Data networking data downloading method and system based on historical records

Abstract

The invention discloses a data networking data downloading method and system based on historical records. The method comprises the steps that a downloading request of a target user and user parameters of the target user are acquired; screening out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters; screening out a plurality of target data nodes from a plurality of candidate data nodes according to request data corresponding to the downloading request; determining a downloading strategy corresponding to the target user according to the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node; the downloading strategy is used for limiting data request transmission to at least one target data node through at least one target signal transmission channel so as to complete the downloading request. Therefore, the optimal downloading strategy of the user can be determined more efficiently and reasonably, so that the data downloading efficiency and safety are improved, and better data downloading experience is provided for the user.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for downloading network data based on historical records. Background Art

[0002] With the increasing demand for big data computing and the widespread improvement of data processing capabilities, the demand for data downloading on the Internet platform is also increasing. How to improve data download efficiency and data download security has become an important technical issue, and traditional data download methods often have the risk of data leakage and tampering. When the existing technology needs data download, it is still mostly based on the analysis of real-time data channels or the encryption processing of data packets. It does not consider the historical record analysis of the channel and data nodes. Therefore, its download efficiency and security cannot meet user needs. It can be seen that the existing technology has defects and needs to be solved urgently. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a method and system for downloading Internet data based on historical records, which can more efficiently and reasonably determine the user's optimal download strategy to improve the efficiency and security of data downloading and provide users with a better data downloading experience.

[0004] In order to solve the above technical problems, the first aspect of the present invention discloses a method for downloading Internet data based on historical records, the method comprising: Obtaining a download request from a target user and user parameters of the target user; Screening out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters; Screening out a plurality of target data nodes from a plurality of candidate data nodes according to the request data corresponding to the download request; Based on the historical transmission records of each of the target signal transmission channels and the historical node storage records of each of the target data nodes, the download strategy corresponding to the target user is determined; the download strategy is used to limit the data request transmission to at least one of the target data nodes through at least one of the target signal transmission channels to complete the download request.

[0005] As an optional implementation, in the first aspect of the present invention, the user parameters include at least one of user authority, user group, user device type and user historical data usage.

[0006] As an optional implementation manner, in the first aspect of the present invention, screening out multiple target signal transmission channels from multiple candidate signal transmission channels according to the user parameters includes: For each candidate signal transmission channel, obtaining channel transmission equipment parameters and channel historical transmission records of the candidate signal transmission channel; Inputting the channel transmission equipment parameters into a transmission efficiency evaluation model to obtain transmission efficiency parameters of the candidate signal transmission channel; Calculating the parameter similarity between the parameter set formed by the data user parameters in each record in the channel historical transmission record and the user parameters; Calculating the product of the transmission efficiency parameter and the parameter similarity to obtain a channel parameter corresponding to the candidate signal transmission channel; A plurality of target signal transmission channels are screened out from the plurality of candidate signal transmission channels according to the channel parameters.

[0007] As an optional embodiment, in the first aspect of the present invention, the channel transmission equipment parameters include transmission medium parameters, transmission routing parameters and transmission mode parameters; the transmission efficiency evaluation model is a random forest model, which is trained by a training data set including multiple training channel transmission equipment parameters and corresponding transmission efficiency annotations.

[0008] As an optional implementation, in the first aspect of the present invention, the selecting a plurality of target signal transmission channels from the plurality of candidate signal transmission channels according to the channel parameters comprises: Sorting all the candidate signal transmission channels from large to small according to the channel parameters to obtain a channel sequence; All the candidate signal transmission channels of the first first number in the channel sequence and whose channel parameters are greater than a first parameter threshold are screened out to obtain a plurality of target signal transmission channels.

[0009] As an optional implementation, in the first aspect of the present invention, the selecting a plurality of target data nodes from a plurality of candidate data nodes according to the request data corresponding to the download request includes: For each candidate data node, obtain the current storage data information of the candidate data node; Determine whether at least a portion of the request data corresponding to the download request exists in the currently stored data information, and obtain a first determination result; Calculate the average value of the data similarity between each data information part other than the requested data in the currently stored data information and the requested data, and obtain the node parameter corresponding to the candidate data node; Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result; The candidate data nodes corresponding to both the first judgment result and the second judgment result are yes are screened out from all the candidate data nodes to obtain multiple target data nodes.

[0010] As an optional implementation, in the first aspect of the present invention, determining the download strategy corresponding to the target user according to the historical transmission record of each of the target signal transmission channels and the historical node storage record of each of the target data nodes includes: Determine the target function and the restriction conditions according to the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node; Based on the dynamic programming algorithm, an iterative calculation is performed according to the objective function and the constraint conditions to obtain an optimal downloading solution, thereby obtaining a downloading strategy corresponding to the target user.

[0011] As an optional implementation, in the first aspect of the present invention, determining the objective function and the constraint conditions according to the historical transmission record of each of the target signal transmission channels and the historical node storage record of each of the target data nodes includes: Determining the objective function to minimize the number of the target signal transmission channels and the number of the target data nodes included in the download solution; Identify constraints including: The predicted transmission efficiency of each target signal transmission channel included in the download scheme for transmitting the request data is greater than a preset efficiency threshold; the predicted transmission efficiency is obtained by inputting the historical transmission record of each target signal transmission channel and the request data into a trained transmission efficiency prediction neural network for prediction; the transmission efficiency prediction neural network is trained by a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations; The predicted storage security of each target data node included in the download scheme for storing the requested data is greater than a preset security threshold; the predicted storage security is predicted by inputting the historical node storage records of each target data node and the requested data into a trained storage security prediction neural network; the storage security prediction neural network is trained by a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations; The union of the download data parts sent by each of the target data nodes included in the download solution is equal to the request data.

[0012] A second aspect of an embodiment of the present invention discloses a data download system based on historical records, the system comprising: An acquisition module, used to acquire a download request from a target user and user parameters of the target user; A first screening module, configured to screen out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters; A second screening module, configured to screen out a plurality of target data nodes from a plurality of candidate data nodes according to request data corresponding to the download request; A determination module is used to determine the download strategy corresponding to the target user based on the historical transmission records of each of the target signal transmission channels and the historical node storage records of each of the target data nodes; the download strategy is used to limit the data request transmission to at least one of the target data nodes through at least one of the target signal transmission channels to complete the download request.

[0013] As an optional implementation, in the second aspect of the present invention, the user parameters include at least one of user authority, user group, user device type and user historical data usage.

[0014] As an optional implementation, in the second aspect of the present invention, the specific manner in which the first screening module screens out multiple target signal transmission channels from multiple candidate signal transmission channels according to the user parameters includes: For each candidate signal transmission channel, obtaining channel transmission equipment parameters and channel historical transmission records of the candidate signal transmission channel; Inputting the channel transmission equipment parameters into a transmission efficiency evaluation model to obtain transmission efficiency parameters of the candidate signal transmission channel; Calculating the parameter similarity between the parameter set formed by the data user parameters in each record in the channel historical transmission record and the user parameters; Calculating the product of the transmission efficiency parameter and the parameter similarity to obtain a channel parameter corresponding to the candidate signal transmission channel; A plurality of target signal transmission channels are screened out from the plurality of candidate signal transmission channels according to the channel parameters.

[0015] As an optional embodiment, in the second aspect of the present invention, the channel transmission equipment parameters include transmission medium parameters, transmission routing parameters and transmission mode parameters; the transmission efficiency evaluation model is a random forest model, which is trained by a training data set including multiple training channel transmission equipment parameters and corresponding transmission efficiency annotations.

[0016] As an optional implementation, in the second aspect of the present invention, the specific manner in which the first screening module screens out multiple target signal transmission channels from the multiple candidate signal transmission channels according to the channel parameters includes: Sorting all the candidate signal transmission channels from large to small according to the channel parameters to obtain a channel sequence; All the candidate signal transmission channels of the first first number in the channel sequence and whose channel parameters are greater than a first parameter threshold are screened out to obtain a plurality of target signal transmission channels.

[0017] As an optional implementation, in the second aspect of the present invention, the specific manner in which the second screening module screens out multiple target data nodes from multiple candidate data nodes according to the request data corresponding to the download request includes: For each candidate data node, obtain the current storage data information of the candidate data node; Determine whether at least a portion of the request data corresponding to the download request exists in the currently stored data information, and obtain a first determination result; Calculate the average value of the data similarity between each data information part other than the requested data in the currently stored data information and the requested data, and obtain the node parameter corresponding to the candidate data node; Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result; The candidate data nodes corresponding to both the first judgment result and the second judgment result are yes are screened out from all the candidate data nodes to obtain multiple target data nodes.

[0018] As an optional implementation, in the second aspect of the present invention, the determination module determines the specific manner of the download strategy corresponding to the target user according to the historical transmission record of each of the target signal transmission channels and the historical node storage record of each of the target data nodes, including: Determine the target function and the restriction conditions according to the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node; Based on the dynamic programming algorithm, an iterative calculation is performed according to the objective function and the constraint conditions to obtain an optimal downloading solution, thereby obtaining a downloading strategy corresponding to the target user.

[0019] As an optional implementation, in the second aspect of the present invention, the determination module determines the specific manner of the objective function and the constraint condition according to the historical transmission record of each of the target signal transmission channels and the historical node storage record of each of the target data nodes, including: Determining the objective function to minimize the number of the target signal transmission channels and the number of the target data nodes included in the download solution; Identify constraints including: The predicted transmission efficiency of each target signal transmission channel included in the download scheme for transmitting the request data is greater than a preset efficiency threshold; the predicted transmission efficiency is obtained by inputting the historical transmission record of each target signal transmission channel and the request data into a trained transmission efficiency prediction neural network for prediction; the transmission efficiency prediction neural network is trained by a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations; The predicted storage security of each target data node included in the download scheme for storing the requested data is greater than a preset security threshold; the predicted storage security is predicted by inputting the historical node storage records of each target data node and the requested data into a trained storage security prediction neural network; the storage security prediction neural network is trained by a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations; The union of the download data parts sent by each of the target data nodes included in the download solution is equal to the request data.

[0020] The third aspect of the present invention discloses another data download system based on historical records, the system comprising: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute part or all of the steps in the method for downloading Internet data based on historical records disclosed in the first aspect of the present invention.

[0021] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the historical record-based digital network data downloading method disclosed in the first aspect of the present invention.

[0022] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: The present invention can screen out multiple target signal transmission channels and multiple target data nodes based on user parameters and request data respectively, so as to determine a reasonable and safe download strategy according to historical records, thereby being able to more efficiently and reasonably determine the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data downloading experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 The present invention discloses a method for downloading data from a digital network based on historical records.

[0025] Figure 2 The present invention discloses a system for downloading data from a digital network based on historical records.

[0026] Figure 3 It is a structural schematic diagram of another digital network data downloading system based on historical records disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0029] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0030] The present invention discloses a method and system for downloading data from a digital network based on historical records, which can screen out multiple target signal transmission channels and multiple target data nodes based on user parameters and request data, respectively, so as to determine a reasonable and safe download strategy based on historical records, thereby being able to more efficiently and reasonably determine the user's optimal download strategy, so as to improve the efficiency and security of data downloading, and provide users with a better data downloading experience. The following are detailed descriptions.

[0031] Embodiment 1 See also Figure 1 , Figure 1 1 is a flow chart of a method for downloading Internet data based on historical records disclosed in an embodiment of the present invention. Figure 1 The described method for downloading Internet data based on historical records can be applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 1 As shown, the method for downloading Internet data based on historical records may include the following operations: 101. Obtain a download request of a target user and user parameters of the target user.

[0032] 102. Filter out multiple target signal transmission channels from multiple candidate signal transmission channels according to user parameters. 103. Select multiple target data nodes from multiple candidate data nodes according to the request data corresponding to the download request. 104. Determine a download strategy corresponding to the target user according to the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node.

[0033] Optionally, the download strategy is used to limit the data request transmission to at least one target data node through at least one target signal transmission channel to complete the download request.

[0034] It can be seen that the above-mentioned embodiments of the invention can screen out multiple target signal transmission channels and multiple target data nodes based on user parameters and request data respectively, so as to determine a reasonable and safe download strategy according to historical records, thereby being able to more efficiently and reasonably determine the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0035] As an optional embodiment, in the above steps, the user parameters include at least one of user authority, user group, user device type and user historical data usage.

[0036] It can be seen that through the above optional embodiments, the content of user parameters is limited, which can better characterize the characteristics of users, so as to accurately screen out more suitable signal transmission channels, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0037] As an optional embodiment, in the above step, selecting multiple target signal transmission channels from multiple candidate signal transmission channels according to user parameters includes: For each candidate signal transmission channel, obtaining channel transmission equipment parameters and channel historical transmission records of the candidate signal transmission channel; Inputting the channel transmission equipment parameters into the transmission efficiency evaluation model to obtain the transmission efficiency parameters of the candidate signal transmission channel; Calculate the parameter similarity between the parameter set formed by the data user parameters in each record in the channel historical transmission record and the user parameters; Calculate the product of the transmission efficiency parameter and the parameter similarity to obtain the channel parameter corresponding to the candidate signal transmission channel; According to the channel parameters, a plurality of target signal transmission channels are screened out from a plurality of candidate signal transmission channels.

[0038] It can be seen that through the above-mentioned optional embodiments, the channel parameters can be determined by calculating the transmission efficiency of the candidate signal transmission channel and the similarity of the user parameters, so as to accurately screen out reasonable and suitable target signal transmission channels, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0039] As an optional embodiment, in the above steps, the channel transmission equipment parameters include transmission medium parameters, transmission routing parameters and transmission mode parameters; the transmission efficiency evaluation model is a random forest model, which is trained by a training data set including multiple training channel transmission equipment parameters and corresponding transmission efficiency annotations.

[0040] It can be seen that through the above-mentioned optional embodiments, the content of the channel transmission equipment parameters and the model details and training details of the transmission efficiency evaluation model are clarified, which can be used to accurately predict the transmission efficiency parameters of the signal transmission channel, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0041] As an optional embodiment, in the above step, selecting multiple target signal transmission channels from multiple candidate signal transmission channels according to the channel parameters includes: All candidate signal transmission channels are sorted from large to small according to the channel parameters to obtain a channel sequence; All candidate signal transmission channels of the first first number in the channel sequence and whose channel parameters are greater than a first parameter threshold are screened out to obtain a plurality of target signal transmission channels.

[0042] It can be seen that through the above-mentioned optional embodiments, it is possible to accurately screen out reasonable and suitable target signal transmission channels by sorting channel parameters and screening quantity thresholds, so as to facilitate subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0043] As an optional embodiment, in the above step, selecting multiple target data nodes from multiple candidate data nodes according to the request data corresponding to the download request includes: For each candidate data node, obtain the current storage data information of the candidate data node; Determine whether there is at least a portion of the request data corresponding to the download request in the currently stored data information, and obtain a first determination result; Calculate the average value of the data similarity between the data information part of each non-requested data in the currently stored data information and the requested data, and obtain the node parameter corresponding to the candidate data node; Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result; The candidate data nodes corresponding to both the first judgment result and the second judgment result are yes from all the candidate data nodes are screened out to obtain a plurality of target data nodes.

[0044] It can be seen that through the above-mentioned optional embodiments, it is possible to accurately screen out reasonable and suitable target data nodes by calculating and judging the data storage content and data storage similarity of the candidate data nodes, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0045] As an optional embodiment, in the above steps, determining the download strategy corresponding to the target user according to the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node includes: Determine the objective function and constraint conditions based on the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node; Based on the dynamic programming algorithm, iterative calculation is performed according to the objective function and constraints to obtain the optimal download solution and the download strategy corresponding to the target user.

[0046] It can be seen that through the above-mentioned optional embodiments, the objective function and constraints can be determined according to the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node, so as to calculate the download strategy based on the dynamic programming algorithm, so as to more efficiently and reasonably determine the user's optimal download strategy, thereby improving the efficiency and security of data downloading and providing users with a better data download experience.

[0047] As an optional embodiment, in the above steps, determining the objective function and the restriction conditions according to the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node includes: Determine the objective function to minimize the number of target signal transmission channels and target data nodes included in the downloading solution; Identify constraints including: The predicted transmission efficiency of each target signal transmission channel included in the download scheme for transmitting the request data is greater than a preset efficiency threshold; optionally, the predicted transmission efficiency is obtained by inputting the historical transmission record and the request data of each target signal transmission channel into a trained transmission efficiency prediction neural network for prediction; the transmission efficiency prediction neural network is trained by a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations; The predicted storage security of each target data node included in the download scheme for storing the requested data is greater than a preset security threshold; optionally, the predicted storage security is obtained by inputting the historical node storage records and the requested data of each target data node into a trained storage security prediction neural network for prediction; the storage security prediction neural network is trained by a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations; The union of the download data parts sent by each target data node included in the download plan is equal to the request data.

[0048] It can be seen that through the above-mentioned optional embodiments, the objective function and constraints can be determined according to the historical transmission records of each target signal transmission channel, the historical node storage records of each target data node and the corresponding prediction neural network, so as to calculate the download strategy based on the dynamic programming algorithm, so as to more efficiently and reasonably determine the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0049] Embodiment 2 See also Figure 2 , Figure 2 The structure diagram of a data download system based on historical records disclosed in an embodiment of the present invention is shown in FIG. Figure 2 The described data download system based on historical records can be applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 2 As shown, the historical record-based data network data download system may include: The acquisition module 201 is used to acquire the download request of the target user and the user parameters of the target user.

[0050] The first screening module 202 is used to screen out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to user parameters. The second screening module 203 is used to screen out a plurality of target data nodes from a plurality of candidate data nodes according to the request data corresponding to the download request. The determination module 204 is used to determine the download strategy corresponding to the target user according to the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node.

[0051] Optionally, the download strategy is used to limit the data request transmission to at least one target data node through at least one target signal transmission channel to complete the download request.

[0052] It can be seen that the above-mentioned embodiments of the invention can screen out multiple target signal transmission channels and multiple target data nodes based on user parameters and request data respectively, so as to determine a reasonable and safe download strategy according to historical records, thereby being able to more efficiently and reasonably determine the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0053] As an optional embodiment, the user parameters include at least one of user authority, user group, user device type and user historical data usage.

[0054] It can be seen that through the above optional embodiments, the content of user parameters is limited, which can better characterize the characteristics of users, so as to accurately screen out more suitable signal transmission channels, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0055] As an optional embodiment, the specific manner in which the first screening module screens out multiple target signal transmission channels from multiple candidate signal transmission channels according to the user parameters includes: For each candidate signal transmission channel, obtaining channel transmission equipment parameters and channel historical transmission records of the candidate signal transmission channel; Inputting the channel transmission equipment parameters into the transmission efficiency evaluation model to obtain the transmission efficiency parameters of the candidate signal transmission channel; Calculate the parameter similarity between the parameter set formed by the data user parameters in each record in the channel historical transmission record and the user parameters; Calculate the product of the transmission efficiency parameter and the parameter similarity to obtain the channel parameter corresponding to the candidate signal transmission channel; According to the channel parameters, a plurality of target signal transmission channels are screened out from a plurality of candidate signal transmission channels.

[0056] It can be seen that through the above-mentioned optional embodiments, the channel parameters can be determined by calculating the transmission efficiency of the candidate signal transmission channel and the similarity of the user parameters, so as to accurately screen out reasonable and suitable target signal transmission channels, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0057] As an optional embodiment, the channel transmission equipment parameters include transmission medium parameters, transmission routing parameters and transmission mode parameters; the transmission efficiency evaluation model is a random forest model, which is trained by a training data set including multiple training channel transmission equipment parameters and corresponding transmission efficiency annotations.

[0058] It can be seen that through the above-mentioned optional embodiments, the content of the channel transmission equipment parameters and the model details and training details of the transmission efficiency evaluation model are clarified, which can be used to accurately predict the transmission efficiency parameters of the signal transmission channel, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0059] As an optional embodiment, the specific manner in which the first screening module screens out multiple target signal transmission channels from multiple candidate signal transmission channels according to the channel parameters includes: All candidate signal transmission channels are sorted from large to small according to the channel parameters to obtain a channel sequence; All candidate signal transmission channels of the first first number in the channel sequence and whose channel parameters are greater than a first parameter threshold are screened out to obtain a plurality of target signal transmission channels.

[0060] It can be seen that through the above-mentioned optional embodiments, it is possible to accurately screen out reasonable and suitable target signal transmission channels by sorting channel parameters and screening quantity thresholds, so as to facilitate subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0061] As an optional embodiment, the specific manner in which the second screening module screens out multiple target data nodes from multiple candidate data nodes according to the request data corresponding to the download request includes: For each candidate data node, obtain the current storage data information of the candidate data node; Determine whether there is at least a portion of the request data corresponding to the download request in the currently stored data information, and obtain a first determination result; Calculate the average value of the data similarity between the data information part of each non-requested data in the currently stored data information and the requested data, and obtain the node parameter corresponding to the candidate data node; Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result; The candidate data nodes corresponding to both the first judgment result and the second judgment result are yes from all the candidate data nodes are screened out to obtain a plurality of target data nodes.

[0062] It can be seen that through the above-mentioned optional embodiments, it is possible to accurately screen out reasonable and suitable target data nodes by calculating and judging the data storage content and data storage similarity of the candidate data nodes, so as to facilitate the subsequent download strategy determination, and assist in more efficiently and reasonably determining the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0063] As an optional embodiment, the determination module determines the specific manner of the download strategy corresponding to the target user according to the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node, including: Determine the objective function and constraint conditions based on the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node; Based on the dynamic programming algorithm, iterative calculation is performed according to the objective function and constraints to obtain the optimal download solution and the download strategy corresponding to the target user.

[0064] It can be seen that through the above-mentioned optional embodiments, the objective function and constraints can be determined according to the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node, so as to calculate the download strategy based on the dynamic programming algorithm, so as to more efficiently and reasonably determine the user's optimal download strategy, thereby improving the efficiency and security of data downloading and providing users with a better data download experience.

[0065] As an optional embodiment, the determination module determines the specific manner of the objective function and the constraint condition according to the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node, including: Determine the objective function to minimize the number of target signal transmission channels and target data nodes included in the downloading solution; Identify constraints including: The predicted transmission efficiency of each target signal transmission channel included in the download scheme for transmitting the request data is greater than a preset efficiency threshold; optionally, the predicted transmission efficiency is obtained by inputting the historical transmission record and the request data of each target signal transmission channel into a trained transmission efficiency prediction neural network for prediction; the transmission efficiency prediction neural network is trained by a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations; The predicted storage security of each target data node included in the download scheme for storing the requested data is greater than a preset security threshold; optionally, the predicted storage security is obtained by inputting the historical node storage records and the requested data of each target data node into a trained storage security prediction neural network for prediction; the storage security prediction neural network is trained by a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations; The union of the download data parts sent by each target data node included in the download plan is equal to the request data.

[0066] It can be seen that through the above-mentioned optional embodiments, the objective function and constraints can be determined according to the historical transmission records of each target signal transmission channel, the historical node storage records of each target data node and the corresponding prediction neural network, so as to calculate the download strategy based on the dynamic programming algorithm, so as to more efficiently and reasonably determine the user's optimal download strategy, so as to improve the efficiency and security of data downloading and provide users with a better data download experience.

[0067] Embodiment 3 See also Figure 3 , Figure 3 This is another digital network data downloading system based on historical records disclosed in an embodiment of the present invention. Figure 3The described data download system based on historical records is applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 3 As shown, the historical record-based data network data download system may include: A memory 301 storing executable program codes; a processor 302 coupled to the memory 301; The processor 302 calls the executable program code stored in the memory 301 to execute the steps of the method for downloading Internet data based on historical records described in the first embodiment.

[0068] Embodiment 4 An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the method for downloading network data based on historical records described in the first embodiment.

[0069] Embodiment 5 An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the historical record-based digital network data downloading method described in the first embodiment.

[0070] The above describes specific embodiments of the present specification, and other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily have to be performed in the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0071] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0072] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0073] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may be in the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the embodiments of this specification may be in the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0074] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0075] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0077] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0078] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0079] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0080] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0081] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0082] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0083] Finally, it should be noted that the method and system for downloading network data based on historical records disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for downloading data from a digital network based on historical records, characterized in that: The method comprises: Obtaining a download request from a target user and user parameters of the target user; Screening out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters; Screening out a plurality of target data nodes from a plurality of candidate data nodes according to the request data corresponding to the download request; Based on the historical transmission records of each of the target signal transmission channels and the historical node storage records of each of the target data nodes, the download strategy corresponding to the target user is determined; the download strategy is used to limit the data request transmission to at least one of the target data nodes through at least one of the target signal transmission channels to complete the download request.

2. The method for downloading data from a digital network based on historical records according to claim 1, characterized in that: The user parameters include at least one of user authority, user group, user device type and user history data usage.

3. The method for downloading data from a digital network based on historical records according to claim 1, characterized in that: The step of selecting a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters comprises: For each candidate signal transmission channel, obtaining channel transmission equipment parameters and channel historical transmission records of the candidate signal transmission channel; Inputting the channel transmission equipment parameters into a transmission efficiency evaluation model to obtain transmission efficiency parameters of the candidate signal transmission channel; Calculating the parameter similarity between the parameter set formed by the data user parameters in each record in the channel historical transmission record and the user parameters; Calculating the product of the transmission efficiency parameter and the parameter similarity to obtain a channel parameter corresponding to the candidate signal transmission channel; A plurality of target signal transmission channels are screened out from the plurality of candidate signal transmission channels according to the channel parameters.

4. The method for downloading data from a digital network based on historical records according to claim 3, characterized in that: The channel transmission equipment parameters include transmission medium parameters, transmission route parameters and transmission mode parameters; the transmission efficiency evaluation model is a random forest model, which is trained by a training data set including multiple training channel transmission equipment parameters and corresponding transmission efficiency annotations.

5. The method for downloading data from a digital network based on historical records according to claim 3, characterized in that: The step of selecting a plurality of target signal transmission channels from the plurality of candidate signal transmission channels according to the channel parameters comprises: Sorting all the candidate signal transmission channels from large to small according to the channel parameters to obtain a channel sequence; All the candidate signal transmission channels of the first first number in the channel sequence and whose channel parameters are greater than a first parameter threshold are screened out to obtain a plurality of target signal transmission channels.

6. The method for downloading data from a digital network based on historical records according to claim 1, characterized in that: The step of selecting a plurality of target data nodes from a plurality of candidate data nodes according to the request data corresponding to the download request includes: For each candidate data node, obtain the current storage data information of the candidate data node; Determine whether at least a portion of the request data corresponding to the download request exists in the currently stored data information, and obtain a first determination result; Calculate the average value of the data similarity between each data information part other than the requested data in the currently stored data information and the requested data, and obtain the node parameter corresponding to the candidate data node; Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result; The candidate data nodes corresponding to both the first judgment result and the second judgment result are yes are screened out from all the candidate data nodes to obtain multiple target data nodes.

7. The method for downloading data from a digital network based on historical records according to claim 1, characterized in that: Determining the download strategy corresponding to the target user according to the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node includes: Determine the objective function and the constraint conditions according to the historical transmission records of each of the target signal transmission channels and the historical node storage records of each of the target data nodes; Based on the dynamic programming algorithm, an iterative calculation is performed according to the objective function and the constraint conditions to obtain an optimal downloading solution, thereby obtaining a downloading strategy corresponding to the target user.

8. The method for downloading data from a digital network based on historical records according to claim 7, characterized in that: Determining the objective function and the restriction conditions according to the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node includes: Determining the objective function to minimize the number of the target signal transmission channels and the number of the target data nodes included in the download solution; Identify constraints including: The predicted transmission efficiency of each target signal transmission channel included in the download scheme for transmitting the request data is greater than a preset efficiency threshold; the predicted transmission efficiency is obtained by inputting the historical transmission record of each target signal transmission channel and the request data into a trained transmission efficiency prediction neural network for prediction; the transmission efficiency prediction neural network is trained by a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations; The predicted storage security of each target data node included in the download scheme for storing the requested data is greater than a preset security threshold; the predicted storage security is predicted by inputting the historical node storage records of each target data node and the requested data into a trained storage security prediction neural network; the storage security prediction neural network is trained by a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations; The union of the download data parts sent by each of the target data nodes included in the download solution is equal to the request data.

9. A data download system based on historical records, characterized in that: The system comprises: An acquisition module, used to acquire a download request from a target user and user parameters of the target user; A first screening module, configured to screen out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters; A second screening module, configured to screen out a plurality of target data nodes from a plurality of candidate data nodes according to request data corresponding to the download request; A determination module is used to determine the download strategy corresponding to the target user based on the historical transmission records of each of the target signal transmission channels and the historical node storage records of each of the target data nodes; the download strategy is used to limit the data request transmission to at least one of the target data nodes through at least one of the target signal transmission channels to complete the download request.

10. A data download system based on historical records, characterized in that: The system comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the method for downloading Internet data based on historical records as described in any one of claims 1 to 8.

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