WO2021197353A1 - 数据分流方法、装置、设备及介质 - Google Patents

数据分流方法、装置、设备及介质 Download PDF

Info

Publication number
WO2021197353A1
WO2021197353A1 PCT/CN2021/084177 CN2021084177W WO2021197353A1 WO 2021197353 A1 WO2021197353 A1 WO 2021197353A1 CN 2021084177 W CN2021084177 W CN 2021084177W WO 2021197353 A1 WO2021197353 A1 WO 2021197353A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
computing device
target computing
gateway
upf
Prior art date
Application number
PCT/CN2021/084177
Other languages
English (en)
French (fr)
Inventor
任骋
林嘉莉
Original Assignee
中移(上海)信息通信科技有限公司
中国移动通信集团有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 中移(上海)信息通信科技有限公司, 中国移动通信集团有限公司 filed Critical 中移(上海)信息通信科技有限公司
Publication of WO2021197353A1 publication Critical patent/WO2021197353A1/zh

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/40—Support for services or applications
    • 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
    • H04L67/50—Network services
    • H04L67/56—Provisioning of proxy services
    • H04L67/565—Conversion or adaptation of application format or content
    • H04L67/5651—Reducing the amount or size of exchanged application data
    • 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
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
    • H04L67/1004—Server selection for load balancing
    • H04L67/1008—Server selection for load balancing based on parameters of servers, e.g. available memory or workload

Definitions

  • This application relates to the field of communication technology, and in particular to a data distribution method, device, device, and computer-readable storage medium.
  • PLC Programmable Logic Controllers
  • the scheme of collecting and analyzing data and uploading it to the central server through a wired switch is generally adopted for unified processing.
  • new industrial applications such as video surveillance, robots, and intelligent production lines are emerging one after another. If all data is uploaded to the business center for processing like a traditional gateway, the pressure on the central server is greater, and many controls have high requirements for delay.
  • the traditional central processing model cannot meet the high concurrent volume of business processing.
  • the embodiments of the present application provide a data distribution method, device, equipment, and computer-readable storage medium.
  • an embodiment of the present application provides a data offloading method, which is used in a gateway, and the method includes: obtaining load information of a network device and first data sent by a terminal, where the first data includes the data of the first data Data type: According to the data type of the first data and the load information of the network device, the target computing device is determined for the target computing device to perform arithmetic processing on the first data.
  • network devices include gateways, mobile edge computing MEC servers, and central cloud servers; target computing devices include any of the following options: gateways, mobile edge computing (Mobile Edge Computing, MEC) servers , Central cloud server.
  • MEC Mobile Edge Computing
  • the method when the target computing device is an MEC server or a central cloud server, the method further includes: determining a user panel function (UPF) according to the identifier of the target computing device and the first data. ); Send the first data to the target computing device according to the UPF.
  • UPF user panel function
  • the first data includes data attribute information; determining the target computing device according to the data type of the first data and the load information of the network device includes: according to the data type of the first data, the network device The load information and data attribute information of the system determine the target computing device.
  • acquiring the first data sent by the terminal includes: acquiring the second data sent by the terminal, and preprocessing the second data to obtain the first data.
  • an embodiment of the present application provides a data offloading method, which is used in an MEC server, and the method includes: receiving first data sent by a gateway, where the first data is sent by the gateway according to UPF, and UPF is based on the gateway.
  • the identification of the MEC server and the first data are determined; the first data is calculated to obtain the result of the calculation; the result of the calculation is sent to the target terminal.
  • an embodiment of the present application provides a data offloading device, which is used in a gateway, and the device includes: an acquisition module configured to acquire load information of a network device and first data sent by a terminal, where the first data The data type includes the first data; the determining module is configured to determine the target computing device according to the data type of the first data and the load information of the network device, for the target computing device to perform arithmetic processing on the first data.
  • the network device includes a gateway, an MEC server, and a central cloud server; the target computing device includes any one of the following options: a gateway, an MEC server, and a central cloud server.
  • the device further includes: a sending module configured to determine the UPF according to the identifier of the target computing device and the first data when the target computing device is an MEC server or a central cloud server; Send the first data to the target computing device.
  • a sending module configured to determine the UPF according to the identifier of the target computing device and the first data when the target computing device is an MEC server or a central cloud server; Send the first data to the target computing device.
  • the first data includes data attribute information; the determining module is configured to determine the target computing device according to the data type of the first data, the load information of the network device, and the data attribute information.
  • the acquisition module is configured to acquire the second data sent by the terminal, and preprocess the second data to obtain the first data.
  • an embodiment of the present application provides a data offloading device, which is used in an MEC server.
  • the device includes: a receiving module configured to receive first data sent by a gateway, where the first data is sent by the gateway according to UPF The UPF is determined by the gateway according to the MEC server identifier and the first data; the calculation module is configured to perform calculation processing on the first data to obtain the calculation processing result; the sending module is configured to send the calculation processing result to the target terminal.
  • an embodiment of the present application provides a data shunt device, which includes: a processor and a memory storing computer program instructions; the processor implements the first aspect or any of the implementable manners of the first aspect when the computer program instructions are executed by the processor.
  • the data distribution method described in, or the data distribution method described in the second aspect is implemented when the processor executes computer program instructions.
  • the embodiments of the present application provide a computer-readable storage medium on which computer program instructions are stored.
  • the computer program instructions are executed by a processor, the first aspect or any of the first aspects can be implemented
  • the data distribution method described in the above, or the computer program instructions when executed by a processor implement the data distribution method described in the second aspect.
  • the data distribution method, device, device, and computer-readable storage medium provided by the embodiments of the present application obtain load information of a network device and first data sent by a terminal, according to the data type of the first data and the load information of the network device , Determine the target computing device for the target computing device to perform arithmetic processing on the first data.
  • the target computing device for computing can be determined according to the data's demand for computing power and computing time, and the data will be diverted to the target computing device, thereby reducing the pressure on the central cloud server, reducing data delay, improving processing efficiency, and reducing Control response time.
  • FIG. 1 is a schematic structural diagram of an edge computing platform provided by an embodiment of the present application.
  • FIG. 2 is a schematic flowchart of a data distribution method provided by an embodiment of the present application.
  • FIG. 3 is a schematic flowchart of another data distribution method provided by an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of another data distribution method provided by an embodiment of the present application.
  • FIG. 5 is a schematic structural diagram of a data distribution device provided by an embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of another data distribution device provided by an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of a data distribution device provided by an embodiment of the present application.
  • the term "and/or" is merely an association relationship describing associated objects, indicating that there can be three relationships, for example, A and/or B, which can mean that A exists alone and A exists at the same time. And B, there are three cases of B alone.
  • the industrial gateway is usually connected to the equipment PLC through the serial port RS232/485 or Registered Jack (RJ) 45, and the industrial gateway transmits the production data to the equipment through the wired three-layer switch architecture (access, convergence, core)
  • the server interacts in a data acquisition and monitoring control system (Supervisory Control And Data Acquisition, SCADA) or a manufacturing execution system (Manufacturing Execution System, MES) to realize remote centralized control.
  • SCADA Supervisory Control And Data Acquisition
  • MES Manufacturing Execution System
  • the gateway uploads all data to the business center for processing, and then sends the calculation results to the terminal, which puts a lot of pressure on the central server, and many controls have high requirements for delay, leading to central processing.
  • the model cannot satisfy high-concurrency business processing.
  • the three-layer architecture (access, convergence, and core) in the wired network has a certain impact on network performance. The more layers, the more devices are used, the greater the delay, and the lower the performance efficiency.
  • the embodiments of the present application provide a data distribution method, device, device, and computer-readable storage medium.
  • the load information of the network device determines the target computing device for the target computing device to perform arithmetic processing on the first data.
  • the target computing device for computing can be determined according to the data's demand for computing power and computing time, and the data will be diverted to the target computing device, thereby reducing the pressure on the central cloud server, reducing data delay, improving processing efficiency, and reducing Control response time.
  • the data distribution method may be applied to an edge computing platform, and the gateway of the edge computing platform is an edge gateway, where the edge computing platform may be as shown in FIG. 1.
  • Fig. 1 is a schematic structural diagram of an edge computing platform provided by an embodiment of the present application.
  • the edge computing platform may include a central cloud, an edge cloud, and an edge gateway.
  • the central cloud can not only manage all edge clouds and edge gateways, provide a unified portal for users and managers, but also display the number of edge clouds, resource usage, and business operation status.
  • the central cloud may refer to a central cloud server.
  • the edge cloud can be a privatized deployment of the central cloud, with network forwarding, storage, big data processing, intelligent data analysis and other capabilities to reduce response delays, reduce central cloud pressure, and reduce bandwidth costs.
  • the edge cloud can be deployed hierarchically in metropolitan area networks, access networks, and base station-level networks.
  • the edge cloud may refer to the MEC server.
  • the edge gateway can provide intelligent network access and high-bandwidth, low-latency network bearer, and rely on open connections, computing and storage resources and application programming interfaces (Application Programming Interface, API) to support the flexibility of multi-ecological services in the field Deployment, local computing and communication can be performed directly through the base station without being affected by the core network.
  • API Application Programming Interface
  • the edge gateway structure can be divided into a hardware layer and a software layer.
  • the hardware layer can support the gateway to have the functions of heterogeneous computing, networks (such as software-defined networks, low-latency networks), and time-series database storage.
  • the edge gateway may have a computing module, a network module, and a storage module.
  • the network module may be a 5th generation mobile networks (5G) module.
  • the software layer can include a device service layer, a core service layer, a support service layer, and an output service layer. Among them, the core service layer and device service layer can complete protocol analysis, physical and logical connections, computing services, and microservice construction.
  • the supporting service layer and the output service layer can complete the end-to-end business flow, including resource feedback, business requests, policy mobilization, multi-view presentation functions, and process, schedule, and publish the microservices established by the core service layer.
  • the edge gateway may include functions such as industrial data collection, data analysis, and 5G network slicing construction.
  • industrial data collection can refer to the use of ubiquitous sensing technology for real-time and efficient collection of multi-source equipment, heterogeneous systems, operating environment, people and other element information and cloud aggregation.
  • Industrial data collection can correspond to the edge layer in the edge computing platform architecture.
  • the edge gateway can be connected to different terminal equipment, systems and products through various communication means to collect large-scale and deep-level industrial data, and then carry out agreements on heterogeneous data. Conversion and edge processing to build the data foundation of the edge computing platform.
  • industrial data collection can include data collection of industrial field equipment and data collection of smart products/equipment outside the factory in a broad sense.
  • the data type of the data collected by the industrial data may include resource type, product type, order type, environment type, image type, and so on.
  • resource data may refer to resource data associated with product production.
  • the operating parameters continuously generated by the sensor such as the vibration of the machine axis, the force of the robot gripper, the electrical parameters of the actuator, the driver and the processing board, the image parameters of the virtual camera), the tool parameters, and the resource status (such as the program execution Errors, program enable/disable, power collisions, calibration errors), the quality of the operations performed (such as duration, part recognition and visual positioning) and energy consumption (such as the duration of each product and operation), etc.
  • Product data can refer to the product data associated with product production, such as the data about the formula required by the product provided by the human-machine interface, and the embedded device on the product to control the processing process (such as geometric measurement, shape finishing, component alignment) ) And data of events that occurred during execution (such as processing traceability during power failure and recovery) and so on. It can be understood that product data can be used in industrial scenarios of flexible manufacturing.
  • the man-machine interface referred to here can access the cloud server.
  • Order data can refer to the order data associated with the production of the product.
  • the embedded device on the product summarizes the data about the conversion execution mode of the product formula in a special batch processing entry, and has precedent operation sequences and assignments for each operation.
  • Environmental data may refer to environmental data associated with product production, for example, it may include data generated by monitoring the environment. For example, in a factory that produces special products (such as radiopharmaceuticals), the sensor collects data such as weight, temperature, relative humidity, pressure, and radioactivity, or in a workstation using a vision system, the sensor collects lighting change data. Since the system needs to respond quickly in the event of an accident, environmental data control requires extremely low latency.
  • special products such as radiopharmaceuticals
  • Image data can refer to image data associated with product production, such as product image data generated based on the quality inspection capabilities of machine vision, image data generated by the operation of video surveillance operators, and various inspection robots. Image data. Image data usually requires large transmission bandwidth and high computing power. It can be understood that the invalid information of the data can be deleted before transmission, which improves the efficiency of data transmission and calculation.
  • Data analysis can mean that the edge gateway integrates the analysis capabilities of multiple industrial protocols.
  • the analysis capabilities of multiple industrial protocols can be used to obtain data reported by various terminals to achieve the conversion and unification of data formats.
  • a variety of industrial protocols can include Ethernet industrial protocol (EtherNet/Industry Protocol, Ethernet/IP), Modbus protocol, Controller Area Network (CAN), Transmission Control Protocol/Internet Protocol (Transmission Control Protocol/Internet) Protocol, TCP/IP), Profinet and other mainstream PLC protocols, and Siemens, Omron, Mitsubishi and other private PLC protocols.
  • the 5G physical network can be converted from a single network to a logical partition based on the Public Land Mobile Network (PLMN)
  • PLMN Public Land Mobile Network
  • the network that is, the 5G physical network is divided into network slices.
  • network slicing has appropriate network isolation, resources, optimized topology and specific configuration, which can meet various service requirements.
  • the construction of 5G network slicing can mean that the edge gateway as a radio access network node can receive routing instructions based on the core network or core network slicing to the radio access network (Radio Access Network, RAN) slice. This instruction can be used at the edge A logical tunnel is established between the gateway and the base station to establish an end-to-end network slice.
  • Radio Access Network Radio Access Network
  • FIG. 2 is a schematic flowchart of a data distribution method provided by an embodiment of the present application.
  • the data distribution method may be applied to an edge gateway.
  • the data distribution method may include S210 to S220. in,
  • S210 Obtain load information of the network device and the first data sent by the terminal.
  • the device service layer of the edge gateway may obtain the second data sent by the terminal, and then the core service layer of the edge gateway preprocesses the second data to obtain the first data.
  • the device service layer of the edge gateway may obtain the second data sent by the terminal according to the analytical capabilities of multiple industrial communication protocols.
  • the core service layer of the edge gateway preprocesses the second data according to the data type of the second data.
  • the preprocessing may include logical operations, data normalization, standardization processing, data noise reduction, redundant data deletion, and so on.
  • the first data may include the data type of the first data
  • the second data may refer to the data collected by industrial data
  • the second data may include the data type of the second data
  • the network equipment may include edge gateways, MEC servers, and central clouds. Server, it can be understood that the data types of the first data and the second data may include resource types, product types, order types, environment types, image types, and so on.
  • S220 Determine the target computing device according to the data type of the first data and the load information of the network device.
  • the support service layer of the edge gateway can integrate the data type of the first data on the computing capability requirements of the network device and the load information of the current network device to determine the target computing device for the target computing device to perform computing processing on the first data.
  • the target computing device may include any one of an edge gateway, an MEC server, and a central cloud server.
  • the edge gateway can be determined as the target computing device for this type of data.
  • the first data may further include data attribute information
  • the supporting service layer of the edge gateway may determine the target computing device according to the data type of the first data, the load information of the network device, and the data attribute information.
  • the data attribute information may include the data size of the first data, the Internet Protocol (IP) address of the data source of the first data, the data pointing to the IP address of the first data, etc., where the data source IP address is the terminal's The IP address, the data pointing to the IP address is the IP address of the target terminal that receives the result of the operation processing of the first data.
  • IP Internet Protocol
  • the target computing device by obtaining the load information of the network device and the first data sent by the terminal, according to the data type of the first data and the load information of the network device, the target computing device is determined to be used for the target computing device Perform arithmetic processing on the first data.
  • the target computing device for computing can be determined according to the data's demand for computing power and computing time, and the data will be diverted to the target computing device, thereby reducing the pressure on the central cloud server, reducing data delay, improving processing efficiency, and reducing Control response time.
  • the Application Function (AF) of the output service layer of the edge gateway may determine the UPF according to the identification of the target computing device and the first data, and the UPF may be used to plan the transmission path corresponding to the first data.
  • the AF can generate a data grooming request according to the identification of the target computing device and the first data, and then determine the UPF according to the data grooming request.
  • the identifier of the target computing device may be the IP address of the target computing device, and the data grooming request may include the network name, the network slice selection identifier, the target terminal information of the target terminal, and so on. It can be understood that the network name may be the name of the network access point, and the target terminal information may include user information and location information of the target terminal, and so on.
  • the AF can determine the UPF according to the identification of the target computing device and the first data.
  • the AF can determine the UPF as the UPF of the MEC server according to the identifier of the edge gateway and the first data.
  • the edge gateway can send the operation processing result to the target terminal based on the UPF.
  • the operation processing result is obtained after the first data is processed by the operation module of the edge gateway.
  • the calculation processing result may be sent to the base station through the 5G air interface, and the base station transmits the calculation processing result to the target terminal through the 5G air interface.
  • the AF can determine the UPF according to the identification of the target computing device and the first data, and the edge gateway sends the first data to the target computing device according to the UPF to use Perform arithmetic processing on the first data on the target computing device.
  • the AF can determine the UPF as the UPF of the MEC server according to the MEC server's identifier and the first data, and the edge gateway sends the first data to the MEC server according to the UPF.
  • sending the first data by the edge gateway to the MEC server may mean that the edge gateway establishes a logical tunnel with the base station, establishes an end-to-end network slice, and transmits the first data to the MEC server based on the network slice.
  • the edge gateway can The first data is sent to the base station through the 5G air interface, and the base station can send the first data to the MEC server through the core network.
  • the AF can determine that the UPF is the UPF of the public network according to the identification of the central cloud server and the first data, and the edge gateway sends the first data to the central cloud server according to the UPF.
  • the edge gateway sending the first data to the central cloud server may mean that the edge gateway transmits the first data to the central cloud server based on the network slice.
  • the edge gateway may send the first data to the base station through the 5G air interface.
  • the base station can send the first data to the central cloud server in the public network.
  • the central cloud server can receive the first data, perform arithmetic processing on the first data, and obtain the result of the arithmetic processing, and send the result of the arithmetic processing to the base station.
  • the base station uses the 5G air interface Send the result of the calculation to the target terminal.
  • the processing flow in the MEC server may be as shown in FIG. 3, where FIG. 3 is a schematic flow diagram of another data distribution method provided in an embodiment of the present application . It can be seen from FIG. 3 that the data distribution method may include S310 to S330. in,
  • S310 Receive the first data sent by the gateway.
  • the first data is sent by the edge gateway according to the UPF, and the UPF is determined by the gateway according to the identifier of the MEC server and the first data.
  • S320 Perform arithmetic processing on the first data to obtain a result of the arithmetic processing.
  • the first data that is distributed is received to perform arithmetic processing on the first data.
  • the pressure on the central cloud server can be reduced, data latency can be reduced, processing efficiency can be improved, and control response time can be reduced.
  • FIG. 4 is a schematic flowchart of another data distribution method provided by the embodiment of the present application.
  • the determined target computing device is the MEC. server.
  • the specific steps include:
  • Step 1 It can be used through industrial Ethernet, industrial optical fiber network, industrial bus, ZigBee protocol (ZigBee), long-distance radio (Long Range Radio, LoRa), Bluetooth Low Energy (BLE), MeoH, sub-1GHZ Wait for the communication technology to connect the terminal to the edge gateway.
  • the terminal can be an industrial field device, an intelligent product/equipment. Modify the IP address of the terminal, and modify the data upload address of the terminal to the IP address of the edge gateway.
  • the edge gateway can establish a communication connection with the base station through the internal network module.
  • the device service layer of the edge gateway can be compatible with industrial communication protocols such as Modbus, CAN, and Profinet based on technologies such as protocol analysis and conversion, middleware, etc., to achieve data format conversion and unification, and obtain the second data reported by the terminal.
  • industrial communication protocols such as Modbus, CAN, and Profinet based on technologies such as protocol analysis and conversion, middleware, etc.
  • Step 3 The core service layer of the edge gateway can preprocess the second data according to the data type of the second data to obtain the first data.
  • the preprocessing can include logical operations, data normalization, standardization, data noise reduction, and redundancy. I deleted the data and so on.
  • Step 4 The support service layer of the edge gateway can integrate the data type of the first data on the computing capability requirements of the network device and the load information of the current network device to determine the target computing device for computing the first data, and then the target can be determined The IP of the computing device.
  • the AF of the edge gateway output service layer can create a data grooming request to the target terminal based on the IP of the target computing device and the first data.
  • the data grooming request may include the network name, the network slice selection identifier, and the target terminal information of the target terminal. , Time information for user plane data rerouting, etc., select a UPF with the nearest location for the target terminal.
  • the determined target computing device is the MEC server, therefore, the UPF is the UPF of the MEC server, and the edge gateway may transmit the first data to the MEC server based on the UPF.
  • the transmission and processing can be performed according to steps 6, 7, 8, and 9.
  • Step 6 The edge gateway may forward the first data to the base station through the 5G air interface.
  • the base station may send the first data to the MEC server on the base station side through the core network, and perform arithmetic processing on the first data through the MEC server to obtain the result of the arithmetic processing.
  • Step 8 The MEC server can return the calculation processing result to the base station through the core network.
  • Step 9 The base station can transmit back to the target terminal through the 5G air interface for the target terminal to perform corresponding operations.
  • Step 1 Connect the quality inspection camera as the terminal to the edge gateway through a network cable, and configure the camera IP address to be the same network segment as the gateway IP address.
  • Step 2 The quality inspection camera on the production line records the video data of the product to be inspected, and the edge gateway obtains the video data uploaded by the quality inspection camera.
  • Step 3 The video data from the quality inspection camera needs to be cleaned at the core service layer of the edge gateway to retain the video data containing product information, and then cut the video data containing product information into pictures to be inspected, waiting for subsequent analysis.
  • Step 4 Since the pre-sorting robot arm as the target terminal needs to sort the products to be inspected, it has high requirements for control delay.
  • the support service layer of the edge gateway decides to hand over the image analysis of the pictures to be inspected
  • the MEC server on the base station side closer to the edge side performs processing.
  • Step 5 The AF of the output service layer of the edge gateway constructs a data grooming request, and selects the UPF of the MEC server at the base station side based on the data grooming request.
  • Step 6 The edge gateway can forward the image to be inspected to the base station through the 5G air interface.
  • Step 7 The base station can send the pictures to be inspected to the MEC server on the base station side through the core network, and compare the models in the MEC server to classify the products to be inspected (for example, qualified or unqualified).
  • Step 8 The MEC server can return the classification result to the base station through the core network.
  • Step 9 The base station can send back to the robotic arm that needs to sort the products to be inspected through the 5G air interface to complete the product inspection and sorting.
  • the terminal camera video and picture data are not uploaded to the central cloud server through the public network for cloud computing, but the MEC server on the base station side completes the classification calculation of the product to be inspected, and quickly returns it to the execution through the core network.
  • the robotic arm of the sorting operation can meet the low-latency requirements of machine vision quality inspection and greatly improve the quality inspection efficiency of the production line.
  • 5G network communication while meeting the low latency of industrial control, it simplifies the data transmission channel, reduces the network level and the equipment used, and realizes the flattening of the network.
  • FIG. 5 is a schematic structural diagram of a data distribution device provided by an embodiment of the present application.
  • the data distribution device 500 may be applied to a gateway.
  • the data distribution device 500 may include: an acquisition module 510 and a determination module 520.
  • the obtaining module 510 is configured to obtain load information of the network device and first data sent by the terminal, where the first data includes a data type of the first data.
  • the determining module 520 is configured to determine a target computing device according to the data type of the first data and the load information of the network device, so as to use the target computing device to perform arithmetic processing on the first data.
  • the network device includes a gateway, an MEC server, and a central cloud server;
  • the target computing device includes any one of the following options: a gateway, an MEC server, and a central cloud server.
  • the apparatus 500 further includes: a sending module, configured to determine the UPF according to the identifier of the target computing device and the first data when the target computing device is the MEC server or the central cloud server, and send the UPF to the target computing device according to the UPF. Send the first data.
  • a sending module configured to determine the UPF according to the identifier of the target computing device and the first data when the target computing device is the MEC server or the central cloud server, and send the UPF to the target computing device according to the UPF. Send the first data.
  • the first data includes data attribute information.
  • the determining module 520 is configured to determine the target computing device according to the data type of the first data, the load information of the network device, and the data attribute information.
  • the obtaining module 510 is configured to obtain the second data sent by the terminal, and preprocess the second data to obtain the first data.
  • the data shunt device 500 in the embodiment of the present application determines the target computing device for the target computing by acquiring the load information of the network device and the first data sent by the terminal, and according to the data type of the first data and the load information of the network device The device performs arithmetic processing on the first data.
  • the target computing device for computing can be determined according to the data requirements for computing power and computing time, and the data can be shunted to the target computing device, thereby reducing the pressure on the central cloud server, reducing data delay, improving processing efficiency, and reducing Control response time.
  • the acquisition module 510 can be implemented by the processor in the data shunt device 500 in combination with a communication interface
  • the determination module 520 can be implemented by the processor in the data shunt device 500
  • the sending module can be implemented by the processor in the data shunt device 500
  • the communication interface is realized.
  • the data distribution device 500 of the embodiment of the present application may correspond to the execution subject of the data distribution method in FIG. 2 of the embodiment of the present application, and the operation and/or function of each module/unit of the data distribution device 500
  • the description of the corresponding part in the data distribution method in FIG. 2 of the embodiment of the present application please refer to the description of the corresponding part in the data distribution method in FIG. 2 of the embodiment of the present application. For brevity, details are not repeated here.
  • FIG. 6 is a schematic structural diagram of another data distribution device provided by an embodiment of the present application.
  • the data distribution device 600 may be applied to an MEC server. As shown in FIG. 6, the data distribution device 600 may include: a receiving module 610, a computing module 620. The sending module 630.
  • the receiving module 610 is configured to receive the first data sent by the gateway, where the first data is sent by the gateway according to UPF, and the UPF is determined by the gateway according to the identifier of the MEC server and the first data.
  • the arithmetic module 620 is configured to perform arithmetic processing on the first data to obtain a result of the arithmetic processing.
  • the sending module 630 is configured to send the operation processing result to the target terminal.
  • the data shunt device 600 of the embodiment of the present application receives the shunted first data to perform arithmetic processing on the first data.
  • the pressure on the central cloud server can be reduced, data latency can be reduced, processing efficiency can be improved, and control response time can be reduced.
  • the arithmetic module 620 can be implemented by a processor in the data shunt device 600; the receiving module 610 and the sending module 630 can be implemented by a communication interface in the data shunt device 600.
  • the data distribution device 600 of the embodiment of the present application may correspond to the execution subject of the data distribution method in FIG. 3 of the embodiment of the present application, and the operation and/or function of each module/unit of the data distribution device 600
  • the description of the corresponding part in the data distribution method of FIG. 3 in the above embodiment of the present application please refer to the description of the corresponding part in the data distribution method of FIG. 3 in the above embodiment of the present application. For brevity, details are not described herein again.
  • FIG. 7 is a schematic diagram of the hardware structure of a data distribution device provided by an embodiment of the present application.
  • the data distribution device 700 in this embodiment includes an input device 701, an input interface 702, a central processing unit 703, a memory 704, an output interface 705, and an output device 706.
  • the input interface 702, the central processing unit 703, the memory 704, and the output interface 705 are connected to each other through the bus 710, and the input device 701 and the output device 706 are connected to the bus 710 through the input interface 702 and the output interface 705, respectively, and then to the data shunt device 700 other components are connected.
  • the input device 701 receives input information from the outside, and transmits the input information to the central processing unit 704 through the input interface 702; the central processing unit 703 processes the input information based on the computer executable instructions stored in the memory 704 to generate output Information, the output information is temporarily or permanently stored in the memory 704, and then the output information is transmitted to the output device 706 through the output interface 705; the output device 706 outputs the output information to the outside of the data distribution device 700 for the user to use.
  • the data distribution device 700 shown in FIG. 7 includes: a memory 704 configured to store a program; a processor 703 configured to run a program stored in the memory to execute the data distribution provided in the embodiment shown in FIG. 2 The method or the data distribution method provided by the embodiment shown in FIG. 3.
  • the embodiment of the present application also provides a computer-readable storage medium on which computer program instructions are stored; when the computer program instructions are executed by a processor, the data shunt method or diagram provided by the embodiment shown in FIG. 2 is implemented. 3 shows the data distribution method provided by the embodiment.
  • the functional blocks shown in the above-mentioned structural block diagram can be implemented as hardware, software, firmware, or a combination thereof.
  • it can be an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, plug-ins, function cards, and so on.
  • ASIC application specific integrated circuit
  • the elements of this application are programs or code segments used to perform required tasks.
  • the program or code segment may be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link through a data signal carried in a carrier wave.
  • "Machine-readable medium” may include any medium that can store or transmit information.
  • machine-readable media examples include electronic circuits, semiconductor memory devices, read-only memory (Read-Only Memory, ROM), flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (Radio Frequency, RF) link, etc.
  • the code segment can be downloaded via a computer network such as the Internet, an intranet, and so on.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Hardware Design (AREA)
  • General Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Information Transfer Between Computers (AREA)

Abstract

本申请提供一种数据分流方法、装置、设备及介质。该方法用于网关，包括：获取网络设备的负载信息、以及终端发送的第一数据，其中，第一数据包括第一数据的数据类型；根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。

Description

数据分流方法、装置、设备及介质
相关申请的交叉引用
本申请基于申请号为202010234561.3、申请日为2020年03月30日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请涉及通信技术领域，尤其涉及一种数据分流方法、装置、设备和计算机可读存储介质。
背景技术
在制造业中，普遍使用可编程逻辑控制器(Programmable Logic Controller，PLC)对生产制造的设备进行离散控制，通过PLC控制，可实现各种指令的下发，以及各类机器运行状态数据的回传。
在相关技术的工业控制系统中，普遍采用将数据收集解析后通过有线交换机上传到中心服务器统一处理的方案。而在现代工业中，视频监控，机器人，智能产线等新型工业应用层出不穷。如果像传统网关一样把所有数据统一上传到业务中心处理，对中心服务器的压力较大，很多控制对时延的要求较高，传统的中心处理模式无法满足高并发量的业务处理。
发明内容
本申请实施例提供了一种数据分流方法、装置、设备和计算机可读存储介质。
第一方面，本申请实施例提供一种数据分流方法，该方法用于网关，该方法包括：获取网络设备的负载信息、以及终端发送的第一数据，其中，第一数据包括第一数据的数据类型；根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。
在第一方面的一些可实现方式中，网络设备包括网关、移动边缘计算MEC服务器、中心云服务器；目标运算设备包括以下选项中任意一项：网关、移动边缘计算(Mobile Edge Computing，MEC)服务器、中心云服务器。
在第一方面的一些可实现方式中，当目标运算设备是MEC服务器或中心云服务器时，该方法还包括：根据目标运算设备的标识和第一数据，确定用户面功能(User Panel Function，UPF)；根据UPF向目标运算设备发送第一数据。
在第一方面的一些可实现方式中，第一数据包括数据属性信息；根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，包括：根据第一数据的数据类型、网络设备的负载信息和数据属性信息，确定目标运算设备。
在第一方面的一些可实现方式中，获取终端发送的第一数据，包括：获取终端的发送的第二数据，对第二数据进行预处理，得到第一数据。
第二方面，本申请实施例提供一种数据分流方法，该方法用于MEC服务器，该方法包括：接收网关发送的第一数据，其中，第一数据是网关根据UPF发送的，UPF是网关根据MEC服务器的标识和第一数据确定的；对第一数据进行运算处理，得到运算处理结果；向目标终端发送运算处理结果。
第三方面，本申请实施例提供一种数据分流装置，该装置用于网关，该装置包括：获取模块，配置为获取网络设备的负载信息、以及终端发送的第一数据，其中，第一数据包括第一数据的数据类型；确定模块，配置为根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。
在第三方面的一些可实现方式中，网络设备包括网关、MEC服务器、中心云服务器；目标运算设备包括以下选项中任意一项：网关、MEC服务器、中心云服务器。
在第三方面的一些可实现方式中，该装置还包括：发送模块，配置为当目标运算设备是MEC服务器或中心云服务器时，根据目标运算设备的标识和第一数据，确定UPF；根据UPF向目标运算设备发送第一数据。
在第三方面的一些可实现方式中，第一数据包括数据属性信息；所述确定模块，配置为根据第一数据的数据类型、网络设备的负载信息和数据属性信息，确定目标运算设备。
在第三方面的一些可实现方式中，所述获取模块，配置为获取终端的发送的第二数据，对第二数据进行预处理，得到第一数据。
第四方面，本申请实施例提供一种数据分流装置，该装置用于MEC服务器，该装置包括：接收模块，配置为接收网关发送的第一数据，其中，第一数据是网关根据UPF发送的，UPF是网关根据MEC服务器的标识和第一数据确定的；运算模块，配置为对第一数据进行运算处理，得到运算处理结果；发送模块，配置为向目标终端发送运算处理结果。
第五方面，本申请实施例提供一种数据分流设备，该设备包括：处理器以及存储有计算机程序指令的存储器；处理器执行计算机程序指令时实 现第一方面或者第一方面任一些可实现方式中所述的数据分流方法，或者，处理器执行计算机程序指令时实现第二方面所述的数据分流方法。
第六方面，本申请实施例提供一种计算机可读存储介质，计算机可读存储介质上存储有计算机程序指令，计算机程序指令被处理器执行时实现第一方面或者第一方面任一些可实现方式中所述的数据分流方法，或者，计算机程序指令被处理器执行时实现第二方面所述的数据分流方法。
本申请实施例提供的一种数据分流方法、装置、设备和计算机可读存储介质，获取网络设备的负载信息、以及终端发送的第一数据，根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。如此，能够根据数据对计算能力和计算时间的需求，确定进行运算处理的目标运算设备，将数据分流至该目标运算设备，进而减轻中心云服务器的压力，减少数据时延，提高处理效率，降低控制的响应时间。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的一种边缘计算平台的结构示意图；
图2是本申请实施例提供的一种数据分流方法的流程示意图；
图3是本申请实施例提供的另一种数据分流方法的流程示意图；
图4是本申请实施例提供的另一种数据分流方法的流程示意图；
图5是本申请实施例提供的一种数据分流装置的结构示意图；
图6是本申请实施例提供的另一种数据分流装置的结构示意图；
图7是本申请实施例提供的一种数据分流设备的结构示意图。
具体实施方式
下面将详细描述本申请的各个方面的特征和示例性实施例，为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细描述。应理解，此处所描述的具体实施例仅被配置为解释本申请，并不被配置为限定本申请。对于本领域技术人员来说，本申请可以在不需要这些具体细节中的一些细节的情况下实施。下面对实施例的描述仅仅是为了通过示出本申请的示例来提供对本申请更好的理解。
需要说明的是，在本申请实施例中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含， 从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
在本申请实施例中，术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，比如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。
相关技术中，通常采用工业网关通过串口RS232/485或注册插座(Registered Jack，RJ)45与设备PLC连接，工业网关经过有线的三层交换机架构(接入，汇聚，核心)将生产数据传送到服务器，在数据采集与监视控制系统(Supervisory Control And Data Acquisition，SCADA)或制造执行系统(Manufacturing Execution System，MES)中交互，从而实现远程集中控制。
但是，在相关技术的生产中，网关把所有数据统一上传到业务中心处理，再将计算结果送至终端，对中心服务器的压力较大，而且很多控制对时延的要求较高，导致中心处理模式无法满足高并发量的业务处理。此外，有线网络中的三层架构(接入，汇聚，核心)对网络性能造成了一定的影响，层次越多，使用的设备就越多，延迟也就越大，性能效率就会降低。
针对于此，本申请实施例提供了一种数据分流方法、装置、设备和计算机可读存储介质，通过获取网络设备的负载信息、以及终端发送的第一数据，根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。如此，能够根据数据对计算能力和计算时间的需求，确定进行运算处理的目标运算设备，将数据分流至该目标运算设备，进而减轻中心云服务器的压力，减少数据时延，提高处理效率，降低控制的响应时间。
在本申请的实施例中，数据分流方法可以应用于边缘计算平台，边缘计算平台的网关是边缘网关，其中，边缘计算平台可以如图1所示。
图1是本申请实施例提供的一种边缘计算平台的结构示意图。如图1所示，边缘计算平台可以包括中心云、边缘云、边缘网关。其中，中心云不仅可以管理所有的边缘云以及边缘网关，为用户和管理者提供统一的门户，而且可以展现边缘云个数，资源使用情况，业务运行状态。作为一个示例，中心云可以是指中心云服务器。边缘云可以是中心云的私有化部署，具备网络转发、存储、大数据处理、智能化数据分析等能力，以降低响应时延、减轻中心云端压力、降低带宽成本。依据对处理能力需求的不同，边缘云可以分级部署在城域网，接入网和基站级别网络。作为一个示例，边缘云可以是指MEC服务器。边缘网关可以提供智能化的网络接入以及高带宽，低时延的网络承载，并依靠开放的连接、计算与存储资源及应用程 序接口(Application Programming Interface，API)支持多生态业务在现场的灵活部署，可以在不受核心网影响的情况下直接通过基站进行本地计算与通讯。
在一些实施例中，边缘网关结构可以分为硬件层和软件层，硬件层可以支撑网关具备异构计算、网络(如软件定义网络，低延时网络)以及时序数据库储存的功能。换句话说，边缘网关可以具有运算模块、网络模块以及储存模块，其中，网络模块可以是第五代移动通信技术(5th generation mobile networks，5G)模组。软件层可以包括设备服务层，核心服务层，支撑服务层以及输出服务层。其中，核心服务层及设备服务层可以完成协议解析，物理及逻辑连接，计算服务以及微服务构建。支撑服务层和输出服务层可以完成端到端的业务流，包括资源反馈，业务请求，策略调动，多视图呈现功能，并且将核心服务层建立的微服务进行处理，调度以及发布输出。
具体地，边缘网关可以包括工业数据采集、数据解析、5G网络切片构建等功能。其中，工业数据采集可以是指利用泛在感知技术对多源设备、异构系统、运营环境、人等要素信息进行实时高效采集和云端汇聚。工业数据采集可以对应边缘计算平台体系架构中的边缘层，通过各类通信手段将边缘网关接入不同终端设备、系统和产品，采集大范围、深层次的工业数据，进而对异构数据进行协议转换与边缘处理，构建边缘计算平台的数据基础。作为一个示例，工业数据采集在广义范围上可以包括工业现场设备的数据采集和工厂外智能产品/装备的数据采集。
其中，工业数据采集的数据的数据类型可以包括资源类、产品类、订单类、环境类、图像类等等。作为一个示例，资源类数据可以是指与产品生产相关联的资源数据。比如，传感器持续生成的操作参数(如机床轴的振动、机器人抓手的力、执行器的电气参数、驱动器和处理板、虚拟摄像机的图像参数)、刀具参数、资源状态(如程序执行时的错误、程序启用/禁用、电源碰撞、校准误差)、执行的操作质量(如持续时间、零件识别和视觉定位)和能耗(如每种产品和操作持续)等等。产品类数据可以是指与产品生产相关联的产品数据，比如人机界面提供的有关产品所需配方的数据，以及产品上的嵌入式设备控制加工过程(如几何测量、形状精加工、部件对齐)和执行过程中发生的事件(如断电和恢复时的加工追溯)的数据等等。可以理解，产品类数据可用于柔性制造的工业场景。这里所指的人机界面可以访问云端服务器。订单类数据可以是指与产品生产相关联的订单数据，比如，产品上的嵌入式设备汇总有关产品配方在专用批处理条目中转换执行方式的数据，具有先例的操作序列和为每个操作分配的资源，关于满足产品的执行顺序和最终的意外事件，关于产品在车间的位置、已执行的操作、与当前计划相关的及时性和延迟以及交付时间等等。环境类数据可以是指与产品生产相关联的环境数据，比如，可以包括监测环境产 生的数据。比如，在生产特殊产品(如放射性药品)的工厂中，传感器采集的重量、温度、相对湿度、压力、放射性等数据，或者在使用视觉系统的工作站中，传感器采集的照明变化数据。由于在发生事故时需要系统做出快速响应，所以环境类数据控制需要极低的延时。图像类数据可以是指与产品生产相关联的图像数据，比如，基于机器视觉的质检能力产生的产品的图像数据、视频监控操作人员的操作产生的图像数据、以及各类巡检机器人产生的图像数据。图像类数据通常需要大传输带宽和高运算能力。可以理解，可以在传输前对数据的无效信息进行删除，提高数据传输和运算效率。
数据解析可以是指边缘网关集成多种工业协议的解析能力，利用多种工业协议的解析能力能够获取各类终端上报的数据，实现数据格式的转换和统一。其中，多种工业协议可以包括以太网工业协议(EtherNet/Industry Protocol，Ethernet/IP)、Modbus协议、控制器局域网总线(Controller Area Network，CAN)、传输控制协议/网际协议(Transmission Control Protocol/Internet Protocol，TCP/IP)、Profinet等主流PLC协议以及西门子、欧姆龙、三菱等私有PLC协议。
由于工厂区域的数据既有本地业务也有云计算业务，而且本地业务需要较高的私密性保护，因此5G物理网络可以基于公共陆地移动网(Public Land Mobile Network，PLMN)从单个网络转换成逻辑分区的网络，也就是说，将5G物理网络切分成网络切片。其中，网络切片具有适当的网络隔离、资源、优化的拓扑和特定配置，可以满足各种服务需求。5G网络切片构建可以是指作为无线接入网节点的边缘网关可以接收基于核心网或核心网切片到无线接入网(Radio Access Network，RAN)切片关联的路由指令，该指令可以用于在边缘网关和基站之间建立逻辑隧道，建立端到端网络切片。
下面结合附图对本申请实施例所提供的数据分流方法进行介绍。
图2是本申请实施例提供的一种数据分流方法的流程示意图。该数据分流方法可以应用于边缘网关，如图2所示，该数据分流方法可以包括S210至S220。其中，
S210，获取网络设备的负载信息、以及终端发送的第一数据。
这里，边缘网关的设备服务层可以获取终端的发送的第二数据，然后边缘网关的核心服务层对第二数据进行预处理，得到第一数据。在一些实施例中，边缘网关的设备服务层可以根据多种工业通信协议的解析能力，获取终端的发送的第二数据。边缘网关的核心服务层根据第二数据的数据类型对第二数据进行预处理，预处理可以包括逻辑运算、数据归一化、标准化处理、数据降噪、冗余数据删除等等。其中，第一数据可以包括第一数据的数据类型，第二数据可以是指工业数据采集的数据，第二数据可以包括第二数据的数据类型，网络设备可以包括边缘网关、MEC服务器、中心云服务器，可以理解，第一数据、第二数据的数据类型可以包括资源类、 产品类、订单类、环境类、图像类等等。
S220，根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备。
这里，边缘网关的支撑服务层可以综合第一数据的数据类型对网络设备的运算能力要求，以及当前网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。其中，目标运算设备可以包括边缘网关、MEC服务器、中心云服务器中任意一项。比如，有的数据类型需要低时延，注重私密性，且计算需求较大，则可以确定边缘网关为该类型数据的目标运算设备。在一些实施例中，第一数据还可以包括数据属性信息，边缘网关的支撑服务层可以根据第一数据的数据类型、网络设备的负载信息和数据属性信息，确定目标运算设备。其中，数据属性信息可以包括第一数据的数据大小、第一数据的数据来源网际协议(Internet Protocol，IP)地址、第一数据的数据指向IP地址等等，其中，数据来源IP地址是终端的IP地址，数据指向IP地址是接收第一数据的运算处理结果的目标终端的IP地址。
本申请实施例的数据分流方法，通过获取网络设备的负载信息、以及终端发送的第一数据，根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。如此，能够根据数据对计算能力和计算时间的需求，确定进行运算处理的目标运算设备，将数据分流至该目标运算设备，进而减轻中心云服务器的压力，减少数据时延，提高处理效率，降低控制的响应时间。
在一些实施例中，边缘网关的输出服务层的应用功能(Application Function，AF)可以根据目标运算设备的标识和第一数据确定UPF，UPF可以用于规划第一数据对应的传输路径。实际应用时，AF可以根据目标运算设备的标识和第一数据，生成数据疏导请求，然后根据数据疏导请求确定UPF。其中，目标运算设备的标识可以是目标运算设备的IP地址，数据疏导请求可以包括网络名称、网络切片选择标识以及目标终端的目标终端信息等等。可以理解，网络名称可以是网络接入点名称，目标终端信息可以包括目标终端的用户信息和位置信息等等。
为了降低数据传输时延，提高处理效率，在一些实施例中，当目标运算设备是边缘网关时，AF可以根据目标运算设备的标识和第一数据，确定UPF。实际应用时，AF可以根据边缘网关的标识和第一数据，确定UPF为MEC服务器的UPF。然后边缘网关可以基于该UPF向目标终端发送运算处理结果。其中，运算处理结果是第一数据在边缘网关的运算模块进行运算处理后得到的。示例性地，可以通过5G空口将运算处理结果发送至基站，基站通过5G空口将运算处理结果发送至目标终端。
在一些实施例中，当目标运算设备是MEC服务器或中心云服务器时，AF可以根据目标运算设备的标识和第一数据，确定UPF，边缘网关根据 UPF向目标运算设备发送第一数据，以用于目标运算设备对第一数据进行运算处理。
实际应用时，当目标运算设备是MEC服务器时，AF可以根据MEC服务器的标识和第一数据，确定UPF为MEC服务器的UPF，边缘网关根据该UPF向MEC服务器发送第一数据。示例性地，边缘网关向MEC服务器发送第一数据可以是指边缘网关与基站建立逻辑隧道，建立端到端的网络切片，基于网络切片将第一数据传输至MEC服务器，换句话说，边缘网关可以通过5G空口将第一数据发送至基站，基站可以通过核心网将第一数据发送至MEC服务器。
实际应用时，当目标运算设备是中心云服务器时，AF可以根据中心云服务器的标识和第一数据，确定UPF为公网的UPF，边缘网关根据该UPF向中心云服务器发送第一数据。示例性地，边缘网关向中心云服务器发送第一数据可以是指边缘网关基于网络切片将第一数据传输至中心云服务器，换句话说，边缘网关可以通过5G空口将第一数据发送至基站，基站可以将第一数据发送至公网中的中心云服务器，中心云服务器可以接收第一数据，对第一数据进行运算处理，得到运算处理结果，将运算处理结果发送至基站，基站通过5G空口将运算处理结果发送至目标终端。
在一些实施例中，当确定的目标运算设备是MEC服务器时，MEC服务器中的处理流程可以如图3所示，其中，图3是本申请实施例提供的另一种数据分流方法的流程示意图。由图3可知，该数据分流方法可以包括S310至S330。其中，
S310，接收网关发送的第一数据。
其中，第一数据是边缘网关根据UPF发送的，UPF是网关根据MEC服务器的标识和第一数据确定的。
S320，对第一数据进行运算处理，得到运算处理结果。
S330，向目标终端发送运算处理结果。
本申请实施例的数据分流方法，通过接收分流的第一数据，以对第一数据进行运算处理。如此，能够减轻中心云服务器的压力，减少数据时延，提高处理效率，降低控制的响应时间。
值得注意的是，图3所示实施例与图2所示实施例的主要区别在于：图3所示实施例所示方法应用于边缘网关侧，而图2所示实施例所示方法应用于MEC服务器侧，他们所描写的角度不同，但工作原理或者方法细节相类似。为了描述简沽，相同或者相似的内容不再赘述，各实施例的内容描述可以相互参考。
下面结合图4对本申请实施例提供的数据分流方法进行具体说明，其中，图4是本申请实施例提供的另一种数据分流方法的流程示意图，在图4中，确定的目标运算设备为MEC服务器。具体步骤包括：
步骤1、可以通过工业以太网、工业光纤网络、工业总线、紫蜂协议 (ZigBee)、远距离无线电(Long Range Radio，LoRa)、蓝牙低能耗(Bluetooth Low Energy，BLE)、MeoH、sub-1GHZ等通信技术，将终端接入边缘网关。其中，终端可以是工业现场设备、智能产品/装备。修改终端的IP地址，并将终端的数据上送地址修改为边缘网关的IP地址，边缘网关可以通过内部网络模块与基站建立通信连接。
步骤2、边缘网关的设备服务层可以基于协议解析与转换、中间件等技术兼容Modbus、CAN、Profinet等工业通信协议，实现数据格式转换和统一，获得终端上报的第二数据。
步骤3、边缘网关的核心服务层可以根据第二数据的数据类型对第二数据进行预处理，得到第一数据，预处理可以包括逻辑运算，数据归一化、标准化处理，数据降噪，冗余数据删除等等。
步骤4、边缘网关的支撑服务层可以综合第一数据的数据类型对网络设备的运算能力要求，以及当前网络设备的负载信息，确定对第一数据进行运算处理的目标运算设备，进而可以确定目标运算设备的IP。
步骤5、边缘网关输出服务层的AF可以根据目标运算设备的IP以及第一数据，创建指向目标终端的数据疏导请求，数据疏导请求可以包括网络名称、网络切片选择标识以及目标终端的目标终端信息、进行用户面数据重路由的时间信息等等，为目标终端选择一个位置最近的UPF。这里，确定的目标运算设备是MEC服务器，故而，UPF是MEC服务器的UPF，边缘网关可以基于该UPF将第一数据传输至MEC服务器。具体地，可以按照步骤6、7、8、9进行传输以及处理。
步骤6、边缘网关可以通过5G空口将第一数据前传至基站。
步骤7、基站可以通过核心网将第一数据发送至基站侧的MEC服务器，通过MEC服务器对第一数据进行运算处理，得到运算处理结果。
步骤8、MEC服务器可以通过核心网将运算处理结果回传至基站。
步骤9、基站可以通过5G空口回传至目标终端，供目标终端执行相应的操作。
下面以机器视觉质检为例，对本申请实施例提供的数据分流方法进行具体说明，具体步骤包括：
步骤1、将作为终端的质检摄像头与边缘网关通过网线连接，配置摄像头IP地址，与网关IP地址相同网段。
步骤2、位于生产线的质检摄像头对待检产品记录视频数据，边缘网关获取质检摄像头上传的视频数据。
步骤3、来自质检摄像头的视频数据需要在边缘网关中的核心服务层经过清洗处理，保留含有产品信息的视频数据，再将含有产品信息的视频数据切割成待检图片，等待后续分析。
步骤4、由于作为目标终端的前序分拣机器臂需要对待检产品进行分拣，对控制时延有较高要求，边缘网关的支撑服务层经过分析，决定将待 检图片的图像分析交由离边缘侧较近的基站侧的MEC服务器进行处理。
步骤5、边缘网关的输出服务层的AF构建数据疏导请求，基于数据疏导请求选择位于基站侧的MEC服务器的UPF。
步骤6、边缘网关可以通过5G空口将待检图片前传至基站。
步骤7、基站可以通过核心网将待检图片发送至基站侧的MEC服务器，通过MEC服务器中的模型对比，将待检产品分类(比如合格或不合格)。
步骤8、MEC服务器可以通过核心网将分类结果回传至基站。
步骤9、基站可以通过5G空口回传至需要对待检产品进行分拣的机械臂，完成产品检测分拣。
在该例中，终端摄像头视频及图片数据没有通过公网上传到中心云服务器进行云计算，而是在基站侧的MEC服务器即完成了待检产品的分类计算，通过核心网快速回传至执行分拣操作的机械臂，可以满足机器视觉质检对低时延的要求，大幅提升产线质检效率。而且基于5G网络通信，在满足工业控制低延时的同时，简化了数据传输通道，减少了网络层次及使用的设备，实现了网络扁平化。
图5是本申请实施例提供的一种数据分流装置的结构示意图，该数据分流装置500可以应用于网关，如图5所示，该数据分流装置500可以包括：获取模块510、确定模块520。
其中，获取模块510，配置为获取网络设备的负载信息、以及终端发送的第一数据，其中，第一数据包括第一数据的数据类型。确定模块520，配置为根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。
在一些实施例中，网络设备包括网关、MEC服务器、中心云服务器；目标运算设备包括以下选项中任意一项：网关、MEC服务器、中心云服务器。
在一些实施例中，该装置500还包括：发送模块，配置为当目标运算设备是MEC服务器或中心云服务器时，根据目标运算设备的标识和第一数据，确定UPF，根据UPF向目标运算设备发送第一数据。
在一些实施例中，第一数据包括数据属性信息。所述确定模块520，配置为根据第一数据的数据类型、网络设备的负载信息和数据属性信息，确定目标运算设备。
在一些实施例中，所述获取模块510，配置为获取终端的发送的第二数据，对第二数据进行预处理，得到第一数据。
本申请实施例的数据分流装置500，通过获取网络设备的负载信息、以及终端发送的第一数据，根据第一数据的数据类型和网络设备的负载信息，确定目标运算设备，以用于目标运算设备对第一数据进行运算处理。如此，能够根据数据对计算能力和计算时间的需求，确定进行运算处理的目标运算设备，将数据分流至该目标运算设备，进而减轻中心云服务器的压力， 减少数据时延，提高处理效率，降低控制的响应时间。
实际应用时，所述获取模块510可由数据分流装置500中的处理器结合通信接口实现，所述确定模块520可由数据分流装置500中的处理器实现；所述发送模块可由数据分流装置500中的通信接口实现。
可以理解的是，本申请实施例的数据分流装置500，可以对应于本申请实施例图2中的数据分流方法的执行主体，数据分流装置500的各个模块/单元的操作和/或功能的具体细节可以参见上述本申请实施例图2的数据分流方法中的相应部分的描述，为了简洁，在此不再赘述。
图6是本申请实施例提供的另一种数据分流装置的结构示意图，该数据分流装置600可以应用于MEC服务器，如图6所示，该数据分流装置600可以包括：接收模块610、运算模块620、发送模块630。
其中，接收模块610，配置为接收网关发送的第一数据，其中，第一数据是网关根据UPF发送的，UPF是网关根据MEC服务器的标识和第一数据确定的。运算模块620，配置为对第一数据进行运算处理，得到运算处理结果。发送模块630，配置为向目标终端发送运算处理结果。
本申请实施例的数据分流装置600，通过接收分流的第一数据，以对第一数据进行运算处理。如此，能够减轻中心云服务器的压力，减少数据时延，提高处理效率，降低控制的响应时间。
实际应用时，所述运算模块620可由数据分流装置600中的处理器实现；所述接收模块610和所述发送模块630可由数据分流装置600中的通信接口实现。
可以理解的是，本申请实施例的数据分流装置600，可以对应于本申请实施例图3中的数据分流方法的执行主体，数据分流装置600的各个模块/单元的操作和/或功能的具体细节可以参见上述本申请实施例图3的数据分流方法中的相应部分的描述，为了简洁，在此不再赘述。
另外，需要说明的是：上述实施例提供的数据分流装置500和数据分流装置600在处理数据时，仅以上述各程序模块的划分进行举例说明，实际应用时，可以根据需要而将上述处理分配由不同的程序模块完成，即将装置的内部结构划分成不同的程序模块，以完成以上描述的全部或者部分处理。
图7是本申请实施例提供的一种数据分流设备的硬件结构示意图。
如图7所示，本实施例中的数据分流设备700包括输入设备701、输入接口702、中央处理器703、存储器704、输出接口705、以及输出设备706。其中，输入接口702、中央处理器703、存储器704、以及输出接口705通过总线710相互连接，输入设备701和输出设备706分别通过输入接口702和输出接口705与总线710连接，进而与数据分流设备700的其他组件连接。
具体地，输入设备701接收来自外部的输入信息，并通过输入接口702 将输入信息传送到中央处理器704；中央处理器703基于存储器704中存储的计算机可执行指令对输入信息进行处理以生成输出信息，将输出信息临时或者永久地存储在存储器704中，然后通过输出接口705将输出信息传送到输出设备706；输出设备706将输出信息输出到数据分流设备700的外部供用户使用。
在一个实施例中，图7所示的数据分流设备700包括：存储器704，配置为存储程序；处理器703，配置为运行存储器中存储的程序，以执行图2所示实施例提供的数据分流方法或图3所示实施例提供的数据分流方法。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质上存储有计算机程序指令；该计算机程序指令被处理器执行时实现图2所示实施例提供的数据分流方法或图3所示实施例提供的数据分流方法。
需要明确的是，本申请并不局限于上文所描述并在图中示出的特定配置和处理。为了简明起见，这里省略了对已知方法的详细描述。在上述实施例中，描述和示出了若干具体的步骤作为示例。但是，本申请的方法过程并不限于所描述和示出的具体步骤，本领域的技术人员可以在领会本申请的精神后，做出各种改变、修改和添加，或者改变步骤之间的顺序。
以上所述的结构框图中所示的功能块可以实现为硬件、软件、固件或者它们的组合。当以硬件方式实现时，可以是电子电路、专用集成电路(Application Specific Integrated Circuit，ASIC)、适当的固件、插件、功能卡等等。当以软件方式实现时，本申请的元素是被用于执行所需任务的程序或者代码段。程序或者代码段可以存储在机器可读介质中，或者通过载波中携带的数据信号在传输介质或者通信链路上传送。“机器可读介质”可以包括能够存储或传输信息的任何介质。机器可读介质的例子包括电子电路、半导体存储器设备、只读存储器(Read-Only Memory，ROM)、闪存、可擦除ROM(EROM)、软盘、CD-ROM、光盘、硬盘、光纤介质、射频(Radio Frequency，RF)链路，等等。代码段可以经由诸如因特网、内联网等的计算机网络被下载。
还需要说明的是，本申请中提及的示例性实施例，基于一系列的步骤或者装置描述一些方法或系统。但是，本申请不局限于上述步骤的顺序，也就是说，可以按照实施例中提及的顺序执行步骤，也可以不同于实施例中的顺序，或者若干步骤同时执行。
以上所述，仅为本申请的具体实施方式，所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，上述描述的系统、模块和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。应理解，本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。

Claims (14)

  1. 一种数据分流方法，所述方法用于网关，所述方法包括：
    获取网络设备的负载信息、以及终端发送的第一数据，其中，所述第一数据包括所述第一数据的数据类型；
    根据所述第一数据的数据类型和所述网络设备的负载信息，确定目标运算设备，以用于所述目标运算设备对所述第一数据进行运算处理。
  2. 根据权利要求1所述的方法，其中，所述网络设备包括所述网关、移动边缘计算MEC服务器、中心云服务器；
    所述目标运算设备包括以下选项中任意一项：所述网关、所述移动边缘计算MEC服务器、所述中心云服务器。
  3. 根据权利要求2所述的方法，其中，当所述目标运算设备是所述MEC服务器或所述中心云服务器时，所述方法还包括：
    根据所述目标运算设备的标识和所述第一数据，确定用户面功能UPF；
    根据所述UPF向所述目标运算设备发送所述第一数据。
  4. 根据权利要求1所述的方法，其中，所述第一数据包括数据属性信息；
    所述根据所述第一数据的数据类型和所述网络设备的负载信息，确定目标运算设备，包括：
    根据所述第一数据的数据类型、所述网络设备的负载信息和所述数据属性信息，确定所述目标运算设备。
  5. 根据权利要求1所述的方法，其中，获取终端发送的第一数据，包括：
    获取所述终端的发送的第二数据，对所述第二数据进行预处理，得到所述第一数据。
  6. 一种数据分流方法，所述方法用于MEC服务器，所述方法包括：
    接收网关发送的第一数据，其中，所述第一数据是所述网关根据UPF发送的，所述UPF是所述网关根据所述MEC服务器的标识和所述第一数据确定的；
    对所述第一数据进行运算处理，得到运算处理结果；
    向目标终端发送所述运算处理结果。
  7. 一种数据分流装置，所述装置用于网关，所述装置包括：
    获取模块，配置为获取网络设备的负载信息、以及终端发送的第一数据，其中，所述第一数据包括所述第一数据的数据类型；
    确定模块，配置为根据所述第一数据的数据类型和所述网络设备的负载信息，确定目标运算设备，以用于所述目标运算设备对所述第一数 据进行运算处理。
  8. 根据权利要求7所述的装置，其中，所述网络设备包括所述网关、MEC服务器、中心云服务器；
    所述目标运算设备包括以下选项中任意一项：所述网关、所述MEC服务器、所述中心云服务器。
  9. 根据权利要求8所述的装置，其中，所述装置还包括：
    发送模块，配置为当所述目标运算设备是所述MEC服务器或所述中心云服务器时，根据所述目标运算设备的标识和所述第一数据，确定UPF；
    根据所述UPF向所述目标运算设备发送所述第一数据。
  10. 根据权利要求7所述的装置，其中，所述第一数据包括数据属性信息；
    所述确定模块，配置为根据所述第一数据的数据类型、所述网络设备的负载信息和所述数据属性信息，确定所述目标运算设备。
  11. 根据权利要求7所述的装置，其中，所述获取模块，配置为获取所述终端的发送的第二数据，对所述第二数据进行预处理，得到所述第一数据。
  12. 一种数据分流装置，所述装置用于MEC服务器，所述装置包括：
    接收模块，配置为接收网关发送的第一数据，其中，所述第一数据是所述网关根据UPF发送的，所述UPF是所述网关根据所述MEC服务器的标识和所述第一数据确定的；
    运算模块，配置为对所述第一数据进行运算处理，得到运算处理结果；
    发送模块，配置为向目标终端发送所述运算处理结果。
  13. 一种数据分流设备，所述设备包括：处理器以及存储有计算机程序指令的存储器；
    所述处理器执行所述计算机程序指令时实现如权利要求1至5任一项所述的数据分流方法，或者，所述处理器执行所述计算机程序指令时实现如权利要求6所述的数据分流方法。
  14. 一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现如权利要求1至5任一项所述的数据分流方法，或者，所述计算机程序指令被处理器执行时实现如权利要求6所述的数据分流方法。
PCT/CN2021/084177 2020-03-30 2021-03-30 数据分流方法、装置、设备及介质 WO2021197353A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202010234561.3A CN113472822A (zh) 2020-03-30 2020-03-30 数据分流方法、装置、设备及介质
CN202010234561.3 2020-03-30

Publications (1)

Publication Number Publication Date
WO2021197353A1 true WO2021197353A1 (zh) 2021-10-07

Family

ID=77865952

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/084177 WO2021197353A1 (zh) 2020-03-30 2021-03-30 数据分流方法、装置、设备及介质

Country Status (2)

Country Link
CN (1) CN113472822A (zh)
WO (1) WO2021197353A1 (zh)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115297509A (zh) * 2022-10-09 2022-11-04 中国移动通信有限公司研究院 一种边缘计算二次分流方法和系统
CN115442864A (zh) * 2022-08-09 2022-12-06 广州通康创智软件有限公司 一种基于多模组的网关链路切换控制方法、装置及系统

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114035964A (zh) * 2021-11-23 2022-02-11 北京邮电大学 一种边缘计算嵌入式微服务器模型、服务方式及设备
CN114095314A (zh) * 2021-11-25 2022-02-25 成都中科微信息技术研究院有限公司 一种基于5g/tsn技术的工业互联网网关
CN114900860B (zh) * 2022-05-05 2024-04-02 中国联合网络通信集团有限公司 移动终端边缘计算方法、装置、边缘计算服务器及介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109561141A (zh) * 2018-11-21 2019-04-02 中国联合网络通信集团有限公司 一种cdn节点的选择方法及设备
CN110198307A (zh) * 2019-05-10 2019-09-03 深圳市腾讯计算机系统有限公司 一种移动边缘计算节点的选择方法、装置及系统
CN110198363A (zh) * 2019-05-10 2019-09-03 深圳市腾讯计算机系统有限公司 一种移动边缘计算节点的选择方法、装置及系统
CN110336885A (zh) * 2019-07-10 2019-10-15 深圳市网心科技有限公司 边缘节点分配方法、装置、调度服务器及存储介质
EP3792758A1 (en) * 2019-09-13 2021-03-17 Intel Corporation Multi-access edge computing (mec) service contract formation and workload execution

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109495929B (zh) * 2017-09-12 2021-08-03 华为技术有限公司 一种业务处理方法、移动边缘计算设备及网络设备
CN110933061B (zh) * 2019-11-22 2022-02-18 中国联合网络通信集团有限公司 一种通信方法及装置

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109561141A (zh) * 2018-11-21 2019-04-02 中国联合网络通信集团有限公司 一种cdn节点的选择方法及设备
CN110198307A (zh) * 2019-05-10 2019-09-03 深圳市腾讯计算机系统有限公司 一种移动边缘计算节点的选择方法、装置及系统
CN110198363A (zh) * 2019-05-10 2019-09-03 深圳市腾讯计算机系统有限公司 一种移动边缘计算节点的选择方法、装置及系统
CN110336885A (zh) * 2019-07-10 2019-10-15 深圳市网心科技有限公司 边缘节点分配方法、装置、调度服务器及存储介质
EP3792758A1 (en) * 2019-09-13 2021-03-17 Intel Corporation Multi-access edge computing (mec) service contract formation and workload execution

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
ETRI, INTEL: "FS_CAV – Update requirements for massive wireless sensor networks use case", 3GPP DRAFT; S1-174488 WAS 4169 FS_CAV - UPDATE REQUIREMENTS FOR MASSIVE WIRELESS SENSOR NETWORKS USE CASE, 3RD GENERATION PARTNERSHIP PROJECT (3GPP), MOBILE COMPETENCE CENTRE ; 650, ROUTE DES LUCIOLES ; F-06921 SOPHIA-ANTIPOLIS CEDEX ; FRANCE, vol. SA WG1, no. Reno, Nevada, USA; 20171127 - 20171201, 4 December 2017 (2017-12-04), Mobile Competence Centre ; 650, route des Lucioles ; F-06921 Sophia-Antipolis Cedex ; France, XP051379105 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115442864A (zh) * 2022-08-09 2022-12-06 广州通康创智软件有限公司 一种基于多模组的网关链路切换控制方法、装置及系统
CN115442864B (zh) * 2022-08-09 2024-03-29 广州通康创智软件有限公司 一种基于多模组的网关链路切换控制方法、装置及系统
CN115297509A (zh) * 2022-10-09 2022-11-04 中国移动通信有限公司研究院 一种边缘计算二次分流方法和系统
CN115297509B (zh) * 2022-10-09 2023-01-10 中国移动通信有限公司研究院 一种边缘计算二次分流方法和系统

Also Published As

Publication number Publication date
CN113472822A (zh) 2021-10-01

Similar Documents

Publication Publication Date Title
WO2021197353A1 (zh) 数据分流方法、装置、设备及介质
CN109639467B (zh) 基于sdn的智能产线多模态数据交互系统及方法
CN109479065B (zh) 边缘服务器及其操作方法
WO2020181729A1 (zh) 一种基于分布式并行计算的路径规划方法及其系统
US11201834B2 (en) Communication control device, communication control method, and communication system
CN108718345A (zh) 一种数字化车间工业数据网络化传输系统
CN104049575A (zh) 在过程控制系统中收集并且向大数据机器递送数据
CN111125230B (zh) 一种基于规则引擎的物联网平台的数据处理方法及系统
CN112631725A (zh) 一种基于云边端协同的智慧城市的管理系统及方法
CN110658759A (zh) 一种可动态部署ai模型的工业智能控制器
CN113946141B (zh) 一种生产示范线的网络系统及控制方法
CN108737169A (zh) 一种基于sdn的异构工业网络集中式融合管理方法
CN115022379B (zh) 一种基于5g云平台的陶瓷生产管理系统
WO2022056927A1 (zh) 一种网关、数据收集方法、电子设备、存储介质和程序
Strinati et al. Beyond 5G private networks: the 5g CONNI perspective
CN112688997A (zh) 基于rpa机器人的通用数据采集、管理方法和系统
CN109739192B (zh) 一种智能物流系统下的控制方法及系统
CN102904967A (zh) 一种基于五金机电领域的智能物联网数据交换平台方案
US20240019852A1 (en) Cloud edge network process automation control
Lee et al. mIoTwins: design and evaluation of mIoT framework for private edge networks
CN115903710A (zh) 发电机定子铁芯叠装机器人边缘控制系统和控制方法
WO2020238764A1 (zh) 时序管理方法、设备及系统
Ke et al. Internet-of-Things monitoring system of robot welding based on software defined networking
CN105227492A (zh) 对控制信息和服务信息进行分离与融合处理的系统
CN105467969A (zh) 一种制造执行系统

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21779938

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21779938

Country of ref document: EP

Kind code of ref document: A1

122 Ep: pct application non-entry in european phase

Ref document number: 21779938

Country of ref document: EP

Kind code of ref document: A1

122 Ep: pct application non-entry in european phase

Ref document number: 21779938

Country of ref document: EP

Kind code of ref document: A1

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 05/07/2023)