for analysis and optimization of network environments. Based on the device type information, the multi-platform network environment information data can be deeply analyzed, and the influence degree and the mode of different device types on the network environment can be disclosed, so that the network performance forming mechanism can be better understood, and guidance and strategies can be provided for optimizing and improving the network environment. The key of the step is that through comprehensive data acquisition and equipment type detection, detailed knowledge of network environment and equipment characteristics is established, so that a foundation is laid for subsequent network optimization. Secondly, through acquiring the multi-platform network transmission demand data, the transmission demand information from each network transmission platform can be collected and arranged, including but not limited to the demands in terms of data volume, transmission frequency, transmission time period, safety requirement and the like, so that the comprehensive understanding of the data interaction demands among different network transmission platforms is facilitated, and basic data and reference basis are provided for subsequent transmission optimization. By carrying out corresponding network transmission strategy analysis on the information data to be transmitted of the multiple platforms based on the network transmission requirement data of the multiple platforms, corresponding transmission strategies can be formulated for the network transmission data with different priorities, so that the transmission strategies suitable for the network environment of the multiple platforms can be formulated by analyzing the aspects of path selection, transmission rate control, transmission mode optimization and the like of data transmission, and the efficiency and the stability of data transmission are improved. The implementation effect of the transmission strategy and the rationality of path selection can be comprehensively evaluated by analyzing the network transmission path of the multi-platform network transmission strategy, so that the transmission path can be further optimized by analyzing the topological structure of the network transmission path, the network congestion condition, the transmission delay and other factors, the success rate and the response speed of data transmission are improved, and the data can be ensured to be transmitted to a target platform in an optimal state, thereby realizing efficient data exchange and sharing among multiple platforms. Then, network load analysis is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data, and based on the load information, load influence analysis is further carried out on the multi-platform information data to be transmitted to obtain network transmission load influence factor data. Finally, the multi-platform network transmission strategy is dynamically optimized according to the network equipment network characteristic influence factor data and the network transmission load influence factor data which are obtained before, so that the multi-platform network transmission optimization strategy is obtained, and the key of the step is that the transmission strategy can be adjusted according to different network environments and transmission requirements by combining the network equipment characteristics and the transmission load conditions so as to maximally optimize the network transmission performance, thereby improving the efficiency and the stability of network information data transmission and reducing the network delay of the information data transmission.
Preferably, the present invention also provides a multi-platform information data optimized transmission system for executing the multi-platform information data optimized transmission method as described above, the multi-platform information data optimized transmission system comprising:
the device network characteristic influence analysis module is used for carrying out network data acquisition processing on different network transmission platforms to obtain multi-platform information data to be transmitted and multi-platform network environment information data; detecting the device types of different network transmission platforms to obtain multi-platform network device type information data; analyzing network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data, so as to obtain network equipment network characteristic influence factor data;
the multi-platform network transmission analysis module is used for acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform based on the multi-platform network transmission demand data to acquire a multi-platform network transmission strategy; carrying out network transmission path analysis on the multi-platform network environment information data according to the multi-platform network transmission strategy, thereby obtaining multi-platform network transmission path information data;
The network transmission load influence analysis module is used for carrying out network load analysis on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data; carrying out load influence analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms, thereby obtaining network transmission load influence factor data;
and the network transmission strategy dynamic optimization module is used for dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data and the network transmission load influence factor data of the network equipment so as to obtain the multi-platform network transmission optimization strategy.
In summary, the invention provides a multi-platform information data optimized transmission system, which is composed of an equipment network characteristic influence analysis module, a multi-platform network transmission analysis module, a network transmission load influence analysis module and a network transmission strategy dynamic optimization module, and can realize any multi-platform information data optimized transmission method.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of a non-limiting implementation, made with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of steps of a multi-platform information data optimization transmission method of the present invention;
FIG. 2 is a detailed step flow chart of step S1 in FIG. 1;
fig. 3 is a detailed step flow chart of step S13 in fig. 2.
Detailed Description
The following is a clear and complete description of the technical method of the present patent in conjunction with the accompanying drawings, and it is evident that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
Furthermore, the drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. The functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor methods and/or microcontroller methods.
It will be understood that, although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
In order to achieve the above objective, referring to fig. 1 to 3, the present invention provides a multi-platform information data optimization transmission method, which includes the following steps:
step S1: acquiring and processing network data of different network transmission platforms to obtain information data to be transmitted of multiple platforms and network environment information data of multiple platforms; detecting the device types of different network transmission platforms to obtain multi-platform network device type information data; analyzing network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data to obtain network characteristic influence factor data of the network equipment;
Step S2: acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform based on the multi-platform network transmission demand data to obtain a multi-platform network transmission strategy; analyzing a network transmission path of the multi-platform network transmission strategy to obtain multi-platform network transmission path information data;
step S3: network load analysis is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data; carrying out load influence analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms to obtain network transmission load influence factor data;
step S4: and dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data and the network transmission load influence factor data of the network equipment to obtain the multi-platform network transmission optimization strategy.
In the embodiment of the present invention, please refer to fig. 1, which is a schematic flow chart of steps of the multi-platform information data optimization transmission method of the present invention, in this example, the steps of the multi-platform information data optimization transmission method include:
step S1: acquiring and processing network data of different network transmission platforms to obtain information data to be transmitted of multiple platforms and network environment information data of multiple platforms; detecting the device types of different network transmission platforms to obtain multi-platform network device type information data; analyzing network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data to obtain network characteristic influence factor data of the network equipment;
According to the embodiment of the invention, the sensor is deployed to collect initial information data to be transmitted from different network transmission platforms (including traditional wired network platforms, mobile communication network platforms (such as 4G and 5G), internet of things platforms and the like) so as to fully know the information data such as the data characteristics, transmission requirements, technical limitations and the like of the different network transmission platforms, and the collected data is preprocessed so as to eliminate the transmission difference condition among the different network transmission platforms, and finally the information data to be transmitted of multiple platforms is obtained. Meanwhile, different network transmission platforms are monitored by using network transmission monitoring equipment so as to monitor and record network environment states of each network transmission platform in real time, wherein the indexes comprise bandwidth, delay, packet loss rate and the like, and therefore multi-platform network environment information data are obtained. And then, performing type detection on the network transmission equipment on different network transmission platforms by using a proper technology or tool so as to accurately identify the equipment type and technical specification adopted by each network transmission platform, thereby obtaining multi-platform network equipment type information data. And finally, analyzing the influence of the network transmission equipment of different types on the network environment transmission characteristics by performing influence analysis on the multi-platform network environment information data according to the equipment characteristics of each network transmission platform in the multi-platform network equipment type information data, so as to analyze the influence factor conditions of the network transmission equipment of different types on the network environment transmission characteristics, and finally obtaining the network equipment network characteristic influence factor data.
Step S2: acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform based on the multi-platform network transmission demand data to obtain a multi-platform network transmission strategy; analyzing a network transmission path of the multi-platform network transmission strategy to obtain multi-platform network transmission path information data;
the embodiment of the invention comprehensively knows the data interaction requirements among different network transmission platforms by knowing the transmission requirements of each network transmission platform, including the requirement information in the aspects of the type, the transmission quantity, the transmission frequency, the transmission time limit, the safety requirement and the like of the transmission data, thereby obtaining the multi-platform network transmission requirement data. Meanwhile, the information data to be transmitted of the multiple platforms is analyzed by using the multi-platform network transmission demand data, so that the importance and the urgency of different information data on the network transmission platform are analyzed and determined, the transmission priority of the different information data is determined, compression transmission is carried out, corresponding transmission strategies are formulated for the data with different priorities, the transmission strategies suitable for the multi-platform network environment are formulated, and the multi-platform network transmission strategies are obtained. And then, analyzing the generated multi-platform network transmission strategy by using a transmission path analysis method to analyze the topological structure, network congestion condition, transmission delay and other factors of the network transmission path so as to comprehensively evaluate the implementation effect of the transmission strategy and the rationality of path selection, ensure that the data can be transmitted to a target platform in an optimal state and finally obtain the multi-platform network transmission path information data.
Step S3: network load analysis is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data; carrying out load influence analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms to obtain network transmission load influence factor data;
the embodiment of the invention collects the flow data on the multi-platform network transmission path by deploying the network flow monitoring tool or equipment so as to monitor the flow change on the multi-platform network transmission path in real time, record the change condition of the flow data, including the change of inflow flow and outflow flow, and simultaneously, quantitatively know the maximum load condition of network transmission by carrying out load peak calculation on the collected flow change data, analyze the corresponding multi-platform network transmission path information data by using the calculated network transmission flow load peak value so as to comprehensively evaluate the condition and change trend of the network load, and identify the load bottleneck and risk point of the network transmission path, thereby obtaining the multi-platform network transmission load information data. And then, analyzing the information data to be transmitted of the multiple platforms by combining the information data of the load transmitted by the multiple platforms by using a data mining technology, so as to deeply explore the influence relation of the network load on the information data transmission to be transmitted, evaluate the specific influence factors of the network load on the information data transmission performance to be transmitted, and finally obtain the network transmission load influence factor data.
Step S4: and dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data and the network transmission load influence factor data of the network equipment to obtain the multi-platform network transmission optimization strategy.
The embodiment of the invention firstly analyzes network equipment network characteristic influence factor data and network transmission load influence factor data by using methods such as statistical analysis, data mining or influence mode analysis and the like to identify influence mode conditions influencing network performance and network transmission load, dynamically adjusts a network transmission protocol and a network transmission path in a multi-platform network transmission strategy, updates the transmission protocol or adjusts network parameters and the like to adapt to network conditions changing in real time, provides more bandwidth resources on key congestion nodes in the network transmission path, ensures that the network transmission path near the congestion point can provide enough bandwidth resources, thereby relieving congestion conditions on the network transmission path, dynamically optimizes the multi-platform network transmission strategy by the dynamic adjustment results, and implements corresponding adjustment to ensure that network transmission can achieve optimal performance, including adjusting the network transmission protocol, adjusting the network transmission path, optimizing a network topology structure or improving a network transmission channel and the like, thereby effectively improving the efficiency and stability of network transmission, and finally obtaining the multi-platform network transmission optimization strategy.
The invention firstly acquires the abundant multi-platform information data to be transmitted and the network environment information data by carrying out network data acquisition processing on different network transmission platforms, which comprises the data information to be transmitted and various parameters and characteristics of the network environment. Meanwhile, by detecting the device types of different network transmission platforms, the device types and technical specifications adopted by each network transmission platform can be accurately identified, so that the capability and limitation of network devices can be understood, and basic information is provided for analysis and optimization of network environments. Based on the device type information, the multi-platform network environment information data can be deeply analyzed, and the influence degree and the mode of different device types on the network environment can be disclosed, so that the network performance forming mechanism can be better understood, and guidance and strategies can be provided for optimizing and improving the network environment. The key of the step is that through comprehensive data acquisition and equipment type detection, detailed knowledge of network environment and equipment characteristics is established, so that a foundation is laid for subsequent network optimization. Secondly, through acquiring the multi-platform network transmission demand data, the transmission demand information from each network transmission platform can be collected and arranged, including but not limited to the demands in terms of data volume, transmission frequency, transmission time period, safety requirement and the like, so that the comprehensive understanding of the data interaction demands among different network transmission platforms is facilitated, and basic data and reference basis are provided for subsequent transmission optimization. By carrying out corresponding network transmission strategy analysis on the information data to be transmitted of the multiple platforms based on the network transmission requirement data of the multiple platforms, corresponding transmission strategies can be formulated for the network transmission data with different priorities, so that the transmission strategies suitable for the network environment of the multiple platforms can be formulated by analyzing the aspects of path selection, transmission rate control, transmission mode optimization and the like of data transmission, and the efficiency and the stability of data transmission are improved. The implementation effect of the transmission strategy and the rationality of path selection can be comprehensively evaluated by analyzing the network transmission path of the multi-platform network transmission strategy, so that the transmission path can be further optimized by analyzing the topological structure of the network transmission path, the network congestion condition, the transmission delay and other factors, the success rate and the response speed of data transmission are improved, and the data can be ensured to be transmitted to a target platform in an optimal state, thereby realizing efficient data exchange and sharing among multiple platforms. Then, network load analysis is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data, and based on the load information, load influence analysis is further carried out on the multi-platform information data to be transmitted to obtain network transmission load influence factor data. Finally, the multi-platform network transmission strategy is dynamically optimized according to the network equipment network characteristic influence factor data and the network transmission load influence factor data which are obtained before, so that the multi-platform network transmission optimization strategy is obtained, and the key of the step is that the transmission strategy can be adjusted according to different network environments and transmission requirements by combining the network equipment characteristics and the transmission load conditions so as to maximally optimize the network transmission performance, thereby improving the efficiency and the stability of network information data transmission and reducing the network delay of the information data transmission.
Preferably, step S1 comprises the steps of:
step S11: acquiring and processing data to be transmitted of different network transmission platforms to obtain initial information data to be transmitted of multiple platforms;
step S12: denoising the initial information data to be transmitted of the multiple platforms to obtain denoising information data to be transmitted of the multiple platforms; performing interpolation and file supplementing on the denoising information data to be transmitted by the multiple platforms to obtain interpolation information data to be transmitted by the multiple platforms; carrying out standardized processing on the interpolation information data to be transmitted by the multiple platforms to obtain standard information data to be transmitted by the multiple platforms;
step S13: acquiring network transmission characteristic information data corresponding to a network transmission platform, and performing transmission difference elimination processing on initial information data to be transmitted of multiple platforms based on the network transmission characteristic information data to obtain the information data to be transmitted of the multiple platforms;
step S14: network environment sensing is carried out on different network transmission platforms through network transmission monitoring equipment, and multi-platform network environment information data are obtained;
step S15: detecting the device types of different network transmission platforms to obtain multi-platform network device type information data;
step S16: and analyzing the network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data to obtain network characteristic influence factor data of the network equipment.
As an embodiment of the present invention, referring to fig. 2, a detailed step flow chart of step S1 in fig. 1 is shown, in which step S1 includes the following steps:
step S11: acquiring and processing data to be transmitted of different network transmission platforms to obtain initial information data to be transmitted of multiple platforms;
according to the embodiment of the invention, the sensor is deployed to collect the initial information data to be transmitted from different network transmission platforms (including traditional wired network platforms, mobile communication network platforms (such as 4G and 5G), and Internet of things platforms) so as to fully know the data characteristics, transmission requirements, technical limitations and other information data of the different network transmission platforms, and finally obtain the initial information data to be transmitted of multiple platforms.
Step S12: denoising the initial information data to be transmitted of the multiple platforms to obtain denoising information data to be transmitted of the multiple platforms; performing interpolation and file supplementing on the denoising information data to be transmitted by the multiple platforms to obtain interpolation information data to be transmitted by the multiple platforms; carrying out standardized processing on the interpolation information data to be transmitted by the multiple platforms to obtain standard information data to be transmitted by the multiple platforms;
according to the embodiment of the invention, the collected multi-platform to-be-transmitted initial information data is processed by using a proper denoising algorithm (such as moving average, median filtering and the like) so as to remove noise and interference in the data, and then the denoised data is subjected to interpolation processing by using a corresponding interpolation method so as to fill in the existing missing value or break point, and a continuous data sequence is obtained so as to ensure the integrity and continuity of the data, thereby obtaining the multi-platform to-be-transmitted interpolation information data. And then, processing the multi-platform to-be-transmitted interpolation information data subjected to interpolation and file supplementing by using a standardized processing method so as to ensure that the data of different platforms have similar scale and distribution characteristics, so that the data accords with certain unified standards and specifications, and finally, the multi-platform to-be-transmitted standard information data is obtained.
Step S13: acquiring network transmission characteristic information data corresponding to a network transmission platform, and performing transmission difference elimination processing on initial information data to be transmitted of multiple platforms based on the network transmission characteristic information data to obtain the information data to be transmitted of the multiple platforms;
the embodiment of the invention acquires the network transmission characteristic information data by collecting the network transmission characteristic information of each network transmission platform, wherein the network transmission characteristic information comprises characteristic information of the technical architecture, bandwidth limitation, transmission protocol, network topology structure and the like of each network transmission platform. And then, processing the initial information data to be transmitted of the multiple platforms by using the collected network transmission characteristic information data and using a transmission difference elimination algorithm so as to eliminate the transmission difference condition among different network transmission platforms, and finally obtaining the information data to be transmitted of the multiple platforms.
Step S14: network environment sensing is carried out on different network transmission platforms through network transmission monitoring equipment, and multi-platform network environment information data are obtained;
according to the embodiment of the invention, different network transmission platforms are monitored by using the network transmission monitoring equipment, so that the network environment states of each network transmission platform, including indexes such as bandwidth, delay and packet loss rate, are monitored and recorded in real time, and the perceived data are arranged and cleaned for further analysis and processing, so that multi-platform network environment information data is finally obtained.
Step S15: detecting the device types of different network transmission platforms to obtain multi-platform network device type information data;
the embodiment of the invention carries out type detection on the network transmission equipment on different network transmission platforms by using a proper technology or tool so as to accurately identify the equipment type and technical specification adopted by each network transmission platform and finally obtain multi-platform network equipment type information data.
Step S16: and analyzing the network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data to obtain network characteristic influence factor data of the network equipment.
According to the embodiment of the invention, the influence analysis is carried out on the multi-platform network environment information data according to the equipment characteristics of each network transmission platform in the multi-platform network equipment type information data so as to analyze the influence factor conditions of different types of network transmission equipment on the network environment transmission characteristics, and finally the network equipment network characteristic influence factor data is obtained.
When the data to be transmitted are acquired and processed on different network transmission platforms, the initial information data to be transmitted on various network transmission platforms can be obtained through a systematic data collection method, and the collection of the data is helpful for knowing the data characteristics, transmission requirements and technical limitations of the different network transmission platforms, so that a foundation is provided for subsequent data processing and transmission optimization. Meanwhile, noise and interference in the data can be effectively eliminated by denoising the initial information data to be transmitted of multiple platforms, and the data quality and accuracy are improved. The subsequent interpolation and shift supplementing operation can fill in the missing value in the data, and ensure the integrity and continuity of the data. And through standardized processing, the data can accord with certain unified standards and specifications, and the subsequent processing and comparison analysis are convenient. And secondly, the transmission characteristics and performance conditions of each network transmission platform can be better understood by acquiring the network transmission characteristic information data corresponding to the network transmission platform, and the transmission difference elimination processing is carried out on the initial information data to be transmitted of the multiple platforms based on the characteristic information data, so that the problem of the transmission difference between different network transmission platforms can be effectively solved, and the consistency and the comparability of the transmission data are improved. Then, network environment sensing is carried out on different network transmission platforms by using network transmission monitoring equipment, network environment states of each network transmission platform including indexes such as bandwidth, delay and packet loss rate can be monitored and recorded in real time, and acquisition of the multi-platform network environment information data is beneficial to evaluating network performance and transmission efficiency and provides reference basis for subsequent data transmission optimization. And then, by detecting the device types of different network transmission platforms, the device types and the technical specifications adopted by each network transmission platform can be accurately identified, which is helpful for understanding the capability and the limitation of the network devices and provides basic information for the analysis and the optimization of the network environment. Finally, by analyzing the network characteristic influence of the multi-platform network device type information data on the multi-platform network environment information data, the influence degree and the manner of different device types on the network environment can be disclosed, so that the forming mechanism of the network performance can be better understood, and guidance and strategies can be provided for optimizing and improving the network environment.
Preferably, step S13 comprises the steps of:
step S131: acquiring network transmission characteristic information data corresponding to a network transmission platform;
step S132: performing differential score calculation on the initial information data to be transmitted of the multiple platforms by utilizing a platform transmission performance differential score calculation formula based on the network transmission characteristic information data to obtain network transmission performance differential score values among different network transmission platforms;
step S133: performing transmission difference elimination processing on the initial information data to be transmitted of the multiple platforms by using a transmission difference elimination algorithm based on the network transmission performance expression difference scoring values among different network transmission platforms to obtain multi-platform information data to be transmitted difference elimination;
step S134: and carrying out performance evaluation optimization again on the multi-platform to-be-transmitted difference elimination information data to obtain the multi-platform to-be-transmitted information data.
As an embodiment of the present invention, referring to fig. 3, a detailed step flow chart of step S13 in fig. 2 is shown, in which step S13 includes the following steps:
step S131: acquiring network transmission characteristic information data corresponding to a network transmission platform;
the embodiment of the invention acquires the network transmission characteristic information data of the corresponding network transmission platform by collecting the network transmission characteristic information of each network transmission platform, wherein the network transmission characteristic information comprises the characteristic information of the technical architecture, bandwidth limitation, transmission protocol, network topology structure and the like of each network transmission platform.
Step S132: performing differential score calculation on the initial information data to be transmitted of the multiple platforms by utilizing a platform transmission performance differential score calculation formula based on the network transmission characteristic information data to obtain network transmission performance differential score values among different network transmission platforms;
according to the embodiment of the invention, firstly, the initial information data to be transmitted of the multiple platforms is analyzed by using network transmission characteristic information data to help better understand the network transmission performance difference conditions (including the difference conditions of network throughput, delay, reliability, jitter, bandwidth and packet loss rate) among different network transmission platforms, and then, a proper platform transmission performance representation difference score calculation is formed by combining the start time and end time, integral time variable parameter, network throughput difference value, network throughput difference weight factor, network throughput difference influence parameter, network delay difference value, network delay difference weight factor, network delay difference influence parameter, network delay difference parameter, network reliability difference value, network reliability difference weight factor, network jitter difference value, network jitter difference weight factor, network jitter difference influence parameter, network bandwidth difference weight factor, network bandwidth difference influence parameter, network packet loss rate difference value, network packet loss difference weight factor, network packet loss difference influence parameter and related parameter calculated, so that the initial information to be transmitted of the multiple platforms is calculated, and the network performance of the network to obtain the network transmission performance quantization and the network quality of the different platforms is calculated according to the network quality of the different values of the network transmission performance of the different platforms. In addition, the platform transmission performance difference score calculation formula can also use any performance difference evaluation algorithm in the field to replace the process of calculating the difference score, and is not limited to the platform transmission performance difference score calculation formula.
Step S133: performing transmission difference elimination processing on the initial information data to be transmitted of the multiple platforms by using a transmission difference elimination algorithm based on the network transmission performance expression difference scoring values among different network transmission platforms to obtain multi-platform information data to be transmitted difference elimination;
according to the embodiment of the invention, the initial information data to be transmitted of the multiple platforms is processed by combining the calculated network transmission performance difference score values among different network transmission platforms by using a transmission difference elimination algorithm, so that the difference condition of the initial information data to be transmitted of the multiple platforms in the transmission process among different network transmission platforms is eliminated, the consistency and stability of the data among different network transmission platforms are ensured, and finally the information data to be transmitted of the multiple platforms is obtained.
Step S134: and carrying out performance evaluation optimization again on the multi-platform to-be-transmitted difference elimination information data to obtain the multi-platform to-be-transmitted information data.
According to the embodiment of the invention, performance evaluation optimization is carried out on the multi-platform to-be-transmitted difference elimination information data subjected to transmission difference elimination again, the performance indexes such as transmission time and bandwidth utilization rate are recalculated, the overall performance of the multi-platform to-be-transmitted information data is improved by considering the reduction of network transmission platform difference, the quality and accuracy of the data are further improved, and finally the multi-platform to-be-transmitted information data is obtained.
According to the invention, the characteristics of the technical architecture, bandwidth limitation, transmission protocol, network topology structure and the like of each network transmission platform can be deeply known by acquiring the network transmission characteristic information data of the corresponding network transmission platform, and the information data can help better understand the differences among different network transmission platforms, so that a foundation is provided for subsequent data transmission optimization. And secondly, carrying out difference score calculation on the initial information data to be transmitted of multiple platforms by combining network transmission characteristic information data and utilizing a proper platform transmission performance difference score calculation formula, thereby obtaining network transmission performance difference score values among different network transmission platforms, and intuitively reflecting the difference degree of each network transmission platform on transmission performance so as to provide quantitative reference for a subsequent optimization strategy. Then, when the transmission difference elimination algorithm is used for processing the initial information data to be transmitted of the multiple platforms, the transmission difference elimination processing can be performed in a targeted manner according to the performance difference grading values among different network transmission platforms, and the key of the step is that the transmission difference elimination algorithm can be effectively used for eliminating the difference in the data transmission process among different network transmission platforms, so that the consistency and the stability of the data among different network transmission platforms are ensured. Finally, performance evaluation optimization is performed on the multi-platform to-be-transmitted difference elimination information data so as to further improve the efficiency and stability of data transmission. By re-evaluating and optimizing the processed data, the quality and accuracy of the data can be further improved, thereby providing a more reliable basis for subsequent data transmission and application. The key of the steps is that the difference between different network transmission platforms can be comprehensively considered, the data transmission process can be effectively optimized through quantitative evaluation and targeted processing, and the efficiency, stability and reliability of data transmission are improved, so that better support and guarantee are provided for practical application scenes.
Preferably, the platform transmission performance difference score calculation formula in step S132 is specifically:
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in the method, in the process of the invention,differential value of network transmission performance between different network transmission platforms is marked by +.>Start time calculated for difference score, +.>End time calculated for the difference score, +.>The integral time variable parameter calculated for the difference score,time between different network transmission platforms>Network throughput difference value at +.>For the network throughput difference weight factor,/>influencing parameters for network throughput differences, +.>Time between different network transmission platforms>Network delay difference value at ∈>For the network delay difference weight factor, +.>Influencing parameters for network delay differences, < >>Time between different network transmission platforms>Network reliability difference value at +.>For the network reliability difference weight factor, +.>Influencing parameters for network reliability differences, +.>Time between different network transmission platforms>Network jitter difference value at +.>For the network jitter difference weight factor, +.>Influence parameters for network jitter differences, < >>Time between different network transmission platforms>Network bandwidth difference value at ∈>For the network bandwidth difference weight factor, +. >Influencing parameters for network bandwidth differences, < >>Time between different network transmission platforms>Network packet loss difference value at +.>For the different weight factors of network packet loss difference, +.>For the network packet loss difference influencing parameters +.>And a correction value representing a difference scoring value for the network transmission performance.
According to the invention, a specific mathematical model is used and verified to obtain a platform transmission performance difference score calculation formula which is used for carrying out difference score calculation on the initial information data to be transmitted of multiple platforms, and the platform transmission performance difference score calculation formula is used for defining a time range for evaluating performance by using time integral range parameters, so that an analyst can be helped to focus on performance differences in a specific period. For example, different network performance may occur during peak hours and during low peak hours, and these conditions may be evaluated targeted by setting a time frame. Reflecting the differences by using network throughput difference valuesThe data transmission rate difference of the network transmission platform at a certain moment can have significant influence on user experience for application scenes such as large file transmission or video streaming which need high bandwidth. By taking this into account, the evaluator may better understand the behavior of the different platforms in terms of data transfer rate. Second, by using the network delay difference value to account for the differences in network delays, the performance of different platforms in terms of data transmission speed and response time can be evaluated, thereby providing customized network selection suggestions for different types of application scenarios. Then, stability and continuity affecting data transmission are evaluated by using the network reliability difference value and the network jitter difference value. High jitter and low reliability may cause data packet loss or disorder, affecting the integrity of data transmission, so that the performance of different platforms in terms of data transmission stability can be known through these difference values, and a more suitable network selection is provided for applications with high requirements on data integrity (such as file transmission). In addition, bandwidth and packet loss rate are one of the key indexes for measuring network performance, the bandwidth determines the maximum data volume that the network can transmit, and the packet loss rate reflects the proportion of data lost in the transmission process. The use of the network bandwidth difference value and the network packet loss rate difference value enables the difference between different platforms in these aspects to be known, and can also help an evaluator to better select a network transmission platform suitable for specific requirements. And the influence degree of the corresponding network performance difference is adjusted by using the corresponding difference weight factor and the difference influence parameter, so that the integral of each difference value is comprehensively considered, and the obtained overall performance score is obtained, and thus, the performance difference between different network transmission platforms can be represented quantitatively. Through the scoring, the performance of each network transmission platform in multiple aspects can be quickly known, so that a reference is provided for selecting the most suitable network transmission platform. In summary, the formula fully considers the network transmission performance difference scoring values among different network transmission platforms Start time of the difference score calculation ∈>End time of the difference score calculation +.>Integration time variable parameter of difference score calculation +.>Time between different network transmission platforms>Network throughput difference value at ∈>Network throughput difference weight factor->Network throughput difference influencing parameter +.>Time between different network transmission platforms>Network delay difference value at->Network delay difference weight factor->Network delay variation influencing parameter->Time between different network transmission platforms>Network reliability difference value at +.>Network reliability difference weight factor +.>Network reliability discrepancy influencing parametersTime between different network transmission platforms>Network jitter difference value at->Network jitter difference weight factor->Network jitter variation influencing parameter->Time between different network transmission platforms>Network bandwidth difference value at->Network bandwidth difference weight factor->Network bandwidth difference influencing parameter->Time between different network transmission platforms>Network packet loss difference at the site +.>Network packet loss difference different weight factor +.>Network packet loss difference influencing parameter +.>Correction value of network transmission performance difference score +. >A differential score value is expressed according to network transmission performance between different network transmission platforms>The interrelationship between the parameters constitutes a functional relationship:
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the formula can realize the calculation process of the difference scores of the initial information data to be transmitted by multiple platforms, and simultaneously, the correction value of the difference score is expressed through the network transmission performanceThe introduction of the method can be adjusted according to the error condition in the calculation process, so that the accuracy and the applicability of the platform transmission performance difference score calculation formula are improved.
Preferably, step S16 comprises the steps of:
step S161: performing characteristic engineering analysis on the multi-platform network equipment type information data to obtain multi-platform network equipment characteristic data;
the embodiment of the invention firstly cleans and processes the multi-platform network equipment type information data, including processing missing values, abnormal values and the like, converts the processed data into an analyzable format to ensure the consistency and the accuracy of the data, then analyzes the processed multi-platform network equipment type information data by using a characteristic engineering technology, extracts meaningful characteristic data from the analyzed multi-platform network equipment type information data, such as the processing capacity, the storage capacity, the network interface type and the like of the equipment, and finally obtains the multi-platform network equipment characteristic data.
Step S162: performing influence association analysis on the multi-platform network environment information data based on the multi-platform network equipment characteristic data to obtain equipment-network environment characteristic influence association relation data;
according to the embodiment of the invention, the multi-platform network environment information data is analyzed by using a data mining analysis technology in combination with the analyzed multi-platform network equipment characteristic data, so that the influence association relationship between equipment characteristics and the network environment is deeply understood, and finally the equipment-network environment characteristic influence association relationship data is obtained.
Step S163: performing equipment influence evaluation analysis on the multi-platform network environment information data according to the equipment-network environment characteristic influence association relation data to obtain equipment-network environment characteristic influence factors;
according to the embodiment of the invention, the multi-platform network environment information data is evaluated and analyzed according to the influence association relation between the device characteristics and the network environment in the device-network environment characteristic influence association relation data, so as to determine the influence degree of the device characteristics on the network environment, and finally, the device-network environment characteristic influence factor is obtained.
Step S164: acquiring average network bandwidth utilization rate data and network delay probability data of each network transmission platform through multi-platform network environment information data, and calculating network packet loss and loss according to the average network bandwidth utilization rate data and the network delay probability data to obtain multi-platform network packet loss and loss probability data;
According to the embodiment of the invention, the network bandwidth utilization rate condition and the network delay time condition of each network transmission platform are obtained from the multi-platform network environment information data, and statistical calculation is performed by using a mathematical statistical analysis method, so that average network bandwidth utilization rate data and network delay probability data are obtained. And then, carrying out statistical calculation on the average network bandwidth utilization rate data and the network delay probability data by using a packet loss statistical method so as to comprehensively evaluate the loss probability condition of network transmission packet loss and finally obtain the multi-platform network packet loss probability data.
Step S165: carrying out packet loss influence evaluation analysis on the multi-platform network environment information data based on the multi-platform network packet loss probability data to obtain a packet loss-network environment characteristic influence factor;
according to the embodiment of the invention, the multi-platform network environment information data is evaluated and analyzed by using the calculated multi-platform network packet loss probability data, so that the influence of packet loss on different network environment characteristics, such as bandwidth utilization rate, network delay and the like, is fully considered, the influence degree and the manner of packet loss on network performance are deeply understood to evaluate the influence degree between the packet loss and the network environment characteristics, and finally the packet loss-network environment characteristic influence factor is obtained.
Step S166: and carrying out network characteristic influence analysis on the multi-platform network environment information data based on the device-network environment characteristic influence factors and the packet loss-network environment characteristic influence factors to obtain network device network characteristic influence factor data.
According to the embodiment of the invention, the influence conditions of the equipment-network environment characteristic influence factors and the packet loss-network environment characteristic influence factors are comprehensively considered to carry out influence analysis on the multi-platform network environment information data, so that the comprehensive influence factors of the equipment characteristics, the network environment, the packet loss and other factors on the network performance are comprehensively considered, the root cause of the network performance problem is deeply understood, and the network equipment network characteristic influence factor data is finally obtained.
The invention can deeply mine and analyze key characteristics such as equipment type, model, performance index and the like by carrying out characteristic engineering analysis on the multi-platform network equipment type information data, so that the characteristic data of a plurality of platform network equipment can be obtained, and the data comprises but is not limited to the information such as processing capacity, storage capacity, network interface type and the like of the equipment, thereby providing an important foundation for subsequent network performance evaluation and optimization. Meanwhile, the association relation between the equipment and the network environment can be deeply understood by carrying out influence association analysis on the multi-platform network environment information data based on the multi-platform network equipment characteristic data. By analyzing the influence degree and mode of the equipment characteristics on the network environment, the association relation data of the equipment-network environment characteristics can be established, so that scientific basis is provided for subsequent network optimization and equipment configuration. Secondly, by carrying out device influence evaluation analysis on the multi-platform network environment information data by combining the device-network environment characteristic influence association relation data, the influence of the device on the network environment can be evaluated more accurately. By analyzing the association relation between the equipment characteristics and the network environment characteristics, the influence factors of the equipment-network environment characteristics can be obtained, and guidance is provided for optimizing the network performance and selecting the equipment types. And then, acquiring data such as average bandwidth utilization rate, network delay probability and the like of each network transmission platform through the multi-platform network environment information data, and calculating packet loss, so that the quality and stability of network transmission can be comprehensively evaluated, and the data provides important basis for analyzing network performance problems and optimizing transmission efficiency, thereby being beneficial to improving the reliability and efficiency of data transmission. And then, carrying out packet loss influence evaluation analysis on the multi-platform network environment information data based on the multi-platform network packet loss probability data, so that the influence degree and mode of packet loss on the network performance can be deeply understood. By evaluating the influencing factors between the packet loss and the network environment characteristics, the influence factors of the packet loss and the network environment characteristics can be obtained, so that guidance is provided for network performance optimization and packet loss processing strategies. Finally, by combining the device-network environment characteristic influence factor and the packet loss-network environment characteristic influence factor to perform network characteristic influence analysis on the multi-platform network environment information data, the comprehensive influence of the device characteristic, the network environment, the packet loss and other factors on the network performance can be comprehensively considered, the root cause of the network performance problem can be well understood, targeted optimization measures are adopted, the network transmission efficiency and stability are improved, and therefore the user experience and the data transmission quality are improved.
Preferably, step S2 comprises the steps of:
step S21: acquiring multi-platform network transmission demand data;
the embodiment of the invention comprehensively knows the data interaction requirements among different network transmission platforms by knowing the transmission requirements of each network transmission platform, including the type, the transmission quantity, the transmission frequency, the transmission time limit, the safety requirement and the like of the transmission data, collates and generalizes the collected transmission requirement information data, and finally obtains the multi-platform network transmission requirement data.
Step S22: carrying out transmission priority detection on the multi-platform information data to be transmitted based on the multi-platform network transmission demand data to obtain information priority ordering sequence data to be transmitted;
according to the embodiment of the invention, the information data to be transmitted of the multiple platforms is analyzed by using the network transmission demand data of the multiple platforms, so that the importance and the urgency of different information data on the network transmission platform are analyzed and determined, the transmission priority of the different information data is determined, the determined transmission priority is comprehensively evaluated and ordered, the important data is ensured to be processed preferentially in the transmission process, and finally the priority ordering sequence data of the information to be transmitted is obtained.
Step S23: compressing and transmitting the information priority ordering sequence data to be transmitted through network transmission protocols and compression algorithms of different network transmission platforms so as to generate a multi-platform information data compression transmission channel;
according to the embodiment of the invention, the information priority ordering sequence data to be transmitted is compressed and transmitted according to the selection of proper network transmission protocols and compression algorithms on different network transmission platforms, and the information priority ordering sequence data to be transmitted is effectively compressed on the premise of ensuring the data integrity and the safety, so that the bandwidth occupation and the transmission time in the data transmission process are effectively reduced, and a multi-platform information data compression transmission channel is finally generated.
Step S24: carrying out network transmission strategy analysis on the priority ordering sequence data of the information to be transmitted based on the multi-platform information data compression transmission channel to obtain a multi-platform network transmission strategy;
the embodiment of the invention analyzes the ordered data of the priority ordering sequence of the information to be transmitted by using the generated multi-platform information data compression transmission channel so as to formulate corresponding transmission strategies aiming at the data with different priorities, including analyzing the aspects of path selection, transmission rate control, transmission mode optimization and the like of data transmission, thereby formulating the transmission strategies suitable for the multi-platform network environment and finally obtaining the multi-platform network transmission strategies.
Step S25: and carrying out network transmission path analysis on the multi-platform network transmission strategy to obtain multi-platform network transmission path information data.
The embodiment of the invention analyzes the generated multi-platform network transmission strategy by using a transmission path analysis method, so as to comprehensively evaluate the implementation effect of the transmission strategy and the rationality of path selection by analyzing the topological structure, network congestion condition, transmission delay and other factors of the network transmission path, ensure that data can be transmitted to a target platform in an optimal state, and finally obtain the multi-platform network transmission path information data.
According to the invention, firstly, the transmission demand data of the multi-platform network is acquired, and the transmission demand information from each network transmission platform can be collected and arranged, including but not limited to the demands in terms of data volume, transmission frequency, transmission time period, safety requirement and the like, so that the comprehensive understanding of the data interaction demands among different network transmission platforms is facilitated, and basic data and reference basis are provided for subsequent transmission optimization. Secondly, transmission priority detection is carried out on the information data to be transmitted of the multiple platforms based on the transmission requirement data of the multiple platform network, so that the transmission priorities of different information data can be effectively identified and determined, and important data can be preferentially processed in the transmission process and timely transmission and processing of key information can be ensured by comprehensively evaluating and sequencing the information data to be transmitted, so that the overall transmission efficiency and the real-time performance of data transmission are improved. And then, the data of the priority ordering sequence of the information to be transmitted is compressed and transmitted through network transmission protocols and compression algorithms of different network transmission platforms, so that the bandwidth occupation and the transmission time in the data transmission process can be effectively reduced. By adopting a proper compression algorithm and a proper transmission protocol, the data can be effectively compressed on the premise of ensuring the data integrity and the safety, the transmission efficiency is improved, the transmission cost is reduced, and the transmission channel of the multi-platform information data is optimized. And then, carrying out network transmission strategy analysis on the information priority ordering sequence data to be transmitted by combining the multi-platform information data compression transmission channel, and formulating corresponding transmission strategies for the data with different priorities, so that the transmission strategies suitable for the multi-platform network environment can be formulated by analyzing the aspects of path selection, transmission rate control, transmission mode optimization and the like of data transmission, thereby improving the efficiency and stability of data transmission. Finally, by analyzing the network transmission path of the multi-platform network transmission strategy, the implementation effect of the transmission strategy and the rationality of path selection can be comprehensively evaluated. By analyzing the topological structure of the network transmission path, network congestion, transmission delay and other factors, the transmission path can be further optimized, the success rate and response speed of data transmission are improved, and the data can be ensured to be transmitted to a target platform in an optimal state, so that efficient data exchange and sharing among multiple platforms are realized.
Preferably, step S3 comprises the steps of:
step S31: network flow monitoring is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission flow change data;
the embodiment of the invention collects the flow data on the multi-platform network transmission path by deploying the network flow monitoring tool or equipment so as to monitor the flow change on the multi-platform network transmission path in real time and record the change condition of the flow data, including the change of inflow flow and outflow flow, and meanwhile, the collected flow change data is processed and arranged, including data cleaning, abnormal value removal, data format conversion and the like, so as to finally obtain the multi-platform network transmission flow change data.
Step S32: carrying out load peak calculation on the multi-platform network transmission flow change data by using a network flow load peak calculation formula to obtain a multi-platform network transmission flow load peak;
the embodiment of the invention forms a proper network flow load peak value calculation formula by combining the initial time and the termination time of load peak value calculation, the network transmission bandwidth capacity, the integral time variable parameter, the additional load time variable parameter, the network transmission flow, the load influence adjustment parameter, the influence time adjustment parameter, the additional load weight adjustment parameter, the network transmission additional load flow and the related parameters to carry out load peak value calculation on the multi-platform network transmission flow change data so as to quantitatively know the maximum load condition of network transmission and finally obtain the multi-platform network transmission flow load peak value. In addition, the network traffic load peak calculation formula can also use any traffic load detection algorithm in the field to replace the process of load peaks, and is not limited to the network traffic load peak calculation formula.
Step S33: carrying out network load analysis on the multi-platform network transmission path information data according to the multi-platform network transmission flow load peak value to obtain multi-platform network transmission load information data;
according to the embodiment of the invention, the calculated peak value of the transmission flow load of the multi-platform network is used for analyzing the corresponding multi-platform network transmission path information data so as to comprehensively evaluate the condition and the change trend of the network load, identify the load bottleneck and the risk point of the network transmission path, determine the condition and the characteristic of the network load and finally obtain the multi-platform network transmission load information data.
Step S34: carrying out transmission influence association analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platform network to obtain the information data of the transmission load influence association relation of the multiple platform network;
according to the embodiment of the invention, the information data to be transmitted of the multiple platforms is analyzed by combining the information data of the load transmitted by the multiple platforms by using a data mining technology, so that the influence relation of the network load on the information data transmission to be transmitted is deeply explored, the influence mechanism of the network load on the data transmission can be better understood, and finally the information data of the influence association relation of the network load of the multiple platforms is obtained.
Step S35: and carrying out load influence analysis on the information data to be transmitted of the multiple platforms according to the network transmission load influence association relation data of the multiple platforms to obtain network transmission load influence factor data.
According to the embodiment of the invention, the information data to be transmitted of the multiple platforms is analyzed according to the influence incidence relation of the network load in the information data to be transmitted of the multiple platforms, so that specific influence factors of the network load on the transmission performance of the information data to be transmitted are analyzed and evaluated, and finally the network transmission load influence factor data is obtained.
According to the invention, network traffic monitoring is carried out on the multi-platform network transmission path information data, so that the traffic conditions of data transmission among all network transmission platforms, including the change conditions of transmission rate, data volume, transmission time period and the like, can be obtained in real time. By monitoring network traffic, transmission bottlenecks and congestion conditions can be found in time, and reliable data support is provided for subsequent load optimization and transmission adjustment. And secondly, carrying out load peak value calculation on the multi-platform network transmission flow change data by using a proper network flow load peak value calculation formula, so that the load peak value in the network transmission process can be accurately calculated. The maximum load condition of network transmission can be known by calculating the load peak value, and a basis is provided for reasonable distribution and load balancing of network resources, so that the stability and efficiency of network transmission are improved. Then, network load analysis is carried out on the multi-platform network transmission path information data by using the calculated multi-platform network transmission flow load peak value, so that the condition and the change trend of the network load can be comprehensively estimated. By analyzing the network load, the load bottleneck and risk point of the network transmission path can be identified, and guidance is provided for network optimization and performance improvement, so that the stability and reliability of data transmission are ensured. And then, carrying out transmission influence association analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms, so that the influence relation of the network load on the information data to be transmitted can be deeply explored. By analyzing the association relation between the load information and the data transmission, the influence mechanism of the network load on the data transmission can be better understood, and a basis is provided for formulating a reasonable transmission strategy and adjusting the network resource configuration. Finally, load influence analysis is carried out on the information data to be transmitted of the multiple platforms according to the load influence association relation data of the network transmission of the multiple platforms, so that specific influence factors of the network transmission load on the transmission performance of the information data to be transmitted can be known in depth, the data transmission strategy can be optimized in a targeted manner through analysis of the load influence factors, the transmission priority can be adjusted, the transmission efficiency and the priority of the key information data can be improved, and the high efficiency and the stability of the data transmission can be ensured.
Preferably, the network traffic load peak calculation formula in step S32 is specifically:
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in the method, in the process of the invention,transmitting traffic load peaks, < >, for multi-platform networks>Initial time calculated for load peak, +.>Termination time calculated for load peak, +.>For the total number of network transmission platforms, +.>Index item times for network transmission platform, +.>Is the firstNetwork transmission bandwidth capacity of a personal network transmission platform, < >>Integration time variable parameter calculated for load peak, +.>For the extra load time variable parameter,/->Is->The personal network transmission platform is at the time->Network transport traffic at->Is->Load influencing adjustment parameters of the individual network transmission platforms, < >>Is->Influence time adjustment parameters of the personal network transmission platform, < >>Adjusting parameters for extra load weight, +.>Is->The personal network transmission platform is at the time->The network at which is transmitting extra load traffic, +.>The correction value of the traffic load peak is transmitted for the multi-platform network.
The invention obtains a network flow load peak value calculation formula through using a specific mathematical model and verifying, which is used for carrying out load peak value calculation on multi-platform network transmission flow change data, and the network flow load peak value calculation formula applies the calculation of the network flow load peak value to the whole time range through integral operation, thereby To->To comprehensively evaluateThe change in network transmission load ensures that the overall consideration of the entire process, not just a snapshot at a certain moment, is ensured. By using the network transmission flow and the network transmission extra load flow, the items reflect the actual transmission flow and the extra load condition of different network transmission platforms in different time periods, so that the different network transmission platforms can have different flow characteristics in different time periods, and the items enable a calculation formula to be closer to the actual condition, thereby improving the accuracy. By using the network transmission bandwidth capacity to reflect the maximum transmission capacity of each network transmission platform, the actual transmission flow can be compared with the bandwidth capacity, and whether the network load is close to or exceeds the capacity limit can be estimated, so that the possible network congestion situation can be early warned in advance. The load influence degree and the time range of the load are adjusted by using the load influence adjustment parameter and the influence time adjustment parameter so as to more accurately reflect the actual influence condition of the network transmission load. By adjusting the parameters, specific load behaviors of different platforms can be considered, and the applicability and accuracy of a calculation formula are improved. The contribution of the additional load to the peak network transmission load can then be more accurately assessed by adjusting the additional load weight adjustment parameter to adjust the overall load impact weight of the additional load, which allows for different degrees of impact that the additional load may have on network performance. In addition, the calculation result of the load peak is corrected by introducing a correction value to take other possible influencing factors into consideration. By correcting the peak value, the accuracy and reliability of the calculation formula can be improved, and the calculation result is ensured to be more accordant with the actual situation. Through the detailed component parts and parameter adjustment, the network traffic load peak value calculation formula can comprehensively and accurately evaluate the load conditions of a plurality of network transmission platforms, thereby providing an important reference basis for network load analysis and optimization. In summary, the formula fully considers peak value of the transmission traffic load of the multi-platform network >Initial time of load peak calculation +.>Termination time of load peak calculation +.>The total number of network transmission platforms ∈ ->Index item of network transmission platform>First->Network transmission bandwidth capacity of a personal network transmission platform>Integration time variable parameter of load peak calculation +.>Extra load time variable parameter->First->The personal network transmission platform is at the time->Network traffic at->First, theLoad influence adjustment parameter of personal network transmission platform>First->Influence of personal network transport platformTime adjustment parameter->Extra load weight adjustment parameter +.>First->The personal network transmission platform is at the time->The network at which is transmitting extra load traffic +.>Correction value of the peak value of the transmission flow load of the multi-platform network +.>Transmission of traffic load peaks according to a multi-platform network>The interrelationship between the parameters constitutes a functional relationship:
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the formula can realize the load peak value calculation process of the flow change data transmitted by the multi-platform network, and simultaneously, the correction value of the flow load peak value is transmitted by the multi-platform networkThe introduction of the network traffic load peak value calculation formula can be adjusted according to error conditions in the calculation process, so that the accuracy and applicability of the network traffic load peak value calculation formula are improved.
Preferably, step S4 comprises the steps of:
step S41: performing influence mode analysis on network characteristic influence factor data and network transmission load influence factor data of the network equipment to obtain network characteristic performance bottleneck influence mode data and network transmission load influence mode data;
according to the embodiment of the invention, the network characteristic influence factor data and the network transmission load influence factor data of the network equipment are analyzed by using methods such as statistical analysis, data mining or influence mode analysis, so that the influence mode conditions affecting the network performance and the network transmission load are identified, and finally the network characteristic bottleneck influence mode data and the network transmission load influence mode data are obtained.
Step S42: dynamically adjusting a network transmission protocol of a multi-platform network transmission strategy according to network characteristic performance bottleneck effect mode data to obtain a multi-platform network transmission update protocol;
according to the embodiment of the invention, the network transmission protocol in the multi-platform network transmission strategy is dynamically adjusted according to the network characteristic bottleneck effect mode condition of the network characteristic bottleneck effect mode data, so that the network transmission protocol is updated or network parameters are adjusted to adapt to the network conditions which change in real time, and the network transmission protocol with stronger applicability and better performance is found out, and finally the multi-platform network transmission update protocol is obtained.
Step S43: performing congestion point prediction analysis on a network transmission process of a multi-platform network transmission strategy based on network transmission load influence mode data to obtain a multi-platform network potential load congestion point;
according to the embodiment of the invention, the network transmission process of the multi-platform network transmission strategy is analyzed by combining the network load influence mode condition in the network transmission load influence mode data, so that the load congestion point in the network transmission process is predicted and identified in advance, the possible time and the possible position of the load congestion point are determined, measures can be taken before congestion occurs, the network transmission path or bandwidth allocation can be adjusted in time, and the potential load congestion point of the multi-platform network can be finally obtained.
Step S44: dynamic bandwidth allocation is carried out on a network transmission path of a multi-platform network transmission strategy based on a multi-platform network potential load congestion point so as to obtain a multi-platform network bandwidth adjustment transmission path;
the embodiment of the invention processes the network transmission path in the network transmission strategy by using the determined potential load congestion point of the multi-platform network so as to provide more bandwidth resources on the key congestion node and ensure that the network transmission path near the congestion point can provide enough bandwidth resources, thereby relieving the congestion condition on the network transmission path and finally obtaining the multi-platform network bandwidth adjustment transmission path.
Step S45: and dynamically optimizing the multi-platform network transmission strategy based on the multi-platform network transmission update protocol and the multi-platform network bandwidth adjustment transmission path to obtain the multi-platform network transmission optimization strategy.
The embodiment of the invention dynamically optimizes the multi-platform network transmission strategy by combining the processing procedure of the multi-platform network transmission update protocol and the multi-platform network bandwidth adjustment transmission path so as to implement corresponding adjustment, thereby enabling the network transmission to achieve the best performance, including adjusting the network transmission protocol, adjusting the network transmission path, optimizing the network topology structure or improving the network transmission channel, and the like, thereby effectively improving the efficiency and the stability of the network transmission, ensuring the timeliness and the reliability of the data transmission and finally obtaining the multi-platform network transmission optimization strategy.
According to the invention, firstly, through carrying out influence mode analysis on network characteristic influence factor data and network transmission load influence factor data of the network equipment, the correlation between the network characteristics and the transmission load can be deeply understood, so that the bottleneck of the network performance, including the equipment performance bottleneck and the transmission load bottleneck, can be accurately identified, and a foundation is provided for further network optimization. In the step, the data is analyzed to obtain network characteristic performance bottleneck influence mode data and network transmission load influence mode data, so that an accurate direction can be provided for subsequent network adjustment and optimization. And secondly, dynamically adjusting the network transmission protocol of the multi-platform network transmission strategy according to the network characteristic performance bottleneck effect mode data so as to adapt to the network condition which changes in real time. By dynamically adjusting the transmission protocol, the efficiency and stability of network transmission can be optimized, thereby improving the success rate and speed of data transmission. The key of the step is to adjust the transmission protocol in time according to the performance bottleneck mode data so as to adapt to different network environments and load requirements, thereby realizing the dynamic optimization of network transmission. Then, by carrying out congestion point prediction analysis on the network transmission process of the multi-platform network transmission strategy based on the network transmission load influence mode data, the possible load congestion points in the network can be identified in advance, which is helpful for taking measures before congestion occurs and avoiding interruption or delay of data transmission. By predicting the congestion point, the network transmission path or bandwidth allocation can be timely adjusted to ensure the smoothness and stability of data transmission. Next, the transmission efficiency of the multi-platform network is optimized by dynamically allocating bandwidth to the transmission paths of the network transmission policy according to the multi-platform network potential load congestion points. Through dynamic bandwidth allocation, more bandwidth resources can be provided on the key nodes, so that congestion conditions are relieved, and smooth data transmission is ensured. The key of this step is to adjust the bandwidth allocation scheme in time according to the prediction result of the congestion point, so as to realize the optimal utilization of the network resources. And finally, carrying out dynamic optimization processing on the network transmission strategy by combining a multi-platform network transmission update protocol and a dynamic bandwidth allocation transmission path so as to achieve the optimal performance of network transmission. By comprehensively considering the adjustment of the transmission protocol and the optimization of bandwidth allocation, the efficiency and stability of network transmission can be effectively improved, and the timeliness and reliability of data transmission are ensured. The key of the step is that various optimization measures can be organically combined to form a comprehensive network transmission optimization strategy so as to realize the optimal effects of the maximum utilization of network resources and data transmission.
Preferably, the present invention also provides a multi-platform information data optimized transmission system for executing the multi-platform information data optimized transmission method as described above, the multi-platform information data optimized transmission system comprising:
the device network characteristic influence analysis module is used for carrying out network data acquisition processing on different network transmission platforms to obtain multi-platform information data to be transmitted and multi-platform network environment information data; detecting the device types of different network transmission platforms to obtain multi-platform network device type information data; analyzing network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data, so as to obtain network equipment network characteristic influence factor data;
the multi-platform network transmission analysis module is used for acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform based on the multi-platform network transmission demand data to acquire a multi-platform network transmission strategy; carrying out network transmission path analysis on the multi-platform network environment information data according to the multi-platform network transmission strategy, thereby obtaining multi-platform network transmission path information data;
The network transmission load influence analysis module is used for carrying out network load analysis on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data; carrying out load influence analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms, thereby obtaining network transmission load influence factor data;
and the network transmission strategy dynamic optimization module is used for dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data and the network transmission load influence factor data of the network equipment so as to obtain the multi-platform network transmission optimization strategy.
In summary, the invention provides a multi-platform information data optimized transmission system, which is composed of an equipment network characteristic influence analysis module, a multi-platform network transmission analysis module, a network transmission load influence analysis module and a network transmission strategy dynamic optimization module, and can realize any multi-platform information data optimized transmission method.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. The multi-platform information data optimized transmission method is characterized by comprising the following steps:
step S1: acquiring and processing network data of different network transmission platforms to obtain information data to be transmitted of multiple platforms and network environment information data of multiple platforms; detecting the device types of different network transmission platforms to obtain multi-platform network device type information data; analyzing network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data to obtain network characteristic influence factor data of the network equipment;
Step S2: acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform based on the multi-platform network transmission demand data to obtain a multi-platform network transmission strategy; analyzing a network transmission path of the multi-platform network transmission strategy to obtain multi-platform network transmission path information data;
step S3: network load analysis is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data; carrying out load influence analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms to obtain network transmission load influence factor data;
step S4: and dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data and the network transmission load influence factor data of the network equipment to obtain the multi-platform network transmission optimization strategy.
2. The multi-platform information data optimized transmission method according to claim 1, wherein step S1 comprises the steps of:
step S11: acquiring and processing data to be transmitted of different network transmission platforms to obtain initial information data to be transmitted of multiple platforms;
Step S12: denoising the initial information data to be transmitted of the multiple platforms to obtain denoising information data to be transmitted of the multiple platforms; performing interpolation and file supplementing on the denoising information data to be transmitted by the multiple platforms to obtain interpolation information data to be transmitted by the multiple platforms; carrying out standardized processing on the interpolation information data to be transmitted by the multiple platforms to obtain standard information data to be transmitted by the multiple platforms;
step S13: acquiring network transmission characteristic information data corresponding to a network transmission platform, and performing transmission difference elimination processing on initial information data to be transmitted of multiple platforms based on the network transmission characteristic information data to obtain the information data to be transmitted of the multiple platforms;
step S14: network environment sensing is carried out on different network transmission platforms through network transmission monitoring equipment, and multi-platform network environment information data are obtained;
step S15: detecting the device types of different network transmission platforms to obtain multi-platform network device type information data;
step S16: and analyzing the network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data to obtain network characteristic influence factor data of the network equipment.
3. The multi-platform information data optimized transmission method according to claim 2, wherein step S13 comprises the steps of:
Step S131: acquiring network transmission characteristic information data corresponding to a network transmission platform;
step S132: performing differential score calculation on the initial information data to be transmitted of the multiple platforms by utilizing a platform transmission performance differential score calculation formula based on the network transmission characteristic information data to obtain network transmission performance differential score values among different network transmission platforms;
step S133: performing transmission difference elimination processing on the initial information data to be transmitted of the multiple platforms by using a transmission difference elimination algorithm based on the network transmission performance expression difference scoring values among different network transmission platforms to obtain multi-platform information data to be transmitted difference elimination;
step S134: and carrying out performance evaluation optimization again on the multi-platform to-be-transmitted difference elimination information data to obtain the multi-platform to-be-transmitted information data.
4. The multi-platform information data optimized transmission method according to claim 3, wherein the platform transmission performance difference score calculation formula in step S132 is specifically:
；
in the method, in the process of the invention,differential value of network transmission performance between different network transmission platforms is marked by +.>Start time calculated for difference score, +.>End time calculated for the difference score, +. >Integration time variable parameters calculated for difference scores，/>Time between different network transmission platforms>Network throughput difference value at +.>For the network throughput difference weight factor, +.>Influencing parameters for network throughput differences, +.>Time between different network transmission platforms>A network delay difference value at which,for the network delay difference weight factor, +.>Influencing parameters for network delay differences, < >>Time between different network transmission platforms>Network reliability difference value at +.>For the network reliability difference weight factor, +.>For differences in network reliabilityInfluencing parameters->Time between different network transmission platforms>Network jitter difference value at +.>For the network jitter difference weight factor, +.>Influence parameters for network jitter differences, < >>Time between different network transmission platforms>Network bandwidth difference value at ∈>For the network bandwidth difference weight factor, +.>Influencing parameters for network bandwidth differences, < >>Time between different network transmission platforms>Network packet loss difference value at +.>For the different weight factors of network packet loss difference, +.>For network packet lossDifference affects parameters, < >>And a correction value representing a difference scoring value for the network transmission performance.
5. The multi-platform information data optimized transmission method according to claim 2, wherein step S16 comprises the steps of:
step S161: performing characteristic engineering analysis on the multi-platform network equipment type information data to obtain multi-platform network equipment characteristic data;
step S162: performing influence association analysis on the multi-platform network environment information data based on the multi-platform network equipment characteristic data to obtain equipment-network environment characteristic influence association relation data;
step S163: performing equipment influence evaluation analysis on the multi-platform network environment information data according to the equipment-network environment characteristic influence association relation data to obtain equipment-network environment characteristic influence factors;
step S164: acquiring average network bandwidth utilization rate data and network delay probability data of each network transmission platform through multi-platform network environment information data, and calculating network packet loss and loss according to the average network bandwidth utilization rate data and the network delay probability data to obtain multi-platform network packet loss and loss probability data;
step S165: carrying out packet loss influence evaluation analysis on the multi-platform network environment information data based on the multi-platform network packet loss probability data to obtain a packet loss-network environment characteristic influence factor;
Step S166: and carrying out network characteristic influence analysis on the multi-platform network environment information data based on the device-network environment characteristic influence factors and the packet loss-network environment characteristic influence factors to obtain network device network characteristic influence factor data.
6. The multi-platform information data optimized transmission method according to claim 1, wherein step S2 comprises the steps of:
step S21: acquiring multi-platform network transmission demand data;
step S22: carrying out transmission priority detection on the multi-platform information data to be transmitted based on the multi-platform network transmission demand data to obtain information priority ordering sequence data to be transmitted;
step S23: compressing and transmitting the information priority ordering sequence data to be transmitted through network transmission protocols and compression algorithms of different network transmission platforms so as to generate a multi-platform information data compression transmission channel;
step S24: carrying out network transmission strategy analysis on the priority ordering sequence data of the information to be transmitted based on the multi-platform information data compression transmission channel to obtain a multi-platform network transmission strategy;
step S25: and carrying out network transmission path analysis on the multi-platform network transmission strategy to obtain multi-platform network transmission path information data.
7. The multi-platform information data optimized transmission method according to claim 1, wherein step S3 comprises the steps of:
step S31: network flow monitoring is carried out on the multi-platform network transmission path information data to obtain multi-platform network transmission flow change data;
step S32: carrying out load peak calculation on the multi-platform network transmission flow change data by using a network flow load peak calculation formula to obtain a multi-platform network transmission flow load peak;
step S33: carrying out network load analysis on the multi-platform network transmission path information data according to the multi-platform network transmission flow load peak value to obtain multi-platform network transmission load information data;
step S34: carrying out transmission influence association analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platform network to obtain the information data of the transmission load influence association relation of the multiple platform network;
step S35: and carrying out load influence analysis on the information data to be transmitted of the multiple platforms according to the network transmission load influence association relation data of the multiple platforms to obtain network transmission load influence factor data.
8. The multi-platform information data optimized transmission method according to claim 7, wherein the network traffic load peak calculation formula in step S32 is specifically:
；
In the method, in the process of the invention,transmitting traffic load peaks, < >, for multi-platform networks>Initial time calculated for load peak, +.>Termination time calculated for load peak, +.>For the total number of network transmission platforms, +.>Index item times for network transmission platform, +.>Is->Network transmission bandwidth capacity of a personal network transmission platform, < >>Integration time variable parameter calculated for load peak, +.>For the extra load time variable parameter,/->Is->The personal network transmission platform is at the time->Network transport traffic at->Is->Load influencing adjustment parameters of the individual network transmission platforms, < >>Is->Influence time adjustment parameters of the personal network transmission platform, < >>Adjusting parameters for extra load weight, +.>Is->The personal network transmission platform is at the time->The network at which is transmitting extra load traffic, +.>The correction value of the traffic load peak is transmitted for the multi-platform network.
9. The multi-platform information data optimized transmission method according to claim 1, wherein step S4 comprises the steps of:
step S41: performing influence mode analysis on network characteristic influence factor data and network transmission load influence factor data of the network equipment to obtain network characteristic performance bottleneck influence mode data and network transmission load influence mode data;
Step S42: dynamically adjusting a network transmission protocol of a multi-platform network transmission strategy according to network characteristic performance bottleneck effect mode data to obtain a multi-platform network transmission update protocol;
step S43: performing congestion point prediction analysis on a network transmission process of a multi-platform network transmission strategy based on network transmission load influence mode data to obtain a multi-platform network potential load congestion point;
step S44: dynamic bandwidth allocation is carried out on a network transmission path of a multi-platform network transmission strategy based on a multi-platform network potential load congestion point so as to obtain a multi-platform network bandwidth adjustment transmission path;
step S45: and dynamically optimizing the multi-platform network transmission strategy based on the multi-platform network transmission update protocol and the multi-platform network bandwidth adjustment transmission path to obtain the multi-platform network transmission optimization strategy.
10. A multi-platform information data optimized transmission system for performing the multi-platform information data optimized transmission method as claimed in claim 1, comprising:
the device network characteristic influence analysis module is used for carrying out network data acquisition processing on different network transmission platforms to obtain multi-platform information data to be transmitted and multi-platform network environment information data; detecting the device types of different network transmission platforms to obtain multi-platform network device type information data; analyzing network characteristic influence on the multi-platform network environment information data based on the multi-platform network equipment type information data, so as to obtain network equipment network characteristic influence factor data;
The multi-platform network transmission analysis module is used for acquiring multi-platform network transmission demand data, and carrying out network transmission strategy analysis on the information data to be transmitted of the multi-platform based on the multi-platform network transmission demand data to acquire a multi-platform network transmission strategy; carrying out network transmission path analysis on the multi-platform network environment information data according to the multi-platform network transmission strategy, thereby obtaining multi-platform network transmission path information data;
the network transmission load influence analysis module is used for carrying out network load analysis on the multi-platform network transmission path information data to obtain multi-platform network transmission load information data; carrying out load influence analysis on the information data to be transmitted of the multiple platforms based on the information data of the transmission load of the multiple platforms, thereby obtaining network transmission load influence factor data;
and the network transmission strategy dynamic optimization module is used for dynamically optimizing the multi-platform network transmission strategy according to the network characteristic influence factor data and the network transmission load influence factor data of the network equipment so as to obtain the multi-platform network transmission optimization strategy.
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