CN114513390B - Intelligent gateway of Internet of things based on edge calculation and working method thereof - Google Patents
Intelligent gateway of Internet of things based on edge calculation and working method thereof Download PDFInfo
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- CN114513390B CN114513390B CN202210037141.5A CN202210037141A CN114513390B CN 114513390 B CN114513390 B CN 114513390B CN 202210037141 A CN202210037141 A CN 202210037141A CN 114513390 B CN114513390 B CN 114513390B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/66—Arrangements for connecting between networks having differing types of switching systems, e.g. gateways
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/211—Schema design and management
- G06F16/213—Schema design and management with details for schema evolution support
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/258—Data format conversion from or to a database
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
- H04L63/101—Access control lists [ACL]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/04—Protocols for data compression, e.g. ROHC
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/18—Multiprotocol handlers, e.g. single devices capable of handling multiple protocols
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/22—Parsing or analysis of headers
Abstract
The invention discloses an intelligent gateway of the Internet of things based on edge calculation and a working method thereof, and the intelligent gateway is applied to a remote system of the Internet of things, and comprises the following steps: the intelligent gateway of the Internet of things receives, converts and compresses/decompresses real-time data communicated with the gateway in the Internet of things system; and the edge gateway monitors the state of the edge terminal equipment which is registered and connected and controls the equipment. Based on dictionary compression thought, the invention adopts a naive Bayes classifier and a Huffman principle to realize the self-adaptive lossless compression of the edge terminal data; based on fuzzy control, the efficient management and control of the edge terminal equipment are realized by adopting a knowledge distillation and transfer learning mode.
Description
Technical Field
The invention belongs to the technical field of the Internet of things, in particular to the field of edge control of the Internet of things, and particularly relates to an intelligent gateway of the Internet of things based on edge calculation and a working method thereof.
Background
Along with the development of society, more and more intelligent electrical appliances enter people's life, a large amount of internet of things equipment that bring are inserted from this for internet of things data transmission and communication pressure greatly increase, have presented the challenge to the real-time of internet of things equipment data.
In a traditional cloud computing architecture, data is often provided by edge-side internet of things equipment, and a cloud terminal processes the data and issues a control instruction to achieve intelligent management and control of the edge-side internet of things equipment. However, this approach requires better network communication, and once the network fluctuates, the control effect is compromised. And a large amount of sensor data is clouded, so that the phenomena of bandwidth waste and data blocking are often caused, and the control effect is not economic and influenced.
Disclosure of Invention
The invention aims to: in order to solve the defects in the prior art, the invention provides the intelligent gateway of the Internet of things based on edge calculation, which is used for preprocessing real-time data of edge side Internet of things equipment, realizing uniform data format, compressing data by using dictionary compression, reducing data transmission and reducing bandwidth occupation. Meanwhile, the edge gateway manages and controls the connected edge Internet of things equipment, sets the equipment connection white list, and ensures safety. And performing edge cloud cooperation by utilizing a fuzzy control table and a transfer learning mode, and operating a cloud training control method in an intelligent gateway of the Internet of things to realize nearby service and reduce control response time delay.
The technical scheme is as follows: an intelligent gateway of the Internet of things based on edge calculation comprises three parts, namely an edge calculation thread, an MQTT client and a MySQL database; wherein:
the edge computing thread comprises three parallel programs, namely an edge control thread, a protocol analysis thread and a data compression thread;
the MQTT client comprises two parts, namely data forwarding and instruction issuing, wherein the data forwarding forwards the compressed real-time data to an Internet of things cloud server to realize data reporting; the instruction issuing comprises receiving a cloud control instruction, a compression dictionary and a fuzzy control table;
the MySQL database realizes a data storage function, stores a fuzzy control table, connects real-time data with equipment to a white list, and cooperates with an edge control thread to realize efficient management and control of edge side equipment.
As an optimization: the intelligent gateway of the Internet of things is developed based on raspberry group CM4 and consists of two COM ports supporting Modbus protocol, a BCM43438WiFi module, a gigabit Ethernet port I and a 16GB SD card, so that the calculation force requirement, hardware communication and data storage are ensured.
As an optimization: the intelligent gateway of the Internet of things is developed based on ubuntu20.04, a python running environment and a MySQL database are internally installed, and multithreading edge calculation and MQTT communication are achieved by calling a python library function, so that the intelligent gateway function is completed.
As an optimization: the protocol analysis thread accesses the edge device supporting the TCP/IP protocol through WiFi, such as: the singlechip and the PLC are connected with the other edge controllers; acquiring parameters of a sensor in the edge equipment by using a Modbus field bus technology; analyzing the collected data according to a contracted message format, converting the analyzed data into a JSON format, and storing the JSON format into a MySQL database to finish real-time data conversion.
As an optimization: the data compression thread realizes data compression and decompression through a compression dictionary; the compression dictionary is stored in a MySQL database, self-adaptively updated and synchronized with the cloud server of the Internet of things in real time; the decompressed and compressed data is stored as historical data in a MySQL database.
As an optimization: in the data compression thread, the compression dictionary is generated according to the Huffman coding principle through the edge equipment data classified by the naive Bayesian classifier, and when the compression rate of the edge data compression rate does not reach a set value, the intelligent gateway carries out real-time dictionary updating.
As an optimization: in the data compression thread, the compression dictionary is updated rapidly in a side cloud cooperative mode, the cloud server of the Internet of things carries out edge equipment judgment according to real-time data of the cloud uploaded by the intelligent gateway, and the similar equipment compression dictionary is searched through big data and synchronized to the intelligent gateway to serve as an initial compression dictionary, so that the compression dictionary generation efficiency is accelerated.
As an optimization: the edge control thread comprises an edge equipment management function, the intelligent gateway of the Internet of things verifies the connection edge side connection equipment, and the equipment meeting the connection requirement is connected, so that the safety is guaranteed.
As an optimization: the edge control thread adopts a fuzzy control thought, and intelligent and quick response of intelligent gateway edge control is realized by means of knowledge distillation and transfer learning, so that the effect of efficient control of edge equipment is achieved; the method comprises the following steps:
the method comprises the steps that an edge device management and control mode is adopted, an Internet of things cloud server calculates a fuzzy control table according to big data, simplifies compression of the fuzzy control table and sends the fuzzy control table to an intelligent gateway, and the intelligent gateway adaptively optimizes the fuzzy control table according to real-time data collected by the edge device;
and a transfer learning mode is adopted to quickly establish a fuzzy control table, and when the cloud server of the Internet of things fails to calculate the fuzzy control table, the fuzzy control table is generated under the similar task requirement to carry out control optimization.
An operating method of an intelligent gateway of the internet of things based on edge calculation comprises the following steps:
s1, protocol analysis process: the method comprises the steps that a management and control edge device supporting a TCP/IP protocol is accessed through WiFi, a Modbus field bus technology collects parameters of a sensor in the edge device, collected data are analyzed according to a agreed message format, and the collected data are converted into a JSON format;
s2, data compression process: the intelligent gateway of the Internet of things carries out dictionary compression on the real-time data according to the compression dictionary, so that the communication data volume is reduced;
s2-1, searching a compression dictionary in a MySQL database by an intelligent gateway of the Internet of things, and if the compression dictionary does not exist, transmitting uncompressed data;
s2-2, the cloud end classifies edge equipment data according to a naive Bayes classifier, generates a data compression dictionary according to a Huffman coding principle, and synchronizes to an intelligent gateway;
s2-3, when the compression rate of the edge data compression rate does not reach a set value, the intelligent gateway updates the dictionary in real time and synchronizes the intelligent gateway with the new dictionary to the cloud server;
s3, edge control: the intelligent gateway performs intelligent management and control on the edge side equipment according to the fuzzy control table provided by the cloud server, and provides intelligent service for near-edge preparation;
s3-1, applying a fuzzy control table to the cloud by the intelligent gateway, and if the cloud server does not generate an optimal control table yet, requesting an edge control table under a similar task to be used initially by utilizing the idea of transfer learning;
s3-2, based on the knowledge distillation idea, the cloud end optimizes a fuzzy control table according to the control effect of the edge side equipment and sends the fuzzy control table to the intelligent gateway along with the new fuzzy control table;
s4, the intelligent gateway authenticates the connected edge equipment through the equipment white list in the MySQL. And setting a user name, a password, authority and MQTT topics according to different edge devices, and performing device management and security authentication.
The beneficial effects are that: the technical scheme of the invention has the following beneficial effects:
(1) According to the method, the data compression is carried out on the data of the Internet of things generated by the edge equipment through dictionary compression, so that the communication bandwidth is reduced, the network pressure is relieved, and the system safety is improved.
(2) According to the invention, intelligent management of the edge equipment is realized through the fuzzy control table, the response time of the edge equipment is shortened, and the safe and reliable operation of the equipment is ensured. The fuzzy control table accelerates the initialization and optimization speed of the control model based on transfer learning and knowledge distillation.
(3) The invention integrates Modbus technology and TCP/IP protocol, and adopts JSON format to realize data formatting at edge side, and communication between edge side devices is opened.
(4) The invention uses the MQTT protocol and realizes the positioning of the edge side equipment through the MQTT title. And carrying out fine control according to different types of equipment, and formulating a compression and control strategy.
Drawings
FIG. 1 is a schematic diagram of the overall framework of the system of the present invention;
FIG. 2 is a diagram of an architecture of the present invention applied to the Internet of things;
FIG. 3 is a flow chart of data compression in accordance with the present invention;
fig. 4 is a schematic diagram of edge cloud data compression according to the present invention.
In the figure: 1. an intelligent gateway of the Internet of things; 2. an edge calculation thread; 3. an MQTT client; 4. MySQL database; 5. an edge device; 6. the cloud server of the Internet of things; 7. the MQTT interface 8 and the data compression module; 9. an edge management and control module; 10. WiFi access; 11. modbus access; 12. and (5) a remote monitor.
Detailed Description
The following technical solutions in the embodiments of the present invention will be clearly and completely described so that those skilled in the art can better understand the advantages and features of the present invention, thereby making a clearer definition of the protection scope of the present invention. The described embodiments of the present invention are intended to be only a few, but not all embodiments of the present invention, and all other embodiments that may be made by one of ordinary skill in the art without inventive faculty are intended to be within the scope of the present invention.
Examples
Referring to fig. 1-4, the invention provides an intelligent gateway of the internet of things based on edge computing, wherein the intelligent gateway 1 of the internet of things comprises an edge computing thread 2, an MQTT client 3 and a MySQL database 4. The system is applied to an Internet of things architecture and can be divided into an MQTT interface 7, a data compression module 8, an edge management and control module 9, a WiFi access 10 and a Modbus access 11. And an edge layer is formed by the cloud server and the edge equipment 5, and the cloud cooperation is realized by the cloud server 6 of the internet of things in the cloud layer. The remote monitor 12 in the monitoring layer realizes the artificial remote control of the edge layer equipment through the cloud layer.
In this embodiment, the WiFi access 10 and the Modbus access 11 implement device authentication, which is specifically as follows: the PLC and the singlechip in the edge equipment 5 are accessed into the intelligent gateway 1 of the Internet of things supporting the TCP/IP protocol through the WiFi access 10, the temperature sensor and the humidity sensor in the edge equipment 5 are accessed into the intelligent gateway 1 of the Internet of things supporting the Modbus field bus technology through the Modbus access 11, the MySQL database 4 is accessed to perform white list verification, and the connection request of the Internet of things equipment passing the verification is requested.
In this embodiment, the data compression module 8 implements real-time data compression of the internet of things, specifically as follows: firstly, the real-time data of the edge device 5 is subjected to unified JSON processing, and different MQTT session names are given to each device to distinguish the device types. Next, dictionary compression is performed according to the compression dictionary in MySQL database 4. And if the dictionary is not compressed, transmitting the original data. Then, the internet of things cloud server 6 performs naive bayes classification according to the device type, and performs Huffman coding on the classified data to form a compression dictionary. Finally, the intelligent gateway 1 of the internet of things receives the compression dictionary and performs dictionary compression. If the expected compression rate is not reached, the compression dictionary is continuously updated.
In this embodiment, the edge management and control module 9 implements management and control of the edge device 5, specifically as follows: firstly, the intelligent gateway 1 of the internet of things performs fuzzy control on the edge device 5 according to a fuzzy control table in the MySQL database 4. And if the control table is fuzzy, sending a request to the cloud. Then, the internet of things cloud server 6 calls the fuzzy control table according to the request. If the fuzzy control table is not generated, the fuzzy control table under the similar task is called to use by utilizing the idea of transfer learning. Finally, the intelligent gateway 1 of the Internet of things receives the fuzzy control table, and optimizes the fuzzy control table by utilizing and controlling the result according to the idea of knowledge distillation. And the control effect is optimized.
In this embodiment, the MQTT interface 7 realizes data interaction between the edge device 5 and the internet of things cloud server 6. Through the MQTT communication function provided by the MQTT interface 7, real-time data of the edge equipment 5 and control commands, compression dictionaries and fuzzy control tables of the cloud server 6 of the Internet of things are reliably transmitted. The remote monitor 12 indirectly accesses the MQTT interface 7 through the connection with the cloud server 6 of the Internet of things to realize remote control.
When data compression of the Internet of things is carried out, the establishment process of the compression dictionary is specifically as follows:
(1) The internet of things cloud server 6 collects real-time data generated by the edge device 5 and stores the real-time data in the internet of things cloud server 6.
(2) Real-time data is classified according to device type by using a naive Bayesian classifier.
(3) According to the characteristics of the JSON data, key value pairs are disassembled, the original data format is kept unchanged, keys are extracted, and dictionary construction is carried out.
(4) Slicing the extracted key, counting the length and the occurrence frequency of the character, and beating the character meeting the compression requirement of the length requirement according to the occurrence frequency to form a compression dictionary.
(5) And taking part of the content of the compression dictionary as a sub-dictionary, and updating the sub-dictionary to the intelligent gateway 1 of the Internet of things for data compression. The complete dictionary is used as a main dictionary for compressing and using data in the cloud server 6 of the Internet of things.
(6) And when the compression rate does not meet the requirement, the internet of things cloud server 6 performs dictionary updating.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. An intelligent gateway of internet of things based on edge calculation, which is characterized in that: the method comprises three parts, namely an edge calculation thread, an MQTT client and a MySQL database; wherein:
the edge computing thread comprises three parallel programs, namely an edge control thread, a protocol analysis thread and a data compression thread;
the MQTT client comprises two parts, namely data forwarding and instruction issuing, wherein the data forwarding forwards the compressed real-time data to an Internet of things cloud server to realize data reporting; the instruction issuing comprises receiving a cloud control instruction, a compression dictionary and a fuzzy control table;
the MySQL database realizes a data storage function, stores a fuzzy control table, connects real-time data with equipment to a white list, and cooperates with an edge control thread to realize efficient management and control of edge side equipment;
the edge control thread comprises an edge equipment management function, the intelligent gateway of the Internet of things verifies the connection of edge side connection equipment, and the equipment meeting the connection requirement is connected, so that the safety is ensured;
the edge control thread adopts a fuzzy control thought, and intelligent and quick response of intelligent gateway edge control is realized by means of knowledge distillation and transfer learning, so that the effect of efficient control of edge equipment is achieved; the method comprises the following steps:
the method comprises the steps that an edge device management and control mode is adopted, an Internet of things cloud server calculates a fuzzy control table according to big data, simplifies compression of the fuzzy control table and sends the fuzzy control table to an intelligent gateway, and the intelligent gateway adaptively optimizes the fuzzy control table according to real-time data collected by the edge device;
and a transfer learning mode is adopted to quickly establish a fuzzy control table, and when the cloud server of the Internet of things fails to calculate the fuzzy control table, the fuzzy control table is generated under the similar task requirement to carry out control optimization.
2. The edge computing-based intelligent gateway of the internet of things of claim 1, wherein: the intelligent gateway of the Internet of things is developed based on raspberry group CM4 and consists of two COM ports supporting Modbus protocol, a BCM43438WiFi module, a gigabit Ethernet port I and a 16GB SD card, so that the calculation force requirement, hardware communication and data storage are ensured.
3. The edge computing-based intelligent gateway of the internet of things of claim 1, wherein: the intelligent gateway of the Internet of things is developed based on ubuntu20.04, a python running environment and a MySQL database are internally installed, and multithreading edge calculation and MQTT communication are achieved by calling a python library function, so that the intelligent gateway function is completed.
4. The edge computing-based intelligent gateway of the internet of things of claim 1, wherein: the protocol analysis thread accesses the edge equipment supporting the TCP/IP protocol through WiFi; acquiring parameters of a sensor in the edge equipment by using a Modbus field bus technology; analyzing the collected data according to a contracted message format, converting the analyzed data into a JSON format, and storing the JSON format into a MySQL database to finish real-time data conversion.
5. The edge computing-based intelligent gateway of the internet of things of claim 1, wherein: the data compression thread realizes data compression and decompression through a compression dictionary; the compression dictionary is stored in a MySQL database, self-adaptively updated and synchronized with the cloud server of the Internet of things in real time; the decompressed and compressed data is stored as historical data in a MySQL database.
6. The edge computing-based intelligent gateway of the internet of things of claim 5, wherein: in the data compression thread, the compression dictionary is generated according to the Huffman coding principle through the edge equipment data classified by the naive Bayesian classifier, and when the compression rate of the edge data does not reach a set value, the intelligent gateway carries out real-time dictionary updating.
7. The edge computing-based intelligent gateway of the internet of things of claim 5, wherein: in the data compression thread, the compression dictionary is updated rapidly in a side cloud cooperative mode, the cloud server of the Internet of things carries out edge equipment judgment according to real-time data of the cloud uploaded by the intelligent gateway, and the similar equipment compression dictionary is searched through big data and synchronized to the intelligent gateway to serve as an initial compression dictionary, so that the compression dictionary generation efficiency is accelerated.
8. The working method of the intelligent gateway of the internet of things based on edge calculation according to claim 1 is characterized in that: the method comprises the following steps:
s1, protocol analysis process: the method comprises the steps that a management and control edge device supporting a TCP/IP protocol is accessed through WiFi, a Modbus field bus technology collects parameters of a sensor in the edge device, collected data are analyzed according to a agreed message format, and the collected data are converted into a JSON format;
s2, data compression process: the intelligent gateway of the Internet of things carries out dictionary compression on the real-time data according to the compression dictionary, so that the communication data volume is reduced;
s2-1, searching a compression dictionary in a MySQL database by an intelligent gateway of the Internet of things, and if the compression dictionary does not exist, transmitting uncompressed data;
s2-2, the cloud end classifies edge equipment data according to a naive Bayes classifier, generates a data compression dictionary according to a Huffman coding principle, and synchronizes to an intelligent gateway;
s2-3, when the edge data compression rate does not reach a set value, the intelligent gateway performs real-time dictionary updating and synchronizes the updated dictionary to the cloud server;
s3, edge control: the intelligent gateway performs intelligent management and control on the edge side equipment according to the fuzzy control table provided by the cloud server, and provides intelligent service for near-edge preparation;
s3-1, applying a fuzzy control table to the cloud by the intelligent gateway, and if the cloud server does not generate an optimal control table yet, requesting an edge control table under a similar task to be used initially by utilizing the idea of transfer learning;
s3-2, based on the knowledge distillation idea, the cloud end optimizes a fuzzy control table according to the control effect of the edge side equipment, and updates the fuzzy control table to the intelligent gateway;
s4, the intelligent gateway authenticates the connected edge equipment through an equipment white list in MySQL; and setting a user name, a password, authority and MQTT topics according to different edge devices, and performing device management and security authentication.
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