Edge computing device, device control method and related apparatus

Abstract

The embodiment of the present application discloses an edge computing device, a device control method and related devices, wherein the edge computing device includes: a core board module and a network interface; the network interface is used to receive a work instruction from a mobile terminal, the work instruction carries a work task parameter, and the work task parameter includes a first task type, a first task object and a first task requirement parameter; the core board module is used to obtain data to be processed according to the first task object, determine a first task execution algorithm according to the first task type, and determine a first control parameter according to the first task type and the first task requirement parameter; process the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result; the network interface is further used to return the first processing result to the mobile terminal. The use of the embodiment of the present application can improve the intelligence of the edge computing device.

Description

Technical Field

[0001] The present application relates to the field of computer technology or artificial intelligence technology, and specifically to an edge computing device, a device control method, and related apparatuses. Background Art

[0002] With the rapid development of electronic technology, artificial intelligence has become a market hotspot, and computing power is becoming increasingly important. As a result, edge computing devices have also seen rapid development. Edge computing devices (such as edge computing boxes) are specially designed to perform data processing tasks at the edge of the network. They mainly reduce latency and bandwidth usage by deploying computing resources close to the data source.

[0003] In practical applications, a typical product structure includes one or more processors, storage units, memory, and network interfaces. These modules work together to enable edge computing devices to quickly respond to locally generated data requests without sending the data to a cloud server for processing. Currently, edge computing devices are still not intelligent enough, so the question of how to improve their intelligence is urgent. Summary of the Invention

[0004] The embodiments of the present application provide an edge computing device, a device control method, and related apparatuses, which can enhance the intelligence of the edge computing device.

[0005] In a first aspect, an embodiment of the present application provides an edge computing device, the edge computing device comprising: a core board module and a network interface, wherein:

[0006] The network interface is configured to receive a work instruction from a mobile terminal, wherein the work instruction carries work task parameters, and the work task parameters include a first task type, a first task object, and a first task requirement parameter;

[0007] The core board module is used to obtain the data to be processed according to the first task object, determine the first task execution algorithm according to the first task type, and determine the first control parameter according to the first task type and the first task requirement parameter; process the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result;

[0008] The network interface is further configured to return the first processing result to the mobile terminal.

[0009] In a second aspect, an embodiment of the present application provides a device control method, which is applied to an edge computing device, wherein the edge computing device includes: a core board module and a network interface, and the method includes:

[0010] receiving a work instruction from a mobile terminal through the network interface, the work instruction carrying work task parameters, the work task parameters including a first task type, a first task object, and a first task requirement parameter;

[0011] Acquiring, by the core board module, data to be processed according to the first task object, determining a first task execution algorithm according to the first task type, and determining a first control parameter according to the first task type and the first task requirement parameter; processing the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result;

[0012] The first processing result is returned to the mobile terminal through the network interface.

[0013] In a third aspect, an embodiment of the present application provides an edge computing device, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the second aspect of the embodiment of the present application.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the above-mentioned computer-readable storage medium stores a computer program for electronic data exchange, wherein the above-mentioned computer program enables a computer to execute some or all of the steps described in the second aspect of the embodiment of the present application.

[0015] In a fifth aspect, embodiments of the present application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to execute some or all of the steps described in the second aspect of the embodiments of the present application. The computer program product may be a software installation package.

[0016] The implementation of the embodiments of this application has the following beneficial effects:

[0017] It can be seen that the edge computing device, device control method and related apparatus described in the embodiments of the present application, the edge computing device includes: a core board module and a network interface, the network interface receives the work instruction of the mobile terminal, the work instruction carries the work task parameters, and the work task parameters include the first task type, the first task object and the first task requirement parameters; the core board module obtains the data to be processed according to the first task object, determines the first task execution algorithm according to the first task type, and determines the first control parameter according to the first task type and the first task requirement parameters; processes the data to be processed according to the first task execution algorithm and the first control parameter to obtain the first processing result; the network interface returns the first processing result to the mobile terminal, so that the corresponding task execution algorithm can be adapted based on the task, and the corresponding control parameters can be determined based on the task-related requirement parameters, so that the task execution effect is deeply adapted to the task requirements required by the user, thereby improving the intelligence of the edge computing device. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a schematic diagram of the structure of an edge computing device provided in an embodiment of the present application;

[0020] Figure 2 This is another structural diagram of an edge computing device provided in an embodiment of the present application;

[0021] Figure 3 This is a schematic diagram of the system architecture of a device control system provided by an embodiment of the present application;

[0022] Figure 4 This is a flow chart of a device control method provided in an embodiment of the present application;

[0023] Figure 5 This is another structural diagram of an edge computing device provided in an embodiment of the present application;

[0024] Figure 6 This is a block diagram of the functional units of a device control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0027] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0028] In the embodiments of the present application, the mobile terminal involved may be a device with communication capabilities, and the mobile terminal may include various wearable devices with wireless communication functions (smart glasses, smart bracelets, Internet of Things devices (such as smart refrigerators, smart washing machines, smart TVs), smart watches, etc.), handheld devices, smart home devices, vehicle-mounted devices (in-vehicle cameras, driving recorders, vehicle-mounted speakers, etc.), computing devices or other processing devices connected to a wireless modem, as well as various forms of user equipment (UE), mobile stations (MS), terminal devices, etc.

[0029] In the embodiments of the present application, the operating principle of the edge computing device is mainly based on the concept of distributed computing. Specifically, it uses devices located at the edge of the network to perform computing-intensive tasks to reduce the burden on centralized data centers and improve application performance. The edge computing device runs specific applications and services that can perform real-time analysis and decision-making on locally collected data. The edge computing device can include at least one of the following: an edge computing box, an edge server, a mobile supercomputing box, etc., which are not limited here.

[0030] Specifically, in terms of data processing, it supports a wide range of tasks, from simple data analysis to complex AI model training and inference. It offers advantages in low latency, bandwidth savings, and enhanced privacy protection. Low latency primarily stems from computing occurring close to where the data is generated, significantly reducing data processing latency. Bandwidth savings primarily stem from transmitting only necessary information to the cloud, reducing network bandwidth consumption. Enhanced privacy protection primarily stems from the ability to process sensitive data locally, reducing the risk of data leakage.

[0031] The following is a detailed introduction to the embodiments of the present application.

[0032] See also Figure 1 , Figure 1 This is a schematic diagram of the structure of an edge computing device provided by an embodiment of the present application, wherein the edge computing device includes: a core board module and a network interface, wherein:

[0033] The network interface is configured to receive a work instruction from a mobile terminal, wherein the work instruction carries work task parameters, and the work task parameters include a first task type, a first task object, and a first task requirement parameter;

[0034] The core board module is used to obtain the data to be processed according to the first task object, determine the first task execution algorithm according to the first task type, and determine the first control parameter according to the first task type and the first task requirement parameter; process the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result;

[0035] The network interface is further configured to return the first processing result to the mobile terminal.

[0036] Among them, the first task type may include any computing task that a user needs to perform, and the first task type may include at least one of the following: target detection, behavior analysis, image enhancement, image denoising, semantic analysis, model training, etc., which are not limited here.

[0037] The first task type may include one or more task types.

[0038] The first task requirement parameters may include at least one of the following: task content, task accuracy, task duration, task complexity, etc., which are not limited here.

[0039] The first task object may be understood as data required to execute a task corresponding to the first task type.

[0040] The data to be processed may include at least one of the following: video, image, voice, sensor data, text data, etc., which are not limited here.

[0041] In a specific implementation, the edge computing device may include: a core board module and a network interface. Figure 2 As shown, the edge computing device may further include at least one of the following modules: an expansion board, a power management module, a cooling system, an external expansion interface module, a storage unit, a memory, etc., which are not limited here. The core board module may include a main processor module.

[0042] In specific implementation, such as Figure 3 As shown, a communication connection is established between the mobile terminal and the edge computing device, for example, the edge computing device communicates with the mobile terminal through a network interface. The network interface can receive a work instruction from the mobile terminal, and the work instruction carries work task parameters, and the work task parameters include a first task type, a first task object, and a first task requirement parameter. The core board module can obtain data to be processed according to the first task object, and can also pre-store a mapping relationship between a preset task type and a task execution algorithm, and then determine the first task execution algorithm corresponding to the first task type based on the mapping relationship. The first control parameter is used to control the algorithm execution effect of the first task execution algorithm, and the algorithm execution effect may include at least one of the following: execution speed, execution accuracy, execution order, execution priority, etc., which are not limited here.

[0043] Next, since the first task type and the first task requirement parameters reflect the task requirements, the first control parameters are determined based on the first task type and the first task requirement parameters, and the data to be processed is processed according to the first task execution algorithm and the first control parameters to obtain the first processing result. The network interface then returns the first processing result to the mobile terminal. That is, the corresponding control parameters can be determined based on the actual task requirements, so that the task execution effect is deeply adapted to the task requirements required by the user, thereby improving the intelligence of the edge computing device.

[0044] In the specific implementation, regarding the function of the core board module, as the core component of the system, it is mainly responsible for executing complex video analysis algorithms. This video analysis algorithm can be used to implement at least one of the following functions: target detection, behavior analysis, etc., which are not limited here. Regarding the location of the core board module, it is located in the center of the edge computing device, above the expansion board, to facilitate efficient data exchange with other key modules. Regarding the connection relationship of the core board, it is directly connected to the storage unit, expansion board and power management module to ensure the stability of data processing and power supply.

[0045] In specific implementations, the expansion board can provide additional hardware support for its functions. For example, it can include additional storage space and interfaces to facilitate programming and testing of the core board. Regarding its location, the expansion board is installed immediately below the core board module, facilitating rapid data transmission and processing. Regarding the connection relationship of the expansion board, it is connected to the main processor module via a high-speed bus, enabling efficient data exchange and resource sharing.

[0046] Specifically, the power management module provides power to the entire system and manages power, including voltage conversion and overload protection, to ensure stable system operation. The module is connected to the baseboard, providing power and managing the entire system. The module's connections are connected to all components requiring power via expansion board wiring, ensuring stable power supply for each component.

[0047] The cooling system may include at least one of the following: a cooling fan, a thermal pad, a coolant, etc., which are not limited here.

[0048] In specific implementations, the cooling system's main principle could be a combination of active and passive cooling to maintain the operating temperature of the main processor module and other heat-generating components within a safe range, preventing performance degradation due to overheating. Regarding the location of the cooling system, passive cooling involves connecting the device's main heat-generating processor chip to the device's housing via a thermal pad, dissipating heat through the housing. Active cooling involves fans located on the side of the device, dissipating heat through air circulation within the box. Regarding the cooling system's connections, the cooling fan is connected to the baseplate and powered by the baseplate power supply module.

[0049] In specific implementations, the external expansion interface module provides multiple external interfaces to facilitate user connection to external devices for data transmission or system maintenance. Specific interfaces include a USB interface for burning the system, an Ethernet port for network connection, a power port for power supply, and a TF card slot for expanding storage capacity. Regarding the location of the external expansion interface module, these interfaces are integrated at the edge of the expansion board for easy access. Regarding the connection relationship of the external expansion interface module, the circuit design on the expansion board ensures that each interface can operate stably and exchange data efficiently with the core board module.

[0050] In a specific implementation, the core board module may include at least one of the following: a main processor module, a high-performance processor (such as an ARM architecture or an x86 architecture), a GPU, an FPGA, a dedicated accelerator to enhance video processing capabilities (such as the NVIDIA Jetson series modules), etc., which are not limited here. Among them, the NVIDIA Jetson series modules can provide powerful parallel computing capabilities, which are particularly suitable for deep learning tasks, thereby improving processing speed and efficiency, especially in application scenarios that require a large number of matrix operations.

[0051] In practice, in addition to using fans for active heat dissipation, passive cooling designs can also be considered, such as increasing the number of heat sinks or heat pipes, or using a liquid cooling system to improve heat dissipation. This can reduce noise and is suitable for environments with high requirements for quietness. Of course, liquid cooling systems can provide better heat dissipation performance in extreme environments.

[0052] In specific implementation, in addition to the existing USB, network port, power port, TF card slot and other interfaces, the external expansion interface module can also integrate other types of interfaces, such as HDMI, DisplayPort, SATA, etc., to meet the needs of more application scenarios. This increases the versatility and flexibility of the device and facilitates connection with other devices.

[0053] In specific implementations, task types may include video processing tasks. For example, for video stream reception and preprocessing, in the specific implementation, in the video stream reception stage, in addition to directly pulling the video stream from the camera, it can also support reading pre-recorded video files from local storage devices (such as hard disks, SSDs) for analysis. This can be used for offline testing or data playback, thereby increasing the flexibility of the system and allowing algorithm debugging and verification without a real-time video source. For example, for core video analysis, in addition to using deep learning models for target detection and classification, it can also be combined with traditional computer vision algorithms (such as background difference method, optical flow method, etc.) as a supplement to adapt to different scene requirements. This can not only improve the robustness and adaptability of the algorithm, but also provide better detection results in certain specific situations.

[0054] In an embodiment of the present application, edge computing devices are deployed in a distributed manner, and multiple edge computing devices are formed into a distributed network. Each box is responsible for processing the video stream within its coverage area, and coordinating communication and data sharing between the boxes through a central node. This not only improves the scalability and fault tolerance of the system, but also can be applied to large-scale monitoring systems or cross-regional applications.

[0055] In the embodiments of this application, cloud-based collaborative processing can also be implemented. Edge computing devices can further enhance processing capabilities and data analysis accuracy by working in conjunction with cloud servers. For example, the results of preliminary processing can be uploaded to the cloud for more in-depth analysis or long-term storage. This combines the advantages of edge computing and cloud computing, ensuring real-time performance while fully utilizing the powerful computing resources of the cloud.

[0056] In an embodiment of the present application, the edge computing device may also have a built-in wireless communication module, such as a Wi-Fi module, a wired network interface (such as Ethernet), and a cellular communication module (4G / 5G / 6G).

[0057] In specific implementation, a Wi-Fi module can be integrated inside the device, enabling it to directly connect to a wireless local area network (WLAN), thereby improving the device's mobility and deployment flexibility. It can quickly access the network without wiring, making it convenient to use in temporary or difficult-to-wire environments, such as outdoor activities, emergency response, and other scenarios.

[0058] In addition, the integrated 4G or 5G cellular communication module enables the device to communicate through the mobile data network in the absence of Wi-Fi coverage, enhancing the device's availability in remote environments or environments without fixed network infrastructure, supporting high-speed data transmission, and is suitable for application scenarios that require real-time processing of large amounts of video data.

[0059] The edge computing device in the embodiments of the present application, through its unique structural design, material selection, and optimized assembly process, has achieved significant beneficial effects in many aspects compared to related technologies, as follows:

[0060] A. Compact structure, easy to carry and install. Dimensional optimization: The device's overall shape is a rectangle, with a length, width, and height no more than 10 cm. This significantly reduces the device's size, making it easier to carry and install in confined spaces. For example, chamfered corners enhance the device's aesthetics while minimizing potential damage to humans or other objects in the event of a collision.

[0061] B. Efficient heat dissipation ensures stable operation. The cooling system includes a cooling fan that effectively increases air circulation within the device. This, combined with ventilation holes on the side of the housing, quickly removes heat generated by the core board and expansion boards, ensuring long-term stable operation. Furthermore, the use of sheet metal aluminum for the housing ensures overall strength while also enhancing heat dissipation due to its excellent thermal conductivity.

[0062] C. Simplify the assembly process and improve production efficiency. Modular assembly: During device assembly, first plug the mainboard into the expansion board, then connect the cooling fan. Finally, place the assembled components into the housing and secure them with screws. This modular assembly method simplifies the assembly process, reduces operational difficulty, and helps improve production efficiency. Easy maintenance: The easy-to-assemble and disassemble design facilitates subsequent maintenance and component replacement, reducing repair costs.

[0063] D. Enhanced applicability and reliability. Through a rational structural design and heat dissipation solution, the device can operate stably in a wider range of environmental conditions, improving its applicability and reliability, making it adaptable to a variety of environments. The use of high-quality materials (such as sheet metal aluminum) and a carefully designed structure enhances the device's ability to withstand external impacts, extending its service life and improving its durability.

[0064] The embodiments of this application, by optimizing the device's form factor, improving heat dissipation design, and simplifying the assembly process, offer significant advantages in portability, stability, ease of use, and durability, resulting in significant market competitiveness and technical advantages. These improvements not only enhance the user experience but also greatly facilitate deployment and maintenance in practical applications.

[0065] In the embodiments of the present application, firstly, by designing a modular hardware and software architecture, the device can quickly adjust its configuration according to the requirements of different application scenarios and support various types of computing tasks, thereby improving flexibility; secondly, it allows users to easily expand computing power according to actual needs without replacing the entire system, and only needs to add or upgrade specific components, thereby enhancing scalability; thirdly, it adopts advanced power management and energy-saving technologies to ensure that energy consumption is minimized while maintaining high performance, which is suitable for application scenarios with long-term operation and optimizes energy efficiency; fourthly, it develops a lightweight and compact design scheme, making the device easy to carry and deploy, adapting to the immediate use needs in various environments, and improving portability.

[0066] In the embodiments of this application, the intelligent scheduling algorithm can be understood as a built-in intelligent scheduling algorithm that can dynamically allocate computing resources to ensure that each task can achieve the optimal processing speed and effect. In specific implementations, a highly integrated all-in-one solution integrates computing, storage, network connectivity, and energy management functions, reducing the need for external components and simplifying the deployment process.

[0067] Optionally, the edge computing device further includes a cooling system; in determining the first control parameter according to the first task type and the first task requirement parameter, the core board module is specifically configured to:

[0068] Obtaining a first operating parameter of the edge computing device;

[0069] determining a first performance evaluation value corresponding to the first operating parameter;

[0070] Determining a second performance evaluation value corresponding to the first task type and the first task requirement parameters;

[0071] When the first performance evaluation value is less than the second performance evaluation value, obtaining a first cooling parameter corresponding to the cooling system;

[0072] determining a first difference between the first performance evaluation value and the second performance evaluation value;

[0073] determining a first adjustment parameter corresponding to the first difference;

[0074] Adjusting the first cooling parameter according to the first adjustment parameter to obtain a second cooling parameter;

[0075] The cooling system is controlled to perform cooling according to the second cooling parameter.

[0076] The first operating parameter may include at least one of the following: operating mode, operating voltage, operating current, operating power, operating system type, system running score, etc., which are not limited here. The first operating parameter is used to reflect the performance of the edge computing device.

[0077] Specifically, a first operating parameter of the edge computing device can be obtained, a mapping relationship between preset operating parameters and performance evaluation values ​​can be pre-stored, and then a first performance evaluation value corresponding to the first operating parameter can be determined based on the mapping relationship.

[0078] The first cooling parameter corresponding to the cooling system may include at least one of the following: cooling mode, cooling rate, cooling degree, cooling area, cooling direction, cooling frequency, etc., which are not limited here.

[0079] Furthermore, the first task type and the first task requirement parameters reflect the performance required by the actual task. The second performance evaluation value corresponding to the first task type and the first task requirement parameters can be determined. When the first performance evaluation value is less than the second performance evaluation value, it means that the performance (operating environment) of the current edge computing device does not meet the performance required by the task. The first cooling parameter corresponding to the cooling system can be obtained, and the first difference between the first performance evaluation value and the second performance evaluation value can also be determined. The first difference = the first performance evaluation value - the second performance evaluation value. The first difference reflects the degree of difference between the actual performance of the edge computing device and the performance required by the actual task.

[0080] The first cooling parameter may include at least one of the following: a first active cooling parameter, a first passive cooling parameter, etc., which are not limited here. The first active cooling parameter may include a cooling parameter corresponding to an active cooling device, and the first passive cooling parameter may include a cooling parameter corresponding to a passive cooling device.

[0081] Next, the mapping relationship between the preset difference and the adjustment parameter can be pre-stored, and then, the first adjustment parameter corresponding to the first difference can be determined based on the mapping relationship, and then the first cooling parameter can be adjusted according to the first adjustment parameter to obtain the second cooling parameter, that is, the second cooling parameter = (1 + first adjustment parameter) * first cooling parameter. Finally, the cooling system can be controlled for cooling according to the second cooling parameter. In this way, the cooling parameters of the cooling system can be dynamically adjusted based on the degree of difference between the actual performance of the edge computing device and the performance required by the actual task, so that the cooling effect depth conforms to the actual performance situation. Therefore, the actual performance (operating environment) of the edge computing device can be further improved, which helps to improve the intelligence of the edge computing device.

[0082] Optionally, in determining the second performance evaluation value corresponding to the first task type and the first task requirement parameters, the core board module is specifically configured to:

[0083] determining a reference performance evaluation value corresponding to the first task type;

[0084] Determining a first influencing parameter corresponding to the first task requirement parameter;

[0085] The second performance evaluation value is determined according to the first influencing parameter and the reference performance evaluation value.

[0086] In the specific implementation, the mapping relationship between the preset task type and the performance evaluation value can be pre-stored, and then, the reference performance evaluation value corresponding to the first task type can be determined based on the mapping relationship. The mapping relationship between the preset task requirement parameters and the influencing parameters can also be pre-stored, and then, the first influencing parameter corresponding to the first task requirement parameter can be determined based on the mapping relationship, and then the second performance evaluation value is determined according to the first influencing parameter and the reference performance evaluation value. The second performance evaluation value = (1 + first influencing parameter) * reference performance evaluation value. Not only can the corresponding reference performance evaluation value be adapted based on the task type, the first task requirement parameter reflects the task effect, and the reference performance evaluation value can also be deeply optimized based on the task effect, so that the performance required for the actual task can be accurately determined, which helps to improve the intelligence of the edge computing device.

[0087] Optionally, in determining the first control parameter according to the first task type and the first task requirement parameter, the core board module is specifically configured to:

[0088] Determining a control parameter set of the first task execution algorithm corresponding to the first task type, the control parameter set including multiple groups of control parameters, each control parameter corresponding to a performance evaluation value;

[0089] determining an absolute value of a difference between the reference performance evaluation value and the performance evaluation values ​​corresponding to the plurality of groups of control parameters to obtain a plurality of absolute values;

[0090] A minimum value among the multiple absolute values ​​is selected, and the first control parameter is determined according to the minimum value.

[0091] In a specific implementation, a mapping relationship between a preset task type and a control parameter set of a task execution algorithm can be pre-stored, and then, based on the mapping relationship, the control parameter set of the first task execution algorithm corresponding to the first task type can be determined. The control parameter set includes multiple groups of control parameters, and each control parameter corresponds to a performance evaluation value. Then, the absolute value of the difference between the reference performance evaluation value and the performance evaluation values ​​corresponding to the multiple groups of control parameters can be determined to obtain multiple absolute values. The minimum value of the multiple absolute values ​​is then selected, and the first control parameter is determined based on the minimum value. For example, the control parameter corresponding to the minimum value is used as the first control parameter. In this way, the control parameters corresponding to the performance required by the actual task can be deeply configured, so that the task effect deeply meets user needs, thereby helping to improve the intelligence of edge computing devices.

[0092] Optionally, the core board module is further specifically used for:

[0093] When the first performance evaluation value is greater than or equal to the reference performance evaluation value, the step of determining the first control parameter according to the first task type and the first task requirement parameter is performed.

[0094] In a specific implementation, when the first performance evaluation value is greater than or equal to the reference performance evaluation value, it means that the performance (operating environment) of the current edge computing device can meet the performance required by the task, and then the step of determining the first control parameter according to the first task type and the first task requirement parameter can be executed, which helps to improve the intelligence of the edge computing device.

[0095] Optionally, the core board module is further specifically used for:

[0096] Acquire the temperature of the edge computing device at every preset time interval to obtain multiple temperatures, each temperature corresponding to a sampling moment;

[0097] Perform fitting according to the multiple temperatures and corresponding sampling moments to obtain a fitting straight line;

[0098] Obtaining the slope of the fitted straight line to obtain a first slope;

[0099] determining a first feedback adjustment parameter corresponding to the first slope;

[0100] performing feedback adjustment on the first control parameter according to the first feedback adjustment parameter to obtain a second control parameter;

[0101] In terms of processing the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result, the core board module is specifically used to:

[0102] The data to be processed is processed according to the first task execution algorithm and the second control parameter to obtain the first processing result.

[0103] The preset time interval may be pre-set or set by system default. The preset time interval may be related to the task type. For example, a mapping relationship between preset task types and time intervals may be pre-stored, and then the preset time interval corresponding to the first task type may be determined based on the mapping relationship.

[0104] In a specific implementation, the temperature of the edge computing device can be obtained at preset time intervals to obtain multiple temperatures, each temperature corresponding to a sampling moment, and each temperature and sampling moment can be regarded as a coordinate point, that is, the multiple temperatures and sampling moments can be mapped to a coordinate system, the horizontal axis of the coordinate system is time, and the vertical axis is temperature, that is, multiple coordinate points can be determined based on the multiple temperatures and corresponding sampling moments, and the multiple coordinate points are fitted to obtain a fitting line, and the slope of the fitting line is obtained to obtain a first slope, which reflects the temperature change trend. That is, a mapping relationship between a preset slope and a feedback adjustment parameter can be pre-stored. Then, a first feedback adjustment parameter corresponding to the first slope can be determined based on the mapping relationship, and then the first control parameter is feedback-adjusted based on the first feedback adjustment parameter to obtain a second control parameter, that is, the second control parameter = (1 + first feedback adjustment parameter) * first control parameter. In this way, the temperature change trend reflects the change in actual performance (operating environment). Based on the temperature change trend feedback, the control parameters related to the task execution algorithm are adjusted, so that the control parameters corresponding to the performance required by the actual task are dynamically adapted, so that the task effect deeply meets user needs, thereby helping to improve the intelligence of the edge computing device.

[0105] Next, the data to be processed is processed according to the first task execution algorithm and the second control parameters to obtain a first processing result, so that the task effect is in line with user needs, thereby helping to improve the intelligence of the edge computing device.

[0106] For example, taking the edge computing device as a mobile supercomputing box, the mobile supercomputing box is paired with a mobile terminal through wireless technology to provide computing power support for the mobile terminal. Specifically, the user can interact with the mobile supercomputing box on a mobile terminal (for example, a mobile phone, a laptop, a walkie-talkie, a tablet computer (PAD), etc.), and issue work instructions through the mobile terminal. The instructions enter the mobile supercomputing box through the wireless network and are temporarily stored in the temporary storage space provided by the expansion board. Subsequently, the core board module starts the preset application and completes the instruction. After the instruction is completed, the result is returned to the mobile terminal through the wireless network and presented to the user.

[0107] It can be seen that the edge computing device described in the embodiment of the present application includes: a core board module and a network interface, the network interface receives the work instructions of the mobile terminal, the work instructions carry work task parameters, and the work task parameters include a first task type, a first task object and a first task requirement parameter; the core board module obtains the data to be processed according to the first task object, determines the first task execution algorithm according to the first task type, and determines the first control parameter according to the first task type and the first task requirement parameter; processes the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result; the network interface returns the first processing result to the mobile terminal, so that the corresponding task execution algorithm can be adapted based on the task, and the corresponding control parameters can be determined based on the task-related requirement parameters, so that the task execution effect is deeply adapted to the task requirements required by the user, thereby improving the intelligence of the edge computing device.

[0108] See also Figure 4 , Figure 4 This is a flow chart of a device control method provided in an embodiment of the present application. The device control method is applied to an edge computing device. The edge computing device includes: a core board module and a network interface. The device control method includes:

[0109] 401. Receive a work instruction from a mobile terminal through the network interface, where the work instruction carries work task parameters, and the work task parameters include a first task type, a first task object, and a first task requirement parameter.

[0110] 402. Obtain the data to be processed according to the first task object through the core board module, determine the first task execution algorithm according to the first task type, and determine the first control parameter according to the first task type and the first task requirement parameter; process the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result.

[0111] 403. Return the first processing result to the mobile terminal through the network interface.

[0112] Among them, the specific description of the above steps 401 to 403 can refer to the relevant description of the above edge computing device, and will not be repeated here.

[0113] Optionally, the edge computing device further includes a cooling system; and may further include the following steps:

[0114] Obtaining a first operating parameter of the edge computing device;

[0115] determining a first performance evaluation value corresponding to the first operating parameter;

[0116] Determining a reference performance evaluation value corresponding to the first task type and the first task requirement parameters;

[0117] When the first performance evaluation value is less than the reference performance evaluation value, obtaining a first cooling parameter of the cooling system at a current moment;

[0118] determining a first difference between the first performance evaluation value and the reference performance evaluation value;

[0119] determining a first adjustment parameter corresponding to the first difference;

[0120] Adjusting the first cooling parameter according to the first adjustment parameter to obtain a second cooling parameter;

[0121] The cooling system is controlled to perform cooling according to the second cooling parameter.

[0122] Among them, the specific description of the relevant steps in this example can refer to the relevant description of the above-mentioned edge computing device, and will not be repeated here.

[0123] Optionally, in determining the second performance evaluation value corresponding to the first task type and the first task requirement parameters, it can be implemented as follows:

[0124] determining a reference performance evaluation value corresponding to the first task type;

[0125] Determining a first influencing parameter corresponding to the first task requirement parameter;

[0126] The second performance evaluation value is determined according to the first influencing parameter and the reference performance evaluation value.

[0127] Among them, the specific description of the relevant steps in this example can refer to the relevant description of the above-mentioned edge computing device, and will not be repeated here.

[0128] It can be seen that the device control method described in the embodiment of the present application is applied to an edge computing device, which includes: a core board module and a network interface, the network interface receives a work instruction from a mobile terminal, the work instruction carries work task parameters, and the work task parameters include a first task type, a first task object, and a first task requirement parameter; the core board module obtains the data to be processed according to the first task object, determines the first task execution algorithm according to the first task type, and determines the first control parameter according to the first task type and the first task requirement parameter; processes the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result; the network interface returns the first processing result to the mobile terminal, so that the corresponding task execution algorithm can be adapted based on the task, and the corresponding control parameters can be determined based on the task-related requirement parameters, so that the task execution effect is deeply adapted to the task requirements required by the user, thereby improving the intelligence of the edge computing device.

[0129] In accordance with the above embodiment, please refer to Figure 5 , Figure 5 This is a structural diagram of an edge computing device provided in an embodiment of the present application. As shown in the figure, the edge computing device includes a processor, a memory, a communication interface, and one or more programs. The one or more programs are stored in the memory and are configured to be executed by the processor. In the embodiment of the present application, the edge computing device includes: a core board module and a network interface. The program includes instructions for performing the following steps:

[0130] receiving a work instruction from a mobile terminal through the network interface, the work instruction carrying work task parameters, the work task parameters including a first task type, a first task object, and a first task requirement parameter;

[0131] Acquiring, by the core board module, data to be processed according to the first task object, determining a first task execution algorithm according to the first task type, and determining a first control parameter according to the first task type and the first task requirement parameter; processing the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result;

[0132] The first processing result is returned to the mobile terminal through the network interface.

[0133] Optionally, the edge computing device further includes a cooling system; and the program further includes instructions for executing the following steps:

[0134] Obtaining a first operating parameter of the edge computing device;

[0135] determining a first performance evaluation value corresponding to the first operating parameter;

[0136] Determining a reference performance evaluation value corresponding to the first task type and the first task requirement parameters;

[0137] When the first performance evaluation value is less than the reference performance evaluation value, obtaining a first cooling parameter of the cooling system at a current moment;

[0138] determining a first difference between the first performance evaluation value and the reference performance evaluation value;

[0139] determining a first adjustment parameter corresponding to the first difference;

[0140] Adjusting the first cooling parameter according to the first adjustment parameter to obtain a second cooling parameter;

[0141] The cooling system is controlled to perform cooling according to the second cooling parameter.

[0142] Optionally, in determining the second performance evaluation value corresponding to the first task type and the first task requirement parameters, the program includes instructions for performing the following steps:

[0143] determining a reference performance evaluation value corresponding to the first task type;

[0144] Determining a first influencing parameter corresponding to the first task requirement parameter;

[0145] The second performance evaluation value is determined according to the first influencing parameter and the reference performance evaluation value.

[0146] It can be seen that the edge computing device described in the embodiment of the present application includes: a core board module and a network interface, the network interface receives the work instructions of the mobile terminal, the work instructions carry work task parameters, and the work task parameters include a first task type, a first task object and a first task requirement parameter; the core board module obtains the data to be processed according to the first task object, determines the first task execution algorithm according to the first task type, and determines the first control parameter according to the first task type and the first task requirement parameter; processes the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result; the network interface returns the first processing result to the mobile terminal, so that the corresponding task execution algorithm can be adapted based on the task, and the corresponding control parameters can be determined based on the task-related requirement parameters, so that the task execution effect is deeply adapted to the task requirements required by the user, thereby improving the intelligence of the edge computing device.

[0147] Figure 6This is a functional unit block diagram of a device control device 600 involved in an embodiment of the present application. The device control device 600 is applied to an edge computing device, and the edge computing device includes: a core board module and a network interface. The device control device 600 includes: a receiving unit 601, a determining unit 602 and a returning unit 603, wherein,

[0148] The receiving unit 601 is configured to receive a work instruction from a mobile terminal through the network interface, wherein the work instruction carries work task parameters, and the work task parameters include a first task type, a first task object, and a first task requirement parameter;

[0149] The determining unit 602 is configured to obtain data to be processed according to the first task object through the core board module, determine a first task execution algorithm according to the first task type, and determine a first control parameter according to the first task type and the first task requirement parameter; and process the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result;

[0150] The returning unit 603 is configured to return the first processing result to the mobile terminal via the network interface.

[0151] Optionally, the edge computing device further includes a cooling system; and the device control device 600 is further specifically configured to:

[0152] Obtaining a first operating parameter of the edge computing device;

[0153] determining a first performance evaluation value corresponding to the first operating parameter;

[0154] Determining a reference performance evaluation value corresponding to the first task type and the first task requirement parameters;

[0155] When the first performance evaluation value is less than the reference performance evaluation value, obtaining a first cooling parameter of the cooling system at a current moment;

[0156] determining a first difference between the first performance evaluation value and the reference performance evaluation value;

[0157] determining a first adjustment parameter corresponding to the first difference;

[0158] Adjusting the first cooling parameter according to the first adjustment parameter to obtain a second cooling parameter;

[0159] The cooling system is controlled to perform cooling according to the second cooling parameter.

[0160] Optionally, in determining the second performance evaluation value corresponding to the first task type and the first task requirement parameters, the device control apparatus 600 is specifically configured to:

[0161] determining a reference performance evaluation value corresponding to the first task type;

[0162] Determining a first influencing parameter corresponding to the first task requirement parameter;

[0163] The second performance evaluation value is determined according to the first influencing parameter and the reference performance evaluation value.

[0164] It can be seen that the device control device described in the embodiment of the present application is applied to an edge computing device, and the edge computing device includes: a core board module and a network interface, the network interface receives the work instruction of the mobile terminal, the work instruction carries the work task parameters, and the work task parameters include the first task type, the first task object and the first task requirement parameters; the core board module obtains the data to be processed according to the first task object, determines the first task execution algorithm according to the first task type, and determines the first control parameter according to the first task type and the first task requirement parameters; processes the data to be processed according to the first task execution algorithm and the first control parameter to obtain the first processing result; the network interface returns the first processing result to the mobile terminal, so that the corresponding task execution algorithm can be adapted based on the task, and the corresponding control parameters can be determined based on the task-related requirement parameters, so that the task execution effect is deeply adapted to the task requirements required by the user, thereby improving the intelligence of the edge computing device.

[0165] It can be understood that the functions of each program module of the equipment control device of this embodiment can be specifically implemented according to the method in the above method embodiment. The specific implementation process can refer to the relevant description of the above method embodiment and will not be repeated here.

[0166] An embodiment of the present application further provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments.

[0167] The present application also provides a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to execute some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package.

[0168] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0169] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0170] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0171] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0172] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0173] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0174] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program. The program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0175] The above is a detailed introduction to the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, according to the idea of ​​the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An edge computing device, characterized in that: The edge computing device includes: a core board module and a network interface, wherein: The network interface is configured to receive a work instruction from a mobile terminal, wherein the work instruction carries work task parameters, and the work task parameters include a first task type, a first task object, and a first task requirement parameter; The core board module is used to obtain the data to be processed according to the first task object, determine the first task execution algorithm according to the first task type, and determine the first control parameter according to the first task type and the first task requirement parameter; process the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result; The network interface is further configured to return the first processing result to the mobile terminal; In the aspect of determining the second performance evaluation value corresponding to the first task type and the first task requirement parameter, the core board module is specifically used to: determining a reference performance evaluation value corresponding to the first task type; Determining a first influencing parameter corresponding to the first task requirement parameter; Determine the second performance evaluation value according to the first influencing parameter and the reference performance evaluation value; Wherein, in determining the first control parameter according to the first task type and the first task requirement parameter, the core board module is specifically used to: Determining a control parameter set of the first task execution algorithm corresponding to the first task type, the control parameter set including multiple groups of control parameters, each control parameter corresponding to a performance evaluation value; determining an absolute value of a difference between the reference performance evaluation value and the performance evaluation values ​​corresponding to the plurality of groups of control parameters to obtain a plurality of absolute values; Selecting a minimum value among the multiple absolute values, and determining the first control parameter according to the minimum value; The core board module is further used for: When the first performance evaluation value is greater than or equal to the reference performance evaluation value, the step of determining the first control parameter according to the first task type and the first task requirement parameter is performed.

2. The edge computing device according to claim 1, characterized in that The edge computing device also includes a cooling system; the core board module is further specifically used for: Obtaining a first operating parameter of the edge computing device; determining a first performance evaluation value corresponding to the first operating parameter; Determining a reference performance evaluation value corresponding to the first task type and the first task requirement parameters; When the first performance evaluation value is less than the reference performance evaluation value, obtaining a first cooling parameter of the cooling system at a current moment; determining a first difference between the first performance evaluation value and the reference performance evaluation value; determining a first adjustment parameter corresponding to the first difference; Adjusting the first cooling parameter according to the first adjustment parameter to obtain a second cooling parameter; The cooling system is controlled to perform cooling according to the second cooling parameter.

3. A device control method, characterized in that: The device control method is applied to an edge computing device, the edge computing device including: a core board module and a network interface, the method including: receiving a work instruction from a mobile terminal through the network interface, the work instruction carrying work task parameters, the work task parameters including a first task type, a first task object, and a first task requirement parameter; Acquiring, by the core board module, data to be processed according to the first task object, determining a first task execution algorithm according to the first task type, and determining a first control parameter according to the first task type and the first task requirement parameter; processing the data to be processed according to the first task execution algorithm and the first control parameter to obtain a first processing result; Returning the first processing result to the mobile terminal through the network interface; The determining of the second performance evaluation value corresponding to the first task type and the first task requirement parameters includes: determining a reference performance evaluation value corresponding to the first task type; Determining a first influencing parameter corresponding to the first task requirement parameter; Determine the second performance evaluation value according to the first influencing parameter and the reference performance evaluation value; The determining of the first control parameter according to the first task type and the first task requirement parameter includes: Determining a control parameter set of the first task execution algorithm corresponding to the first task type, the control parameter set including multiple groups of control parameters, each control parameter corresponding to a performance evaluation value; determining an absolute value of a difference between the reference performance evaluation value and the performance evaluation values ​​corresponding to the plurality of groups of control parameters to obtain a plurality of absolute values; Selecting a minimum value among the multiple absolute values, and determining the first control parameter according to the minimum value; The method further comprises: When the first performance evaluation value is greater than or equal to the reference performance evaluation value, the step of determining the first control parameter according to the first task type and the first task requirement parameter is performed.

4. The method according to claim 3, characterized in that The edge computing device further includes a cooling system; and the method further includes: Obtaining a first operating parameter of the edge computing device; determining a first performance evaluation value corresponding to the first operating parameter; Determining a reference performance evaluation value corresponding to the first task type and the first task requirement parameters; When the first performance evaluation value is less than the reference performance evaluation value, obtaining a first cooling parameter of the cooling system at a current moment; determining a first difference between the first performance evaluation value and the reference performance evaluation value; determining a first adjustment parameter corresponding to the first difference; Adjusting the first cooling parameter according to the first adjustment parameter to obtain a second cooling parameter; The cooling system is controlled to perform cooling according to the second cooling parameter.

5. An edge computing device, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the method according to claim 3 or 4.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to claim 3 or 4.

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