CN112583899A - Internet of things data acquisition system and method and edge computing equipment - Google Patents

Abstract

The application provides a data acquisition system and method of the Internet of things and edge computing equipment. Wherein the edge computing device comprises a computing unit and a storage device, the computing unit is coupled with at least one of a sensor, an internet of things gateway and a cloud computing platform, the computing unit is further coupled with the storage device, and the cloud computing platform is coupled with the edge computing device through a network; the calculating unit acquires first data, wherein the first data is data collected by a sensor; the computing unit compresses, counts and/or marks the first data to obtain second data; the computing unit writes the second data to the storage device.

Description

Internet of things data acquisition system and method and edge computing equipment

Technical Field

The application relates to a storage technology, in particular to a data acquisition system and method of the Internet of things and edge computing equipment.

Background

The Internet of Things (IoT) has been widely used in various fields, such as industry, agriculture, environment, traffic, etc. The traditional physical network data acquisition method is that a sensor acquires data, and a physical network gateway pushes the data to a cloud server. The data volume collected by the sensor is huge, so that data are pushed to the cloud server every moment, and the cloud server load processes massive data. Therefore, the traditional physical network data acquisition system not only requires that the network bandwidth is wide enough, but also requires that the cloud server has strong data processing capacity.

Fig. 1 shows a schematic diagram of an internet of things system in the prior art. As shown in fig. 1, the internet of things system includes a cloud computing platform, a plurality of internet of things gateways, and a plurality of sensors. Each internet of things gateway is connected with at least one sensor and used for coupling the sensor to the network and further to the cloud computing platform. The sensors include various types such as temperature sensors, cameras, position sensors, and the like.

The size of the internet of things is massive. The number of sensors may be thousands or even more. The sensors are of various kinds, come from various suppliers, and have various data formats and various data transmission protocols. The sensors are also operated for long periods of time, for example, collecting data every minute. The cloud computing platform needs to acquire data collected by each sensor, process the data, and utilize the data.

In order to accommodate a large number of devices in the internet of things, a hierarchical network provided by the internet of things network is effective. The gateway of the Internet of things is coupled with a plurality of sensors at the edge end so as to reduce the equipment scale required to be managed by the cloud. In order to accommodate various types of devices, a protocol such as Modbus, MQTT (Message Queuing Telemetry Transport), etc. has been proposed to standardize data transmission between devices of the internet of things.

Disclosure of Invention

With the further increase of the number and variety of devices accommodated by the internet of things, especially the widespread deployment of large-data-volume sensors such as cameras, the scale of data continuously produced in the internet of things brings challenges to the deployment and operation of large-scale internet of things. Taking the camera as an example, the number of the cameras deployed in a large city exceeds 100 ten thousand, 1MB of video data is generated per second by each high-definition camera, and the video data generated in the whole city within 1 day is close to 10^8 GB. Storage and retrieval of data of this size cannot be provided by a typical cloud platform or requires extremely high cost.

Further, data produced in the internet of things needs to be applied to generate value. The mass data generated by the mass sensor is usually only a very small part, which needs to be accessed in the application. For example, it is desirable to obtain the time and location of the appearance of a certain face or license plate from the video data captured by the camera, and it is not reasonable to store and traverse all 10^8GB of data for retrieval purposes. For another example, temperature data of the area needs to be obtained from a temperature sensor. The temperature of the area is typically represented by a daily average temperature, and the temperature sensor provides data that is updated every second.

New internet of things equipment is rapidly generating, and the development of the existing internet of things data transmission protocol cannot meet the requirements of the new equipment.

It is desirable to improve the data acquisition and application modes in the internet of things and internet of things to meet the above requirements.

In order to solve the above technical problem, according to a first aspect of an embodiment of the present application, there is provided a first edge computing device according to the first aspect of the embodiment of the present application, including a computing unit and a storage device, the computing unit being coupled with at least one of a sensor, an internet of things gateway, and a cloud computing platform, the computing unit being further coupled with the storage device, the cloud computing platform being coupled with the edge computing device through a network; the calculating unit acquires first data, wherein the first data is data collected by a sensor; the computing unit compresses, counts and/or marks the first data to obtain second data; the computing unit writes the second data to the storage device.

The first edge computing device according to the first aspect of the embodiments of the present application provides the second edge computing device according to the first aspect of the embodiments of the present application, further comprising a network unit coupled with at least one of a sensor, an internet of things gateway, and a cloud computing platform, the network unit coupled with the computing unit and the storage device, the computing unit coupled with at least one of a sensor, an internet of things gateway, and a cloud computing platform through the network unit; the computing unit obtains the first data through the network unit.

According to the first or second edge computing device of the first aspect of the embodiment of the present application, there is provided the third edge computing device of the first aspect of the embodiment of the present application, where the edge computing device further includes a memory, and after the first data is obtained, the first data is stored in the memory.

According to one of the first to third edge computing devices of the first aspect of the embodiment of the present application, there is provided the fourth edge computing device of the first aspect of the embodiment of the present application, wherein the computing unit sends a first request indicating to acquire data to the storage device; in response to the first request, the storage device decompresses and retrieves the second data to obtain third data, where the third data is a partial data of the first data; the storage device sends the third data to the computing unit; and the computing unit pushes the third data to a cloud computing platform.

According to one of the first to third edge computing devices of the first aspect of the embodiment of the present application, there is provided the fifth edge computing device of the first aspect of the embodiment of the present application, wherein the computing unit sends a second request indicating to acquire data to the storage device; in response to the second request, the storage device decompresses the second data and stores the first data in a memory; in response to the first data being stored in the memory, the computing unit retrieves the first data and obtains third data, where the third data is a partial data of the first data; and the computing unit pushes the third data to a cloud computing platform.

According to one of the first to fifth edge computing devices of the first aspect of an embodiment of the present application, there is provided the sixth edge computing device of the first aspect of an embodiment of the present application, wherein the second data is a compressed storage form of the first data; or the second data comprises a compressed storage form of the first data and statistical information of the first data.

The sixth edge calculation device according to the first aspect of the embodiments of the present application provides the seventh edge calculation device according to the first aspect of the embodiments of the present application, wherein the first data and the third data are time-series data, and the second data is key-value data.

According to the second edge computing device of the first aspect of the embodiment of the present application, there is provided the eighth edge computing device of the first aspect of the embodiment of the present application, where the network unit sends, to the storage device, a first request indicating to acquire data; in response to the first request, the storage device decompresses and retrieves the second data to obtain third data, where the third data is a partial data of the first data; the storage device sends the third data to the network element; and the network unit pushes the third data to the cloud computing platform.

According to one of the first to eighth edge computing devices of the first aspect of the embodiment of the present application, there is provided the ninth edge computing device of the first aspect of the embodiment of the present application, before the computing unit acquires the first data, the computing unit acquires configuration information indicating at least one of a data acquisition manner, a data push manner, and a data processing manner, so that the computing unit processes the first data according to the configuration information.

According to a fifth edge computing device of the first aspect of the embodiments of the present application, there is provided the tenth edge computing device of the first aspect of the embodiments of the present application, wherein in response to the second request, the computing unit retrieves the first data according to the configuration information, and acquires the third data; the configuration information indicates a data index, and the third data is a part of the first data corresponding to the data.

According to a ninth edge computing device of the first aspect of an embodiment of the present application, there is provided the eleventh edge computing device of the first aspect of an embodiment of the present application, wherein the configuration information is stored in the edge computing device in advance; or, the configuration information is obtained by the edge computing device from the cloud computing platform.

According to a third aspect of the present application, there is provided a first data acquisition system according to the third aspect of the present application, comprising at least one sensor, at least one edge computing device, each edge computing device being coupled with at least one sensor, and a cloud computing platform coupled with the at least one edge computing device over a network; the at least one sensor collects first data; the at least one sensor sends the first data to the at least one edge computing device; each edge computing device processes the first data according to configuration information to obtain second data, wherein the size of a storage space occupied by the second data is smaller than that of a storage space occupied by the first data, the formats of the first data and the second data are different, and the configuration information indicates at least one of a data acquisition mode, a data pushing mode and a data processing mode; the edge computing device writes the second data to a storage medium, the storage medium being a storage medium in the edge computing device or the storage medium being coupled with the edge computing device.

A second data acquisition system according to the third aspect of the present application is provided in accordance with the first data acquisition system of the third aspect of the present application, the data acquisition system further comprising at least one internet of things gateway, each internet of things gateway coupled with at least one sensor, each edge computing device coupled with at least one internet of things gateway; the at least one sensor sends the first data to the at least one edge computing device through the at least one internet of things gateway.

According to the first or second data acquisition system of the third aspect of the present application, there is provided the third data acquisition system of the third aspect of the present application, wherein the edge computing device acquires third data from the storage medium according to the configuration information, the third data being partial data of the first data; and the edge computing equipment pushes the third data to the cloud computing platform according to the configuration information.

According to one of the first to third data acquisition systems of the third aspect of the present application, there is provided a fourth data acquisition system according to the third aspect of the present application, the edge computing device being an edge computing device as defined in any one of the above first aspects.

According to a fourth aspect of the present application, there is provided a first internet of things data acquisition method according to the fourth aspect of the present application, which is applied to the data acquisition system as described in any one of the above third aspects, the method includes: acquiring first data according to configuration information, wherein the first data is acquired by a sensor, and the configuration information indicates at least one of a data acquisition mode, a data pushing mode and a data processing mode; processing the first data according to the configuration information to obtain second data, wherein the first data and the second data have different formats; storing the second data in a local storage device.

According to the first internet of things data acquisition system of the fourth aspect of the application, the second internet of things data acquisition method of the fourth aspect of the application is provided, and the configuration information is acquired before the first data is acquired.

According to the first or second internet-of-things data acquisition system of the fourth aspect of the present application, there is provided a third internet-of-things data acquisition method of the fourth aspect of the present application, wherein third data is acquired from the local storage device according to the configuration information, and the third data is partial data of the first data; and pushing the third data.

According to a third aspect of the present application, there is provided a fourth internet of things data acquisition method according to the fourth aspect of the present application, where the acquiring third data from the local storage device includes: acquiring a data index according to the configuration information, wherein the data index points to the position of part of second data corresponding to the third data in the local storage device; and acquiring the part of the second data, and processing the part of the second data to restore the part of the second data into a part of first data corresponding to the part of the second data, wherein the part of the first data is the third data.

According to a fifth aspect of the present application, there is provided a first device registration method according to the fifth aspect of the present application, applied to the data acquisition system as described in any one of the above third aspects, the method including: the method comprises the steps that a second device obtains a self-registration request of a first device, wherein the first device comprises a sensor, an Internet of things gateway and an edge computing device, the second device is a registered device in a data acquisition system, and the second device comprises the Internet of things gateway, the edge computing device and a cloud computing platform; and the second equipment authenticates the first equipment according to the information carried by the self-registration request.

According to a first device registration method of a fifth aspect of the present application, there is provided a second device registration method of the fifth aspect of the present application, the method further comprising: in response to authentication completion, the second device sends authentication completion information to the first device to indicate that the first device registration is complete.

According to the first or second device registration method of the fifth aspect of the present application, there is provided the third device registration method of the fifth aspect of the present application, where after the first device acquires the authentication completion information or the push enabling information sent by the second device, a function of pushing data to the second device by the first device is enabled.

According to a first device registration method of a fifth aspect of the present application, there is provided a fourth device registration method of the fifth aspect of the present application, wherein when the first device is a sensor, the second device is an internet of things gateway or an edge computing device; when the first device is an internet of things gateway, the second device is an edge computing device; and when the first equipment is edge computing equipment, the second equipment is a cloud computing platform.

According to a fourth device registration method of a fifth aspect of the present application, there is provided the fifth device registration method of the fifth aspect of the present application, where when the first device is an edge computing device and the second device is a cloud computing platform, the method further includes: in response to the completion of authentication, the second device sends configuration information to the first device, the configuration information indicating at least one of a data acquisition mode, a data push mode, and a data processing mode.

According to a fourth device registration method of a fifth aspect of the present application, there is provided the sixth device registration method of the fifth aspect of the present application, where when the first device is an edge computing device and the second device is a cloud computing platform, the method further includes: the first device sends a message for confirming configuration information to the second device, wherein the configuration information indicates at least one of a data acquisition mode, a data pushing mode and a data processing mode; and the second equipment confirms whether the configuration information is wrong or not.

According to a sixth device registration method of the fifth aspect of the present application, there is provided a seventh device registration method of the fifth aspect of the present application, wherein the second device sends push enabling information to the first device when confirming that the configuration information is correct; and the second equipment sends correct configuration information to the first equipment when confirming that the configuration information is wrong.

According to the embodiment of the application, partial data processing is performed by using the edge computing equipment to replace a cloud computing platform, the technical problem that the equipment of the Internet of things in the prior art cannot meet the requirements of people for the Internet of things is solved, and the technical effects of reducing the deployment and operation difficulty of the Internet of things and improving the data acquisition and application mode of the Internet of things are achieved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art according to the drawings.

Fig. 1 is a schematic diagram of a conventional data acquisition system of the internet of things in the prior art;

fig. 2 is a schematic diagram of a physical network data acquisition system according to an embodiment of the present application;

FIG. 3 is a block diagram of an edge computing device provided by an embodiment of the present application;

fig. 4 is a timing diagram of an internet of things data acquisition system provided in an embodiment of the present application;

fig. 5 is a schematic flow chart of a data acquisition method of the internet of things according to an embodiment of the present application;

fig. 6 is a schematic flow chart of another method for acquiring data of the internet of things according to the embodiment of the present application;

fig. 7 is a schematic diagram of an edge computing device pushing data to a cloud computing platform according to an embodiment of the present application;

FIG. 8 is a schematic diagram of an edge computing device compressing data according to an embodiment of the present disclosure;

fig. 9 is a schematic diagram of an edge computing device reading data and pushing the data according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application are clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Although the present application has been described with reference to examples, which are intended to be illustrative only and not to be limiting of the application, changes, additions and/or deletions may be made to the embodiments without departing from the scope of the application.

Fig. 2 is a schematic diagram of a data acquisition system 200 according to an embodiment of the present disclosure. As shown in fig. 2, the data acquisition system 200 includes a cloud computing platform 210, an edge computing device 220, an edge computing device 221, an edge computing device 222, an internet of things gateway 230, an internet of things gateway 231, an internet of things gateway 232, and sensors 240, 241, 242, … …, 248. The cloud computing platform 210 is coupled to the edge computing device 220 and 222, the edge computing device 220 is coupled to the IOT gateway 230 and 232, the IOT gateway 230 is coupled to the sensor 240 and 242, the IOT gateway 231 is coupled to the sensor 243 and 245, and the IOT gateway 232 is coupled to the sensor 246 and 248. Although not shown in fig. 2, optionally, edge computing devices 221 and 222 are also coupled to the internet of things gateway. Still alternatively, the edge computing devices 221 and 222 are not directly coupled to the one or more sensors through the internet of things gateway. The sensor in the embodiment of the present application includes information sensing devices such as a temperature sensor, a Radio Frequency Identification (RFID) device, an infrared sensor, a humidity sensor, a global positioning system, a laser scanner, a video/audio recorder, and the like.

Compared with the Internet of things system in the prior art, the data acquisition system according to the embodiment of the application is provided with a plurality of edge computing devices. The edge computing device manages data acquisition from the sensors and stores raw data acquired by the sensors to reduce the storage capacity and storage bandwidth requirements of the data acquisition system on the cloud computing platform. The edge computing device also aggregates, counts, or processes the collected data to reduce data transmission in the network when the cloud computing platform applies the sensor data. The edge computing device also pushes data to the cloud computing platform.

The working mode of the data acquisition system 200 is described below by taking the sensor 240, the internet of things gateway 230, the edge computing device 220, and the cloud computing platform 210 as examples. The sensors 240 collect data according to the internet of things protocol. Optionally, the internet of things protocol includes MQTT, DDS, AMQP, XMPP, JMS, REST, CoAP, and the like. Further optionally, the data collected by the sensor 240 includes status data, positioning data, personalization data, data that can be referenced by behavior, user feedback data, and the like. The sensor 240 collects and transmits data at predetermined time intervals or continuously, so that data obtained from the sensor 240 is referred to as time-series data. Table 1 illustrates the characteristics of time series data, whose data source is, for example, (sensor a), comprising a plurality of time value data in chronological order. New time value data is constantly present over time, while old time value data generally does not need to be overwritten. The time series data may be retrieved over time. In table 1, for entry 1, the data value collected for time value 1 is 12, the data value collected for time value 2 is 17, and the data value collected for time value 3 is 10.

TABLE 1

Index	Time value	1	Time value 2	Time value 3	…
						Sensor A	12	17	10	…

In accessing time series data, an index (e.g., sensor a) and time interval are typically specified to obtain a corresponding one or more numerical values. In yet another example, it may be desirable to obtain statistics (e.g., averages) of the time series data.

Sensor a also includes attributes such as the location where sensor a is located, the data transmission protocol used, etc. This type of data is characterized by KV (key-value) data.

In order to effectively store and retrieve data collected by the sensor, the edge computing device according to the embodiment of the application further comprises a time-series database and a KV storage device, so as to respectively accommodate the time-series data collected by the sensor and the KV data related to the sensor. Alternatively, the time-series data is also regarded as KV data with the "index" (see also table 1) as a key and the time-value series as a value, and thus may be recorded in the KV storage device as well.

According to an embodiment of the application, in the data acquisition system 200, the edge computing devices (220, 221, and 222) store data acquired by each sensor. Whereby a plurality of edge computing devices form a distributed storage system. Data collected by the sensor does not need to be sent to the cloud computing platform 210, and the cloud computing platform 210 does not need to store raw data collected by the sensor, so that the data transmission quantity in the data collection system 200 is reduced, and the requirements on the storage space and data access of the cloud computing platform are also reduced. The edge computing devices (220, 221, and 222) also provide data retrieval services for the data acquisition system to replace or assist in the utilization of the sensor data by the cloud computing platform 210. For example, if the cloud computing platform 210 needs to use the data of the sensor 244 in a specified time period, a data query request for the sensor 244 in the specified time period is broadcast to the whole network, for example, and the edge device 220, in response to receiving the query request and knowing that it stores the data of the sensor 244, acquires the data of the sensor 244 in the specified time period from its timing database and/or KV storage device and provides the data to the cloud computing platform 210.

For example, the sensor 240 pushes data to the internet of things gateway 230 every 10 minutes, or the sensor 240 also pushes data to the internet of things gateway 230 while collecting data. After receiving the data pushed by the sensor 240, the internet of things gateway 230 continues to push the data to the edge computing device 220 according to the internet of things protocol. Optionally, a data pushing manner of the internet of things gateway 230 is similar to that of the sensor 240, and reference may be made to the data pushing manner of the sensor 240, which is not described herein again. The data pushed by the internet of things gateway 230 of the edge computing device 220 is processed and stored. Optionally, the edge computing device 220 compresses, merges, statistics, tags, indexes, defines the arrangement of the data, and so on. The edge computing device 220 stores the processed data in a local storage device. Further optionally, the edge computing device 220 periodically pushes the partial data in the local storage device to the cloud computing platform 210, or, in response to an instruction from the cloud computing platform 210, the edge computing device 220 pushes the partial data in the local storage device to the cloud computing platform 210 according to the instruction. Optionally, the plurality of sensors of the data acquisition system 200 in this embodiment are the same or different kinds of sensors.

In one embodiment, the data acquisition system is not provided with an internet of things gateway, and the sensors directly push data to the edge computing device. For example, the data collection system 200 does not include the internet of things gateway 230 and 232, and the sensor 240 and 248 directly push the collected data to the edge computing device 220. The data pushing manner of the sensors 240 and 248 can be referred to the description in the above embodiments, and will not be described herein.

In another embodiment, part of the sensors in the data acquisition system push data to the gateway of the internet of things, and the other part of the sensors push data to the edge computing device. For example, the data collection system 200 is not provided with the internet of things gateway 232, the sensor 240 and 242 push data to the internet of things gateway 230, the sensor 243 and 245 push data to the internet of things gateway 231, and the sensor 246 and 248 push data to the edge computing device 220.

For example, the data collection system 200 is applied to an automation control system, and the data collection system 200 needs to collect 50 or 60 kinds of data, such as gas amount, power generation amount, average power generation efficiency, and the like. The edge calculation device in the data collection system 200 in the present embodiment calculates, for example, an average power generation efficiency (average power generation efficiency is, for example, a ratio of the amount of power generation to the input energy accumulated for the past 1 hour) from the collected data every hour. The edge computing devices simply push the computing results representing the average power generation efficiency to the cloud computing platform 210. Therefore, a cloud computing platform is not needed to obtain all the collected data such as the generated energy/the input energy. Optionally, one or more of the plurality of edge computing devices (220, 221, and 223) provide the cloud computing platform 210 with the power generation amount and the input energy of the last 1 hour provided by the sensor that it is responsible for collecting per hour, so that the cloud computing platform 210 obtains the power generation amount and the input energy provided by the plurality of or all the sensors of the data collection system 200 per hour, and further obtains the average power generation efficiency of the whole system of the data collection system 200.

The edge computing equipment is used for storing and computing the acquired data, so that the data volume uploaded to the cloud computing platform is reduced, and the requirements on the storage and computing capacity of the cloud computing platform are lowered, so that the technical effects of handling the service of the data acquisition system and improving the overall performance are achieved.

Fig. 3 is a block diagram of an edge computing device provided in an embodiment of the present application.

Referring to fig. 3, the edge computing device 300 includes a solid state disk 310 and a computing unit 330. The solid state disk 310 is coupled to the computing unit 330, and the computing unit 330 is coupled to a sensor and a cloud computing platform external to the edge computing device 300.

Optionally, the edge computing device 300 further comprises a network unit 320. The solid state disk 310 is coupled with the computing unit 330 and the network unit 320, the computing unit 330 is coupled with the network unit 320, and the network unit 320 is further coupled with a sensor external to the edge computing device 300, an internet of things gateway (the internet of things gateway is not shown in fig. 3), and a cloud computing platform.

The operation of the edge computing device 300 will be described below by taking the edge computing device 220 in the data acquisition system 200 as the edge computing device 300 shown in fig. 3 and taking the data collected by the sensor as image data.

In one embodiment, the computing unit 330 receives image data pushed by the sensor 247 or the internet of things gateway 232. The calculation unit 330 stores the image data in the memory of the edge calculation device 300. The computing unit 330 further processes the image data in the memory according to the configuration information. The calculation unit 330 stores the processed image data in the solid state disk 310.

In yet another embodiment, the computing unit 330 receives image data pushed by the sensor 247 or the internet of things gateway 232. The calculation unit 330 stores the image data in the memory of the edge calculation device 300. The computing unit 330 compresses and/or marks the first data (i.e., the image data) in the memory to obtain the second data. The computing unit 330 stores the second data in the solid state disk 310.

In yet another embodiment, the network unit 320 receives image data pushed by the sensor 247 or the internet of things gateway 232. The network unit 320 stores the image data in the memory of the edge computing device 300. The network unit 320 sends a first message to the computing unit 330 instructing the computing unit 330 to process the data in memory. In response to acquiring the first message, the computing unit 330 processes the image data in the memory according to the configuration information. The calculation unit 330 stores the processed image data in the solid state disk 310. (use of configuration information is a separate embodiment; not use of configuration information is also an embodiment) (Recommendations of configuration information)

In another embodiment, the network unit 320 receives image data pushed by the sensor 247 or the internet of things gateway 232. The network unit 320 stores the image data in the memory of the edge computing device 300. The network unit 320 sends a first message to the computing unit 330 instructing the computing unit 330 to process the data in memory. In response to acquiring the first message, the computing unit 330 compresses and/or marks the first data in the memory to acquire the second data. The computing unit 330 stores the second data in the solid state disk 310.

Optionally, the computing unit 330 in this embodiment includes a configuration acquisition module, a sensor data acquisition configuration module, and a command processing module. The configuration acquisition module acquires configuration information sent by a cloud computing platform or configuration information locally stored by the edge computing device. The command processing module processes a data reading command sent by the cloud computing platform.

The sensor data acquisition and configuration module is used for operating one or more of the acquisition module, the aggregation module, the storage module and the pushing module to acquire sensor data according to configuration information provided by the configuration acquisition module and pushing the sensor data to the cloud computing platform. The configuration information indicates, for example, an address, a model, a transmission protocol of the sensor, a format of the acquired data, a storage name and/or a location of the acquired data, a kind of aggregation operation on the acquired data, a pushing manner on the acquired data, and the like.

The acquisition module acquires data to be processed sent by the network unit 320, the sensor or the gateway of the internet of things. The aggregation module generates encoded time series data (see also table 3) according to the acquired data, and marks and/or compresses the data acquired by the acquisition module to acquire statistical information and/or compressed data corresponding to the data. The storage module stores the data processed by the aggregation module into the solid state disk 310 in the form of compressed time series data and/or KV data, and reads the specified data from the solid state disk 310. The pushing module pushes the data read from the solid state disk 310 to the network unit 320 or the cloud computing platform. The command processing module acquires a data reading command sent by the cloud computing platform, and indicates one or more of the acquisition module, the aggregation module, the storage module and the push module according to the data reading command so as to process the data reading command.

In this embodiment, the configuration information is obtained by the computing unit 330 from the cloud computing platform 210. Alternatively, after the edge computing device 300 registers in the data acquisition system, the cloud computing platform 210 sends the configuration information to the edge computing device 300, the edge computing device 300 stores the configuration information locally (for example, in the memory or the solid state disk 310), and the computing unit 330 obtains the configuration information locally. Or, after the edge computing device 300 acquires the configuration information, the computing unit 330 is configured so that the subsequent data processing modes are performed according to the configuration information. The configuration information includes data acquisition configuration information, and indicates the name, type, enabling state, address and length of data to be acquired, etc. of each sensor in the data acquisition system. The configuration information also indicates the internet of things protocol (e.g., ModbusTCP) used to collect data from each sensor, the type of data collected, warehousing rules in the time series database (added to the data table and corresponding index), and triggering conditions (e.g., interval time) for collecting data. The configuration information also indicates the type and manner of aggregating the collected data, such as the compression algorithm, sorting method, and encoding method used, calculating the average value, calculating the accumulated value, and the name of the key or label used for recording the aggregated data. Optionally, the configuration information indicates that multiple data are collected from a single sensor, and/or that data are collected in multiple ways.

As an example, according to the configuration information, the sensor data acquisition configuration unit instructs the acquisition module to acquire each frame of image data in the video stream from the sensor, instructs the aggregation module to extract a human face from the image data, generates a tag for the image data containing the human face, instructs the storage module to record each frame of image data in the time series database, and stores the image data with the tag in the solid state disk 310 in KV. Optionally, the label also indicates clustering information for the face.

Still alternatively, the computing unit 330 requests the cloud computing platform 210 to update/acquire the configuration information at intervals of a preset duration (e.g., 1 hour, 1 day, 3 days, etc.). As another example, in response to receiving a command provided by cloud computing platform 210, computing unit 330 requests to obtain configuration information from cloud computing platform 210.

Optionally, the configuration information further includes data push configuration information. The data push information indicates a requirement for the edge computing device to push data to the cloud computing platform, for example, the data push configuration includes a data index of the data to be pushed or an identification pointing to the data index. As another example, the data push configuration includes algorithms to process the data (e.g., averaging, accumulating, etc.). Further optionally, the configuration information is transmitted or stored in the data acquisition system in the form of a configuration table.

In one embodiment, the computing unit 330 receives a data push request of the cloud computing platform 210, where the data push request carries a data index or an identifier indicating the data index. Chinese patent applications with application numbers 201910874351.8, 201910944900.4, 201910247686.7, 201810271465.9, 201810207416.9 and 201810332295.0 provide methods for querying or searching data in distributed storage systems. By way of example, the data push request provided by the cloud computing platform includes the query request or the request for searching data in the previous application. Specifically, one data push request (denoted as R1) desires to acquire image data of a specified time and place, and the other data push request (denoted as R2) desires to acquire image data of a human face having a specified type.

For the request R1, the calculation unit 330 acquires the address of the time-series data image data to be read in the solid-state hard disk 310 according to the data index or the identification of the data index. The calculation unit 330 sends a read data access request to the solid state disk 310 according to the address, and after receiving the read data access request, the solid state disk 310 reads out the encoded time-series data stored in the address and restores the encoded time-series data to the image data before processing (i.e., restores the image data collected by the sensor 247). Further, the computing unit also acquires image data corresponding to a specified place (a sensor corresponding to the place) and a specified time from the read data, and the computing unit 330 pushes the acquired image data to the cloud computing platform 210. Thus, for request R1, only the required image data at the specified time and place is transmitted to the cloud computing platform, and no data at other places or other times is transmitted.

For the request R2, the calculation unit 330 generates a key of the data to be read (corresponding to the type of face to be accessed) from the data index or the identification of the data index. The value corresponding to the key is retrieved from the solid state disk 310 by the storage module. The acquired value is a face image having a face type to be accessed. Alternatively, the acquired value is a thumbnail of the face image and its index in the time-series database, and the original image data in the time-series database may be further obtained. The pushing module pushes the obtained value to the cloud computing platform 210. In this embodiment, only the face data of the face type to be accessed is pushed to the cloud computing platform, so that the image data amount to be pushed to the cloud computing platform corresponding to the data index is greatly reduced. For example, 100 ten thousand pieces of image data are stored in the solid-state disk 310, and the 100 ten thousand pieces of data are divided into 1000 classes by clustering, each of which has 1000 pieces of image data. Compared with the conventional method that 100 ten thousand image data are required to be pushed to the cloud computing platform, the method and the device only need to push the 1-type (namely 1000) image data corresponding to the data index, and the effect of greatly reducing the data volume to be pushed to the cloud computing platform is achieved.

In yet another embodiment, the network unit 320 receives a data push request of the cloud computing platform 210, where the data push request carries a data index or an identifier indicating the data index. The network unit 320 obtains the address of the image data to be read in the solid state disk 310 from the memory according to the data index or the identifier of the data index. The network unit 320 sends a read data access request to the solid state disk 310 according to the address, and after receiving the read data access request, the solid state disk 310 reads the processed image data stored in the address and restores the processed image data to the image data before processing. The network unit 320 pushes the image data before processing to the cloud computing platform 210.

Optionally, in this embodiment, the processed image data stored in the solid state disk 310 is stored in a Key-Value (KV) storage manner.

TABLE 2

Index	Time value	1	Time value 2	Time value 3	…
						Item 1	12	17	10	…
Item 2	17	11	21	…
					Item 3	22	29	14	…
…	…	…	…	…

Table 2 illustrates raw data collected from sensors stored in the memory of the edge computing device. The data in table 2 was collected by a number of timing sensors. The index includes different entries, each entry corresponding to a different sensor. For example, entry 1 corresponds to sensor 240, entry 2 corresponds to sensor 241, entry 3 corresponds to sensor 247, and table 2 shows that at the time of time value 1, the data collected by sensors 240, 241, and 247 take values of 12,17, and 22, respectively; at the time of time value 2, the data collected by sensors 240, 241 and 247 take values of 17, 11 and 29, respectively; at the time of time value 3, the data collected by sensors 240, 241, and 247 take values of 10, 21, and 14, respectively. Optionally, the data to be processed is stored in the edge computing device in the form of a time series database. The time series database is implemented by the providing calculation unit 330 running software, the data of which is also stored in, for example, the solid state disk 310.

TABLE 3

Key	Value
		Item
1	Encode{12,17，…}
		Item 2	Encode{…，…，…}
…	…

Table 3 gives the data stored in Key-Value form. In this embodiment, the data in the solid state disk 310 is stored in the storage form as described in table 3.

For example, the edge computing device 300 receives the time series data in the format shown in table 2, and the aggregation module or the time series database performs format conversion on the received time series data to obtain key-value (KV) data and store the KV data in the solid state disk 310. Optionally, format conversion includes compression, merging, indexing, defining an arrangement structure, and the like.

Optionally, the aggregation module performs clustering, statistics, and the like on the received time series data shown in table 2, and optionally generates a tag. The storage module records the generated information in the form of KV in the solid-state disk 310.

As another example, according to the configuration information, data of specified characteristics is required to be pushed to the cloud computing platform. The solid state disk 310 obtains data meeting the specified characteristics from all data stored in the solid state disk according to the configuration information. For example, image data acquired by a sensor is divided into an image including a person and an image not including a person. If the specified features indicated by the configuration information include people and the shooting time is 7 o 'clock to 7 o' clock and 10 minutes, the computing unit 330 reads all image data including people and having the shooting time of 7 o 'clock to 7 o' clock and 10 minutes from the solid state disk 310 and pushes the image data to the cloud computing platform 210 according to the requirements of the configuration information.

Optionally, before outputting the data with the specified characteristics, the solid state disk 310 further decompresses the data, defines an arrangement structure, and the like, so that the output data with the specified characteristics has the same format as the data collected by the sensor.

Further optionally, the edge computing device 300 does not set the computing unit 330, and after receiving the pushed data, the edge computing device 300 stores the pushed data in the memory and instructs the solid state disk 310 to store the data. In response to the data storage instruction, the solid state disk 310 performs format conversion, compression, merging, arrangement structure definition, and the like on the pushed data, and stores the processed data.

Fig. 4 is a timing diagram illustrating device registration in a data collection system according to an embodiment of the present disclosure.

In this embodiment, the sensor registers with the internet of things gateway or the edge computing device, the internet of things gateway registers with the edge computing device, and the edge computing device registers with the cloud computing platform. When the data acquisition system is established and equipment is added to the data acquisition system, equipment registration is required. Fig. 4 shows a process of registering a sensor with an internet of things gateway, a process of registering a sensor with an edge computing device, a process of registering an internet of things gateway with an edge computing device, and a process of registering an edge computing device with a cloud computing platform.

Specifically, the process of registering the sensor with the internet of things gateway includes: the sensor pushes self-registration information to the gateway of the Internet of things; the gateway of the Internet of things receives the self-registration information; and the default sensor of the gateway of the Internet of things is successfully registered, or the gateway of the Internet of things sends a message representing successful authentication connection to the sensor. For example, the internet of things gateway and the sensor are configured such that the default sensor of the internet of things gateway is successfully registered, that is, the sensor pushes the self-registration information to the internet of things gateway and also completes the default self-registration, so that the sensor can start to push data to the internet of things gateway at any time after pushing the self-registration information to the internet of things gateway. For another example, if the internet of things gateway and the sensor are configured such that the sensor receives the message representing the successful authentication connection, and the device registration is completed, the sensor can push data to the internet of things gateway only after the sensor receives the message representing the successful authentication connection.

The process of registering a sensor with an edge computing device is similar to the process of registering a sensor with an internet of things gateway, and the only difference is that the object of the sensor pushing self-registration information is the edge computing device. The process of registering the internet of things gateway to the edge computing device is similar to the process of registering the sensor to the internet of things gateway, and the difference is that the internet of things gateway pushes self-registration information to the edge computing device.

The process of registering the edge computing device with the cloud computing platform comprises the following steps: the edge computing equipment pushes self-registration information to the cloud computing platform; the cloud computing platform receives the self-registration information; optionally, the cloud computing platform sends a message representing that the authentication connection is successful to the edge computing device; optionally, the cloud computing platform sends configuration information or a configuration table to the edge computing device; further, the edge computing device confirms the configuration information to the cloud computing platform, for example, the edge computing device sends a confirmation message carrying the configuration information to the cloud computing platform. The cloud computing platform optionally sends a push enabling indication to the edge computing device when confirming that the configuration information on the edge computing device side is correct. And if the cloud computing platform confirms that the configuration information of the edge computing equipment side is wrong, sending an instruction for correcting the configuration information to the edge computing equipment. The edge computing device may begin pushing data to the cloud computing platform without receiving an indication to correct the configuration information.

In the embodiment, after registering in the data acquisition system, the sensor positioned at the tail end of the data acquisition system starts to acquire data and pushes the data to the upper stage; after receiving the data pushed from the lower stage, the gateway and/or the edge computing device of the internet of things can also push the data to the upper stage, so that the data collected by the sensor can flow in the data collection system. For example, in fig. 4, besides pushing the collected data, the upper and lower devices may also perform other data (such as self-registration information) transfer therebetween. And after registering in the data acquisition system, each device can complete data push according to the configuration information.

According to the embodiment of the application, the cloud computing platform obtains the data of the data acquisition system through the edge computing equipment. The cloud computing platform provides a configuration table to the edge computing device, and the configuration table carries configuration information according to the embodiment of the application. And the edge computing equipment acquires data from the sensor according to the configuration information and pushes the data to the cloud computing platform. Optionally, the cloud computing platform issues the data push request by providing the configuration table to the edge computing device.

Fig. 5 is a schematic diagram of a data acquisition method of the internet of things provided in the embodiment of the present application. Taking the example that the edge computing device 300 executes the data collection method of the internet of things as shown in fig. 5, the execution process of the method is described.

In step S501, the edge computing device 300 obtains data collection configuration information. For example, the computing unit 330 obtains configuration information indicating data collection from the cloud computing platform. In step S502, the edge computing device 300 collects data from the sensors according to the data collection manner indicated by the configuration information.

In step S503, the edge computing device 300 compresses the acquired data according to the data processing manner indicated by the configuration information, obtains compressed data, and calculates aggregation information of the acquired data.

In step S504, the edge computing device 300 writes the compressed data and the aggregation information to the local storage device. After the computing unit 330 executes step S503, the compressed data and the aggregation information are written in the solid state disk 310.

In step S505, the edge computing device 300 pushes the decompressed data to the cloud computing platform according to the configuration information. In this embodiment, step S505 is an optional step, that is, when the configuration information indicates that data is pushed to the cloud computing platform after the data is processed, the computing unit 330 executes step S505; if the configuration information does not indicate that data is also pushed to the cloud computing platform, the computing unit 330 stops after executing step S504.

Fig. 6 is a schematic view of another internet of things data pushing method provided in the embodiment of the present application.

Step S601, acquiring data push configuration information.

Step S602, obtaining a data index to be pushed according to the configuration information.

Step S603, data is acquired from the storage device by using the data index.

Step S604, pushing the acquired data to the cloud computing platform.

The implementation of the method is also described, taking the edge computing device 300 as an example. For example, the edge computing device 300 obtains data push configuration information from the cloud computing platform, where the data push configuration information indicates a data index and a push opportunity of data to be pushed. The calculating unit 330 obtains the data index according to the data pushing configuration information, and reads the data to be pushed from the solid state disk 310 according to the data index. And pushing the data to be pushed to the cloud computing platform. Where step S601 is an optional step, step S601 may be selectively performed in the case where the edge computing device 300 has learned the data push configuration information.

Fig. 7 is a schematic diagram of an edge computing device pushing data to a cloud computing platform according to an embodiment of the present application.

The computing unit of the edge computing device first obtains the data index according to the configuration information. For example, the configuration information indicates that the data index of the data to be pushed is "entry 1". The computing unit accesses the solid state disk in KV, for example, according to the data index. In the solid state disk, the corresponding key (K ═ entry 1) stores compressed time-series data (denoted as Ecode {12,17, … }) corresponding to entry 1. In response to receiving the key (K ═ entry 1), the solid state disk reads the corresponding value (Ecode {12,17, … }), and also decompresses the value (Ecode {12,17, … }), moving the key (K ═ entry 1) and the decompressed value ({12,17, … }) into the memory of the edge computing device. The computing unit pushes the key in memory (K ═ entry 1) and the decompressed value ({12,17, … }) to the cloud computing platform.

According to the embodiment of the application, the solid state disk responds to the access request of the read data and also decompresses the read compressed data (such as Ecode {12,17, … }), so that the computing unit of the edge computing device can directly use the decompressed data. Optionally still, the computing unit compresses the data before writing the data into the solid state disk, and the compressed data is recorded in the solid state disk in the KV form, so as to save the storage space of the solid state disk.

Fig. 8 is a schematic diagram of an edge computing device compressing data according to an embodiment of the present application.

Fig. 8 illustrates a storage form of data collected by the sensor in the edge computing device. Data collected by the sensors is stored in the memory in the form of time series data, and each entry includes a plurality of values, for example, a value 1, a value 2, a value 3, and a value 4. And the computing unit of the edge computing device performs data compression on the data entries in the memory to obtain compressed data, and then stores the compressed data in the solid state disk in a KV storage mode.

Fig. 9 is a schematic diagram of an edge computing device reading data and pushing the data according to an embodiment of the present application.

As shown in fig. 9, the computing unit of the edge computing device first reads data from the solid state disk according to the data index (key K). After the solid state disk receives the read data request from the computing unit, the solid state disk decompresses the compressed data in addition to reading the compressed data stored in the solid state disk. And the solid state disk outputs the decompressed data to a memory of the edge computing equipment. In fig. 9, the data corresponding to the decompressed same key K, which is output by the solid state disk and includes the time-series data shown by the 4 sensor data entries, is shown in the memory. The calculation unit searches the 4 sensor data entries stored in the memory according to the configuration information or the data index to obtain, for example, the 2 nd value (denoted as "sensor data entry 1, value 2") of the sensor data entry 1. The computing unit pushes the data obtained after the coupling ("sensor data entry 1, value 2") to the cloud computing platform.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (10)

1. An edge computing device comprising a computing unit and a storage device, the computing unit coupled with at least one of a sensor, an internet of things gateway, and a cloud computing platform, the computing unit further coupled with the storage device, the cloud computing platform coupled with the edge computing device over a network;

the calculating unit acquires first data, wherein the first data is data collected by a sensor;

the computing unit compresses, counts and/or marks the first data to obtain second data;

the computing unit writes the second data to the storage device.

2. The edge computing device of claim 1, further comprising a network unit coupled with at least one of a sensor, an internet of things gateway, and a cloud computing platform, the network unit coupled with the computing unit and the storage device, the computing unit coupled with at least one of a sensor, an internet of things gateway, and a cloud computing platform through the network unit;

the computing unit obtains the first data through the network unit.

3. The edge computing device of claim 1 or 2,

the computing unit sends a first request indicating to acquire data to the storage device;

in response to the first request, the storage device decompresses and retrieves the second data to obtain third data, where the third data is a partial data of the first data;

the storage device sends the third data to the computing unit;

and the computing unit pushes the third data to a cloud computing platform.

4. The edge computing device of claim 1 or 2, wherein the computing unit is to send a second request to the storage device indicating to obtain data;

in response to the second request, the storage device decompresses the second data and stores the first data in a memory;

in response to the first data being stored in the memory, the computing unit retrieves the first data and obtains third data, where the third data is a partial data of the first data;

and the computing unit pushes the third data to a cloud computing platform.

5. The edge computing device of claim 4, wherein the second data is a compressed stored form of the first data; or the second data comprises a compressed storage form of the first data and statistical information of the first data.

6. The edge computing device of claim 2,

the network unit sends a first request indicating to acquire data to the storage device;

in response to the first request, the storage device decompresses and retrieves the second data to obtain third data, where the third data is a partial data of the first data;

the storage device sends the third data to the network element;

and the network unit pushes the third data to the cloud computing platform.

7. The edge computing device of claim 4, wherein in response to the second request, the computing unit retrieves the first data according to the configuration information, obtaining the third data;

the configuration information indicates a data index, and the third data is a part of the first data corresponding to the data.

8. A data acquisition system comprising at least one sensor, at least one edge computing device, each edge computing device coupled with at least one sensor, and a cloud computing platform coupled with the at least one edge computing device over a network;

the at least one sensor collects first data;

the at least one sensor sends the first data to the at least one edge computing device;

each edge computing device processes the first data according to configuration information to obtain second data, wherein the size of a storage space occupied by the second data is smaller than that of a storage space occupied by the first data, the formats of the first data and the second data are different, and the configuration information indicates at least one of a data acquisition mode, a data pushing mode and a data processing mode;

the edge computing device writes the second data to a storage medium, wherein the storage medium is a storage medium in the edge computing device or the storage medium is coupled with the edge computing device;

the edge computing device is the edge computing device of any of claims 1-7.

9. An internet-of-things data acquisition method applied to the data acquisition system of claim 8, the method comprising:

acquiring first data according to configuration information, wherein the first data is acquired by a sensor, and the configuration information indicates at least one of a data acquisition mode, a data pushing mode and a data processing mode;

processing the first data according to the configuration information to obtain second data, wherein the first data and the second data have different formats;

storing the second data in a local storage device.

10. A device registration method applied to the data acquisition system according to claim 8, the method comprising:

the method comprises the steps that a second device obtains a self-registration request of a first device, wherein the first device comprises a sensor, an Internet of things gateway and an edge computing device, the second device is a registered device in a data acquisition system, and the second device comprises the Internet of things gateway, the edge computing device and a cloud computing platform;

and the second equipment authenticates the first equipment according to the information carried by the self-registration request.

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