CN113179316B - Cloud edge-side cooperative computing system and method based on containerization design - Google Patents

Cloud edge-side cooperative computing system and method based on containerization design Download PDF

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CN113179316B
CN113179316B CN202110453105.2A CN202110453105A CN113179316B CN 113179316 B CN113179316 B CN 113179316B CN 202110453105 A CN202110453105 A CN 202110453105A CN 113179316 B CN113179316 B CN 113179316B
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data
service
edge
layer
services
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CN113179316A (en
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宋虎
冯落落
李锐
王建华
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Shandong New Generation Information Industry Technology Research Institute Co Ltd
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Shandong New Generation Information Industry Technology Research Institute Co Ltd
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network arrangements or protocols for supporting network services or applications
    • H04L67/34Network arrangements or protocols for supporting network services or applications involving the movement of software or configuration parameters 
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/08Configuration management of networks or network elements
    • H04L41/0803Configuration setting

Abstract

The invention provides a cloud edge-side cooperative computing method based on containerization design, which mainly comprises four large system services of a core layer, an application layer, an equipment layer and a basic system layer, and particularly relates to services of a registration center, data storage, data export, data storage, equipment service, a rule engine, system monitoring and the like. The invention provides a middleware service for performing data interaction between physical sensing equipment and an information system. The cloud edge cooperative computing method based on the containerization design redefines boundaries among edge equipment, edge servers and cloud servers flexibly, provides services such as a registration center, data storage, data export, data storage, a rule engine and system monitoring and the like based on the containerization service design method, can be deployed flexibly, and uses different deployment schemes according to actual application scene requirements.

Description

Cloud edge-side cooperative computing system and method based on containerization design
Technical Field
The invention relates to a cloud edge-side cooperative computing system and method based on containerization design, and belongs to the technical field of data storage.
Background
Data generated by edge equipment is exponentially increased along with popularization and application of 5G communication technology, the data is generated, cached and transmitted to a cloud end by an equipment end, and the cloud end returns a most data processing result to the edge end and drives the equipment end to make corresponding actions. The mass data transmission has ultrahigh requirements on network bandwidth, and simultaneously faces huge loan cost, and the fact that the edge equipment has certain data conversion and data processing capacity becomes more important. The edge terminal equipment is complex and diverse, and the data generated by the edge terminal equipment cannot be coordinated and unified are also diverse, which causes great problems for data processing, and the existing cloud edge terminal cooperative computing method has poor compatibility and expansibility on the bottom layer edge terminal equipment.
Disclosure of Invention
The invention aims to provide a cloud edge-side cooperative computing system and method based on containerization design, which not only realize interconnection and intercommunication of equipment, but also are flexible and convenient to deploy.
In order to achieve the purpose, the invention is realized by the following technical scheme:
a cloud edge-side collaborative computing system based on containerization design comprises four large system services of a core layer, an application layer, a device layer and a basic system layer;
the core service layer is used as a medium for connecting the edge device measurement and the cloud measurement, comprises a data center and stores various data uploaded by the edge device; the registration center is used for carrying out correlation configuration on all the micro-services to provide initialization configuration information and is provided with a service heartbeat monitoring mechanism to monitor the survival state of each micro-service; and the control center is used for realizing the action request of the edge measurement or the cloud measurement on the edge equipment and controlling the edge equipment to finish a certain action. (ii) a
The device layer is used for accessing the sensors to the whole system and connecting concrete physical devices and the system, the transaction comprises but is not limited to one or more sensors, actuators and robot IoT objects, and the device layer can abstract and convert data uploaded by the accessed physical devices into a data structure for the system by means of device services;
the basic service layer is mainly used for providing basic support for each micro-service, specifically, log collection is carried out, logs generated by the operation of each micro-service are collected and monitored in a unified mode, and the basic service layer is mainly used for aggregating each service log and establishing an alarm mechanism to report related service states in time; system management, monitoring service operation index, for starting/stopping/restarting each service;
the application layer is used for processing, converting, analyzing and exporting the data uploaded by the edge equipment to a fixed address, the rule engine enables the edge measurement simple data analysis capability, and the average value and the maximum value in a time window can be calculated by analyzing the data uploaded by the edge equipment through SQL-like and statement; and data export, namely exporting the data of the edge equipment to a certain fixed address after processing such as filtering, format conversion, compression, encryption and the like, and directly writing the data into a non-relational database by supporting MQTT and HTTP protocol export data.
Preferably, the device service contained in the device service layer can access to devices supporting Modbus, MQTT and ONVIF communication protocols.
A cloud edge-side cooperative computing method based on containerization design comprises the following steps:
the method comprises the following steps: deploying a core layer and a base layer, wherein services can be selectively deployed to a cloud end or an edge end gateway or an edge end server, and the services comprise a data center, a registration center, a control center service, log collection and system management; the left and right micro services are registered in a registration center and provide initial configuration information, after the registration is completed, the running state of each micro service is monitored, logs are aggregated and output to a unified interface, and the system management service provides occupation information of each service such as a CPU (central processing unit), a memory and the like for a user to monitor;
step two: the device layer is deployed, the layer is generally deployed to an edge gateway for connecting edge end devices, devices supporting various communication protocols are provided for accessing data, device services perform abstract conversion on device data for a core layer and an application layer to use, and the core layer data center stores the data into a local database without persistence;
step three: the method comprises the steps of deploying application layer services, wherein the layer services are mainly selectively deployed according to field requirements, and the layer services can be separately deployed without mutual dependency; when the edge measurement is required to have certain data analysis capability in the field, a rule engine can be selected to be deployed, and the service can complete the data analysis requirement by writing in SQL-like statements; the service can be selected when data export is needed to a certain fixed address on site, and data format conversion can be performed when the data export is carried out.
The invention has the advantages that: the invention provides a middleware service for performing data interaction between physical sensing equipment and an information system. The cloud edge collaborative computing method based on the containerization design redefines boundaries among the edge equipment, the edge server and the cloud server flexibly, provides services such as a registry, data storage, data export, data storage, a rule engine and system monitoring and the like based on the design method of the containerization service, can be deployed flexibly, and uses different deployment schemes according to the requirements of practical application scenes.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
FIG. 1 is a schematic diagram of an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
A cloud edge-side collaborative computing system based on containerization design comprises four large system services of a core layer, an application layer, a device layer and a basic system layer;
the core service layer is used as a medium for connecting the edge device measurement and the cloud measurement, comprises a data center and stores various data uploaded by the edge device; the registration center is used for carrying out correlation configuration on all the micro-services to provide initialization configuration information and is provided with a service heartbeat monitoring mechanism to monitor the survival state of each micro-service; and the control center is used for realizing the action request of the edge measurement or the cloud measurement on the edge equipment and controlling the edge equipment to finish a certain action. (ii) a
The device layer is used for accessing the sensors to the whole system and connecting concrete physical devices and the system, the transaction comprises but is not limited to one or more sensors, actuators and robot IoT objects, and the device layer can abstract and convert data uploaded by the accessed physical devices into a data structure for the system by means of device services;
the basic service layer is mainly used for providing basic support for each micro-service, specifically, log collection is carried out, logs generated by the operation of each micro-service are collected and monitored in a unified mode, and the basic service layer is mainly used for aggregating each service log and establishing an alarm mechanism to report related service states in time; the system management is used for monitoring service operation indexes and starting/stopping/restarting each service;
the application layer is used for processing, converting, analyzing and exporting the data uploaded by the edge equipment to a fixed address, the rule engine enables the edge measurement simple data analysis capability, and the average value and the maximum value in a time window can be calculated by analyzing the data uploaded by the edge equipment through SQL-like and statement; and data export, namely exporting the data of the edge equipment to a certain fixed address after processing such as filtering, format conversion, compression, encryption and the like, and directly writing the data into a non-relational database by supporting MQTT and HTTP protocol export data. The equipment service contained in the equipment service layer can be accessed to the equipment supporting the Modbus, MQTT and ONVIF communication protocols.
A cloud edge-side cooperative computing method based on containerization design comprises the following steps:
the method comprises the following steps: deploying a core layer and a base layer, wherein services can be selectively deployed to a cloud end or an edge end gateway or an edge end server, and the services comprise a data center, a registration center, a control center service, log collection and system management; the left and right micro services are registered in a registration center and provide initial configuration information, after the registration is completed, the running state of each micro service is monitored, logs are aggregated and output to a unified interface, and the system management service provides occupation information of each service such as a CPU (central processing unit), a memory and the like for a user to monitor;
step two: the device layer is deployed, the layer is generally deployed to an edge gateway for connecting edge end devices, devices supporting various communication protocols are provided for accessing data, device services perform abstract conversion on device data for a core layer and an application layer to use, and the core layer data center stores the data into a local database without persistence;
step three: the method comprises the steps of deploying application layer services, wherein the layer services are mainly selected to be deployed according to field requirements, and the layer services can be separately deployed without mutual dependency; when the edge measurement is required to have certain data analysis capability in the field, a rule engine can be selected to be deployed, and the service can complete the data analysis requirement by writing in SQL-like statements; the service can be selected when the field needs to export data to a certain fixed address, and data format conversion can be performed when the data is exported.

Claims (3)

1. A cloud edge-side cooperative computing system based on containerization design is characterized by comprising four large system services of a core layer, an application layer, a device layer and a basic system layer;
the core service layer serves as an intermediary for connecting the edge device side and the cloud end side, and comprises a data center for storing various data uploaded by the edge device side; the registration center is used for carrying out correlation configuration on all the micro-services to provide initialization configuration information and is provided with a service heartbeat monitoring mechanism to monitor the survival state of each micro-service; the control center is used for realizing an action request of the edge side or the cloud side to the edge side equipment and controlling the edge side equipment to complete a certain action;
the device layer is used for accessing the sensors to the whole system and connecting concrete physical devices and the system, the device layer comprises but is not limited to one or more sensors, actuators and robot IoT objects, and the device layer can abstract and convert data uploaded by the accessed physical devices into a data structure for the system by means of device services;
the basic service layer is used for providing basic support for each micro service, and specifically relates to the following steps: collecting logs, namely collecting and monitoring logs generated by the operation of each micro service in a unified manner, and aggregating the service logs and establishing an alarm mechanism to report related service states in time; the system management is used for monitoring service operation indexes and starting/stopping/restarting each service;
the application layer is used for processing, converting, analyzing and exporting the data uploaded by the edge equipment to a fixed address, the rule engine enables the simple data analysis capability of the edge side, and the average value and the maximum value in a time window can be calculated by analyzing the data uploaded by the edge equipment through SQL-like and statement; and data export, namely exporting data of the edge equipment to a certain fixed address after filtering, format conversion, compression and encryption processing, and directly writing the data into a non-relational database by supporting MQTT and HTTP protocol export data.
2. The cloud edge cooperative computing system based on containerization design of claim 1, wherein the device services included in the device service layer have access to devices supporting Modbus, MQTT, ONVIF communication protocols.
3. A cloud-edge collaborative computing method based on containerization design according to any one of claims 1-2, comprising the steps of:
the method comprises the following steps: deploying a core layer and a base layer, wherein services can be selectively deployed to a cloud end or an edge end gateway or an edge end server, and the services comprise a data center, a registration center, a control center service, log collection and system management; the left and right micro services are registered in a registration center and provide initial configuration information, after the registration is completed, the running state of each micro service is monitored, logs are aggregated and output to a unified interface, and system management service provides information of occupation of CPUs and memories of each service for a user to monitor;
step two: the device layer is deployed to the edge gateway and used for connecting edge end devices, devices supporting various communication protocols are provided for accessing data, device services perform abstract conversion on device data for the core layer and the application layer to use, and the core layer data center stores the data into a local database without persistence in the process;
step three: the method comprises the steps of deploying application layer services, wherein the layer services are selectively deployed according to field requirements, and the layer services can be separately deployed without mutual dependency; when the edge side is required to have data analysis capability on site, a rule engine is selected to be deployed, and the service completes the data analysis requirement by writing in SQL-like statements; and when the field needs to export data to a certain fixed address, the service is selected, and when the data is exported, data format conversion is carried out.
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