Industrial Internet data service processing system based on multi-dimensional data

Abstract

The present invention discloses an industrial Internet data service processing system based on multidimensional data, which belongs to the field of industrial Internet data service processing technology, and includes an application analysis module, a data acquisition module, a transmission control module and a storage management module; the application analysis module performs demand analysis on each upper-layer application, obtains each demand data type corresponding to each upper-layer application and the demand urgency value corresponding to each demand data type; the data acquisition module is used to collect multidimensional data in real time, obtain corresponding network monitoring data and storage monitoring data; the transmission control module is used to perform transmission control; identify each data type corresponding to the multidimensional data, perform association analysis on each data type, and form an association chain for each data type; evaluate each data type association chain, and obtain the transmission order corresponding to each data type association chain; determine the transmission data according to the network monitoring data and the transmission order; transmit the transmission data; the storage management module is used to perform data storage management.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial Internet data service processing, specifically an industrial Internet data service processing system based on multidimensional data. Background Art

[0002] With the rapid development of Industrial Internet technologies, enterprises are increasingly demanding the collection, processing, and analysis of industrial data. Industrial Internet data service processing systems, as a critical bridge connecting industrial sites with upper-level applications, undertake multiple tasks, including data collection, storage, processing, analysis, and transmission. However, existing Industrial Internet data service processing systems still face numerous problems and challenges when processing multidimensional data.

[0003] For example, existing systems have shortcomings in data collection. Due to the complex and ever-changing Industrial Internet environment, data sources are diverse, including sensor data, device status data, operational data, and more. This data is often heterogeneous, real-time, and massive. Traditional data collection methods often struggle to meet these requirements, resulting in low data collection efficiency and low data quality. Furthermore, existing systems also have shortcomings in data services. Because Industrial Internet data service processing systems must provide real-time, accurate, and reliable data support to upper-level applications, the performance and stability of data services are crucial. However, existing data service processing systems often fail to meet these requirements, resulting in upper-level applications being unable to obtain the required data in a timely manner, which in turn affects enterprise production efficiency and decision-making accuracy.

[0004] In response to the above problems, the present invention proposes an industrial Internet data service processing system based on multidimensional data. Summary of the Invention

[0005] In order to solve the problems existing in the above-mentioned solutions, the present invention provides an industrial Internet data service processing system based on multi-dimensional data.

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

[0007] An industrial Internet data service processing system based on multi-dimensional data, including an application analysis module, a data acquisition module, a transmission control module, and a storage management module;

[0008] The application analysis module performs demand analysis on each upper-layer application to obtain each demand data type corresponding to each upper-layer application and a demand urgency value corresponding to each demand data type.

[0009] Furthermore, the method of performing demand analysis on each upper-layer application includes:

[0010] Acquire historical application data of each upper layer application, and determine the types of required data corresponding to each upper layer application according to each historical application data;

[0011] Establishing a usage detail database, wherein the usage detail database is used to store each application usage corresponding to each upper-layer application and usage feature collection items corresponding to each application usage;

[0012] Identify the current application usage of each upper-layer application and the usage feature collection items corresponding to each application usage in real time according to the usage detail database, collect data according to each usage feature collection item, and obtain usage emergency analysis data of each application usage;

[0013] An emergency analysis model is established, and the use emergency analysis data of the corresponding application use is analyzed by the emergency analysis model to obtain the demand emergency value of each demand data type.

[0014] Furthermore, the method for establishing the usage details library includes:

[0015] Obtain each application purpose of each upper-layer application; set corresponding purpose feature collection items according to each application purpose; integrate each application purpose and each purpose feature collection item to establish a purpose detail library.

[0016] The data acquisition module is used to collect multi-dimensional data in real time, and monitor the network load status and local data storage status in real time, and obtain corresponding network monitoring data and storage monitoring data.

[0017] The transmission control module is used to perform transmission control based on the collected multi-dimensional data, network monitoring data and storage monitoring data;

[0018] Identify each data type corresponding to the multidimensional data, perform association analysis on each data type, and form association chains for each data type; evaluate each data type association chain and obtain a transmission order corresponding to each data type association chain;

[0019] Determine the transmission data according to the network monitoring data and the transmission order; and transmit the transmission data.

[0020] Furthermore, the method of performing association analysis on each data type includes:

[0021] Acquire historical application data of each upper layer application, determine each combination data according to each historical application data; set each data type association chain according to each combination data, and mark each data type association chain with a corresponding application usage label.

[0022] Furthermore, the method for evaluating the association chain of each data type includes:

[0023] Real-time acquisition of the demand data types of each upper-layer application and the demand urgency value corresponding to each demand data type; marking the corresponding demand urgency representative value for each data type in the data type association chain;

[0024] Sort the demand urgency representative values ​​in the data type association chain from high to low to obtain a first sequence, and mark each demand urgency representative value as XDv according to the first sequence, where v is the rank of the corresponding demand urgency representative value in the first sequence, and v = 1, 2, ..., z, where z is a positive integer;

[0025] According to the formula Calculate the transmission value of the association chain of each data type;

[0026] Where: PB is the transmission value; XDv is the emergency representative value of the corresponding demand; v = 1, 2, ..., z, z is a positive integer; e is a natural constant;

[0027] The corresponding transmission order is determined according to the transmission value corresponding to the association chain of each data type.

[0028] Furthermore, the method of marking a corresponding demand urgency representative value for each data type in the data type association chain includes:

[0029] Identify the required data types corresponding to each data type in the data type association chain, and identify the urgency values ​​of each required data type;

[0030] Determine the weight index corresponding to each of the demand urgency values, and obtain the weight value of each of the weight indexes; mark the weight index as i, i = 1, 2, ..., n, n is a positive integer; mark the weight value as δi;

[0031] According to the formula Calculate the weight coefficient of each demand urgency value;

[0032] Where: β is the weight coefficient;

[0033] The urgency value of each demand is marked as XQj, j = 1, 2, ..., m, m is a positive integer; the corresponding weight coefficient is marked as βj;

[0034] According to the formula Calculate the demand urgency representative value of each data type;

[0035] Where: XD is the representative value of demand urgency;

[0036] When the data type has no corresponding demand data type, a preset emergency value corresponding to the data type is obtained; and the preset emergency value is marked as a demand emergency representative value of the data type.

[0037] Furthermore, when determining the transmission data, identifying each data type association chain that the transmission data does not correspond to; identifying the transmission value corresponding to each data type association chain;

[0038] Marking the data type association chain with a transmission value greater than a threshold value X1 as a target to be adjusted; determining the adjustment data to be transmitted according to the target to be adjusted;

[0039] Transmission adjustment is performed according to the adjusted data to be transmitted to obtain new transmission data, and the transmission data is transmitted.

[0040] The storage management module is used to perform data storage management, receive transmission data in real time, and perform data management according to a preset data management method and storage monitoring data.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] Through the cooperation between the application analysis module, data acquisition module, transmission control module and storage management module, comprehensive, efficient and accurate processing of multi-dimensional data in the industrial Internet is achieved, providing standard and reliable data services for upper-layer applications; solving problems existing in existing technologies and improving data acquisition efficiency, data processing capabilities and data service quality; BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 paying any creative work.

[0044] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0045] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0046] like Figure 1 As shown, the industrial Internet data service processing system based on multi-dimensional data includes an application analysis module, a data acquisition module, a transmission control module, and a storage management module;

[0047] The application analysis module is used to analyze the upper-layer applications served by the industrial Internet data service processing system, determine the types of demand data of each upper-layer application and the demand urgency value corresponding to each type of demand data.

[0048] The term "upper-layer application" is relative to the underlying system or platform. While the underlying system may include infrastructure such as the operating system, database, and network communication protocols, upper-layer applications are the specific applications or services built on top of this infrastructure. These applications can be user-facing desktop applications, mobile applications, web applications, or backend services and middleware for business logic.

[0049] The type of required data is determined based on the actual data required by the corresponding upper-layer application.

[0050] The demand urgency value is the urgency of the upper-layer application's demand for the corresponding demand data type under the current circumstances; the demand urgency value ranges from [0, 100], and the higher the demand urgency value, the more urgent the demand for the data type.

[0051] In one embodiment, an emergency status assessment may be performed based on existing methods to obtain a corresponding demand emergency value.

[0052] In one embodiment, the method for evaluating the demand urgency value is:

[0053] Obtain the application purposes of each upper-layer application, that is, the working purpose of the upper-layer application; set corresponding use feature collection items according to each application use, for collecting corresponding data on the demand and emergency situations of the application use; the above steps can be set manually; integrate each application use and each use feature collection item to establish a use detail library;

[0054] According to the usage details library, the application usage of each upper-layer application and the usage feature collection items corresponding to each application usage are identified in real time. Data is collected according to the usage feature collection items to obtain the usage emergency analysis data of each application usage.

[0055] Establish an emergency analysis model. In one embodiment, a large amount of historical use emergency analysis data can be analyzed, and the demand emergency values ​​corresponding to each demand data type under the emergency analysis data of each use for different application uses can be preset. Subsequently, matching calculations can be performed in combination with interpolation. In other embodiments, emergency analysis models can also be established based on other existing technologies, such as establishing an emergency analysis model based on a neural network such as a CNN network or a DNN network, and manually establishing a corresponding training set. The training set includes input data and output data. The input data is the application use and use emergency analysis data; the output data is the demand emergency value of the corresponding demand data type; and analysis is performed after successful training.

[0056] The use emergency analysis data of the corresponding application use is analyzed through the emergency analysis model to obtain the demand emergency value of each demand data type.

[0057] The data acquisition module is used to collect multi-dimensional data in real time in the industrial Internet environment through various sensors, smart terminals and other devices; at the same time, it continuously monitors the network load status and local data storage status, including key indicators such as network bandwidth usage, data storage capacity, data reading and writing speed, and obtains corresponding network monitoring data and storage monitoring data.

[0058] The transmission control module is used to perform transmission control based on the collected multi-dimensional data, network monitoring data and storage monitoring data, and obtain the types of demand data of each upper-layer application and the corresponding demand urgency value in real time;

[0059] Identify the data types corresponding to the multidimensional data, perform association analysis on the data types, and form association chains for the data types; evaluate the association chains for the data types, and obtain the transmission order corresponding to the association chains for the data types;

[0060] The amount of data that can be transmitted is determined based on network monitoring data, and the transmission data is determined in combination with the multi-dimensional data amount corresponding to the association chain of each data type corresponding to the transmission order; and the transmission data is transmitted.

[0061] In one embodiment, the method for performing association analysis on various data types includes:

[0062] Obtain the historical application data of each upper-level application, and determine the various combinations of data that the upper-level application needs to apply when performing data analysis based on each historical application data. That is, in order to achieve a certain analysis goal, a combination of required data types is required. If a single required data type can serve as all the analysis materials for a certain goal, it can be used as combined data alone. Set up association chains for each data type based on each combined data to represent the association between each data type, and mark each data type association chain with a corresponding application usage label, that is, to which application usage the target to be analyzed belongs.

[0063] In one embodiment, the method for evaluating association chains of various data types includes:

[0064] Obtain the demand data types of each upper-layer application and the demand urgency values ​​corresponding to each demand data type in real time; mark the corresponding demand urgency representative value for each data type in the data type association chain;

[0065] Sort the demand urgency representative values ​​in the data type association chain from high to low to obtain a first sequence, and mark each demand urgency representative value as XDv according to the first sequence, where v is the rank of the corresponding demand urgency representative value in the first sequence, and v = 1, 2, ..., z, where z is a positive integer;

[0066] According to the formula Calculate the transmission value of the association chain of each data type;

[0067] Where: PB is the transmission value; XDv is the emergency representative value of the corresponding demand; v = 1, 2, ..., z, z is a positive integer; e is a natural constant;

[0068] The corresponding transmission order is determined according to the transmission value corresponding to the association chain of each data type.

[0069] The method of marking the corresponding demand urgency representative value for each data type in the data type association chain includes:

[0070] Identify the demand data type corresponding to each data type in the data type association chain, and identify the demand urgency values ​​corresponding to each data type, because the urgency demand values ​​of the same demand data type may be different in different upper-layer applications, because a data type can have multiple demand urgency values;

[0071] According to user needs, a corresponding weight value is set for each upper-layer application or application purpose, and the upper-layer application or application purpose based on it is marked as a weight index, and the weight value is the weight value of the corresponding weight index; the weight index is marked as i, i = 1, 2, ..., n, n is a positive integer; the weight value is marked as δi;

[0072] According to the formula Calculate the weight coefficient of each demand urgency value;

[0073] The urgency value of each demand is marked as XQj, j = 1, 2, ..., m, m is a positive integer; the corresponding weight coefficient is marked as βj;

[0074] According to the formula Calculate the demand urgency representative value of each data type;

[0075] Where: XD is the representative value of demand urgency;

[0076] When a data type does not have a corresponding demand data type, that is, there is no corresponding demand urgency value, its demand urgency value is set to a default value, such as 0, 10, etc. The specific default value is set according to user needs and the importance of the corresponding data type, and the corresponding default value is marked as a preset urgency value; the preset urgency value is marked as a demand urgency representative value.

[0077] In one embodiment, in actual applications, there may be a situation where the transmitted data cannot meet the application requirements, that is, data that must be transmitted promptly according to an emergency situation cannot be transmitted in time. To address this situation, this embodiment is proposed to identify the association chains of various data types that are not included in the transmitted data and identify the transmission values ​​corresponding to the association chains of the corresponding data types.

[0078] Mark the data type association chain whose transmission value is greater than the threshold value X1 as the target to be adjusted; determine the data to be transmitted and adjusted based on the multidimensional data corresponding to each target to be adjusted;

[0079] Transmission adjustment is performed according to the adjusted data to be transmitted, so that the transmission adjustment data is merged into the transmission data for transmission, such as performing flow adjustment, data compression and other existing methods to achieve the transmission of the merged transmission data.

[0080] The storage management module is used to perform data storage management. Before transmitting data to the storage management module, it identifies the storage space required for the transmitted data and performs corresponding storage management in advance, such as data compression, deletion of useless elements, etc., to avoid storage failure, and at the same time adjusts the data format, consistency, etc.; obtains the corresponding storage status according to the storage monitoring data; specifically based on the existing storage management method; that is, the received transmission data is managed according to the preset data management method.

[0081] The above formulas are all calculated by removing dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technicians in this field according to actual conditions or obtained by simulating a large amount of data.

[0082] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The industrial Internet data service processing system based on multi-dimensional data is characterized by: It includes application analysis module, data acquisition module, transmission control module and storage management module; The application analysis module performs demand analysis on each upper-layer application to obtain each demand data type corresponding to each upper-layer application and a demand urgency value corresponding to each demand data type; The data acquisition module is used to collect multi-dimensional data in real time, and monitor the network load status and local data storage status in real time, and obtain corresponding network monitoring data and storage monitoring data; The transmission control module is used to perform transmission control based on the collected multi-dimensional data, network monitoring data and storage monitoring data; Identifying each data type corresponding to the multidimensional data, obtaining historical application data of each upper-layer application, and determining each combination data based on each historical application data; setting each data type association chain based on each combination data, and marking each data type association chain with a corresponding application usage label; evaluating each data type association chain to obtain a transmission order corresponding to each data type association chain; determining transmission data based on network monitoring data and the transmission order; and transmitting the transmission data; The storage management module is used to perform data storage management, receive and transmit data in real time, and perform data management according to a preset data management method and storage monitoring data; Methods for evaluating the association chains of various data types include: Real-time acquisition of the demand data types of each upper-layer application and the demand urgency value corresponding to each demand data type; marking the corresponding demand urgency representative value for each data type in the data type association chain; Sort the urgency representative values ​​of each demand in the data type association chain in descending order to obtain a first sequence; Mark the urgency representative value of each demand as XD according to the first sequence v , v is the ranking of the corresponding demand urgency representative value in the first sequence, v=1, 2, ..., z, z is a positive integer; According to the formula Calculate the transmission value of the association chain of each data type; Where: PB is the transmission value; e is the natural constant; The corresponding transmission order is determined according to the transmission value corresponding to the association chain of each data type.

2. The industrial Internet data service processing system based on multidimensional data according to claim 1, characterized in that: Methods for demand analysis of upper-layer applications include: Acquire historical application data of each upper layer application, and determine the types of required data corresponding to each upper layer application according to each historical application data; Establishing a usage detail database, wherein the usage detail database is used to store each application usage corresponding to each upper-layer application and usage feature collection items corresponding to each application usage; Identify the current application usage of each upper-layer application and the usage feature collection items corresponding to each application usage in real time according to the usage detail database, collect data according to each usage feature collection item, and obtain usage emergency analysis data of each application usage; An emergency analysis model is established, and the use emergency analysis data of the corresponding application use is analyzed by the emergency analysis model to obtain the demand emergency value of each demand data type.

3. The industrial Internet data service processing system based on multidimensional data according to claim 2, characterized in that: The methods for establishing a usage details library include: Obtain each application purpose of each upper-layer application; set corresponding purpose feature collection items according to each application purpose; integrate each application purpose and each purpose feature collection item to establish a purpose detail library.

4. The industrial Internet data service processing system based on multidimensional data according to claim 1, characterized in that: The method of marking the corresponding demand urgency representative value for each data type in the data type association chain includes: Identify the required data types corresponding to each data type in the data type association chain, and identify the urgency values ​​of each required data type; Determine the weight index corresponding to each of the demand urgency values, and obtain the weight value of each of the weight indexes; mark the weight index as i, i=1, 2, ..., n, n is a positive integer; mark the weight value as δ i ; According to the formula Calculate the weight coefficient of each demand urgency value; Where: β is the weight coefficient; Mark each demand's urgency value as XQ j , j = 1, 2, ..., m, m is a positive integer; the corresponding weight coefficient is marked as β j ; According to the formula Calculate the demand urgency representative value of each data type; Where: XD is the representative value of demand urgency; When the data type has no corresponding demand data type, a preset emergency value corresponding to the data type is obtained; and the preset emergency value is marked as a demand emergency representative value of the data type.

5. The industrial Internet data service processing system based on multidimensional data according to claim 1, characterized in that: When determining the transmission data, identifying each data type association chain that the transmission data does not correspond to; identifying the transmission value corresponding to each data type association chain; Marking the data type association chain with a transmission value greater than a threshold value X1 as a target to be adjusted; determining the adjustment data to be transmitted according to the target to be adjusted; Transmission adjustment is performed according to the adjusted data to be transmitted to obtain new transmission data, and the transmission data is transmitted.

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