WO2023093129A1 - 物联网架构以及应用于物联网架构的数据处理方法 - Google Patents

物联网架构以及应用于物联网架构的数据处理方法 Download PDF

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WO2023093129A1
WO2023093129A1 PCT/CN2022/111464 CN2022111464W WO2023093129A1 WO 2023093129 A1 WO2023093129 A1 WO 2023093129A1 CN 2022111464 W CN2022111464 W CN 2022111464W WO 2023093129 A1 WO2023093129 A1 WO 2023093129A1
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data
application program
framework
label
architecture
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PCT/CN2022/111464
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French (fr)
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江朝晖
刘新旭
袁博浒
陈东坡
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广东跃昉科技有限公司
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
    • G16Y10/00—Economic sectors
    • G16Y10/75—Information technology; Communication
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
    • G16Y30/00—IoT infrastructure
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Definitions

  • the embodiments of the present invention relate to the technical field of the Internet of Things, and in particular to an Internet of Things architecture and a data processing method applied to the Internet of Things architecture.
  • Container Container
  • Container is a lightweight operating system layer virtualization technology for the kernel. It provides a technology that allows applications to escape the limitations of the underlying hardware. Containers share the same operating system and isolate the application process from other parts of the system. , so as to realize the isolation of computing resources and data, which can ensure the stable operation of the system.
  • the problem solved by the embodiments of the present invention is to provide an Internet of Things architecture and a data processing method applied to the Internet of Things architecture, which can analyze and mine the value of data on the device side, so that the data value can be reflected in the device-side architecture.
  • an embodiment of the present invention provides an Internet of Things architecture, including: a cloud platform; a device-side architecture, the device-side architecture includes: one or more functional frameworks; wherein, at least one of the functional frameworks is provided with Corresponding labeling module, described labeling module is used for responding to triggering request, track the operation situation in described functional frame, output corresponding data label;
  • Security component comprise block chain engine, described block chain The engine is used to accelerate processing of the data tags, obtain processed data, and upload the processed data to the cloud platform.
  • cloud data is stored in the cloud platform;
  • the functional framework includes a container framework for accommodating one or more application programs;
  • a first label marking module is set in the container framework; the first label The marking module is configured to respond to the start message of the application, track the resource usage of the application in the container framework, and output the first data label.
  • the functional framework includes an application program, the application program is used to collect data, and is also used to perform corresponding data processing in response to the user's operation request; the application program is provided with a second labeling module; the The second tag marking module is used to respond to the application program start or application program operation request, track the actual usage of the application program and the access status of the application program to the cloud platform data, and output the second data label.
  • cloud data is stored in the cloud platform;
  • the functional framework includes an artificial intelligence framework for training artificial intelligence models using data collected by applications;
  • a third label is set in the artificial intelligence framework module, the third label marking module is used to respond to the request of the application program to apply the artificial intelligence model, track the cloud data's participation in the training of the artificial intelligence model, and output the third data label.
  • the tagging module is a blockchain tagging module; the blockchain engine uploads the processed data to the cloud platform as an on-chain certificate.
  • the IoT architecture further includes: a hardware block chain drive device connected to the block chain engine, and the hardware block chain drive device is used to perform hardware accelerated processing on the chain data on the block chain.
  • the security component further includes: a secure transmission module, configured to upload the data collected by the application program to the cloud platform.
  • the embodiment of the present invention also provides a data processing method applied to the Internet of Things architecture, the Internet of Things architecture includes a device-side architecture, and the device-side architecture includes one or more functional frameworks; the Internet of Things architecture
  • the data processing method includes: responding to the trigger request, tracking the operation status within the current functional framework, and outputting the corresponding data label; performing accelerated processing on the data label, obtaining processed data, and uploading the processed data to cloud platform.
  • the functional framework includes a container framework for accommodating one or more application programs; the data processing method includes: responding to a startup message of the application program, tracking resources of the application program in the container framework Using case, output the first data label.
  • the functional framework includes an application program, the application program is used to collect data, and is also used to perform corresponding data processing in response to the user's operation request;
  • the data processing method includes: responding to application program startup or application
  • the program operation request tracks the actual usage of the application program and the application program's access to cloud platform data, and outputs a second data label.
  • the functional framework includes: an artificial intelligence framework, which is used to use the data collected by the application program to train the artificial intelligence model; the data processing method includes: responding to the request of the application program for applying the artificial intelligence model, tracking The cloud data participates in the training of the artificial intelligence model, and outputs the third data label.
  • an artificial intelligence framework which is used to use the data collected by the application program to train the artificial intelligence model
  • the data processing method includes: responding to the request of the application program for applying the artificial intelligence model, tracking The cloud data participates in the training of the artificial intelligence model, and outputs the third data label.
  • the data tag is a blockchain data tag; the data tag is accelerated to obtain processed data, and the processed data is uploaded to the cloud platform as an on-chain certificate.
  • the technical solution of the embodiment of the present invention has the following advantages: the Internet of Things architecture provided by the embodiment of the present invention, the end-side architecture includes one or more functional frameworks, and at least one of the functional frameworks is provided with a corresponding A label marking module, the label marking module is used to respond to the trigger request, track the operation within the functional framework, and output the corresponding data label; in the Internet of Things architecture, the end-side architecture directly interacts with the user , by setting the labeling module within the functional framework of the device-side architecture, it is possible to track and record the usage and operation of the data in the device-side Value analysis and mining, so that the value of data can be reflected in the device-side architecture.
  • the operation status in the current functional framework is tracked, and the corresponding data label is output; the data label is accelerated to obtain the processing and upload the processed data to the cloud platform, so that the usage and operation of the data in the end-side architecture can be tracked and recorded, and the data flow can be tracked, and the value of the data in the end-side can be analyzed correspondingly And mining, so that the value of data can be reflected in the device-side architecture.
  • FIG. 1 is a schematic structural diagram of an Internet of Things architecture in the prior art.
  • FIG. 2 is a schematic structural diagram of an embodiment of the Internet of Things architecture of the present invention.
  • FIG. 3 is a schematic flowchart of an embodiment of a data processing method applying the Internet of Things framework in the present invention.
  • FIG. 1 is a schematic structural diagram of an Internet of Things architecture in the prior art.
  • the IoT architecture 1 includes: a device-side architecture 11 and a cloud platform 12 .
  • the end-side architecture 11 generally includes: a bottom operating system 111 , a middle layer software development library 112 , a series of application programs isolated based on container technology, an artificial intelligence (AI) framework 113 and a security component 114 .
  • AI artificial intelligence
  • the cloud platform 12 is usually used for equipment management, data processing and data value analysis and mining, and the cloud platform 12 is also used for deploying a block chain module, and the block chain module is used for tracking and recording the flow of data.
  • the application program in the end-side architecture 11 will use peripherals to collect data, and then transmit the collected data to the cloud platform 12 through the secure transmission module 1141 in the security component 114, and then the cloud platform 12 will store and calculate the data , records, and then the cloud platform 12 performs demand processing, provides services for the end side, and so on.
  • the end-side architecture 11 is only responsible for data collection, and the analysis and processing of data are usually completed by the cloud platform 12, and then the value of the data is mined.
  • data is a crucial asset, and data is the value of the Internet of Things.
  • the end-side architecture 11 only becomes the data generator, not the real owner, and the value generated by the data is obtained by the cloud platform 12 and cannot be reflected on the end; and , the end side cannot perceive the real flow information of the data.
  • an embodiment of the present invention provides an Internet of Things architecture, including: a cloud platform; a device-side architecture, the device-side architecture includes: one or more functional frameworks; wherein, at least one of the functional frameworks A corresponding label marking module is provided, and the label marking module is used to track the operation within the functional framework in response to the trigger request, and output the corresponding data label; the security component includes a block chain engine, and the area The block chain engine is used to accelerate the processing of the data label, obtain the processed data, and upload the processed data to the cloud platform.
  • the end-side architecture includes one or more functional frameworks, at least one of the functional frameworks is provided with a corresponding labeling module, and the labeling module is used to respond to the trigger request, Track the operation status within the above functional framework and output corresponding data tags;
  • the device-side architecture directly interacts with users, by setting the label marking module in the functional framework of the device-side architecture, In this way, it is possible to track and record the use and operation of the data in the device-side architecture, and to track the data flow, and to analyze and mine the value of the data in the device-side, so that the data value can be reflected in the device-side architecture.
  • FIG. 2 shows a schematic structural diagram of an embodiment of the Internet of Things architecture of the present invention.
  • the IoT architecture 100 includes a cloud platform 120 and a device-side architecture 110 .
  • the cloud platform 120 performs data interaction with the end-side architecture 110 to provide device management, data processing, and data value analysis and mining.
  • the cloud platform 120 is used to store, calculate, and record data transmitted by the device-side architecture 110 , and then perform demand processing and provide services for the device-side architecture.
  • the cloud platform 120 stores cloud data, such as: perception data generated by end-side devices, usage statistics data, calculation data, and the like.
  • a blockchain module (not shown) is deployed in the cloud platform 120 for tracking and recording the flow of data.
  • the end-side architecture 110 is used for data interaction with peripheral devices, so as to collect data through the peripheral devices, and upload the collected data to the cloud platform 120 for analysis and processing.
  • the end-side architecture 110 includes: one or more functional frameworks 200; wherein at least one of the functional frameworks 200 is provided with a corresponding label marking module 300, and the label marking module 300 is configured to respond to a trigger request, The operation status in the functional framework 200 is tracked, and the corresponding data label is output; the security component 130 includes a blockchain engine 131, and the blockchain engine 131 is used to accelerate the processing of the data label and obtain the processed data , and upload the processed data to the cloud platform 120.
  • the end-side architecture 110 includes one or more functional frameworks, and the functional framework 200 is used to implement specific functions.
  • At least one of the functional frameworks 200 is provided with a corresponding labeling module 300, and the labeling module 300 is used to track the operation conditions in the functional framework 200 in response to a trigger request, and output a corresponding data label;
  • the end-side architecture 110 directly interacts with the user, and by setting the labeling module 300 in the functional framework 200 of the end-side architecture 110, the data can be identified on the end-side
  • the use and operation of the architecture 110 are tracked and recorded, and the data flow can be tracked, and the value of the data on the end side can be analyzed and mined accordingly, so that the data value can be reflected in the end-side architecture 110 .
  • the label marking module 300 is a blockchain label marking module.
  • the label marking module 300 is a block chain label marking module.
  • the functional framework 200 includes a container framework 210 for accommodating one or more application programs 220; the container framework 210 is provided with a first label marking module 310; the first label marking module 310 uses In response to the start message of the application program 220 , tracking the resource usage of the application program 220 in the container framework 210 , a first data tag is output.
  • the trigger request is a start message of the application program 220 .
  • the container framework 210 is used to accommodate one or more application programs 220, so as to realize the basic isolation of the application programs 220, thereby ensuring the stable operation of the device.
  • container (Container) technology is a lightweight operating system layer virtualization technology for the kernel, which provides a technology that allows applications to be separated from the constraints of the underlying hardware. Containers share the same operating system, and the application process and other system Partial isolation to achieve isolation of computing resources and data can ensure the stable operation of the system.
  • the end-side structure 110 is provided with a plurality of mutually isolated container frames 210 .
  • the container framework 210 accommodates two application programs 220 .
  • the number of application programs 220 accommodated in the container framework 210 is not limited thereto. In other embodiments, based on actual requirements, the number of application programs accommodated in the container framework may also be other numbers.
  • the first label marking module 310 is configured to track the resource usage of the application program 220 in the container framework 210 in response to the start message of the application program 220 , and output a first data label.
  • the current container framework 210 when the current container framework 210 detects the startup message of the application program 220, it enters into the first label marking module 310 in the container framework 210 for processing.
  • the tracking of the resource usage of the application program 220 in the container framework 210 by the first label marking module 310 includes: triggering the specific application program 220 started by the first label marking module 310, the application Resources occupied by the program 220 in the current container frame 210 .
  • the resources occupied by the application program 220 in the current container framework 210 may include: the memory occupation used by the application program 220, the proportion of the processor (for example: CPU), input/output (Input/Output, I /O) usage, and network occupancy and other information.
  • the functional framework 200 includes an application program 220, and the application program 220 is used to collect data, and is also used to perform corresponding data processing in response to a user's operation request.
  • the application program 220 collects data through a specific peripheral device.
  • the application program 220 is an intelligent voice assistant program, which is used to collect the user's real-time voice and audio information, perform feature recognition, and reply to the user's voice, and the application program 220 communicates and interacts with the microphone device , to collect real-time sound and audio information through the microphone device.
  • the application program 220 is provided with a second label marking module 320; the second label marking module 320 is used to track the application program 220 in response to the application program 220 startup or application program 220 operation request.
  • the actual usage status and the access status of the application program 220 to the cloud platform data output the second data label.
  • the trigger request is the application program 220 startup or application program 220 operation request.
  • the operation request of the application program 220 refers to an operation request within the application program 220 .
  • the second label marking module 320 tracks the actual usage of the application 220 , which refers to: the application's CPU usage, memory usage, network bandwidth usage, and data I/O ratio.
  • the functions provided by the application program to the user can be recorded, and the value of the application program to the user can be judged accordingly.
  • the functional framework 200 includes an artificial intelligence framework 230 for training an artificial intelligence model using the data collected by the application program 220 .
  • the artificial intelligence framework 230 is provided with a third labeling module 330, and the third labeling module 330 is used to respond to the request of the application program 220 to apply the artificial intelligence model, and track the cloud data to participate in the artificial intelligence model. In the training situation, the third data label is output.
  • the trigger request is a request of the application program 220 to apply the artificial intelligence model.
  • the security component 130 is used to ensure the security of the IoT architecture 100 .
  • the blockchain engine 131 is used to accelerate the processing of the data tags to obtain processed data.
  • the label marking module 300 is a blockchain label marking module
  • the data label is correspondingly a blockchain data label
  • the blockchain engine 131 accelerates processing of the blockchain data label
  • the processed data is obtained, and the processed data is uploaded to the cloud platform 120 as an on-chain certificate, which helps to ensure the authenticity and validity of the data, makes the data difficult to be tampered with, and improves the security of the data.
  • the security component 130 further includes: a secure transmission module 132 configured to upload the data collected by the application program 220 to the cloud platform 120 .
  • the data collected by the application program 220 is uploaded to the cloud platform 120 through the secure transmission module 132, which is beneficial to improve the security of data transmission.
  • the secure transmission module 132 includes a data encryption module (not shown in the figure), and the data encryption module is used for encrypting the data collected by the application program 220, thereby improving data security.
  • the security component 130 further includes: a root of trust 133, which is used for secure boot, data authentication, and key derivation; a secure boot module 134, which stores a boot key and is used for The data authentication during the start-up process of the start-up key includes safe update and signature verification of firmware stored on the Flash.
  • the IoT architecture 100 further includes: a bottom operating system 150 and a middle layer software development library 140 .
  • the underlying operating system 150 may include an operating system kernel, a board-level support package, a device driver, and a hardware abstraction layer.
  • the middle layer software development library 140 may include software development kits, function libraries, middleware, and the like.
  • the IoT architecture 100 also includes: a hardware block chain drive device (not shown), connected to the block chain engine 131, and the hardware block chain drive device is used to Uplink data is processed with hardware acceleration.
  • a hardware block chain drive device (not shown), connected to the block chain engine 131, and the hardware block chain drive device is used to Uplink data is processed with hardware acceleration.
  • Fig. 3 is a schematic flow chart of an embodiment of the data processing method of the present invention.
  • the data processing method applies an Internet of Things architecture, wherein the Internet of Things architecture includes a device-side architecture, and the device-side architecture includes one or more functional frameworks.
  • the end-side architecture 110 is used for data interaction with peripheral devices, so as to collect data through the peripheral devices, and upload the collected data to the cloud platform 120 for analysis and processing.
  • the end-side architecture 110 includes one or more functional frameworks 200, and the functional frameworks 200 are used to implement specific functions.
  • the data processing method may include the following steps.
  • Step S1 In response to the trigger request, track the operation situation in the current functional framework, and output the corresponding data label.
  • Step S2 Perform accelerated processing on the data tags, obtain processed data, and upload the processed data to the cloud platform.
  • the operation status in the current functional framework is tracked, and the corresponding data label is output; the data label is accelerated to obtain the processed data, and the The processed data is uploaded to the cloud platform, so that the usage and operation of the data on the end-side architecture can be tracked and recorded, and the data flow can be tracked, and the value of the data on the end-side can be analyzed and mined accordingly, so that the value of the data is in the It is reflected in the end-side architecture.
  • step S1 in response to the trigger request, track the operation status in the current functional framework 200 and output the corresponding data label.
  • the operation status in the current functional framework 200 is tracked, and corresponding data tags are output; in the IoT architecture 100, the end-side architecture 110 directly interacts with the user, The operation status is tracked and the corresponding data tags are output, so that the usage and operation status of the data in the end-side architecture 110 can be tracked and recorded, and the data flow direction can be tracked, and the value of the data on the end-side can be analyzed and mined accordingly. The value of data is reflected in the device-side architecture 110 .
  • the data label is a blockchain data label, which can ensure the uniqueness and authenticity of the data, and is correspondingly beneficial to ensure the security of the data.
  • the functional framework 200 includes a container framework 210 for accommodating one or more application programs 220 .
  • the data processing method includes: responding to the start message of the application program, tracking the resource usage of the application program 220 in the container framework 210, and outputting a first data label.
  • the container framework 210 is provided with a first label marking module 310; the first label marking module 310 is used to track the application program 220 in the container framework 210 in response to the start message of the application program 220 The resource usage, output the first data label.
  • the trigger request is a start message of the application program 220 .
  • the current container framework 210 when the current container framework 210 detects the startup message of the application program 220, it enters into the first label marking module 310 in the container framework 210 for processing.
  • tracking the resource usage of the application program 220 in the container framework 210 includes: triggering the specific application program 220 started by the first label marking module 310, and the application program 220 in the current container framework 210 resources used.
  • the resources occupied by the application program 220 in the current container framework 210 may include: the memory occupation used by the application program 220, the proportion of the processor (for example: CPU), input/output (Input/Output, I /O) usage, and network occupancy and other information.
  • the functional framework 200 includes an application program 220, and the application program 220 is used to collect data, and is also used to perform corresponding data processing in response to a user's operation request.
  • the data processing method includes: responding to the application program startup or application program operation request, tracking the actual usage of the application program and the access status of the application program to the cloud platform data, and outputting the second data label.
  • the application 220 is provided with a second tagging module 320; the second tagging module 320 is used to track the application The actual usage of the program 220 and the access of the application program 220 to the cloud platform data output the second data label.
  • the trigger request is a request for starting the application program 220 or an operation request for the application program 220 .
  • the operation request of the application program 220 refers to an operation request within the application program 220 .
  • tracking the actual usage of the application program 220 refers to: the application program's CPU usage, memory usage, network bandwidth usage, and data I/O ratio.
  • the functions provided by the application program to the user can be recorded, and the value of the application program to the user can be judged accordingly.
  • the functional framework 200 includes an artificial intelligence framework 230 for training an artificial intelligence model using the data collected by the application program 220 .
  • the data processing method includes: responding to the request of the application program 220 for applying the artificial intelligence model, tracking cloud data participating in the training of the artificial intelligence model, and outputting a third data label.
  • the artificial intelligence framework 230 is provided with a third labeling module 330, and the third labeling module 330 is used to track the The cloud data participates in the training of the artificial intelligence model, and outputs a third data label.
  • the trigger request is a request of the application program 220 to apply the artificial intelligence model.
  • step S2 perform accelerated processing on the data tags, obtain processed data, and upload the processed data to the cloud platform.
  • the block chain engine 131 performs accelerated processing on the data tags to obtain processed data.
  • the data tag is a blockchain data tag; the data tag is accelerated to obtain the processed data, and the processed data is uploaded to the cloud platform as an on-chain certificate, which is beneficial to guarantee The authenticity and validity of the data makes the data not easy to be tampered with, thereby improving the security of the data.

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Abstract

一种物联网架构以及应用于物联网架构的数据处理方法，所述物联网架构包括：云端平台；端侧架构，所述端侧架构包括：一个或多个功能框架；其中，至少一个所述功能框架内设置有相应的标签标记模块，所述标签标记模块用于响应于触发请求，对所述功能框架内的操作情况进行跟踪，输出相应的数据标签；安全组件，包括区块链引擎，所述区块链引擎用于对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至所述云端平台。本发明实施例能够对数据在端侧架构的使用情况、操作情况进行跟踪记录，并且能够跟踪数据流向，相应能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构中得以体现。

Description

物联网架构以及应用于物联网架构的数据处理方法 技术领域
本发明实施例涉及物联网技术领域，尤其涉及一种物联网架构以及应用于物联网架构的数据处理方法。
背景技术
随着物联网的广泛应用，无数的物联网设备会产生大量的数据，数据的收集、处理和分析将会变的非常复杂；云端平台则可以提供海量数据的存储，价值挖掘等；AI(Artificial Intelligence，人工智能)的接入，则让IoT(Internet Of Things，万物互联)有了连接的“大脑”，深度学习和机器学习成了预测未来的关键；而区块链技术的应用，则让数据的交换，有了有源可朔、提升互信。
随着应用场景的不断的增加，需要进行应用程序的基本隔离，以保证设备的稳定运行，不至于“一毁俱毁”。容器(Container)技术是一种内核轻量级的操作系统层虚拟化技术，它提供了一种应用脱离底层硬件限制的技术，容器共享同一个操作系统，将应用进程和系统其他的部分隔离开，以实现计算资源和数据的隔离，即可保证系统的稳定运行问题。
但是，目前物联网架构中仍存在数据价值体现不均衡以及端侧无法追踪数据的问题。
技术问题
本发明实施例解决的问题是提供一种物联网架构以及应用于物联网架构的数据处理方法，能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构中得以体现。
技术解决方案
为解决上述问题，本发明实施例提供一种物联网架构，包括：云端平台；端侧架构，所述端侧架构包括：一个或多个功能框架；其中， 至少一个所述功能框架内设置有相应的标签标记模块，所述标签标记模块用于响应于触发请求，对所述功能框架内的操作情况进行跟踪，输出相应的数据标签；安全组件，包括区块链引擎，所述区块链引擎用于对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至所述云端平台。
可选的，所述云端平台内存储有云端数据；所述功能框架包括容器框架，用于容纳一个或多个应用程序；所述容器框架内设置有第一标签标记模块；所述第一标签标记模块用于响应于所述应用程序的启动消息，跟踪所述应用程序在容器框架中的资源使用情况，输出第一数据标签。
可选的，所述功能框架包括应用程序，所述应用程序用于采集数据，还用于响应于用户的操作请求进行相应的数据处理；所述应用程序内设置有第二标签标记模块；所述第二标签标记模块用于响应于应用程序启动或应用程序操作请求，跟踪所述应用程序的实际使用情况、以及应用程序对云端平台数据的访问情况，输出第二数据标签。
可选的，所述云端平台内存储有云端数据；所述功能框架包括人工智能框架，用于利用应用程序采集的数据进行人工智能模型的训练；所述人工智能框架内设置有第三标签标记模块，所述第三标签标记模块用于响应于应用程序的应用人工智能模型的请求，追踪所述云端数据参与所述人工智能模型的训练情况，输出第三数据标签。
可选的，所述标签标记模块为区块链标签标记模块；所述区块链引擎将所述处理后数据上传至所述云端平台作为上链凭证。
可选的，所述物联网架构还包括：硬件区块链驱动设备，与所述区块链引擎相连，所述硬件区块链驱动设备用于对区块链上链数据进行硬件加速处理。
可选的，所述安全组件还包括：安全传输模块，用于将所述应用程序采集的数据上传至所述云端平台。
相应的，本发明实施例还提供一种应用于物联网架构的数据处理方法，所述物联网架构包括端侧架构，所述端侧架构包括一个或多个功能框架；所述物联网架构的数据处理方法包括：响应于触发请求，对当前功能框架内的操作情况进行跟踪，输出相应的数据标签；对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台。
可选的，所述功能框架包括容器框架，用于容纳一个或多个应用程序；所述数据处理方法包括：响应于所述应用程序的启动消息，跟踪所述应用程序在容器框架中的资源使用情况，输出第一数据标签。
可选的，所述功能框架包括应用程序，所述应用程序用于采集数据，还用于响应于用户的操作请求进行相应的数据处理；所述数据处理方法包括：响应于应用程序启动或应用程序操作请求，跟踪所述应用程序的实际使用情况、以及应用程序对云端平台数据的访问情况，输出第二数据标签。
可选的，所述功能框架包括：人工智能框架，用于利用应用程序所采集的数据进行人工智能模型的训练；所述数据处理方法包括：响应于应用程序的应用人工智能模型的请求，追踪云端数据参与所述人工智能模型的训练情况，输出第三数据标签。
可选的，所述数据标签为区块链数据标签；对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台作为上链凭证。
有益效果
与现有技术相比，本发明实施例的技术方案具有以下优点：本发明实施例提供的物联网架构，端侧架构包括一个或多个功能框架，至少一个所述功能框架内设置有相应的标签标记模块，所述标签标记模块用于响应于触发请求，对所述功能框架内的操作情况进行跟踪，输出相应的数据标签；在物联网架构中，端侧架构是直接与用户进行交互的，通过在端侧架构中的功能框架内设置所述标签标记模块，从而 能够对数据在端侧架构的使用情况、操作情况进行跟踪记录，并且能够跟踪数据流向，相应能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构中得以体现。
本发明实施例提供的应用于物联网架构的数据处理方法中，响应于触发请求，对当前功能框架内的操作情况进行跟踪，输出相应的数据标签；对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台，从而能够对数据在端侧架构的使用情况、操作情况进行跟踪记录，并且能够跟踪数据流向，相应能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构中得以体现。
附图说明
图1是现有技术一种物联网架构的结构示意图。
图2是本发明物联网架构一实施例的结构示意图。
图3是本发明应用物联网架构的数据处理方法一实施例的流程示意图。
本发明的实施方式
由背景技术可知，目前物联网架构中仍存在数据价值体现不均衡以及端侧无法追踪数据的问题。现结合一种物联网架构分析数据价值体现不均衡以及端侧无法追踪数据的原因。
图1是现有技术一种物联网架构的结构示意图。
如图1所示，以一种基于区块链的物联网架构为示例，所述物联网架构1包括：端侧架构11与云端平台12。
其中，所述端侧架构11通常包括：底层操作系统111、中间层软件开发库112、基于容器技术隔离的一系列应用程序、人工智能(AI)框架113以及安全组件114。
所述云端平台12通常用于进行设备管理、数据处理以及数据价值的分析挖掘，所述云端平台12还用于部署区块链模块，所述区块 链模块用于跟踪和记录数据的流向。
一般的，端侧架构11中的应用程序会运用外设采集数据，然后通过安全组件114中的安全传输模块1141将采集到的数据传送到云端平台12，之后云端平台12对数据进行存储、计算、记录，进而云端平台12进行需求处理、面向端侧提供服务等。
在上述物联网架构1中，端侧架构11只负责数据的收集，而数据的分析以及处理等通常均由云端平台12完成，进而挖掘出数据的价值。在物联网时代，数据是至关重要的资产，数据才是物联网的价值所在。但是，在上述物联网架构中，端侧架构11仅仅变成了数据的产生者，而不是真正的拥有者，数据所能产生的价值均被云端平台12侧获取，无法在端侧体现；并且，端侧无法感知数据的真实流向信息。
为了解决所述技术问题，本发明实施例提供一种物联网架构，包括：云端平台；端侧架构，所述端侧架构包括：一个或多个功能框架；其中，至少一个所述功能框架内设置有相应的标签标记模块，所述标签标记模块用于响应于触发请求，对所述功能框架内的操作情况进行跟踪，输出相应的数据标签；安全组件，包括区块链引擎，所述区块链引擎用于对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至所述云端平台。
本发明实施例提供的物联网架构，端侧架构包括一个或多个功能框架，至少一个所述功能框架内设置有相应的标签标记模块，所述标签标记模块用于响应于触发请求，对所述功能框架内的操作情况进行跟踪，输出相应的数据标签；在物联网架构中，端侧架构是直接与用户进行交互的，通过在端侧架构中的功能框架内设置所述标签标记模块，从而能够对数据在端侧架构的使用情况、操作情况进行跟踪记录，并且能够跟踪数据流向，相应能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构中得以体现。
为使本发明实施例的上述目的、特征和优点能够更为明显易懂， 下面结合附图对本发明的具体实施例做详细的说明。参考图2，示出了本发明物联网架构一实施例的结构示意图。
如图2所示，本实施例中，所述物联网架构100包括云端平台120和端侧架构110。
所述云端平台120与所述端侧架构110进行数据的交互，用于提供设备的管理、数据的处理、以及数据价值的分析和挖掘。
具体地，所述云端平台120用于对端侧架构110传输的数据进行存储、计算以及记录等，进而进行需求处理，并面向端侧架构提供服务等。
所述云端平台120内存储有云端数据，例如：端侧设备产生的感知数据、使用统计数据以及计算数据等。
本实施例中，所述云端平台120内部署有区块链模块(图未示)，用于跟踪和记录数据的流向。
所述端侧架构110用于与外围设备进行数据交互，以便通过外围设备进行数据的采集，并将采集到的数据上传至云端平台120进行分析和处理。
所述端侧架构110包括：一个或多个功能框架200；其中，至少一个所述功能框架200内设置有相应的标签标记模块300，所述标签标记模块300用于响应于触发请求，对所述功能框架200内的操作情况进行跟踪，输出相应的数据标签；安全组件130，包括区块链引擎131，所述区块链引擎131用于对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至所述云端平台120。
所述端侧架构110包括一个或多个功能框架，所述功能框架200用于实现特定的功能。
本实施例中，至少一个所述功能框架200内设置有相应的标签标记模块300，所述标签标记模块300用于响应于触发请求，对所述功能框架200内的操作情况进行跟踪，输出相应的数据标签；在物联网 架构100中，端侧架构110是直接与用户进行交互的，通过在端侧架构110中的功能框架200内设置所述标签标记模块300，从而能够对数据在端侧架构110的使用情况、操作情况进行跟踪记录，并且能够跟踪数据流向，相应能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构110中得以体现。
本实施例中，所述标签标记模块300为区块链标签标记模块。通过使所述标签标记模块300为区块链标签标记模块，能够保证数据的唯一性和真实性，相应有利于保障数据的安全性。
作为一实施例，所述功能框架200包括容器框架210，用于容纳一个或多个应用程序220；所述容器框架210内设置有第一标签标记模块310；所述第一标签标记模块310用于响应于所述应用程序220的启动消息，跟踪所述应用程序220在容器框架210中的资源使用情况，输出第一数据标签。
相应地，对于所述第一标签标记模块310来说，所述触发请求为所述应用程序220的启动消息。
所述容器框架210用于容纳一个或多个应用程序220，以实现应用程序220的基本隔离，进而保证设备的稳定运行。具体地，容器(Container)技术是一种内核轻量级的操作系统层虚拟化技术，它提供了一种应用脱离底层硬件限制的技术，容器共享同一个操作系统，将应用进程和系统其他的部分隔离开，以实现计算资源和数据的隔离，即可保证系统的稳定运行问题。
作为一种示例，所述端侧架构110中设置有多个相互隔离的容器框架210。
作为一种示例，所述容器框架210容纳有两个应用程序220。所述容器框架210内所容纳的应用程序220的数量不仅限于此。在其他实施例中，基于实际的需求，所述容器框架内所容纳的应用程序的数量还可以为其他数量。
所述第一标签标记模块310用于响应于所述应用程序220的启动消息，跟踪所述应用程序220在容器框架210中的资源使用情况，输出第一数据标签。
具体地，本实施例中，在当前容器框架210检测到应用程序220的启动消息时，即进入所述容器框架210内的第一标签标记模块310进行处理。
作为一种实施例，所述第一标签标记模块310跟踪所述应用程序220在容器框架210中的资源使用情况包括：触发所述第一标签标记模块310启动的具体应用程序220、所述应用程序220在当前容器框架210内所占用的资源。
更具体地，所述应用程序220在当前容器框架210内所占用的资源可以包括：应用程序220使用的内存占用、处理器(例如：CPU)的占比、输入/输出(Input/Output，I/O)的使用情况、以及网络占用情况等信息。
作为一种实施例，所述功能框架200包括应用程序220，所述应用程序220用于采集数据，还用于响应于用户的操作请求进行相应的数据处理。
具体地，所述应用程序220通过特定的外围设备进行数据的采集。
作为一种示例，所述应用程序220为智能语音助手程序，用于收集用户的实时声音和音频信息，进行特征识别，并且对用户的声音进行回复，所述应用程序220与麦克风设备进行通信交互，以通过所述麦克风设备采集实时声音和音频信息。
本实施例中，所述应用程序220内设置有第二标签标记模块320；所述第二标签标记模块320用于响应于应用程序220启动或应用程序220操作请求，跟踪所述应用程序220的实际使用情况、以及应用程序220对云端平台数据的访问情况，输出第二数据标签。
相应地，对于所述第二标签标记模块320来说，所述触发请求为 所述应用程序220启动或应用程序220操作请求。
其中，所述应用程序220操作请求指的是，所述应用程序220内部的操作请求。
所述第二标签标记模块320跟踪应用程序220的实际使用情况指的是：应用程序的CPU使用率、内存占用情况、网络带宽使用情况、以及数据I/O的占比。
通过跟踪所述应用程序220的实际使用情况，从而能够记录应用程序为用户提供的功能，相应能够判别应用程序对用户的价值。
记录应用程序220对云端平台数据的访问情况，从而一方面能够追踪云端平台数据的使用流向，一方面也可以统计云端平台数据的使用情况，进而能够挖掘出云端平台数据的价值。
作为一实施例，所述功能框架200包括人工智能框架230，用于利用应用程序220采集的数据进行人工智能模型的训练。
所述人工智能框架230内设置有第三标签标记模块330，所述第三标签标记模块330用于响应于应用程序220的应用人工智能模型的请求，追踪所述云端数据参与所述人工智能模型的训练情况，输出第三数据标签。
相应地，对于所述第三标签标记模块330来说，所述触发请求为应用程序220的应用人工智能模型的请求。
通过追踪云端数据参与人工智能模型的训练情况，从而有效统计云端数据在端侧使用情况，以提升数据价值的挖掘。
所述安全组件130用于保证所述物联网架构100的安全性。
其中，所述区块链引擎131用于对所述数据标签进行加速处理，获得处理后数据。
本实施例中，所述标签标记模块300为区块链标签标记模块，所述数据标签相应为区块链数据标签，所述区块链引擎131对所述区块 链数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台120作为上链凭证，从而有利于保证数据的真实有效性，使得数据不易被篡改，进而提高了数据的安全性。
需要说明的是，本实施例中，所述安全组件130还包括：安全传输模块132，用于将所述应用程序220采集的数据上传至所述云端平台120。
将应用程序220采集的数据上传至云端平台120，以便所述云端平台120用于对应用程序220传输的数据进行存储、计算以及记录等，进而进行需求处理，并面向端侧架构提供服务等，相应进行数据的处理、以及数据价值的分析和挖掘。
通过安全传输模块132将应用程序220采集的数据上传至云端平台120，有利于提高数据传输的安全性。
具体地，所述安全传输模块132包括数据加密模块(图未示)，所述数据加密模块用于对所述应用程序220采集的数据进行加密处理，从而提高数据的安全性。
本实施例中，所述安全组件130还包括：信根133，所述信根133用于安全启动、数据鉴权以及密钥派生等；安全启动模块134，存储有启动密钥，用于基于所述启动密钥的启动过程中的数据鉴权，包括安全的更新、以及Flash上存储的固件的验签。
通过所述安全启动模块134，从而能够对启动过程中进行安全保证，还能够实现数据访问的安全隔离，进而保证数据在端侧设备中的安全性。
本实施例中，所述物联网架构100还包括：底层操作系统150和中间层软件开发库140。
其中，所述底层操作系统150可以包括操作系统核、板级支持包、设备驱动以及硬件抽象层等。
所述中间层软件开发库140可以包括软件开发包、功能库、以及 中间件等。
本实施例中，所述物联网架构100还包括：硬件区块链驱动设备(图未示)，与所述区块链引擎131相连，所述硬件区块链驱动设备用于对区块链上链数据进行硬加速处理。
为了解决所述问题，本发明还提供一种应用于物联网架构的数据处理方法。图3是本发明数据处理方法一实施例流程示意图。
本实施例中，所述数据处理方法应用物联网架构，其中，所述物联网架构包括端侧架构，所述端侧架构包括一个或多个功能框架。
所述端侧架构110用于与外围设备进行数据交互，以便通过外围设备进行数据的采集，并将采集到的数据上传至云端平台120进行分析和处理。
所述端侧架构110包括一个或多个功能框架200，所述功能框架200用于实现特定的功能。
本实施例中，所述数据处理方法，可以包括如下的步骤。
步骤S1：响应于触发请求，对当前功能框架内的操作情况进行跟踪，输出相应的数据标签。
步骤S2：对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台。
本实施例提供的数据处理方法中，响应于触发请求，对当前功能框架内的操作情况进行跟踪，输出相应的数据标签；对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台，从而能够对数据在端侧架构的使用情况、操作情况进行跟踪记录，并且能够跟踪数据流向，相应能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构中得以体现。
为了便于理解和说明，下面结合本发明实施例提供的物联网架构，对本实施例的数据处理方法进行详细的说明。
参考图3，步骤S1：响应于触发请求，对当前功能框架200内的操作情况进行跟踪，输出相应的数据标签。
响应于触发请求，对当前功能框架200内的操作情况进行跟踪，输出相应的数据标签；在物联网架构100中，端侧架构110是直接与用户进行交互的，通过对当前功能框架200内的操作情况进行跟踪，输出相应的数据标签，从而能够对数据在端侧架构110的使用情况、操作情况进行跟踪记录，并且能够跟踪数据流向，相应能够对数据在端侧的价值进行分析和挖掘，使得数据价值在端侧架构110中得以体现。
本实施例中，所述数据标签为区块链数据标签，能够保证数据的唯一性和真实性，相应有利于保障数据的安全性。
作为一实施例，所述功能框架200包括容器框架210，用于容纳一个或多个应用程序220。所述数据处理方法包括：响应于所述应用程序的启动消息，跟踪所述应用程序220在容器框架210中的资源使用情况，输出第一数据标签。
具体地，所述容器框架210内设置有第一标签标记模块310；所述第一标签标记模块310用于响应于所述应用程序220的启动消息，跟踪所述应用程序220在容器框架210中的资源使用情况，输出第一数据标签。
相应地，对于所述第一标签标记模块310来说，所述触发请求为所述应用程序220的启动消息。
具体地，本实施例中，在当前容器框架210检测到应用程序220的启动消息时，即进入所述容器框架210内的第一标签标记模块310进行处理。
作为一种实施例，跟踪所述应用程序220在容器框架210中的资源使用情况包括：触发所述第一标签标记模块310启动的具体应用程序220、所述应用程序220在当前容器框架210内所占用的资源。
更具体地，所述应用程序220在当前容器框架210内所占用的资源可以包括：应用程序220使用的内存占用、处理器(例如：CPU)的占比、输入/输出(Input/Output，I/O)的使用情况、以及网络占用情况等信息。
作为一种实施例，所述功能框架200包括应用程序220，所述应用程序220用于采集数据，还用于响应于用户的操作请求进行相应的数据处理。
相应地，所述数据处理方法包括：响应于应用程序启动或应用程序操作请求，跟踪所述应用程序的实际使用情况、以及应用程序对云端平台数据的访问情况，输出第二数据标签。
具体地，本实施例中，所述应用程序220内设置有第二标签标记模块320；所述第二标签标记模块320用于响应于应用程序220启动或应用程序220操作请求，跟踪所述应用程序220的实际使用情况、以及应用程序220对云端平台数据的访问情况，输出第二数据标签。
相应地，对于所述第二标签标记模块320来说，所述触发请求为所述应用程序220启动或应用程序220操作请求。
其中，所述应用程序220操作请求指的是，所述应用程序220内部的操作请求。
本实施例中，跟踪应用程序220的实际使用情况指的是：应用程序的CPU使用率、内存占用情况、网络带宽使用情况、以及数据I/O的占比。
通过跟踪所述应用程序220的实际使用情况，从而能够记录应用程序为用户提供的功能，相应能够判别应用程序对用户的价值。
记录应用程序220对云端平台数据的访问情况，从而一方面能够追踪云端平台数据的使用流向，一方面也可以统计云端平台数据的使用情况，进而能够挖掘出云端平台数据的价值。
作为一实施例，所述功能框架200包括人工智能框架230，用于 利用应用程序220采集的数据进行人工智能模型的训练。
相应地，本实施例中，所述数据处理方法包括：响应于应用程序220的应用人工智能模型的请求，追踪云端数据参与所述人工智能模型的训练情况，输出第三数据标签。
具体地，作为一种实施例，所述人工智能框架230内设置有第三标签标记模块330，所述第三标签标记模块330用于响应于应用程序220的应用人工智能模型的请求，追踪所述云端数据参与所述人工智能模型的训练情况，输出第三数据标签。
相应地，对于所述第三标签标记模块330来说，所述触发请求为应用程序220的应用人工智能模型的请求。
通过追踪云端数据参与人工智能模型的训练情况，从而有效统计云端数据在端侧使用情况，以提升数据价值的挖掘。
继续参考图3，步骤S2：对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台。
具体地，通过区块链引擎131对所述数据标签进行加速处理，获得处理后数据。
本实施例中，所述数据标签为区块链数据标签；对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台作为上链凭证，从而有利于保证数据的真实有效性，使得数据不易被篡改，进而提高了数据的安全性。
虽然本发明披露如上，但本发明并非限定于此。任何本领域技术人员，在不脱离本发明的精神和范围内，均可作各种更动与修改，因此本发明的保护范围应当以权利要求所限定的范围为准。

Claims (12)

  1. 一种物联网架构，其特征在于，包括：
    云端平台；
    端侧架构，所述端侧架构包括：
    一个或多个功能框架；其中，至少一个所述功能框架内设置有相应的标签标记模块，所述标签标记模块用于响应于触发请求，对所述功能框架内的操作情况进行跟踪，输出相应的数据标签；
    安全组件，包括区块链引擎，所述区块链引擎用于对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至所述云端平台。
  2. 如权利要求1所述的物联网架构，其特征在于，所述云端平台内存储有云端数据；
    所述功能框架包括容器框架，用于容纳一个或多个应用程序；所述容器框架内设置有第一标签标记模块；所述第一标签标记模块用于响应于所述应用程序的启动消息，跟踪所述应用程序在容器框架中的资源使用情况，输出第一数据标签。
  3. 如权利要求1或2所述的物联网架构，其特征在于，所述功能框架包括应用程序，所述应用程序用于采集数据，还用于响应于用户的操作请求进行相应的数据处理；
    所述应用程序内设置有第二标签标记模块；所述第二标签标记模块用于响应于应用程序启动或应用程序操作请求，跟踪所述应用程序的实际使用情况、以及应用程序对云端平台数据的访问情况，输出第二数据标签。
  4. 如权利要求1所述的物联网架构，其特征在于，所述云端平台内存储有云端数据；
    所述功能框架包括人工智能框架，用于利用应用程序采集的数据 进行人工智能模型的训练；
    所述人工智能框架内设置有第三标签标记模块，所述第三标签标记模块用于响应于应用程序的应用人工智能模型的请求，追踪所述云端数据参与所述人工智能模型的训练情况，输出第三数据标签。
  5. 如权利要求1所述的物联网架构，其特征在于，所述标签标记模块为区块链标签标记模块；
    所述区块链引擎将所述处理后数据上传至所述云端平台作为上链凭证。
  6. 如权利要求1所述的物联网架构，其特征在于，所述物联网架构还包括：硬件区块链驱动设备，与所述区块链引擎相连，所述硬件区块链驱动设备用于对区块链上链数据进行硬件加速处理。
  7. 如权利要求3所述的物联网架构，其特征在于，所述安全组件还包括：安全传输模块，用于将所述应用程序采集的数据上传至所述云端平台。
  8. 一种应用于物联网架构的数据处理方法，所述物联网架构包括端侧架构，所述端侧架构包括一个或多个功能框架，其特征在于，所述物联网架构的数据处理方法包括：
    响应于触发请求，对当前功能框架内的操作情况进行跟踪，输出相应的数据标签；
    对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台。
  9. 如权利要求8所述的数据处理方法，其特征在于，所述功能框架包括容器框架，用于容纳一个或多个应用程序；
    所述数据处理方法包括：响应于所述应用程序的启动消息，跟踪所述应用程序在容器框架中的资源使用情况，输出第一数据标签。
  10. 如权利要求8或9所述的数据处理方法，其特征在于，所述功能 框架包括应用程序，所述应用程序用于采集数据，还用于响应于用户的操作请求进行相应的数据处理；
    所述数据处理方法包括：响应于应用程序启动或应用程序操作请求，跟踪所述应用程序的实际使用情况、以及应用程序对云端平台数据的访问情况，输出第二数据标签。
  11. 如权利要求8所述的数据处理方法，其特征在于，所述功能框架包括：人工智能框架，用于利用应用程序所采集的数据进行人工智能模型的训练；
    所述数据处理方法包括：响应于应用程序的应用人工智能模型的请求，追踪云端数据参与所述人工智能模型的训练情况，输出第三数据标签。
  12. 如权利要求8所述的数据处理方法，其特征在于，所述数据标签为区块链数据标签；对所述数据标签进行加速处理，获得处理后数据，并将所述处理后数据上传至云端平台作为上链凭证。
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