CN116540597A - Industrial control system based on edge calculation - Google Patents
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Abstract
The invention discloses an industrial control system based on edge calculation, which relates to the technical field of edge calculation and comprises a data acquisition module, a data encryption module and a signal verification module; the data acquisition module is used for acquiring equipment data received by a plurality of edge nodes and carrying out data encapsulation processing; the encapsulated data is subjected to protocol conversion through a protocol conversion module, and is converted into a data protocol with a uniform fixed format; carrying out algorithm analysis and processing on the converted data protocol through a data analysis module, and packaging the analyzed and processed data into a data packet to be transmitted to a server; if the core node is the core node, the data encryption module is utilized to encrypt and transmit the data packet; the signal verification module is used for verifying the communication state of the edge node in real time, and calculating to obtain a limit deviation coefficient GF; if GF is greater than the deviation coefficient threshold value, generating a communication abnormal signal; to remind the manager to maintain the edge node, guarantee the accuracy of data monitoring.
Description
Technical Field
The invention relates to the technical field of edge calculation, in particular to an industrial control system based on edge calculation.
Background
The edge calculation is a distributed open platform integrating network, calculation, storage and application core capabilities at the network edge side close to an object or data source, provides edge intelligent service nearby, and meets key requirements of industry digitization in aspects of agile connection, real-time service, data optimization, application intelligence, safety, privacy protection and the like. The intelligent network system can be used as a bridge for connecting physical and digital worlds to realize intelligent assets, intelligent gateways, intelligent systems and intelligent services;
with the advent of the big data age, the data volume of enterprises is larger and larger, and the timeliness requirement is higher and higher; uploading a large amount of data to a server end for processing, and returning a result to equipment, wherein the response time delay of the large closed-loop data is high, the data of the equipment end cannot be processed in time, the network congestion has a large influence on the data, and meanwhile, potential safety hazards exist in network safety and management maintenance; based on the defects, the invention provides an industrial control system based on edge calculation.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the invention proposes an industrial control system based on edge computation.
To achieve the above objective, an embodiment according to a first aspect of the present invention provides an industrial control system based on edge computing, which includes a data acquisition module, a protocol conversion module, an FPGA master control, a data analysis module, a data encryption module, a feature acquisition module, a node analysis module, and a signal verification module;
the data acquisition module is used for acquiring equipment data received by a plurality of edge nodes and carrying out data encapsulation processing on the acquired equipment data; the encapsulated data is subjected to protocol conversion through a protocol conversion module, and is converted into a data protocol with a uniform fixed format;
the FPGA main control is in control connection with the protocol conversion module and is used for acquiring the data protocol converted by the protocol conversion module, carrying out algorithm analysis and processing on the converted data protocol through the data analysis module, packaging the analyzed and processed data into a data packet, and transmitting the data packet to the server through the 5G communication module;
the characteristic acquisition module is used for acquiring characteristic information of the equipment data received by each edge node and transmitting the acquired characteristic information to the node analysis module for analysis of the optimizing coefficient YS;
the node analysis module is used for classifying the edge nodes according to the optimal coefficient YS, and if the optimal coefficient YS is larger than a set value, the corresponding edge nodes are marked as core nodes;
before the data analysis module transmits the data packet after analysis to the server, the data analysis module is further used for acquiring an edge node corresponding to the data packet, and if the edge node is a core node, the data packet is encrypted and transmitted by the data encryption module;
the signal verification module is used for verifying the communication state of the edge node in real time, and calculating to obtain a limit deviation coefficient GF; if GF is larger than the deviation coefficient threshold value, judging that the edge node is abnormal in communication, and generating a communication abnormal signal; to alert the manager to repair and maintain the edge node.
Further, the specific analysis steps of the node analysis module are as follows:
aiming at a certain edge node, acquiring characteristic information of equipment data received by the edge node; counting the total operation times of the edge nodes as C1 in a preset time period;
sequentially marking corresponding equipment data quantity, equipment data transmission distance and equipment data transmission bandwidth in the characteristic information as Li, di and Wi; acquiring equipment data types in the characteristic information, setting a corresponding preset type value for each data type, and matching the equipment data types with all the data types to acquire the corresponding preset type value and marking the corresponding preset type value as CYi;
the calculation value Yi required for the edge node to process each device data is calculated using the formula yi= (CYi ×a1+li×a2+di×a3)/(wi×a4); wherein a1, a2, a3 and a4 are coefficient factors;
comparing the operation value Yi with a preset operation threshold value; counting the times of Yi > a preset operation threshold value as P1; when Yi is larger than a preset operation threshold, obtaining a difference value of Yi and the preset operation threshold and summing to obtain an supercomputed total value CZ; and calculating to obtain the running and optimizing coefficient YS by using a formula YS= (P1×g1+CZ×g2)/C1, wherein g1 and g2 are preset coefficient factors.
Further, the data encryption module is used for carrying out distributed multi-layer encryption on the received data packet and transmitting the encrypted ciphertext to the server; the specific encryption steps are as follows:
randomly splitting the data packet into a plurality of data blocks; generating an AES128 encryption key, and generating a plurality of groups of sub-keys by the encryption key according to a preset rule;
performing MD5 processing on the obtained subkeys to obtain processed subkeys; wherein the number of subkeys is equal to the number of data blocks; carrying out multi-layer encryption processing on the split data blocks through the processing sub-secret key to generate an information encryption identification code and a layer 1 secret key; and (5) the information encryption identification code and the layer 1 key are subjected to time stamp fusion to form an encryption ciphertext.
Further, the server is used for analyzing received data through a self-written model algorithm input by a user terminal after decrypting the received data, judging whether the corresponding data is abnormal or not, and providing a data early warning notice for the user; the model algorithm is written for users by oneself and comprises a safety range of various data, and is used for judging whether the data are abnormal or not; the safety range is preset by a user.
Further, the specific verification steps of the signal verification module are as follows:
the signal verification module sends a verification configuration message to the edge node according to a preset verification period, wherein the verification configuration message comprises a first signal quality threshold; in response to receiving the verification configuration message sent by the signal verification module, the edge node sends a second synchronization signal to the signal verification module;
determining, by the signal verification module, a signal quality of the second synchronization signal; comparing the signal quality of the second synchronous signal with the first signal quality threshold to obtain a corresponding quality difference Zc;
performing time difference calculation on the time when the signal verification module sends the verification configuration message and the time when the signal verification module monitors the second synchronous signal again to obtain response time XT;
calculating a signal loss index SH of the edge node by using a formula SH=Zc×g4+XT×g5, wherein g4 and g5 are coefficient factors; establishing a graph of the change of the signal loss index SH with time;
the time required for the signal loss index SH to reach the preset loss threshold G1 is counted as the communication limit time Gn; wherein G1 is a preset value; acquiring the communication limit duration of each operation of the edge node, taking the value of Gn and the previous X1 group communication limit duration thereof, and marking the values as GS1, GS2, … and GSn in sequence according to the time sequence; when GSm is less than or equal to GS (m-1), marking the GS (m-1) with a first limit value;
counting the occurrence number of the first limit value as limit frequency P1; when GSm is less than or equal to GS (m-1), obtaining a difference value between GS (m-1) and GSm and summing to obtain a limit difference value PX; the limiting deviation factor GF is calculated using the formula gf=p1×k3+px×k4, where k3, k4 are factor coefficients.
Further, each layer of encryption processing of the encryption module is a group of processing subkeys to encrypt one of the data blocks, which are not overlapped with each other.
Further, the layer 1 key is used for identifying the layer 1 encryption information in the information encryption identification code and generating a layer 2 key, the layer 2 key is used for identifying the layer 2 encryption information in the information encryption identification code and generating a layer 3 key, and the like.
Compared with the prior art, the invention has the beneficial effects that:
1. the data acquisition module is used for acquiring equipment data received by a plurality of edge nodes and carrying out data encapsulation processing on the acquired equipment data; the encapsulated data is subjected to protocol conversion through a protocol conversion module, and is converted into a data protocol with a uniform fixed format; carrying out algorithm analysis and processing on the converted data protocol through a data analysis module, packaging the analyzed and processed data into a data packet, and transmitting the data packet to a server through a 5G communication module; the server is used for decrypting the received data, analyzing the received data through a self-written model algorithm input by the user terminal, and judging whether the corresponding data is abnormal or not; the parallel time acquisition of the data of the different edge nodes of the multichannel is realized, the real-time performance and timeliness of the edge nodes are improved, meanwhile, the data correlation analysis is carried out on the data of the different edge nodes, a reference basis is provided for the subsequent data processing analysis and early warning, and the data processing efficiency is improved;
2. the characteristic acquisition module is used for acquiring characteristic information of equipment data received by each edge node, transmitting the acquired characteristic information to the node analysis module for analysis of the fortune optimizing coefficient YS, and classifying the edge nodes according to the fortune optimizing coefficient YS; if the data packet is a core node, before the data analysis module transmits the data packet after analysis processing to the server, the data encryption module is utilized to encrypt and transmit the data packet, so that the data transmission safety is improved; the signal verification module is used for verifying the communication state of the edge node in real time, and judging that the edge node is abnormal in communication if the limit deviation coefficient GF is greater than the deviation coefficient threshold value, and generating a communication abnormal signal; in order to remind the manager in time to carry out maintenance to this edge node, reduce the influence of interference signal, guarantee the accuracy of data monitoring.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of an industrial control system based on edge computing according to the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, an industrial control system based on edge calculation comprises a data acquisition module, a protocol conversion module, an FPGA master control, a data analysis module, a 5G communication module, a server, a data encryption module, a feature acquisition module, a node analysis module and a signal verification module;
the data acquisition module is used for acquiring equipment data received by a plurality of edge nodes and carrying out data encapsulation processing on the acquired equipment data; the encapsulated data is subjected to protocol conversion through a protocol conversion module, and is converted into a data protocol with a uniform fixed format;
the FPGA main control is in control connection with the protocol conversion module and is used for acquiring the data protocol converted by the protocol conversion module, carrying out algorithm analysis and processing on the converted data protocol through the data analysis module, packaging the analyzed and processed data into a data packet, and transmitting the data packet to the server through the 5G communication module; wherein the algorithm analysis and processing is performed to reject significantly erroneous and missing data;
in the embodiment, the invention realizes the simultaneous acquisition of the data of different edge nodes in multiple channels, improves the instantaneity and timeliness of the edge nodes, simultaneously carries out data correlation analysis on the data of the different edge nodes, and provides a reference basis for subsequent data processing analysis and early warning;
in this embodiment, before the data analysis module transmits the data packet after analysis processing to the server, the data analysis module is further configured to obtain an edge node corresponding to the data packet, and if the edge node is a core node, encrypt and transmit the data packet by using the data encryption module;
the data encryption module is used for carrying out distributed multi-layer encryption on the received data packet and transmitting the encrypted ciphertext to the server; the specific encryption steps are as follows:
randomly splitting the data packet into a plurality of data blocks; generating an AES128 encryption key, and generating a plurality of groups of sub-keys by the encryption key according to a preset rule; wherein the number of subkeys is equal to the number of data blocks;
performing MD5 processing on the obtained subkeys to obtain processed subkeys; carrying out multi-layer encryption processing on the split data blocks through the processing sub-secret key to generate an information encryption identification code and a layer 1 secret key; the information encryption identification code and the layer 1 secret key are subjected to time stamp fusion to form an encryption ciphertext;
each layer of encryption processing of the encryption module is a group of processing subkeys for carrying out encryption processing on one data block, and the data blocks are not overlapped with each other;
the layer 1 secret key is used for identifying the layer 1 encryption information in the information encryption identification code and generating a layer 2 secret key, the layer 2 secret key is used for identifying the layer 2 encryption information in the information encryption identification code and generating a layer 3 secret key, and the like;
the server is used for decrypting the received data, analyzing the received data through a self-written model algorithm input by the user terminal, judging whether the corresponding data is abnormal or not, and providing a data early warning notice for the user; the model algorithm is written for users in a self-running way and comprises a safety range of various data, and is used for judging whether the data are abnormal or not; the safety range is preset by a user;
the characteristic acquisition module is used for acquiring characteristic information of the equipment data received by each edge node and transmitting the acquired characteristic information to the node analysis module; the characteristic information comprises equipment data type, equipment data quantity, equipment data transmission distance and equipment data transmission bandwidth;
the node analysis module is used for carrying out the analysis of the operation optimization coefficient YS on each edge node according to the received characteristic information, and classifying the edge nodes according to the operation optimization coefficient YS, and specifically comprises the following steps:
aiming at a certain edge node, acquiring characteristic information of equipment data received by the edge node; counting the total operation times of the edge nodes as C1 in a preset time period;
sequentially marking corresponding equipment data quantity, equipment data transmission distance and equipment data transmission bandwidth in the characteristic information as Li, di and Wi; acquiring equipment data types in the characteristic information, setting a corresponding preset type value for each data type, and matching the equipment data types with all the data types to acquire the corresponding preset type value and marking the corresponding preset type value as CYi;
the calculation value Yi required for the edge node to process each device data is calculated using the formula yi= (CYi ×a1+li×a2+di×a3)/(wi×a4); wherein a1, a2, a3 and a4 are coefficient factors;
comparing the operation value Yi with a preset operation threshold value; counting the times of Yi > a preset operation threshold value as P1; when Yi is larger than a preset operation threshold, obtaining a difference value of Yi and the preset operation threshold and summing to obtain an supercomputed total value CZ; calculating to obtain an optimal coefficient YS by using a formula YS= (P1×g1+CZ×g2)/C1, wherein g1 and g2 are preset coefficient factors;
comparing the running coefficient YS with a set value; if the running and optimizing coefficient YS is larger than the set value, marking the corresponding edge node as a core node; otherwise, marking the corresponding edge node as a common node;
in an alternative embodiment, in order to reduce the influence of interference signals, the accuracy of data monitoring is ensured; the edge node is connected with a signal verification module, and the signal verification module is used for verifying the communication state of the edge node in real time; the specific verification steps are as follows:
the signal verification module sends a verification configuration message to the edge node according to a preset verification period, wherein the verification configuration message comprises a first signal quality threshold; in response to receiving the verification configuration message sent by the signal verification module, the edge node sends a second synchronization signal to the signal verification module;
determining, by the signal verification module, a signal quality of the second synchronization signal in response to monitoring the second synchronization signal; comparing the signal quality of the second synchronization signal with the first signal quality threshold to obtain a corresponding quality difference Zc, wherein it will be appreciated by those skilled in the art that any metric known in the art can be used to characterize the signal quality, e.g. RSRQ, RSRP, RSSI, etc.; the quality difference here may reflect the attenuation of the signal during transmission;
performing time difference calculation on the time when the signal verification module sends the verification configuration message and the time when the signal verification module monitors the second synchronous signal again to obtain response time XT; calculating a signal loss index SH of the edge node by using a formula SH=Zc×g4+XT×g5, wherein g4 and g5 are coefficient factors;
establishing a graph of the change of the signal loss index SH along with time, and counting the time required for the signal loss index SH to reach a preset loss threshold G1 as the communication limit time Gn; wherein G1 is a preset value;
acquiring the communication limit duration of each operation of the edge node, taking the value of Gn and the previous X1 group communication limit duration thereof, and marking the values as GS1, GS2, … and GSn in sequence according to the time sequence;
when GSm is less than or equal to GS (m-1), marking the GS (m-1) with a first limit value; counting the occurrence number of the first limit value as limit frequency P1; when GSm is less than or equal to GS (m-1), obtaining a difference value between GS (m-1) and GSm and summing to obtain a limit difference value PX; calculating a limit deviation coefficient GF by using a formula GF=P1×k3+PX×k4, wherein k3 and k4 are coefficient factors;
comparing the limiting departure coefficient GF with a departure coefficient threshold; if GF is larger than the deviation coefficient threshold value, judging that the edge node is abnormal in communication, and generating a communication abnormal signal;
the signal verification module is used for uploading the communication abnormal signal to the server so as to remind a manager of timely repairing and maintaining the edge node, and data monitoring efficiency is improved.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the industrial control system based on edge calculation is used for acquiring equipment data received by a plurality of edge nodes and carrying out data encapsulation processing on the acquired equipment data when the industrial control system works; the encapsulated data is subjected to protocol conversion through a protocol conversion module, and is converted into a data protocol with a uniform fixed format; carrying out algorithm analysis and processing on the converted data protocol through a data analysis module, packaging the analyzed and processed data into a data packet, and transmitting the data packet to a server through a 5G communication module; the server is used for decrypting the received data, analyzing the received data through a self-written model algorithm input by the user terminal, and judging whether the corresponding data is abnormal or not; the parallel time acquisition of the data of the different edge nodes of the multichannel is realized, the real-time performance and timeliness of the edge nodes are improved, meanwhile, the data correlation analysis is carried out on the data of the different edge nodes, a reference basis is provided for the subsequent data processing analysis and early warning, and the data processing efficiency is improved;
the characteristic acquisition module is used for acquiring characteristic information of the equipment data received by each edge node and transmitting the acquired characteristic information to the node analysis module; the node analysis module is used for carrying out analysis on the optimizing coefficient YS of each edge node according to the received characteristic information and classifying the edge nodes according to the optimizing coefficient YS; if the data packet is a core node, before the data analysis module transmits the data packet after analysis processing to the server, the data encryption module is utilized to encrypt and transmit the data packet, so that the data transmission safety is improved; the signal verification module is used for verifying the communication state of the edge node in real time, and judging that the edge node is abnormal in communication if the limit deviation coefficient GF is greater than the deviation coefficient threshold value, and generating a communication abnormal signal; in order to remind the manager in time to carry out maintenance to this edge node, reduce the influence of interference signal, guarantee the accuracy of data monitoring.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (7)
1. The industrial control system based on the edge calculation is characterized by comprising a data acquisition module, a protocol conversion module, an FPGA main control module, a data analysis module, a data encryption module, a characteristic acquisition module, a node analysis module and a signal verification module;
the data acquisition module is used for acquiring equipment data received by a plurality of edge nodes and carrying out data encapsulation processing on the acquired equipment data; the encapsulated data is subjected to protocol conversion through a protocol conversion module, and is converted into a data protocol with a uniform fixed format;
the FPGA main control is in control connection with the protocol conversion module and is used for acquiring the data protocol converted by the protocol conversion module, carrying out algorithm analysis and processing on the converted data protocol through the data analysis module, packaging the analyzed and processed data into a data packet, and transmitting the data packet to the server through the 5G communication module;
the characteristic acquisition module is used for acquiring characteristic information of the equipment data received by each edge node and transmitting the acquired characteristic information to the node analysis module for analysis of the optimizing coefficient YS;
the node analysis module is used for classifying the edge nodes according to the optimal coefficient YS, and if the optimal coefficient YS is larger than a set value, the corresponding edge nodes are marked as core nodes;
before the data analysis module transmits the data packet after analysis to the server, the data analysis module is further used for acquiring an edge node corresponding to the data packet, and if the edge node is a core node, the data packet is encrypted and transmitted by the data encryption module;
the signal verification module is used for verifying the communication state of the edge node in real time, and calculating to obtain a limit deviation coefficient GF; if GF is larger than the deviation coefficient threshold value, judging that the edge node is abnormal in communication, and generating a communication abnormal signal; to alert the manager to repair and maintain the edge node.
2. The industrial control system based on edge computing according to claim 1, wherein the specific analysis steps of the node analysis module are:
aiming at a certain edge node, acquiring characteristic information of equipment data received by the edge node; counting the total operation times of the edge nodes as C1 in a preset time period;
sequentially marking corresponding equipment data quantity, equipment data transmission distance and equipment data transmission bandwidth in the characteristic information as Li, di and Wi; acquiring equipment data types in the characteristic information, setting a corresponding preset type value for each data type, and matching the equipment data types with all the data types to acquire the corresponding preset type value and marking the corresponding preset type value as CYi;
the calculation value Yi required for the edge node to process each device data is calculated using the formula yi= (CYi ×a1+li×a2+di×a3)/(wi×a4); wherein a1, a2, a3 and a4 are coefficient factors;
comparing the operation value Yi with a preset operation threshold value; counting the times of Yi > a preset operation threshold value as P1; when Yi is larger than a preset operation threshold, obtaining a difference value of Yi and the preset operation threshold and summing to obtain an supercomputed total value CZ; and calculating to obtain the running and optimizing coefficient YS by using a formula YS= (P1×g1+CZ×g2)/C1, wherein g1 and g2 are preset coefficient factors.
3. The industrial control system based on edge computing according to claim 1, wherein the data encryption module is configured to perform distributed multi-layer encryption on the received data packet and transmit the encrypted ciphertext to the server; the specific encryption steps are as follows:
randomly splitting the data packet into a plurality of data blocks; generating an AES128 encryption key, and generating a plurality of groups of sub-keys by the encryption key according to a preset rule;
performing MD5 processing on the obtained subkeys to obtain processed subkeys; wherein the number of subkeys is equal to the number of data blocks; carrying out multi-layer encryption processing on the split data blocks through the processing sub-secret key to generate an information encryption identification code and a layer 1 secret key; and (5) the information encryption identification code and the layer 1 key are subjected to time stamp fusion to form an encryption ciphertext.
4. The industrial control system based on edge calculation according to claim 1, wherein the server is configured to decrypt the received data, analyze the decrypted data through a self-written model algorithm input by a user terminal, determine whether the corresponding data is abnormal, and provide a data early warning notification for the user; the model algorithm is written for users by oneself and comprises a safety range of various data, and is used for judging whether the data are abnormal or not; the safety range is preset by a user.
5. The industrial control system based on edge computing according to claim 1, wherein the specific verification steps of the signal verification module are:
the signal verification module sends a verification configuration message to the edge node according to a preset verification period, wherein the verification configuration message comprises a first signal quality threshold; in response to receiving the verification configuration message sent by the signal verification module, the edge node sends a second synchronization signal to the signal verification module;
determining, by the signal verification module, a signal quality of the second synchronization signal; comparing the signal quality of the second synchronous signal with the first signal quality threshold to obtain a corresponding quality difference Zc;
performing time difference calculation on the time when the signal verification module sends the verification configuration message and the time when the signal verification module monitors the second synchronous signal again to obtain response time XT;
calculating a signal loss index SH of the edge node by using a formula SH=Zc×g4+XT×g5, wherein g4 and g5 are coefficient factors; establishing a graph of the change of the signal loss index SH with time;
the time required for the signal loss index SH to reach the preset loss threshold G1 is counted as the communication limit time Gn; wherein G1 is a preset value; acquiring the communication limit duration of each operation of the edge node, taking the value of Gn and the previous X1 group communication limit duration thereof, and marking the values as GS1, GS2, … and GSn in sequence according to the time sequence; when GSm is less than or equal to GS (m-1), marking the GS (m-1) with a first limit value;
counting the occurrence number of the first limit value as limit frequency P1; when GSm is less than or equal to GS (m-1), obtaining a difference value between GS (m-1) and GSm and summing to obtain a limit difference value PX; the limiting deviation factor GF is calculated using the formula gf=p1×k3+px×k4, where k3, k4 are factor coefficients.
6. An industrial control system based on edge computation according to claim 3, wherein each layer of encryption processing of the encryption module is a set of processing subkeys for encrypting one of the data blocks, without overlapping each other.
7. An industrial control system based on edge computation according to claim 3, wherein the layer 1 key is used to identify layer 1 encryption information in the information encryption identifier and to generate a layer 2 key, wherein the layer 2 key is used to identify layer 2 encryption information in the information encryption identifier and to generate a layer 3 key, and so on.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310422178.4A CN116540597A (en) | 2023-04-19 | 2023-04-19 | Industrial control system based on edge calculation |
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| CN117518939A (en) * | 2023-12-06 | 2024-02-06 | 广州市顺风船舶服务有限公司 | Industrial control system based on big data |
| CN117891614A (en) * | 2024-03-14 | 2024-04-16 | 山西泓禾惜贤科贸有限公司 | Big data analysis platform based on cloud service |
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| CN117891614B (en) * | 2024-03-14 | 2024-05-14 | 山西泓禾惜贤科贸有限公司 | Big data analysis platform based on cloud service |
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