Multi-level edge computing architecture based on cloud-edge collaboration and its implementation method

Abstract

The present invention discloses a multi-level edge computing architecture based on cloud-edge collaboration and its implementation method, wherein the multi-level edge computing architecture based on the cloud-edge system includes a core cloud data center, edge data nodes, and distribution network side and user side devices, wherein the edge data nodes collect data based on the rule of collecting data nearby and upload the collected data to the core cloud data center for data analysis and utilization of the core cloud data center, wherein the edge data nodes include regional edge computing nodes and station-level edge computing nodes; the edge data nodes and the local distribution network side and the configured power equipment on the user side, and the edge intermediate equipment together form a three-level routing structure and transmit data based on a high-speed power line carrier. The present invention can realize the integration of power-related data, effectively stimulate data value, and enhance data application innovation capabilities.

Description

Technical Field

[0001] The present invention relates to the field of power communication technology, and in particular to a multi-level edge computing system architecture based on cloud-edge collaboration and an implementation method thereof. Background Art

[0002] The construction of the power Internet of Things requires not only that the existing power Internet of Things system can achieve "one-time collection and use everywhere" to solve the problem of data sharing, but also that it must connect more objects, such as power users and their equipment, power grid companies and their equipment, power generation companies and their equipment, suppliers and their equipment, and the connection between people and things, collect richer information, support a wider range of application areas, and support the development of power grid business and emerging businesses through extensive interaction and full sharing of information. With the arrival of these "new" data, it will bring pressure and challenges to existing data centers from multiple levels such as management, technology and personnel. For example, how to uniformly manage massive amounts of new and old data, how to transform existing systems to better support data penetration, how to use Internet of Things data to create new business forms, how to develop digital products to realize data operations, etc. In short, the construction of the power Internet of Things has expanded the service boundaries of power grid companies while also placing higher requirements on their own ability to "control" data. Summary of the invention

[0003] In response to the above-mentioned problems, the present invention provides a multi-level edge computing system architecture based on cloud-edge collaboration and an implementation method thereof, which can realize the integration of power-related data, effectively stimulate data value, and enhance data application innovation capabilities.

[0004] In order to achieve the above-mentioned object, the present invention provides a multi-level edge computing system architecture based on cloud-edge collaboration, which includes: a core cloud data center, which is used to analyze and utilize the collected data; an edge data node, which collects data based on the rule of collecting data nearby and uploads the collected data to the core cloud data center; a distribution network side and a user side device, which transmits data to the edge data node through an edge intermediate device;

[0005] The edge data node is also used to provide data support for localized applications. The edge data node includes a regional edge computing node, which includes: an intranet cloud, which is used to provide complete data service functions for local organizations and to support the deployment of distribution network and user side applications; an extranet cloud, a logical strong isolation device is deployed between the intranet cloud and the extranet cloud, and the extranet cloud is used to support the development, deployment and operation and maintenance of external service applications, and provide meter reading and metering and billing data services for at least one of power sales units, water supply agencies, and gas units;

[0006] The edge data node also includes a station-level edge computing node that aggregates data to the regional edge computing node. The station-level edge computing node is connected to the user-side device through the edge IoT agent, the intelligent distribution transformer terminal, and the edge intermediate device and distribution network side of at least one of the concentrators, and is used for closed-loop monitoring of the access and collection link between the distribution network side and the user-side device of the IoT management terminal.

[0007] In a preferred manner, the regional edge computing node provides the data service functions of the intranet cloud and the extranet cloud through a four-layer structure of IaaS layer, PaaS layer, DaaS layer and SaaS layer; the IaaS layer is based on a server-based resource pool and is used to provide computing services, storage services and network services for at least one of virtual machines, physical hosts and container hosts; the PaaS layer is used to provide at least one database service of relational database, memory database, real-time database, time series database and GIS database, as well as message services and middleware services; the DaaS layer is used to provide data services to the SaaS layer, and the data in the DaaS layer data service includes the master data of the core cloud data center, business data and data collected by the station-level edge computing nodes; the SaaS layer adopts a microservice architecture and uses an API gateway to support the development, deployment and operation of applications.

[0008] In a preferred manner, the edge data node provides pre-processing of collected data for the core cloud data center, and the pre-processing includes at least one operation of data analysis, conversion, cleaning, verification, and supplementation.

[0009] In a preferred manner, the core cloud data center and edge data nodes share data based on a unified data service directory and a high-speed network between data centers.

[0010] In a preferred embodiment, the distribution network side equipment includes at least one of a smart terminal, a low-voltage circuit breaker, and a reactive power compensation device, and the user side equipment includes at least one of a smart meter, a smart home, an electric vehicle charging pile, and a distributed power source.

[0011] A method for implementing a multi-level edge computing architecture based on cloud-edge collaboration, based on the multi-level edge computing architecture based on cloud-edge collaboration, the method comprising:

[0012] S1: Deploy core cloud data centers and edge data nodes in a multi-level edge computing architecture based on cloud-edge collaboration, where the edge data nodes include regional edge computing nodes and station-level edge computing nodes;

[0013] S2: The power equipment, edge intermediate equipment and edge data nodes configured on the distribution network side and the user side form a three-level routing structure and transmit data through a high-speed power line carrier;

[0014] S3: The edge data node collects the power equipment data configured on the distribution network side and the user side through the edge intermediate device based on the rule of collecting data nearby;

[0015] S4: The edge data node uploads the collected data to the core cloud data center, and the core cloud data center analyzes and utilizes the collected data.

[0016] The beneficial effects of the present invention are as follows: the present invention is based on the "core + edge" cloud-edge collaborative multi-level edge data computing node construction model, combining the core cloud data center with the edge data node to form a multi-level computing node model that sinks step by step, realizing data integration and cloud-edge collaboration, effectively stimulating data value, and enhancing data application innovation capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a multi-level edge computing architecture based on cloud-edge collaboration of the present invention;

[0018] Figure 2 It is a flow chart of an implementation method of a multi-level edge computing architecture based on cloud-edge collaboration of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] The terms used in this disclosure are for the purpose of describing specific embodiments only and are not intended to limit the disclosure. The singular forms "a", "the" and "the" used in this disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items. Specific embodiment:

[0022] According to one aspect of the present invention, a multi-level edge computing architecture based on cloud-edge collaboration is provided. Among them, cloud-edge collaboration refers to the interactive collaboration between cloud and edge devices; the edge computing can refer to providing services on the edge of the network closer to the terminal, that is, on the edge of the network close to the source of objects or data, a distributed open platform integrating network, computing, storage, and application core capabilities provides edge intelligent services nearby. In the field of power grids, edge computing can process and analyze multiple data from sensors, smart devices, and smart terminals on the spot, provide edge intelligence, agile connection, real-time judgment, data optimization, and security protection nearby, improve data transmission and processing efficiency, meet the rapid response requirements of equipment and users in the power grid, and provide support for applications such as intelligent scheduling, active distribution network, and distribution Internet of Things. Most of the data of the power Internet of Things also comes from the edge of the power grid. Using these data nearby at the source end and mining the data value is more conducive to improving power supply reliability and enhancing efficient interaction with customers.

[0023] In the present invention, data is collected through edge computing nodes / edge clouds and used locally, while simultaneously supporting a centralized business system deployed in the cloud, which can be, for example, a provincial data center. Data is then "sedimented" in the cloud to carry out big data analysis and utilization, and to provide algorithms and intelligence for the edge cloud in reverse.

[0024] The multi-level edge computing architecture based on cloud-edge collaboration adopted by the present invention extends the storage and computing capabilities of the cloud to the edge, realizing the provision of services and edge intelligence nearby. The field of power Internet of Things is different from the one-way data flow of commercial Internet of Things. The data of the cloud and edge in the field of power Internet of Things are mostly transmitted in two directions, involving both the edge uploading the collected data to the cloud and the cloud sending control instructions to the edge. Especially with the development of smart homes, electric vehicles, distributed energy, and virtual power plants, the interaction between the edge and the cloud is more frequent.

[0025] Specifically, from the overall architecture point of view, the multi-level edge computing system architecture based on the cloud-edge system of the present invention includes a core cloud data center, edge data nodes, and distribution network and user side equipment. The edge data nodes collect data based on the rule of collecting data nearby and upload the collected data to the core cloud data center for data analysis and utilization in the core cloud data center, wherein the edge data nodes include regional edge computing nodes and station-level edge computing nodes; the edge computing nodes and the power equipment and edge intermediate devices configured on the local distribution network side and the user side together form a three-level routing structure, and data is transmitted based on high-speed power line carriers.

[0026] Among them, the regional edge computing node can be deployed in the regional power grid company, mainly providing local companies with intelligent services based on the power Internet of Things in the fields of marketing and distribution and customer service. The English name of the regional edge computing node is Region Edge Computing, referred to as REC; the station-level edge computing node can be arranged around the construction of large-scale parks, industrial bases, energy storage stations, distributed energy and other units, and provide virtual power plants, energy efficiency management and other services to the outside world. The English name of the station-level edge computing node is Station Edge Computing, referred to as SEC.

[0027] Among them, the core cloud data center is, for example, a cloud data center deployed at the provincial level. By extending the services or capabilities of the cloud data center to edge data nodes, it realizes the center-edge system, full-network computing power scheduling, and unified network management and control, and builds a logically unified and physically distributed distributed cloud computing architecture to jointly support data processing in the power Internet of Things.

[0028] The edge data node can also be called an edge computing node, which can be composed of various collection devices, concentrators, sensors, IoT agents, etc. located on the site, such as the power grid side and the user side, and undertakes functions such as data collection, protocol conversion, and data routing. The concentrator and IoT agent device are mainly for non-intelligent collection devices and sensors, and unified access is achieved through the concentrator of the IoT agent or the IoT agent gateway.

[0029] Preferably, the edge data node of the present invention is composed of at least one of an edge cloud service system, an edge access service system, an edge data service system, an edge application service system, a cloud-edge collaborative service system and a security management system system.

[0030] Specifically, for the edge cloud service system, the edge cloud service preferably provides computing, storage, and network resources for edge data nodes in the form of a private cloud. In the edge cloud service system, optionally, the regional edge computing node includes an intranet cloud and an extranet cloud, and a logical strong isolation device is deployed between the intranet cloud and the extranet cloud. The intranet cloud provides complete data services from the perception layer to the application layer for the local organization and is used to support the deployment of distribution network and user side applications; the extranet cloud is used to support the development, deployment, and operation and maintenance of external service applications, and provides meter reading and metering and billing data services for at least one of the electricity sales unit, water supply agency, and gas unit.

[0031] Optionally, in the edge cloud service system, please refer to Figure 1 , Figure 1 FIG. 1 is a schematic diagram of a multi-level edge computing architecture based on cloud-edge collaboration according to a preferred embodiment of the present invention. Figure 1As shown, the regional edge computing node adopts a four-layer structure of IaaS layer, PaaS layer, DaaS layer and SaaS layer:

[0032] At the IaaS layer, resource pools are formed based on servers to provide computing services, storage services, and network services for at least one of the following: virtual machines, physical hosts, and container hosts. In addition, in the external cloud, regional edge computing nodes can mainly provide virtual hosts, object storage, and block storage services.

[0033] At the PaaS layer, at least one database service among relational database, in-memory database, real-time database, time series database, and GIS database is provided, as well as message service and middleware service; in addition, in the external network cloud, the regional edge computing nodes can mainly provide relational database, time series database and middleware services.

[0034] At the DaaS layer, data services are provided to the application layer. The data in the data services include: master data and business data from the provincial centralized data center; collected data from the perception layer, and subject data that has been cleaned, converted, and assembled. Among them, the external network cloud mainly provides externally released transaction information and announcements, as well as meteorological data and industry data from external units, and saves some basic data.

[0035] At the SaaS layer, a microservice architecture is adopted, using an API gateway to support application development, deployment, and operation.

[0036] Optionally, in the edge cloud service system, the station-level edge computing nodes are mainly composed of intranet clouds, providing SEC-IaaS, SEC-PaaS and SEC-SaaS services to surrounding users, supporting the development of virtual power plants, integrated energy management and other businesses. A small number of physical hosts are deployed on the external network to provide services mainly based on information publishing. In terms of technical routes, station-level edge computing nodes are the same as regional-level edge computing nodes, with only differences in scale.

[0037] Specifically, for the edge access service system, the edge access service is implemented at the edge data node: under the dispatch of the provincial IoT management center, the IoT management terminal is accessed and the closed-loop monitoring of the collection link is realized; at the source end, "collect once and use everywhere" is realized to provide data support for localized applications. At the edge computing node, through the local access network, the edge IoT agent, intelligent distribution transformer terminal, concentrator and other intelligent devices are used to access the intelligent terminals, low-voltage circuit breakers, reactive compensation devices and other equipment on the distribution network side or / and the smart meters, smart homes, electric vehicle charging piles, distributed power supplies and other equipment on the user side. Local closed-loop management of terminal devices and access networks is formed at the edge computing node. After parsing, conversion, cleaning and calculation, the collected data is sent to local applications and provincial data center business systems on demand to achieve "collect once and use everywhere".

[0038] Specifically, for the edge data service system, it mainly provides pre-processing operations for the collected data for the core cloud data center, and the core cloud data center can be exemplified as a provincial data center, and provides data support for localized applications, such as providing basic data for collection for localized applications at the source end, more specifically, high-frequency data and extended data for fault diagnosis and line loss analysis. Optionally, the pre-processing includes at least one operation of data parsing, conversion, cleaning, verification, and supplementation, thereby saving computing resources, network resources, and storage resources of the data center. Preferably, the edge data service system can also set or establish a data resource directory to ensure that the provincial data center can easily access and use edge data at any time through the data resource directory.

[0039] Specifically, for edge application service systems, it provides a development, deployment and operation environment based on the microservice architecture based on the edge data service system. In the intranet cloud, it provides a complete set of services from the perception layer to the application layer for local units, supporting the deployment of distribution network and user side applications such as the power service command system and the integrated energy management platform. In the extranet cloud, it supports the development, deployment and operation and maintenance of external service applications, and can provide meter reading, metering and billing services for electricity sellers, water companies, gas companies and other units.

[0040] Specifically, for the cloud-edge collaborative service system, the provincial data center and edge computing nodes complement and collaborate in cloud service resources, security management, data lifecycle management, etc., and have unified logic. Through a unified data service directory and high-speed networks between data centers, data sharing is achieved, fully supporting the intelligent operation of core businesses, fully serving the energy Internet ecosystem, and promoting management improvement and business transformation.

[0041] Specifically, for the security management system, it may include but is not limited to personnel safety information management modules, application security management modules, equipment security management modules and data security management modules. Based on multiple management modules, the corresponding information is analyzed and based on the analysis results and preset execution rules, corresponding operations are performed on the corresponding devices or applications, such as sending early warning information to the user terminal.

[0042] Optionally, the station-level edge computing node is based on the scheduling of the core cloud data center, accesses the network on the distribution network side or / and the user side through the local access network, and utilizes at least one of the edge intermediate devices including the edge IoT agent, the intelligent distribution transformer terminal, and the concentrator to achieve access to the IoT management terminal and closed-loop monitoring of the collection link, wherein the equipment on the distribution network side includes at least one of the intelligent terminal, the low-voltage circuit breaker, and the reactive compensation device, and the equipment on the user side includes at least one of the smart meter, the smart home, the electric vehicle charging pile, and the distributed power supply.

[0043] Optionally, the core cloud data center and edge data nodes share data based on a unified data service directory and a high-speed network between data centers.

[0044] The technical solution of the present invention has the following technical effects:

[0045] (1) Based on the "core + edge" cloud-edge collaborative multi-level edge data computing node construction model, the core cloud data center is combined with the edge data node to form a multi-level computing node model that sinks step by step, realizes data integration and cloud-edge collaboration, effectively stimulates data value, and enhances data application innovation capabilities.

[0046] (2) After the technical solution of the present invention is applied, it can realize the rapid and effective direct use of locally collected data, solve the problem that the data transmission link is too long and cannot be processed in real time, improve the data processing efficiency, and reduce the electricity collection rate from T+1 day to minute-level frequency; relying on the real-time call of the energy meter, the minute-level reporting of power outage events, line tripping monitoring and other information, accurately determine the cause of the fault and the scope of the power outage, and shorten the average fault repair time; realize a 15-minute power supply service circle, process terminal data in real time nearby, realize holographic perception, ubiquitous connection, and intelligent regulation of customer data, and improve power supply reliability and service level.

[0047] (3) The technical solution of the present invention can effectively improve the efficiency of data collection and processing, process terminal data in real time, and realize holographic perception, ubiquitous connection, and intelligent regulation of user data. Taking the electricity consumption information collection system as an example, the power supply company collects electricity consumption from 3.8 million households, and the amount of data collected daily in the province is 24,014,531. It takes 7 minutes to traverse and query the electricity consumption data. If the edge data node mode of the present invention is used to collect local data, the query of electricity consumption data can be achieved within 1 minute. The frequency of electricity collection changes from T+1 day to 5 minutes, and special requirements reach 1 minute level.

[0048] (4) Compared with the prior art, it can significantly improve the efficiency of data transmission. In the prior art, the centralized data center collects data for local access and transmission as follows: meter-concentrator-provincial company electricity consumption information collection system-marketing basic data platform-full business data center-city supply and service command system. After the regional edge node of the present invention is implemented, the supply and service system is deployed locally, and high-speed carrier HPLC technology is used to realize the processing by the edge computing nodes or computing nodes at all levels of the meter-concentrator-supply and service system, and the data collection and transmission of the smart meter is reduced from 7-hop routing links to 3-hop routing links.

[0049] (5) The present invention can effectively improve the power access index. Relying on regional edge computing nodes, external business extension, integration of user resource information, rapid response to customer demands, deep data mining, providing customers with personalized value-added services, improving power supply reliability and service levels, promoting the business environment, and improving the power company's "power access" index.

[0050] According to a general inventive concept of the present invention, an embodiment of the present invention also provides a method for implementing a multi-level edge computing architecture based on cloud-edge collaboration, please refer to Figure 2 , the implementation method includes:

[0051] S1: Deploy core cloud data centers and edge data nodes in a multi-level edge computing architecture based on cloud-edge collaboration, where the edge data nodes include regional edge computing nodes and station-level edge computing nodes;

[0052] S2: The power equipment, edge intermediate equipment and edge data nodes configured on the distribution network side and the user side form a three-level routing structure and transmit data through a high-speed power line carrier;

[0053] S3: The edge data node collects the power equipment data configured on the distribution network side and the user side through the edge intermediate device based on the rule of collecting data nearby;

[0054] S4: The edge data node uploads the collected data to the core cloud data center, and the core cloud data center analyzes and utilizes the collected data.

[0055] It should be noted that although the operations of the disclosed method are described in a particular order in the accompanying drawings, this does not require or imply that the operations must be performed in this particular order, or that all the operations shown must be performed to achieve the desired results. On the contrary, the steps depicted in the flow chart can be performed in a different order. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be decomposed into multiple steps.

[0056] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention.

[0057] The implementation method of the embodiment of the present invention corresponds to the multi-level edge computing system architecture of the embodiment of the present invention. The technical features and beneficial effects described in the embodiment of the above-mentioned multi-level edge computing system architecture are applicable to the embodiment of the implementation method.

[0058] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A multi-level edge computing architecture based on cloud-edge collaboration, characterized in that: It includes: A core cloud data center, which is used to analyze and utilize the collected data; Edge data nodes, which collect data based on the rule of collecting data nearby and upload the collected data to the core cloud data center; distribution network side and user side devices, which transmit data to the edge data nodes through edge intermediate devices; The edge data node is also used to provide data support for localized applications. The edge data node includes a regional edge computing node, which includes: an intranet cloud, which is used to provide complete data service functions for local organizations and to support the deployment of distribution network and user side applications; an extranet cloud, a logical strong isolation device is deployed between the intranet cloud and the extranet cloud, and the extranet cloud is used to support the development, deployment and operation and maintenance of external service applications, and provide meter reading and metering and billing data services for at least one of power sales units, water supply agencies, and gas units; The edge data node also includes a station-level edge computing node that aggregates data to the regional edge computing node, and the station-level edge computing node is connected to the user-side device through the edge IoT agent, the intelligent distribution transformer terminal, and the edge intermediate device of at least one of the concentrators and the distribution network side, and is used for closed-loop monitoring of the distribution network side and user-side device access and collection links of the IoT management terminal; The regional edge computing node provides the data service functions of the intranet cloud and the extranet cloud through the four-layer structure of IaaS layer, PaaS layer, DaaS layer and SaaS layer; the IaaS layer is based on the server to form a resource pool and is used to provide computing services, storage services and network services for at least one of virtual machines, physical hosts and container hosts; the PaaS layer is used to provide database services, message services and middleware services for at least one of relational databases, memory databases, real-time databases, time series databases and GIS databases; the DaaS layer is used to provide data services to the SaaS layer, and the data in the DaaS layer data service includes the master data of the core cloud data center, business data and data collected by the station-level edge computing nodes; the SaaS layer adopts a microservice architecture and uses an API gateway to support the development, deployment and operation of applications; The edge data node is composed of edge cloud service system, edge access service system, edge data service system, edge application service system, cloud-edge collaborative service system and security management system; The edge access service system, the edge access service is implemented at the edge data node: under the dispatch of the provincial IoT management center, the IoT management terminal is accessed and the closed-loop monitoring of the acquisition link is realized; The edge data service system provides pre-processing operations for collected data for the core cloud data center, which is a provincial data center and provides data support for localized applications; The edge application service system provides a development, deployment and operation environment based on the microservice architecture on the basis of the edge data service system; The cloud-edge collaborative service system is a logically unified system for the provincial data center and edge computing nodes to complement and collaborate in cloud service resources, security management, and data lifecycle management; The security management system includes: a personnel safety information management module, an application security management module, a device security management module and a data security management module. Based on multiple management modules, corresponding information is analyzed and based on the analysis results and preset execution rules, corresponding operations are performed on corresponding devices or applications.

2. The multi-level edge computing architecture based on cloud-edge collaboration according to claim 1 is characterized in that: The edge data node provides pre-processing of collected data for the core cloud data center, and the pre-processing includes at least one operation of data analysis, conversion, cleaning, verification, and supplementation.

3. The multi-level edge computing architecture based on cloud-edge collaboration according to claim 1 is characterized in that: The core cloud data center and edge data nodes share data based on a unified data service directory and a high-speed network between data centers.

4. The multi-level edge computing architecture based on cloud-edge collaboration according to claim 1 is characterized in that: The distribution network side equipment includes at least one of a smart terminal, a low-voltage circuit breaker, and a reactive power compensation device; the user side equipment includes at least one of a smart meter, a smart home, an electric vehicle charging pile, and a distributed power source.

5. A method for implementing a multi-level edge computing architecture based on cloud-edge collaboration, characterized in that: Based on the multi-level edge computing architecture based on cloud-edge collaboration as claimed in claim 1, its implementation method includes: S1: Deploy core cloud data centers and edge data nodes in a multi-level edge computing architecture based on cloud-edge collaboration, where the edge data nodes include regional edge computing nodes and station-level edge computing nodes; S2: The power equipment, edge intermediate equipment and edge data nodes configured on the distribution network side and the user side form a three-level routing structure and transmit data through a high-speed power line carrier; S3: The edge data node collects the power equipment data configured on the distribution network side and the user side through the edge intermediate device based on the rule of collecting data nearby; S4: The edge data node uploads the collected data to the core cloud data center, and the core cloud data center analyzes and utilizes the collected data.

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