Method and system for downloading digital network data based on historical records

Abstract

The present invention discloses a method and system for downloading data from a digital network based on historical records, the method comprising: obtaining a download request of a target user and user parameters of the target user; screening out multiple target signal transmission channels from multiple candidate signal transmission channels according to the user parameters; screening out multiple target data nodes from multiple candidate data nodes according to the request data corresponding to the download request; determining a download strategy corresponding to the target user 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; the download strategy is used to limit the transmission of data requests to at least one of the target data nodes through at least one of the target signal transmission channels to complete the download request. It can be seen that the present invention can more efficiently and reasonably determine the optimal download strategy for the user, so as to improve the efficiency and security of data downloading and provide the user with a better data download experience.

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 downloads on digital networking platforms is also increasing. Improving data download efficiency and security has become a major technical issue. Traditional data download methods often carry the risk of data leakage and tampering. Existing technologies still rely heavily on real-time data channel analysis or data packet encryption to meet data download requirements, without considering the integration of channel and data node historical records. As a result, the download efficiency and security cannot meet user needs. Clearly, existing technologies have shortcomings that need to be addressed 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 download 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:

[0005] Obtaining a download request from a target user and user parameters of the target user;

[0006] screening out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters;

[0007] 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;

[0008] 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.

[0009] 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 history data usage.

[0010] As an optional embodiment, 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:

[0011] For each candidate signal transmission channel, obtaining channel transmission device parameters and channel historical transmission records of the candidate signal transmission channel;

[0012] Inputting the channel transmission equipment parameters into a transmission efficiency evaluation model to obtain transmission efficiency parameters of the candidate signal transmission channel;

[0013] Calculating parameter similarity between a parameter set formed by the data user parameters in each record in the channel historical transmission record and the user parameters;

[0014] Calculating the product of the transmission efficiency parameter and the parameter similarity to obtain a channel parameter corresponding to the candidate signal transmission channel;

[0015] A plurality of target signal transmission channels are selected from the plurality of candidate signal transmission channels according to the channel parameters.

[0016] 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.

[0017] As an optional embodiment, in the first aspect of the present invention, screening out multiple target signal transmission channels from the multiple candidate signal transmission channels according to the channel parameters includes:

[0018] Sort all the candidate signal transmission channels according to the channel parameters from large to small to obtain a channel sequence;

[0019] All the candidate signal transmission channels that are a 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.

[0020] As an optional implementation, in the first aspect of the present invention, screening out multiple target data nodes from multiple candidate data nodes according to the request data corresponding to the download request includes:

[0021] For each candidate data node, obtain the current storage data information of the candidate data node;

[0022] 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;

[0023] Calculating an average value of data similarities between each data information portion other than the requested data in the currently stored data information and the requested data, to obtain a node parameter corresponding to the candidate data node;

[0024] Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result;

[0025] 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 a plurality of target data nodes.

[0026] As an optional embodiment, in the first aspect of the present invention, determining the download strategy corresponding to the target user based on the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node includes:

[0027] Determining an 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;

[0028] Based on a dynamic programming algorithm, an iterative calculation is performed according to the objective function and the constraint conditions to obtain an optimal download solution and a download strategy corresponding to the target user.

[0029] As an optional embodiment, in the first aspect of the present invention, determining the objective function and the 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 includes:

[0030] Determining an objective function such that the number of the target signal transmission channels and the number of the target data nodes included in the download solution are both minimized;

[0031] Identify constraints including:

[0032] The predicted transmission efficiency of each target signal transmission channel included in the download plan for transmitting the request data is greater than a preset efficiency threshold; the predicted transmission efficiency is predicted by inputting historical transmission records of each target signal transmission channel and the request data into a trained transmission efficiency prediction neural network; the transmission efficiency prediction neural network is trained using a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations;

[0033] The predicted storage security of each target data node included in the download solution 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 request data into a trained storage security prediction neural network; the storage security prediction neural network is trained using a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations;

[0034] The union of the download data parts sent by each target data node included in the download solution is equal to the request data.

[0035] A second aspect of an embodiment of the present invention discloses a system for downloading data from a digital network based on historical records, the system comprising:

[0036] An acquisition module, configured to acquire a download request from a target user and user parameters of the target user;

[0037] 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;

[0038] 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;

[0039] 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.

[0040] 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 history data usage.

[0041] As an optional embodiment, 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:

[0042] For each candidate signal transmission channel, obtaining channel transmission device parameters and channel historical transmission records of the candidate signal transmission channel;

[0043] Inputting the channel transmission equipment parameters into a transmission efficiency evaluation model to obtain transmission efficiency parameters of the candidate signal transmission channel;

[0044] Calculating parameter similarity between a parameter set formed by the data user parameters in each record in the channel historical transmission record and the user parameters;

[0045] Calculating the product of the transmission efficiency parameter and the parameter similarity to obtain a channel parameter corresponding to the candidate signal transmission channel;

[0046] A plurality of target signal transmission channels are selected from the plurality of candidate signal transmission channels according to the channel parameters.

[0047] 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.

[0048] As an optional embodiment, 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:

[0049] Sort all the candidate signal transmission channels according to the channel parameters from large to small to obtain a channel sequence;

[0050] All the candidate signal transmission channels that are a 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.

[0051] As an optional embodiment, 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:

[0052] For each candidate data node, obtain the current storage data information of the candidate data node;

[0053] 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;

[0054] Calculating an average value of data similarities between each data information portion other than the requested data in the currently stored data information and the requested data, to obtain a node parameter corresponding to the candidate data node;

[0055] Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result;

[0056] 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 a plurality of target data nodes.

[0057] As an optional embodiment, in the second aspect of the present invention, the determination module determines the specific manner of the download strategy corresponding to the target user based on the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node, including:

[0058] Determining an 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;

[0059] Based on a dynamic programming algorithm, an iterative calculation is performed according to the objective function and the constraint conditions to obtain an optimal download solution and a download strategy corresponding to the target user.

[0060] As an optional embodiment, in the second aspect of the present invention, the determination module determines the specific manner of the objective function and the 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, including:

[0061] Determining an objective function such that the number of the target signal transmission channels and the number of the target data nodes included in the download solution are both minimized;

[0062] Identify constraints including:

[0063] The predicted transmission efficiency of each target signal transmission channel included in the download plan for transmitting the request data is greater than a preset efficiency threshold; the predicted transmission efficiency is predicted by inputting historical transmission records of each target signal transmission channel and the request data into a trained transmission efficiency prediction neural network; the transmission efficiency prediction neural network is trained using a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations;

[0064] The predicted storage security of each target data node included in the download solution 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 request data into a trained storage security prediction neural network; the storage security prediction neural network is trained using a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations;

[0065] 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.

[0066] A third aspect of the present invention discloses another system for downloading data from a digital network based on historical records, the system comprising:

[0067] a memory storing executable program code;

[0068] a processor coupled to the memory;

[0069] 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.

[0070] 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 steps in the historical record-based digital network data downloading method disclosed in the first aspect of the present invention.

[0071] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0072] 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, thereby improving the efficiency and security of data downloading and providing users with a better data download experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] 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.

[0074] Figure 1 The present invention discloses a method for downloading data from a digital network based on historical records.

[0075] Figure 2 The present invention is a schematic structural diagram of a data download system based on historical records disclosed in an embodiment of the present invention.

[0076] Figure 3 This is a structural diagram of another historical record-based digital network data downloading system disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0077] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0078] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different objects, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or device.

[0079] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0080] The present invention discloses a method and system for downloading data from a digital network based on historical records. The method can screen multiple target signal transmission channels and multiple target data nodes based on user parameters and request data, respectively, to determine a reasonable and secure download strategy based on historical records. This method can more efficiently and reasonably determine the user's optimal download strategy, thereby improving the efficiency and security of data downloads and providing users with a better data download experience. These are described in detail below.

[0081] Example 1

[0082] See also Figure 1 , Figure 1 This 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:

[0083] 101. Obtain a download request of a target user and user parameters of the target user.

[0084] 102. Filter out multiple target signal transmission channels from multiple candidate signal transmission channels according to user parameters.

[0085] 103. Filter out multiple target data nodes from multiple candidate data nodes according to the request data corresponding to the download request.

[0086] 104. Determine a download strategy corresponding to the target user based on the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node.

[0087] Optionally, the download strategy is used to limit data request transmission to at least one target data node through at least one target signal transmission channel to complete the download request.

[0088] 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 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 download experience.

[0089] 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 history data usage.

[0090] 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 and accurately screen out more suitable signal transmission channels 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.

[0091] As an optional embodiment, in the above step, screening out multiple target signal transmission channels from multiple candidate signal transmission channels according to user parameters includes:

[0092] For each candidate signal transmission channel, obtaining channel transmission device parameters and channel historical transmission records of the candidate signal transmission channel;

[0093] Inputting the channel transmission equipment parameters into the transmission efficiency evaluation model to obtain the transmission efficiency parameters of the candidate signal transmission channel;

[0094] 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;

[0095] Calculate the product of the transmission efficiency parameter and the parameter similarity to obtain the channel parameter corresponding to the candidate signal transmission channel;

[0096] A plurality of target signal transmission channels are selected from a plurality of candidate signal transmission channels according to the channel parameters.

[0097] It can be seen that through the above 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.

[0098] As an optional embodiment, in the above steps, the channel transmission device 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 device parameters and corresponding transmission efficiency annotations.

[0099] It can be seen that through the above 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.

[0100] As an optional embodiment, in the above step, screening out multiple target signal transmission channels from multiple candidate signal transmission channels according to channel parameters includes:

[0101] Sort all candidate signal transmission channels from large to small according to channel parameters to obtain a channel sequence;

[0102] All candidate signal transmission channels that are a 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.

[0103] It can be seen that through the above 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.

[0104] 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:

[0105] For each candidate data node, obtain the current storage data information of the candidate data node;

[0106] 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;

[0107] Calculate the average value of the data similarity between the data information portion of each non-requested data in the currently stored data information and the requested data, and obtain the node parameters corresponding to the candidate data node;

[0108] Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result;

[0109] 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 a plurality of target data nodes.

[0110] It can be seen that through the above 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 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.

[0111] As an optional embodiment, in the above steps, determining the download strategy corresponding to the target user based on the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node includes:

[0112] 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;

[0113] 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.

[0114] It can be seen that through the above-mentioned optional embodiments, the objective function and constraints can be determined based on 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, thereby more efficiently and reasonably determining the user's optimal download strategy, thereby improving the efficiency and security of data downloading and providing users with a better data download experience.

[0115] As an optional embodiment, in the above steps, determining the objective function and the 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 includes:

[0116] Determining the objective function to minimize the number of target signal transmission channels and target data nodes included in the downloading solution;

[0117] Identify constraints including:

[0118] The predicted transmission efficiency of each target signal transmission channel included in the download plan for transmitting the requested data is greater than a preset efficiency threshold; optionally, the predicted transmission efficiency is obtained by inputting historical transmission records and request data of each target signal transmission channel into a trained transmission efficiency prediction neural network; the transmission efficiency prediction neural network is trained using a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations;

[0119] The predicted storage security of each target data node included in the download plan for storing the requested data is greater than a preset security threshold; optionally, the predicted storage security is obtained by inputting historical node storage records and request data of each target data node into a trained storage security prediction neural network for prediction; the storage security prediction neural network is trained using a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations;

[0120] The union of the download data parts sent by each target data node included in the download plan is equal to the request data.

[0121] It can be seen that through the above optional embodiments, the objective function and constraints can be determined based on the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node and the corresponding predictive neural network, so as to calculate the download strategy based on the dynamic programming algorithm, and achieve a more efficient and reasonable determination of 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.

[0122] Example 2

[0123] See also Figure 2 , Figure 2 This is a schematic diagram of the structure of a data download system based on historical records disclosed in an embodiment of the present invention. 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 2As shown, the historical record-based data network download system may include:

[0124] The acquisition module 201 is used to acquire the download request of the target user and the user parameters of the target user.

[0125] The first screening module 202 is configured to screen out a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to user parameters.

[0126] The second screening module 203 is configured 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.

[0127] The determination module 204 is configured to determine a download strategy corresponding to a target user based on the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node.

[0128] Optionally, the download strategy is used to limit data request transmission to at least one target data node through at least one target signal transmission channel to complete the download request.

[0129] 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 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 download experience.

[0130] As an optional embodiment, the user parameters include at least one of user authority, user group, user device type, and user history data usage.

[0131] 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 and accurately screen out more suitable signal transmission channels 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.

[0132] 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:

[0133] For each candidate signal transmission channel, obtaining channel transmission device parameters and channel historical transmission records of the candidate signal transmission channel;

[0134] Inputting the channel transmission equipment parameters into the transmission efficiency evaluation model to obtain the transmission efficiency parameters of the candidate signal transmission channel;

[0135] 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;

[0136] Calculate the product of the transmission efficiency parameter and the parameter similarity to obtain the channel parameter corresponding to the candidate signal transmission channel;

[0137] A plurality of target signal transmission channels are selected from a plurality of candidate signal transmission channels according to the channel parameters.

[0138] It can be seen that through the above 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.

[0139] As an optional embodiment, the channel transmission device 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 device parameters and corresponding transmission efficiency annotations.

[0140] It can be seen that through the above 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.

[0141] 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:

[0142] Sort all candidate signal transmission channels from large to small according to channel parameters to obtain a channel sequence;

[0143] All candidate signal transmission channels that are a 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.

[0144] It can be seen that through the above 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.

[0145] 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:

[0146] For each candidate data node, obtain the current storage data information of the candidate data node;

[0147] 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;

[0148] Calculate the average value of the data similarity between the data information portion of each non-requested data in the currently stored data information and the requested data, and obtain the node parameters corresponding to the candidate data node;

[0149] Determine whether the node parameter is greater than a second parameter threshold, and obtain a second determination result;

[0150] 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 a plurality of target data nodes.

[0151] It can be seen that through the above 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 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.

[0152] As an optional embodiment, the determination module determines the specific manner of the download strategy corresponding to the target user based on the historical transmission record of each target signal transmission channel and the historical node storage record of each target data node, including:

[0153] 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;

[0154] 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.

[0155] It can be seen that through the above-mentioned optional embodiments, the objective function and constraints can be determined based on 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, thereby more efficiently and reasonably determining the user's optimal download strategy, thereby improving the efficiency and security of data downloading and providing users with a better data download experience.

[0156] As an optional embodiment, the determination module determines the specific manner of the objective function and the 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, including:

[0157] Determining the objective function to minimize the number of target signal transmission channels and target data nodes included in the downloading solution;

[0158] Identify constraints including:

[0159] The predicted transmission efficiency of each target signal transmission channel included in the download plan for transmitting the requested data is greater than a preset efficiency threshold; optionally, the predicted transmission efficiency is obtained by inputting historical transmission records and request data of each target signal transmission channel into a trained transmission efficiency prediction neural network; the transmission efficiency prediction neural network is trained using a training data set including a plurality of training historical transmission records and corresponding request data annotations and transmission efficiency annotations;

[0160] The predicted storage security of each target data node included in the download plan for storing the requested data is greater than a preset security threshold; optionally, the predicted storage security is obtained by inputting historical node storage records and request data of each target data node into a trained storage security prediction neural network for prediction; the storage security prediction neural network is trained using a training data set including a plurality of training historical node storage records and corresponding request data annotations and storage security annotations;

[0161] The union of the download data parts sent by each target data node included in the download plan is equal to the request data.

[0162] It can be seen that through the above optional embodiments, the objective function and constraints can be determined based on the historical transmission records of each target signal transmission channel and the historical node storage records of each target data node and the corresponding predictive neural network, so as to calculate the download strategy based on the dynamic programming algorithm, and achieve a more efficient and reasonable determination of 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.

[0163] Example 3

[0164] 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 3 The 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 download system may include:

[0165] A memory 301 storing executable program code;

[0166] a processor 302 coupled to the memory 301;

[0167] 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.

[0168] Example 4

[0169] 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.

[0170] Example 5

[0171] 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 Example 1.

[0172] The foregoing description of specific embodiments of the present disclosure is intended to illustrate a method for performing a multi-tasking process. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0173] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having 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 smartphone, 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.

[0174] For the convenience of description, the above devices are described as being divided into 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.

[0175] 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 take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0176] 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 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.

[0177] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0178] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device 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.

[0179] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0180] 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. Memory is an example of a computer-readable medium.

[0181] 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. The 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 disc read-only memory (CD-ROM), digital versatile disc (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 transitory media such as modulated data signals and carrier waves.

[0182] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0183] This specification may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like 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 communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including storage devices.

[0184] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0185] 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 solutions of the present invention, rather than to limit them. 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 therein 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 various 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 selecting a plurality of target signal transmission channels from a plurality of candidate signal transmission channels according to the user parameters includes: For each candidate signal transmission channel, obtaining channel transmission device 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 parameter similarity between a 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 selected 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 selecting a plurality of target signal transmission channels from the plurality of candidate signal transmission channels according to the channel parameters includes: Sort all the candidate signal transmission channels according to the channel parameters from large to small to obtain a channel sequence; All the candidate signal transmission channels that are a 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; Calculating an average value of data similarities between each data information portion other than the requested data in the currently stored data information and the requested data, to obtain a 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 a plurality of target data nodes.

7. The method for downloading data from a digital network based on historical records according to claim 1, characterized in that: The step of 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: Determining an 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 a dynamic programming algorithm, an iterative calculation is performed according to the objective function and the constraint conditions to obtain an optimal download solution and a download 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 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 includes: Determining an objective function such that the number of the target signal transmission channels and the number of the target data nodes included in the download solution are both minimized; Identify constraints including: The predicted transmission efficiency of each target signal transmission channel included in the download plan for transmitting the request data is greater than a preset efficiency threshold; the predicted transmission efficiency is predicted by inputting historical transmission records of each target signal transmission channel and the request data into a trained transmission efficiency prediction neural network; the transmission efficiency prediction neural network is trained using 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 solution 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 request data into a trained storage security prediction neural network; the storage security prediction neural network is trained using 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, configured 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 according to any one of claims 1 to 8.

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