Edge computing operation and maintenance method, device, system, electronic device, and storage medium

Abstract

An edge computing operation and maintenance method, comprising: acquiring AI source data in a target area, wherein a first packet transport device is arranged in the target area; on the basis of the AI source data, running AI application software corresponding to the AI source data so as to obtain an AI running result; and sending the AI running result to an AI running result response device, wherein the first packet transport device and the response device are both deployed in the target area.

Description

Edge computing operation and maintenance methods, equipment, systems, electronic devices, and storage media

[0001] Cross-references

[0002] This application claims priority to the Chinese patent application filed with the China Patent Office on November 2, 2023, with application number 202311469596.5 and invention name “Operation and maintenance methods, equipment, systems, electronic devices and storage media for edge computing”. The entire contents of the application are incorporated by reference into this application. Technical Field

[0003] The embodiments of the present application relate to the field of artificial intelligence, and in particular to an edge computing operation and maintenance method, system, electronic device, and storage medium. Background Art

[0004] With the development of artificial intelligence (AI), AI technology has been widely applied in targeted areas, such as factories within industrial parks. For example, image classification can be used in factories for product quality inspection. Deep learning algorithms involved in AI, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and self-attention models, are computationally intensive and consume large amounts of memory. These models rely on numerous software packages, which consume both memory and disk space.

[0005] When deploying AI technology in industrial production scenarios, some methods can meet the requirements of low cost and easy deployment, but there are risks to data security, data dispersion cannot be centralized, and there is high latency. Other methods may be able to achieve data security and centralized management, but they are costly and difficult to deploy. In short, the current edge computing operation and maintenance methods cannot simultaneously meet the requirements of low cost, easy deployment, data security, centralized management, and low latency.

[0006] Summary of the Invention

[0007] The embodiments of the present application provide an edge computing operation and maintenance method, system, electronic device, and storage medium, which can solve the problem that the edge computing operation and maintenance method cannot simultaneously meet the requirements of low cost, easy deployment, data security, centralized management, and low latency.

[0008] In a first aspect, an edge computing operation and maintenance method is provided, which is applied to a first packet transmission device, the method comprising: obtaining AI source data within a target area, wherein the first packet transmission device is arranged in the target area; based on the AI ​​source data, running AI application software corresponding to the AI ​​source data to obtain an AI operation result; and sending the AI ​​operation result to an AI operation result response device, wherein the response device is deployed in the target area.

[0009] In a second aspect, a packet transmission device is provided, which is arranged in a target area, and the packet transmission device includes: a communication service unit, which is used to obtain AI source data in the target area through a data interface unit; an AI unit, which is used to run corresponding AI application software based on the AI ​​source data to obtain the AI ​​operation result; the communication service unit is also used to send the AI ​​operation result to an AI operation result response device, and the AI ​​operation result response device is deployed in the target area.

[0010] According to a third aspect, an edge computing operation and maintenance system is provided, including: a packet transmission device, which is used to obtain AI source data within a target area; perform AI operations based on the AI ​​source data to obtain AI operation results; and send the AI ​​operation results to an AI operation result response device; a control device, which is connected to the packet transmission device and is used to control the packet transmission device; the packet transmission device and the control device are both arranged within the target area.

[0011] In a fourth aspect, an electronic device is provided, which terminal includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the method described in the first aspect are implemented.

[0012] In a fifth aspect, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0013] In a sixth aspect, a chip is provided, comprising a processor and a communication card slot, wherein the communication card slot is coupled to the processor, and the processor is used to run a program or instruction to implement the steps of the method described in the first aspect.

[0014] In a seventh aspect, a computer program / program product is provided, wherein the computer program / program product is stored in a storage medium and is executed by at least one processor to implement the steps of the method described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG1 is a schematic flowchart of an edge computing operation and maintenance method provided in an embodiment of the present application.

[0016] Figure 2 is a schematic flowchart of another edge computing operation and maintenance method provided in an embodiment of the present application.

[0017] Figure 3a is a structural diagram of an edge computing operation and maintenance system provided in an embodiment of the present application.

[0018] Figure 3b is a structural diagram of another edge computing operation and maintenance system provided in an embodiment of the present application.

[0019] Figure 3c is a structural diagram of another edge computing operation and maintenance system provided in an embodiment of the present application.

[0020] FIG4 is a schematic structural diagram of a packet transmission device according to an embodiment of the present application.

[0021] FIG5 is a schematic structural diagram of an electronic device according to another embodiment of the present application. DETAILED DESCRIPTION

[0022] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0023] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first" and "second" are generally of the same type, and do not limit the number of objects. For example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0024] As shown in FIG1 , an embodiment of the present application provides an edge computing operation and maintenance method. The method can be performed by a first packet transmission device. The first packet transmission device can be the packet transmission device in the embodiments of FIG3 a-c and FIG4 below. In other words, the method can be performed by hardware included in the first packet transmission device or software installed in the first packet transmission device. The method includes the following steps:

[0025] Step S102: Acquire AI source data within the target area.

[0026] The first packet transmission device is set in the target area. The embodiment of the present application can provide edge computing for AI source data in the target area. The target area can be set according to needs, for example, it can include a factory that needs to perform edge computing as described in the embodiment of the present application. An AI source data acquisition device 1 is also deployed in the target area. The AI ​​source data acquisition device 1 can include, for example, a camera for acquiring images, a scanner for acquiring QR codes, and a recorder for acquiring sounds.

[0027] As shown in the subsequent Figure 3a, the packet transmission device 31 reuses packet transmission devices deployed in the target area. In one embodiment, the packet transmission device 31 supports parsing of industrial control protocols such as Modbus or FINS, and can encode and decode industrial computer data. The packet transmission device 31 also has image / video data encoding and decoding capabilities, using codecs such as H.264 / H.265, and can encode and decode image / video data from cameras.

[0028] In one embodiment, this step may include: a first packet transmission device receiving the AI ​​source data collected and transmitted by a data acquisition device within the target area. The first packet transmission device may be connected to the data acquisition device via a port. As shown in FIG3a , when the first packet transmission device is packet transmission device C, packet transmission device C is connected to the data acquisition device via a port, and may directly receive the AI ​​source data collected and transmitted by the data acquisition device within the target area.

[0029] In another implementation, this step may include: a first packet transmission device receiving, via the operator slice network, the AI ​​source data sent by a second packet transmission device in the target area, where the second packet transmission device is a device connected to a data acquisition device that collects the AI ​​source data. With reference to FIG3a , when the first packet transmission device is packet transmission device B in the figure, packet transmission device B is not directly connected to the data acquisition device via a port, and can receive the AI ​​source data forwarded by packet transmission device C via the operator slice network, i.e., packet transmission device C is the second packet transmission device.

[0030] In one embodiment, there may be multiple packet transmission devices 32, and edge computing data between the multiple packet transmission devices is transmitted via operator slicing network technology. Specifically, the packet transmission device described in the embodiment of the present application is formed based on the packet transmission device provided by the network operator, and its functions include: operator data transmission function and edge computing function. The operator data transmission function is data transmitted to achieve network connection in the target area. Therefore, the data transmission between the packet transmission devices includes: operator network data and edge computing data. The embodiment of the present application includes edge computing data transmitted using slicing network technology. The edge computing data may include edge computing data including all edge computing operation and maintenance system-related data, such as AI source data collected by the AI ​​source data acquisition device, the running results of the AI ​​application software, the processing results after processing the running results, and the control commands used by the control device to control the packet transmission device. The transmission method of the operator network data is not limited. Slicing network technology includes technologies that support network slicing functions, including: SPN (Slicing Packet Network) technology or IPRAN (IP Radio Access Network) technology. Therefore, the edge computing operation and maintenance system provided in the embodiment of the present application realizes the transmission of AI application-related data between the packet transmission devices 31 in the target area through slicing network technology, so that different packet transmission devices can share computing power.

[0031] Step S104: Based on the AI ​​source data, run the AI ​​application software corresponding to the AI ​​source data to obtain an AI running result.

[0032] In this step, based on the AI ​​source data, the AI ​​application software corresponding to the AI ​​source data can be run by an AI unit to obtain an AI operation result, wherein the AI ​​unit includes an AI acceleration chip or a computing board with an AI acceleration chip, and there is a corresponding relationship between the AI ​​acceleration chip and the AI ​​application software. The corresponding relationship between the AI ​​acceleration chip and the AI ​​application software, for example, the AI ​​acceleration chip identified as 1 is used to run AI application software of category A.

[0033] In one embodiment, in response to the AI ​​application software configuration command, the correspondence between the AI ​​application software and the AI ​​acceleration chip is adjusted. For example, if the original correspondence includes: the AI ​​acceleration chip identified as 1 is used to run AI application software of category A, in this step, in response to the AI ​​application software configuration command, the correspondence can be adjusted so that the AI ​​acceleration chip identified as 2 is used to run AI application software of category A, etc.

[0034] Step S106: Send the AI ​​operation result to the AI ​​operation result response device.

[0035] The response device is deployed in the target area. The AI ​​operation result response device includes: the AI ​​source data acquisition device or a third device running the AI ​​application, which processes the AI ​​operation result through the result processing end of the AI ​​application software. The AI ​​operation result response device can be the same device as the AI ​​source data acquisition device, or a different device. For example, the AI ​​source data acquisition device can be a terminal, which collects user data and sends it to the packet transmission device for AI calculation. The packet transmission device can send the AI ​​operation result to the terminal (the above-mentioned AI operation result response device), and the terminal performs subsequent data processing. For another example, the AI ​​source data acquisition device can be a camera, which collects the user's facial image and sends it to the packet transmission device for AI image recognition. The packet transmission device can send the AI ​​operation result to a terminal, and the terminal performs subsequent data processing on the image recognition result.

[0036] Step S106 may include one of the following:

[0037] The AI ​​execution result is transmitted to the AI ​​execution result response device via the first destination port of the first packet transmission device, where the first destination port is a preconfigured port for communication with the AI ​​execution result response device. For example, if the AI ​​execution result response device is the AI ​​source data acquisition device 1 and the first packet transmission device is packet transmission device C in Figure 3a, then in this step, the AI ​​execution result can be transmitted to the AI ​​source data acquisition device 1 via the first destination port of packet transmission device C.

[0038] The AI ​​operation result is sent to a third packet transmission device directly connected to the AI ​​operation result response device through the operator slice network, so as to send the AI ​​operation result to the AI ​​operation result response device through the second target port of the third packet transmission device. For example, the AI ​​operation result response device is the AI ​​source data acquisition device 1, and the first packet transmission device is the packet transmission device B in Figure 3a. Then, in this step, the packet transmission device B sends the AI ​​operation result to the packet transmission device C through the operator slice network, and sends the AI ​​operation result to the AI ​​source data acquisition device 1 through the packet transmission device C. Similarly, this step also includes the case where the AI ​​operation result response device is the above-mentioned third device, which is not exhaustive.

[0039] Therefore, in the embodiment of the present application, when there are multiple packet transmission devices, the AI ​​source data collected from the AI ​​source data collection device can be received by the second packet transmission device among the multiple packet transmission devices. The AI ​​source data is forwarded to the first packet transmission device for performing AI operations among the multiple packet transmission devices through the operator slice network by the second packet transmission device. The AI ​​application software corresponding to the AI ​​source data is run by the first packet transmission device to obtain the AI ​​operation result. The AI ​​operation result is sent to the AI ​​operation result response device through the first packet transmission device. In this way, computing power sharing of multiple packet transmission devices in the target area is achieved.

[0040] As shown in FIG2 , an embodiment of the present application provides an edge computing operation and maintenance method, which includes the following steps:

[0041] Step S202: Acquire AI source data within the target area.

[0042] The first packet transmission device is set in the target area, and the first packet transmission device can be the packet transmission device in the above embodiment.

[0043] Step S204: Based on the AI ​​source data, run the AI ​​application software corresponding to the AI ​​source data to obtain an AI running result.

[0044] Step S206: Send the AI ​​operation result to the AI ​​operation result response device.

[0045] Steps S202 to S206 may use the description of the embodiment of FIG1 , and will not be described again to avoid repetition.

[0046] Step S208: Send the AI ​​operation result to the control device in the target area.

[0047] In one embodiment, this step may include: sending the AI ​​execution result to a directly connected edge computing device directly connected to the control device via the operator slice network, so that the directly connected edge computing device can send the AI ​​execution result to the control device via a third target port. The directly connected edge computing device is connected to the control device via the third target port set thereon. The data sent to the control device may also include: AI software execution process data, such as collected source data, execution time, etc. The source data may include image data.

[0048] In one embodiment, when there are multiple packet transmission devices within the target area, the control device can configure a directly connected packet transmission device connected to the control device through a port from the multiple packet transmission devices; and the control device can configure a third target port for connecting to the control device from the multiple ports of the directly connected packet transmission device. Specifically, the control device provided by the network operator to implement network management can, during initialization, initially configure the connection port for connecting the packet transmission device to the control device by the network management software. In one embodiment, in this step, the control device can confirm that the connection port initially configured by the network management software is configured as the third target port for connecting the directly connected packet transmission device to the control device in the embodiment of the present application. In another implementation, in this step, the control device modifies the connection port and configures other ports except the connection port as the third target port for connecting the directly connected packet transmission device to the control device in the embodiment of the present application.

[0049] In one embodiment, step S208 may include: transmitting the AI ​​execution result to the control device via a fourth destination port of the first packet transmission device, wherein the fourth destination port is pre-configured as a port for communicating with the control device. Similar to the configuration of the third destination port described above, the fourth destination port may be configured by the control device.

[0050] The control device can control the packet transmission device, including at least one of the following:

[0051] In one embodiment, before step S202, the control device may further configure a data transmission path for an indirect packet transmission device among the plurality of packet transmission devices; and based on the data transmission path, the indirect packet transmission device may be controlled to perform routing configuration. Thus, after the direct packet transmission device and the third destination port are set, routing configuration may be performed on the indirect packet transmission device.

[0052] In one embodiment, before step S202, a topological relationship between the packet transmission devices in the target area may be obtained by a control device; and routing transmission channels between the packet transmission devices are configured based on the topological relationship, where the routing transmission channels are used to transmit target service data, including the edge computing data.

[0053] In one embodiment, after obtaining the topological relationship, the above-mentioned routing transmission channel can also be manually configured according to the topological relationship of the packet transmission device. In another embodiment, after obtaining the topological relationship, the routing transmission channel can also be manually configured according to the topological relationship of the packet transmission device; the routing configuration command can be sent to the packet transmission device through the control device; and the packet transmission device can be controlled to perform routing configuration based on the routing configuration command. The topological relationship of the packet transmission device includes: the port identifier of the second packet transmission device, the AI ​​chip identifier of the first packet transmission device, and the port identifier of the result processing end of the AI ​​application software, and the routing configuration command is generated by the control device.

[0054] In one embodiment, a port attribute modification command can be sent to the packet transmission device through the control device; based on the attribute modification command, the port attribute of the first packet transmission device is modified to a dedicated port attribute, and the dedicated port attribute is used to characterize that the transmission path between the first packet transmission device and the outside of the target area is disabled, and data from the dedicated port is prohibited from being transmitted outside the target area. The ports of the first packet transmission device may include the above-mentioned first target port, the fourth target port and other ports on the first packet transmission device. Thereby, the network management function provided by the operator is restricted, and the data within the target area will not flow out of the edge computing operation and maintenance system provided by the embodiment of the present application, thereby ensuring data security. Optionally, after modifying the port attributes, it is also possible to interact with the operator's network management, and report the information that the factory's operator network port is modified to an AI dedicated application port to the operator's network management. In one embodiment, the control of the packet transmission device by the control device may also include at least one of the following:

[0055] Controlling the installation of AI application software on the packet transmission device. This method can be executed by the AI ​​application software installation module, which supports uploading the AI ​​application software to the packet transmission device via a network cable for installation or update. It also supports configuring the corresponding data transmission channel for the AI ​​application software, namely specifying the network port / serial port, and configuring the corresponding packet transmission device, AI chip, and AI computing board. It also supports completing the uninstallation of the AI ​​application software.

[0056] Control the uninstallation of the AI ​​application software in the packet transmission device. This method can be executed by the uninstallation module of the AI ​​application software and supports the complete uninstallation of the AI ​​application software.

[0057] Controlling the configuration of the AI ​​application software in the packet transmission device; controlling the update of the AI ​​application software in the packet transmission device; controlling the startup of the AI ​​application software in the packet transmission device; this method can be executed by the control module of the AI ​​application software, which supports the start / stop function of controlling the AI ​​application software.

[0058] Controlling the stopping of the AI ​​application software in the packet transmission device may be performed by a control module of the AI ​​application software, which supports the start / stop function of controlling the AI ​​application software.

[0059] Control data management of the AI ​​application software in the packet transmission device. This method can be executed by the AI ​​application software's operation data management module. This module supports the acquisition, storage, and statistics of AI operation process data transmitted from the packet transmission device via the network port. This data includes but is not limited to raw image data collected from the production line, operation results, and processing time. This module also supports displaying this data to factory staff via a web page or application software UI.

[0060] The following uses the ZXCTN 6180H device as an example to explain the specific process in actual usage scenarios.

[0061] Single packet transport device scenario: Through the operator's network management and maintenance, a port of the packet transport device in the target area is configured as the third target port. After connecting to the control device, the packet transport device will respond to various commands from the control device and transmit data related to the AI ​​application software back to the control device.

[0062] The control device sends AI application software, its data input and output ports, and the AI ​​processing chip / computing board numbers to the packet transmission device. After receiving this command from the control device, the packet transmission device automatically performs routing configuration, such as SPN's VLSS (Virtual Local Switching Service) technology, to complete communication between the input and output data ports.

[0063] In steps S202 and S204, after the packet transmission device receives the network camera data from the input port, it will run the AI ​​application on the AI ​​acceleration unit and transmit the results to the application end through the output port, while transmitting the relevant data of the AI ​​application software back to the control device.

[0064] Multiple packet transport device scenario: As shown in Figure 3b, the operator's network management and maintenance configures a port on a packet transport device 31 in the factory area to connect to a control device 32. Routing settings are also configured for packet transport devices that are not directly connected to control device 32, specifying the data transmission path between the packet transport device and control device 32. Slicing network technologies, such as SPN and IPRAN, are used for data transmission.

[0065] The AI ​​application software and its related port configuration are distributed through the control device. For non-inter-packet transmission scenarios, routing configuration follows the same steps as for single-packet transmission. For inter-packet transmission scenarios, the relevant data transmission paths can be configured manually or automatically, such as using typical virtual private wire service (VPWS) technology.

[0066] In steps S202 and S204, after the packet transmission device receives the network camera data from the input port, it runs the AI ​​application on the AI ​​acceleration unit and transmits the results to the application end through the output port, while transmitting the relevant data of the AI ​​application software back to the control device.

[0067] Several comparative examples will be introduced below to further illustrate the scheme and beneficial effects of the embodiments of the present application by comparing the embodiments of the present application with the following comparative examples.

[0068] Comparative Example 1: Deployment of AI algorithms based on cloud computing. This involves transmitting the factory's AI source data to a public cloud via a carrier's private or public network. The AI ​​application software on the public cloud then runs the data to generate the results, which are then transmitted back to the AI ​​result response device via the carrier network. While this approach is cost-effective and easy to deploy, it has the following drawbacks: a. Industrial production data has already left the factory, posing a risk of data leakage; b. Data is first sent via the carrier network to the core network, then to the public cloud, and the results are then transmitted back to the AI ​​result response device via the carrier network. This data transmission is time-consuming and cannot guarantee the real-time performance required for industrial production.

[0069] In contrast, in the embodiments of this application, the AI ​​source data in the target area has not left the factory, eliminating the risk of data leakage. b. Data is processed near the target area, minimizing data transmission time and ensuring the real-time nature of data processing. In other words, the edge computing operation and maintenance method provided by the embodiments of this application can simultaneously meet the requirements of low cost, easy deployment, data security, centralized management, and low latency.

[0070] Comparative Example 2: Private Cloud-Based AI Algorithm Deployment. This method involves building a network and AI server within the factory. Industrial production line terminals transmit the raw data required for AI operations to the AI ​​server via the self-built network. The server then runs the industrial AI application software to obtain the results, which are then transmitted back to the AI ​​operation result response device via the self-built network. In Comparative Example 2, data does not leave the factory, ensuring real-time performance. However, the entire AI acceleration system requires extensive construction, is difficult to deploy, and is costly. Later operations and maintenance require significant manpower and require high technical skills from the personnel involved.

[0071] In contrast, the hardware required for the edge computing operation and maintenance method in the embodiment of the present application can reuse the hardware provided by existing operators, resulting in a small construction workload, simple and easy deployment, low cost, and subsequent operation and maintenance with the operator without the need for additional manpower. In other words, the edge computing operation and maintenance method provided in the embodiment of the present application can simultaneously meet the requirements of low cost, easy deployment, data security, centralized management, and low latency.

[0072] Comparative Example 3: Adding a computer or AI accelerator to the factory, using a camera as an AI source data acquisition device as an example, with an AI chip built into the camera to run the AI ​​algorithm. This Comparative Example 3 has the advantages of not leaving the factory, guaranteed real-time performance, and easy deployment. However, Comparative Example 3 requires customization of the equipment corresponding to the AI ​​source data acquisition device, lacks versatility, and cannot centrally manage multiple AI applications. Therefore, there is a risk of high cost and low efficiency.

[0073] In contrast, the edge computing operation and maintenance method in the embodiment of the present application centrally manages multiple AI applications through packet transmission equipment and control equipment. In other words, the edge computing operation and maintenance method provided by the embodiment of the present application can simultaneously meet the requirements of low cost, easy deployment, data security, centralized management, and low latency.

[0074] FIG3a is a schematic diagram of the structure of an edge computing operation and maintenance system provided in an embodiment of the present application. As shown in FIG3a , the edge computing operation and maintenance system 30 includes: a packet transmission device 31 and a control device 32. The packet transmission device and the control device are both arranged in the target area.

[0075] The packet transmission device 31 is used to obtain AI source data in the target area, perform AI operations based on the AI ​​source data, obtain AI operation results, and send the AI ​​operation results to the AI ​​operation result response device. The control device 32 is connected to the packet transmission device and is used to control the packet transmission device.

[0076] In one embodiment, the control device is connected to a directly connected packet transmission device via a first network port. The directly connected packet transmission device is one of a plurality of packet transmission devices. The directly connected packet transmission device is configured to receive control commands from the control device via the first network port. The directly connected packet transmission device may be illustrated as packet transmission device A in FIG3 a.

[0077] In one embodiment, the directly connected packet transmission device is further configured to forward control commands from the control device to other packet transmission devices via the operator slicing network technology. For example, in Figure 3a, packet transmission device B is not directly connected to control device 32 via a port, and packet transmission device A can forward control commands from the control device to packet transmission device B. This embodiment of the present application can provide edge computing for AI source data in a target area. The target area can be set as needed, and may include, for example, a factory that requires edge computing as described in this embodiment of the application. An AI source data acquisition device 1 is also deployed in the target area. The AI ​​source data acquisition device 1 may include, for example, a camera for capturing images, a scanner for capturing QR codes, and a recorder for capturing sound. The packet transmission device may be a packet transmission device provided by a network operator that provides network connectivity for the target area. Thus, the packet transmission device 31 provided in this embodiment of the present application can reuse the packet transmission device provided by the network operator, providing edge computing functionality by only adding a chip that provides AI computing, an expanded network port, and a serial port, thereby offering the advantage of low cost.

[0078] The control device 32 is set in the target area, and the control device is connected to the packet transmission device to control the packet transmission device 31. The control device 32 may include AI application management software and operator network management software that can support the control of the packet transmission device and the hardware environment for their operation, for example, it may include computers or servers and other devices. Specifically, the network operator provides a network connection for the target area, and the network management software will run on a certain hardware management device to run. The control device 32 provided in the embodiment of the present application can also be reused on the hardware management device provided by the network operator for the target area. Thus, the management edge computing function can be provided without increasing the additional hardware cost.

[0079] The operation and maintenance system based on edge computing can perform AI calculations based on the collected data of the AI ​​source data acquisition device in the target area through the packet transmission device 31, and can control the packet transmission device through the control device 32.

[0080] In one embodiment, there may be multiple packet transmission devices 32, and edge computing data between the multiple packet transmission devices is transmitted via operator slicing network technology. Specifically, the packet transmission device described in the embodiment of the present application is formed based on the packet transmission device provided by the network operator, and its functions include: operator data transmission function and edge computing function. The operator data transmission function is data transmitted to achieve network connectivity in the target area. Therefore, the data transmission between the packet transmission devices includes: operator network data and edge computing data. The embodiment of the present application includes edge computing data transmitted using slicing network technology. The edge computing data may include edge computing data including all edge computing operation and maintenance system-related data, such as AI source data collected by the AI ​​source data acquisition device, the running results of the AI ​​application software, the processing results after processing the running results, and the control commands used by the control device to control the packet transmission device. The transmission method of the operator network data is not limited. Therefore, the edge computing operation and maintenance system provided in the embodiment of the present application uses slicing network technology to achieve AI application-related data transmission between the packet transmission devices 31 in the target area, thereby enabling different packet transmission devices to share computing power.

[0081] In addition, the packet transmission equipment in the target area is interconnected using the transmission network of the operator network, and the packet transmission equipment in the park can use slicing network technology, such as SPN (Slicing Packet Network), to provide a dedicated transmission channel for AI-related data to ensure the security and low latency of data transmission. As a result, the AI ​​computing power of the packet transmission equipment 31 in the park can achieve computing power sharing, that is, the AI ​​source data collected from the AI ​​source data acquisition device can be received through the second packet transmission device among the multiple packet transmission devices; the AI ​​source data is forwarded to the first packet transmission device for AI calculation among the multiple packet transmission devices through the operator slicing network through the second packet transmission device; the AI ​​application software corresponding to the AI ​​source data is run through the first packet transmission device to obtain the AI ​​operation result. The AI ​​operation result is sent to the control device through the slicing network through the first packet transmission device for easy monitoring.

[0082] In one embodiment, the first network port of a directly connected packet transmission device among the plurality of packet transmission devices is used to connect to the control device. Other non-directly connected packet transmission devices among the plurality of packet transmission devices, excluding the directly connected packet transmission device, transmit the edge computing data to the directly connected packet transmission device via a slice network, and transmit the edge computing data to the control device via the directly connected packet transmission device. Thus, in the case of including multiple packet transmission devices, the transmission of edge computing data between multiple devices in the edge computing operation and maintenance system is achieved. Specifically, during initialization, the control device provided by the network operator for network management can initially configure the connection port connecting the packet transmission device to the control device 32 by the network management software. In one embodiment, in this step, the control device 32 can confirm that the connection port initially configured by the network management software is configured as the third target port for the connection between the directly connected packet transmission device and the control device 32 in the embodiment of the present application. In another implementation, in this step, the control device 32 can also modify the connection port, configuring other ports other than the connection port as the third target port for the connection between the directly connected packet transmission device and the control device 32 in the embodiment of the present application.

[0083] As shown in FIG. 3 c , in one embodiment, the packet transmission device may include: a communication service unit 41 and an AI unit 42 , as specifically described in the embodiment of FIG. 4 .

[0084] FIG4 is a schematic structural diagram of a packet transmission device provided in an embodiment of the present application. As shown in FIG4 , in one embodiment, the packet transmission device 40 includes: a communication service unit 41 and an AI unit 42 .

[0085] Communication service unit 41 is configured to obtain AI source data within the target area via data interface unit 43. AI unit 42 is configured to execute corresponding AI application software based on the AI ​​source data to obtain the AI ​​execution results. Communication service unit 41 is further configured to transmit the AI ​​execution results to an AI execution result response device, which is deployed within the target area.

[0086] The data interface unit 43 is connected to the communication service unit 41 and is configured to receive AI source data within the target area. The data interface unit 43 is also connected to the AI ​​operation result response device and is configured to send the AI ​​operation result to the AI ​​operation result response device, which is deployed within the target area.

[0087] For example, the communication service unit 41 of packet transmission device A may distribute the AI ​​source data to the AI ​​unit 42 of packet transmission device A. For another example, the communication service unit 41 of packet transmission device A may distribute the AI ​​source data to the communication service unit 41 of packet transmission device B, and the communication service unit 41 of packet transmission device B may then distribute the AI ​​source data to the AI ​​unit 42 of packet transmission device B.

[0088] In one embodiment, the AI ​​unit 42 includes an AI acceleration chip or a computing board with an AI acceleration chip, and the AI ​​unit is disposed in a card slot of the packet transmission device. Optionally, the AI ​​unit 42 can return the AI ​​operation result to the communication service unit 41.

[0089] In one embodiment, the AI ​​unit 42 is connected to the communication service unit 41 via a high-speed serial computer expansion bus standard (Peripheral Component Interconnect Express, PCIE) or a network port. Specifically, the connection between the AI ​​unit 42 and the communication service unit 41 can be via PCIE or a network port, or PCIE and a network port.

[0090] Therefore, the packet transmission equipment provided in the embodiment of the present application reuses the network port, serial port, communication service board, AI acceleration chip or computing power board in the packet transmission equipment of the operator network, and provides an external interface for the AI ​​source data acquisition equipment in a low-cost, fast and easy-to-deploy manner, realizes data distribution and AI application operation, and realizes rapid networking.

[0091] In one embodiment, the communication service unit 41 is further configured to send the AI ​​operation result to the data interface unit, and the data interface unit is further configured to send the AI ​​operation result to an AI operation result response device. The AI ​​operation result response device is configured to perform subsequent processing on the AI ​​operation result. The AI ​​operation result response device may be the same device as the AI ​​source data acquisition device, or a different device. For example, the AI ​​source data acquisition device may be a terminal that collects user data and sends it to the packet transmission device 31 for AI calculation. The packet transmission device 31 may send the AI ​​operation result to the terminal, which then performs subsequent data processing. For another example, the AI ​​source data acquisition device may be a camera that collects a user's facial image and sends it to the packet transmission device 31 for AI image recognition. The packet transmission device 31 may send the AI ​​operation result to a terminal, which then performs subsequent data processing on the image recognition result.

[0092] In one embodiment, the port attribute of the packet transmission device is set to a dedicated port, and data from the dedicated port is prohibited from being transmitted outside the target area. Therefore, this embodiment of the application can ensure that data does not flow out of the edge computing operation and maintenance system, ensuring the data security of the edge computing operation and maintenance system.

[0093] The following describes the embodiments of this application in detail using the ZXCTN 6180H packet transmission device as an example. The ZXCTN 6180H device is a packet transmission device for a 5G transmission network (SPN). The device is presented in the form of a cabinet or frame and includes multiple network ports and a communication service board. It can complete the reading and distribution of network port data. The device reserves multiple card slots for board chip expansion.

[0094] The communication service unit 41 supports parsing of industrial control protocols such as Modbus or FINS, and can encode and decode industrial computer data. The communication service unit 41 also has image / video data encoding and decoding capabilities, including encoding and decoding protocols such as H.264 / H.265, and can encode and decode image / video data from cameras.

[0095] The communication service unit 41 may also include control device response software, which responds to various instructions from the control device. The instructions include at least one of the following:

[0096] The control device is used to configure a data transmission path for a non-directly connected packet transmission device among the plurality of packet transmission devices; and based on the data transmission path, the non-directly connected packet transmission device is controlled to perform routing configuration.

[0097] A computing power orchestration command is sent to the packet transmission device through the control device, where the computing power orchestration command includes at least one of the following: a port identifier of the second packet transmission device, an AI chip identifier of the first packet transmission device, and a port identifier of the result processing end of the AI ​​application software.

[0098] Generate a routing configuration command through the control device according to the port identifier of the second packet transmission device, the AI ​​chip identifier of the first packet transmission device, and the port identifier of the result processing end of the AI ​​application software; send the routing configuration command to the packet transmission device through the control device; control the packet transmission device to perform routing configuration based on the routing configuration command.

[0099] The instructions also include the installation, uninstallation, configuration, update, start, stop, and data reporting of AI application software. The communication service unit 41 may also include network management and operation response software. This module responds to various instructions from network management and operation, and can set a certain network port as a connection port for connecting to the control device. The communication service unit 41 may also include AI operation data forwarding software. After obtaining the image data from the camera from the network port, the software will perform encoding and decoding operations, and then transfer the image to the AI ​​application software and obtain the operation results. The results are then encoded and decoded and transmitted to the factory application end through the designated network port. At the same time, the operation data of the AI ​​application software can also be transmitted to the console.

[0100] AI unit 42, taking ZXCTN 6180H as an example, has multiple card slots reserved for each card slot. Each card slot can be inserted into an AI computing board for running AI applications. After inserting the computing board consisting of CPU + Xilinx2802 chip + memory card, it uses PCIE and network ports to connect to the communication business board for communication, completing the data transmission required for AI computing, such as images, AI computing results, etc.

[0101] The data interface unit 43 may include multiple external network ports and serial ports. The network ports may include Gigabit Ethernet (GE) or Fast Ethernet (FE) interfaces, and the serial ports may include multiple RS485 physical interfaces or Modbus serial communication interfaces. The data interface unit 43 is connected to the communication service board. The network port can be connected to a network camera or industrial camera. The camera can capture on-site photos and transmit them to the packet transmission device via the network port.

[0102] The control device can be composed of AI application management software and the operator's factory network management software and the hardware environment in which it runs. It is located inside the factory and connected to the packet transmission equipment through the network port. The main function of the AI ​​application management software is to manage, upgrade, configure the AI ​​application software running on the packet transmission equipment, monitor, count and save the AI ​​operation results. In this way, the needs of centralized management in the deployment of AI application software are met. The main function of the operator's factory network management software is to manage the operator's network port in a restricted manner. The original public network port can be modified into the factory AI application port. In this way, the factory application end only needs to connect to the factory AI application port to transmit data to the packet transmission equipment, thereby accelerating networking efficiency.

[0103] As shown in Figure 5, the embodiment of the present application also provides an electronic device 500, including a processor 501, a memory 502, and a program or instruction stored in the memory 502 and executable on the processor 501. When the program or instruction is executed by the processor 501, each process of the embodiment of the edge computing operation and maintenance method described above is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0104] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned edge computing operation and maintenance method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0105] The processor is the processor in the terminal described in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0106] An embodiment of the present application further provides a chip, which includes a processor and a communication card slot, the communication card slot and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned edge computing operation and maintenance method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0107] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0108] An embodiment of the present application further provides a computer program / program product, which is stored in a storage medium. The computer program / program product is executed by at least one processor to implement the various processes of the above-mentioned edge computing operation and maintenance method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0109] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0110] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0111] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. An edge computing operation and maintenance method, applied to a first packet transmission device, the method comprising: Acquire AI source data in a target area, wherein the first packet transmission device is arranged in the target area; Based on the AI ​​source data, running the AI ​​application software corresponding to the AI ​​source data to obtain an AI running result; The AI ​​operation result is sent to an AI operation result response device, and the response device is deployed in the target area.

2. The method of claim 1, wherein: The obtaining of AI source data in the target area includes: Receiving the AI ​​source data collected and sent by a data collection device in the target area; or The AI ​​source data is received through the operator slice network from a second packet transmission device in the target area, where the second packet transmission device is a device connected to a data collection device that collects the AI ​​source data.

3. The method of claim 1, wherein: The step of running the AI ​​application software corresponding to the AI ​​source data based on the AI ​​source data to obtain the AI ​​running result includes: Based on the AI ​​source data, the AI ​​application software corresponding to the AI ​​source data is run through the AI ​​unit to obtain an AI running result, wherein the AI ​​unit includes an AI acceleration chip or a computing power board with an AI acceleration chip, and there is a corresponding relationship between the AI ​​acceleration chip and the AI ​​application software.

4. The method of claim 3, wherein: The method further comprises: In response to the AI ​​application software configuration command, the correspondence between the AI ​​application software and the AI ​​acceleration chip is adjusted.

5. The method of claim 1, wherein: Sending the AI ​​operation result to the AI ​​operation result response device includes: Sending the AI ​​operation result to the AI ​​operation result response device through a first target port of the first packet transmission device, wherein the first target port is a pre-configured port for communicating with the AI ​​operation result response device; or The AI ​​operation result is sent to a third packet transmission device directly connected to the AI ​​operation result response device through the operator slice network, so as to send the AI ​​operation result to the AI ​​operation result response device through the second target port of the third packet transmission device.

6. The method of claim 1, wherein: Before obtaining the AI ​​source data in the target area, the method further includes: Acquire a topological relationship between each of the packet transmission devices in the target area; According to the topological relationship, the routing transmission channel between each of the packet transmission devices is configured. To transmit target business data.

7. The method of claim 1, wherein: After the AI ​​application software corresponding to the AI ​​source data is run based on the AI ​​source data to obtain the AI ​​running result, the method further includes: The AI ​​operation result is sent to the control device in the target area.

8. The method of claim 7, wherein: Sending the AI ​​operation result to the control device in the target area includes: Sending the AI ​​operation result to a directly connected edge computing device directly connected to the control device through the operator slice network, so that the directly connected edge computing device sends the AI ​​operation result to the control device through the third target port; or, The AI ​​operation result is sent to the control device through a fourth target port of the first packet transmission device, wherein the fourth target port is a pre-configured port for communicating with the control device.

9. The method of claim 8, wherein: The method further comprises: Receiving a port attribute modification command sent by the control device; Based on the attribute modification command, the port attribute of the first packet transmission device is modified to a dedicated port attribute, where the dedicated port attribute is used to indicate that a transmission path between the first packet transmission device and outside the target area is disabled.

10. The method of claim 7, wherein: The control device is used to control at least one of the following: Controlling the installation of AI application software in the packet transmission device; Controlling the uninstallation of the AI ​​application software in the packet transmission device; Controlling the configuration of the AI ​​application software in the packet transmission device; Controlling the update of AI application software in the packet transmission device; Controlling the startup of the AI ​​application software in the packet transmission device; Controlling the stopping of the AI ​​application software in the packet transmission device; Controlling data management of the AI ​​application software in the packet transmission device.

11. A packet transmission device, arranged in a target area, comprising: A communication service unit, used to obtain AI source data in a target area through a data interface unit; An AI unit is used to run corresponding AI application software based on the AI ​​source data to obtain the AI ​​running result; The communication service unit is further used to send the AI ​​operation result to an AI operation result response device, and the AI ​​operation result response device is deployed in the target area.

12. The packet transmission device according to claim 11, wherein: The AI ​​unit is connected to the communication service board and includes: The AI ​​unit and the communication service unit are connected via a high-speed serial computer expansion bus standard PCIE or a network port.

13. The packet transmission device according to claim 11, wherein: The AI ​​unit includes: an AI acceleration chip or a computing board with an AI acceleration chip, and the AI ​​unit is arranged on a card slot of the packet transmission device.

14. The packet transmission device according to claim 11, wherein: The data interface unit is also used to connect with the AI ​​source data acquisition device, the control device, and other packet transmission devices in the target area.

15. An edge computing operation and maintenance system, wherein: include: A packet transmission device, the packet transmission device is used to obtain AI source data in a target area; Perform AI operation based on the AI ​​source data to obtain an AI operation result; and send the AI ​​operation result to an AI operation result response device; a control device, the control device being connected to the packet transmission device and being used to control the packet transmission device; The packet transmission device and the control device are both arranged in the target area.

16. The edge computing operation and maintenance system according to claim 15, wherein: There are multiple packet transmission devices, the control device is connected to the direct-connected packet transmission device through a first network port, the direct-connected packet transmission device is one of the multiple packet transmission devices, and the direct-connected packet transmission device is used to receive a control command from the control device through the first network port; The directly connected packet transmission device is also used to forward the control commands of the control device to other packet transmission devices through the operator slicing network technology.

17. An electronic device, wherein: It includes a processor and a memory, the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the edge computing operation and maintenance method as described in any one of claims 1 to 10 are implemented.

18. A readable storage medium, wherein: The readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of the edge computing operation and maintenance method as described in any one of claims 1 to 10 are implemented.

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