Equipment cooperative computing method and device, equipment and computer readable storage medium

Abstract

The invention discloses an equipment cooperative computing method and device, equipment and a computer readable storage medium. The method obtains algorithm deployment request information. And based on the algorithm deployment request information, screening a target first device from the plurality of first devices according to the resource parameters. And sending the algorithm program information to the target first device. And sending the data transmission information to the second device. And receiving a calculation result sent by the target first equipment, and sending the calculation result to the user equipment. The target algorithm program is sent to the target first equipment according to the algorithm deployment request information, and the target first equipment obtains the target data, so that the target first equipment can process the target data according to the target algorithm program, and the calculation result is obtained by cooperative calculation of the target first equipment and the second equipment; therefore, cooperative computing among multiple devices is realized based on the full-scene distributed operating system.

Description

Technical Field

[0001] This invention relates to the field of the Internet of Things (IoT), and more particularly to a method, apparatus, device, and computer-readable storage medium for device collaborative computing. Background Technology

[0002] Currently, open-source, full-scenario distributed operating systems, such as OpenHarmony, are capable of enabling interconnection and interoperability among devices across all scenarios, and are therefore widely applicable to Internet of Things (IoT) devices.

[0003] In related technologies, collaborative computing between multiple devices is typically achieved using pre-defined frameworks based on Linux or Android systems. However, the underlying code of a full-scenario distributed operating system does not support such pre-defined frameworks, making it impossible to achieve collaborative computing between multiple devices on a full-scenario distributed operating system. Summary of the Invention

[0004] This invention provides a method, apparatus, device, computer-readable storage medium, and computer program product for collaborative computing among devices, which can realize collaborative computing among multiple devices on a distributed operating system in all scenarios.

[0005] In a first aspect, embodiments of the present invention provide a method for device collaborative computing, applied to a control terminal, the control terminal including a full-scenario distributed operating system, the method comprising:

[0006] Receive algorithm deployment request information sent by user equipment;

[0007] Based on the algorithm deployment request information, and according to the resource parameters, the target first device with the highest device score corresponding to the resource parameters is selected from multiple first devices;

[0008] The algorithm program information is sent to the target first device through the soft bus of the full-scenario distributed operating system, so that the target first device can obtain the target algorithm program based on the algorithm program information;

[0009] Data transmission information is sent to the second device via a soft bus, which is used by the second device to send address information to the control terminal, which is used by the control terminal to send address information to the target first device, which is used by the target first device to obtain target data based on the address information and to calculate the target data using the target algorithm program. The computing power of the target first device is greater than that of the second device.

[0010] Receive the calculation results sent by the target first device and send the calculation results to the user equipment.

[0011] In an implementable embodiment, the resource parameter comprises at least one of a resource utilization and a device affinity probability; based on the algorithm deployment request information, the target first device with the maximum device score value corresponding to the resource parameter is selected from the plurality of first devices according to the resource parameter, comprising:

[0012] The resource utilization corresponding to the plurality of first devices is compared with the preset resource utilization threshold value respectively, and a first comparison result is obtained;

[0013] The device affinity probability corresponding to the plurality of first devices is compared with the preset device affinity probability threshold value respectively, and a second comparison result is obtained;

[0014] In the case that the first comparison result represents that the resource utilization corresponding to the first device is greater than or equal to the preset resource utilization threshold value, and the second comparison result represents that the device affinity probability corresponding to the first device is greater than or equal to the preset device affinity probability threshold value, the first device is taken as a candidate first device;

[0015] The resource utilization and the device affinity probability corresponding to each candidate first device are weighted calculated, and a plurality of device scores are obtained;

[0016] The candidate first device corresponding to the device score with the highest value in the plurality of device scores is taken as the target first device.

[0017] In a second aspect, an embodiment of the present application provides a device cooperative computing method applied to a first device, the first device comprising a full-scene distributed operating system, and the method comprising:

[0018] A communication connection is established with a second device through a soft bus of the full-scene distributed operating system;

[0019] Algorithm program information sent by a control end is received through the soft bus;

[0020] A target algorithm program is obtained according to the algorithm program information;

[0021] Address information sent by the control end is obtained through the soft bus;

[0022] Target data is obtained based on the address information;

[0023] A computing operation is performed on the target data by using the target algorithm program, and a computing result is obtained;

[0024] The computing result is sent to the control end through the soft bus, so that the control end sends the computing result to a user device.

[0025] In an implementable embodiment, the communication connection is established with the second device through the soft bus of the full-scene distributed operating system, comprising:

[0026] The request information is broadcasted through the target port.

[0027] obtaining response information corresponding to the request information through the soft bus;

[0028] establishing a communication connection with the second device corresponding to the response information.

[0029] In a third aspect, an embodiment of the present application provides a device cooperative computing method, applied to a second device, the second device comprising a full-scene distributed operating system, the method comprising:

[0030] establishing a communication connection with a target first device through a soft bus of the full-scene distributed operating system;

[0031] sending address information to the control end through the soft bus according to the data transmission information sent by the control end, so as to control the control end to send the address information to the target first device, so that the target first device obtains target data based on the address information and performs calculation on the target data by using the target algorithm program.

[0032] In an implementable embodiment, after sending the address information to the control end through the soft bus according to the data transmission information sent by the control end, the method further comprises:

[0033] obtaining initial data;

[0034] translating the initial data into target data corresponding to the preset parameter type according to the parameter information of the initial data.

[0035] In a fourth aspect, an embodiment of the present application provides a device cooperative computing apparatus, applied to a control end, the control end comprising a full-scene distributed operating system, the apparatus comprising:

[0036] a receiving module configured to receive algorithm deployment request information sent by a user device;

[0037] a screening module configured to screen, based on the algorithm deployment request information, a target first device with the largest device score value corresponding to a resource parameter from a plurality of first devices according to the resource parameter;

[0038] a sending module configured to send algorithm program information to the target first device through a soft bus of the full-scene distributed operating system, so that the target first device obtains a target algorithm program according to the algorithm program information;

[0039] The sending module is further configured to send data transmission information to the second device through the soft bus, so that the second device sends address information to the control end, so that the control end sends the address information to the target first device, so that the target first device obtains target data based on the address information and performs calculation on the target data by using the target algorithm program, and the computing power of the target first device is greater than that of the second device.

[0040] The receiving module is further configured to receive the calculation result sent by the target first device, and send the calculation result to the user equipment.

[0041] In a fifth aspect, an embodiment of the present application provides a device cooperative calculation apparatus applied to a first device, the first device comprising a full-scene distributed operating system, and the apparatus comprising:

[0042] The establishing module is configured to establish a communication connection with a second device through a soft bus of the full-scene distributed operating system;

[0043] The receiving module is configured to receive algorithm program information sent by a control end through the soft bus;

[0044] The obtaining module is configured to obtain a target algorithm program according to the algorithm program information;

[0045] The obtaining module is further configured to obtain address information sent by the control end through the soft bus;

[0046] The obtaining module is further configured to obtain target data based on the address information;

[0047] The executing module is configured to perform a calculation operation on the target data by using the target algorithm program to obtain a calculation result;

[0048] The sending module is configured to send the calculation result to the control end through the soft bus, so that the control end sends the calculation result to user equipment.

[0049] In a sixth aspect, an embodiment of the present application provides a device cooperative calculation apparatus applied to a second device, the second device comprising a full-scene distributed operating system, and the apparatus comprising:

[0050] The establishing module is configured to establish a communication connection with a target first device through a soft bus of the full-scene distributed operating system;

[0051] The sending module is configured to send address information to the control end through the soft bus according to data transmission information sent by the control end, so that the control end sends the address information to the target first device, and the target first device obtains target data based on the address information and performs a calculation on the target data by using a target algorithm program.

[0052] In a seventh aspect, an embodiment of the present application provides a device for device cooperative calculation, comprising a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to realize the method for device cooperative calculation according to any one of the first aspect or the second aspect or the third aspect.

[0053] In an eighth aspect, the embodiments of the present disclosure provide a computer readable storage medium, which stores computer program instructions. The computer program instructions are executed by a processor to implement the device cooperative computing method according to any one of the first aspect or the second aspect or the third aspect.

[0054] In a ninth aspect, the embodiments of the present disclosure provide a computer program product, which includes a computer program. The computer program is executed by a processor to implement the device cooperative computing method according to any one of the first aspect or the second aspect or the third aspect.

[0055] The embodiments of the present disclosure provide a device cooperative computing method, device, computer storage medium and computer program product. The method obtains algorithm deployment request information sent by a user device. Based on the algorithm deployment request information, a target first device with the maximum device score value corresponding to a resource parameter is selected from a plurality of first devices according to the resource parameter. Algorithm program information is sent to the target first device through a soft bus of a full-scene distributed operating system. Data transmission information is sent to a second device through the soft bus, so that the target first device obtains target data and calculates a calculation result. The calculation result sent by the target first device is received, and the calculation result is sent to the user device. According to the embodiments of the present disclosure, the target algorithm program is sent to the target first device according to the algorithm deployment request information, and the second device sends address information to the control end, so that the control end sends the address information to the target first device, so that the target first device obtains the target data according to the address information, and the target first device can process the target data according to the target algorithm program. Therefore, the calculation result is obtained by the cooperative calculation of the target first device and the second device, so that the cooperative calculation among a plurality of devices based on the full-scene distributed operating system is realized. BRIEF DESCRIPTION OF DRAWINGS

[0056] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate an embodiment consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure without imposing undue limitations on the disclosure. In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiment or prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0057] Figure 1 is a flowchart of a device cooperative computing method provided by the embodiments of the present disclosure.

[0058] Figure 2 is a flowchart of a method for determining a target first device provided by the embodiments of the present disclosure.

[0059] Figure 3 is a flowchart of a method for establishing a communication connection between a first device and a second device according to an embodiment of the present application.

[0060] Figure 4 is a flowchart of a method for obtaining target data according to an embodiment of the present application.

[0061] Figure 5 is a schematic diagram of an architecture for device collaborative computing according to an embodiment of the present application.

[0062] Figure 6 is a structural schematic diagram of a device for device collaborative computing according to an embodiment of the present application.

[0063] Figure 7 is a structural schematic diagram of another device for device collaborative computing according to an embodiment of the present application.

[0064] Figure 8 is a structural schematic diagram of another device for device collaborative computing according to an embodiment of the present application.

[0065] Figure 9 is a structural schematic diagram of a device for device collaborative computing according to an embodiment of the present application. DETAILED DESCRIPTION

[0066] In order to make the ordinary person skilled in the art better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings.

[0067] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0068] Before the technical solutions provided by the embodiments of the present application are described, in order to facilitate the understanding of the embodiments of the present application, the present application specifically describes the problems existing in the related art:

[0069] At present, the Internet of Things device management system in the related art is mostly based on a Linux or Android operating system, and multi-device collaborative computing is implemented through a combination framework of the Linux or Android operating system, for example, "DDS communication + SQLite database + OpenCV coding", specifically, multiple devices establish a communication link through DDS, and then the images collected by the multiple devices are preprocessed based on Opencv coding, and finally the processed data is stored in the SQLite database. However, the underlying code of the full-scene distributed operating system does not support this framework, which leads to the inability to implement collaborative computing among multiple devices on the full-scene distributed operating system.

[0070] In addition, the communication among devices in the related art needs to rely on manual configuration of protocols, such as MQTT topic binding and CoAP resource path mapping, so the efficiency of establishing a communication connection between devices is not high.

[0071] The embodiments of the present application provide a device collaborative computing method, device, apparatus, computer storage medium and computer program product, which can solve at least one of the above technical problems in the related art.

[0072] According to the algorithm deployment request information, the target algorithm program is sent to the target first device, and the second device sends the target data to the target first device, so that the target first device can process the target data sent by the second device according to the target algorithm program, and thus the calculation result is obtained by the collaborative calculation of the target first device and the second device, thereby realizing the collaborative calculation among multiple devices based on the full-scene distributed operating system.

[0073] The method for device collaborative computing provided by the embodiments of the present application is introduced below.

[0074] Figure 1 A flowchart of the method for device collaborative computing provided by an embodiment of the present application is shown. As shown in Figure 1 The method includes steps S101-S113.

[0075] S101: The first device establishes a communication connection with the second device through a soft bus of the full-scene distributed operating system.

[0076] The all-scene distributed operating system can include a Hongmeng operating system, and a soft bus of the all-scene distributed operating system is a distributed communication middleware system running on all devices supporting the all-scene distributed operating system, and can connect different devices together in the form of a software virtual bus to form a unified distributed system. The first device represents an Internet of Things device with a computing power greater than or equal to a preset computing power threshold, such as a gateway, a network attached storage (NAS) device, and the like. The second device represents an Internet of Things device with a computing power less than the preset computing power threshold, such as a camera, a smart door lock, a smart bracelet, and the like.

[0077] In one embodiment, the first device can send, to the second device through a soft bus of the all-scene distributed operating system, request information for establishing a communication connection with the second device.

[0078] In one example, the NAS device can send, to the smart door lock through a soft bus of the Hongmeng operating system, request information for establishing a communication connection with the smart door lock.

[0079] In the step flow of the embodiment of the application, by establishing the communication connection between the first device and the second device, the first device and the second device can interact with each other, and subsequent multiple devices can be facilitated to perform collaborative computing according to the interaction data.

[0080] S102: The control end receives algorithm deployment request information sent by a user device.

[0081] The control end includes an all-scene distributed operating system. The algorithm deployment request information represents a request for deploying an algorithm program on a first device.

[0082] In one embodiment, the control end receives the algorithm deployment request information sent by the user device through a receiving component.

[0083] S103: The control end selects, based on the algorithm deployment request information, a target first device with a maximum device score value corresponding to a resource parameter from multiple first devices according to the resource parameter.

[0084] The resource parameter represents information of a physical resource of the first device.

[0085] In one embodiment, after receiving the algorithm deployment request information, the control end can calculate a device score corresponding to a resource parameter of each first device according to the resource parameter of the multiple first devices and a corresponding weight coefficient. The control end selects a maximum device score from the multiple device scores, and determines the first device corresponding to the device score as the target first device.

[0086] In one example, the resource parameter of the first device a corresponds to a device score of 80, and the resource parameter of the first device b corresponds to a device score of 90, and the first device b can be determined as the target first device.

[0087] S104: The control end sends algorithm program information to the target first device through the soft bus of the full-scene distributed operating system, so that the target first device obtains the target algorithm program according to the algorithm program information.

[0088] In one embodiment, the control end sends algorithm program information to the target first device through the soft bus of the full-scene distributed operating system, so that the target first device obtains the target algorithm program according to the algorithm program information.

[0089] S105: The first device receives the algorithm program information sent by the control end through the soft bus.

[0090] In one embodiment, the first device can receive the algorithm program information sent by the control end through the soft bus of the full-scene distributed operating system by using the receiving component.

[0091] S106: The first device obtains the target algorithm program according to the algorithm program information.

[0092] The target algorithm program represents an algorithm program corresponding to the algorithm deployment request information.

[0093] In this embodiment, after receiving the algorithm program information, the first device obtains the target algorithm program according to the algorithm program information.

[0094] S107: The control end sends data transmission information to the second device through the soft bus, so that the second device sends address information to the control end, so that the control end sends the address information to the target first device, so that the target first device obtains target data based on the address information and calculates the target data by using the target algorithm program.

[0095] The data transmission information is used to control the second device to send response information, i.e., address information, to the control end. The address information is used to transmit target data related to the second device. The target data represents data to be calculated. The computing power of the target first device is greater than that of the second device.

[0096] In this embodiment, the control end sends data transmission information to the second device through the soft bus of the full-scene distributed operating system, so that the second device sends address information to the control end, so that the control end sends the address information to the target first device, so that the target first device obtains target data based on the address information and calculates the target data by using the target algorithm program.

[0097] S108: The second device sends address information to the control end through the soft bus according to the data transmission information sent by the control end, so that the control end sends the address information to the target first device, and the target first device obtains target data based on the address information and performs calculation on the target data by using the target algorithm program.

[0098] In this embodiment, after receiving the data transmission information sent by the control end, the second device sends address information to the control end through the soft bus of the full-scene distributed operating system according to the data transmission information, so that the control end sends the address information to the target first device, and the target first device obtains target data based on the address information and performs calculation on the target data by using the target algorithm program.

[0099] S109: The control end sends address information to the first device through the soft bus.

[0100] In one embodiment, after obtaining the address information, the control end sends the address information to the first device through the soft bus of the full-scene distributed operating system.

[0101] S110: The first device obtains the address information sent by the control end through the soft bus and obtains target data according to the address information.

[0102] In one embodiment, the first device obtains the address information sent by the control end through the soft bus of the full-scene distributed operating system by using a receiving component and obtains target data according to the address information.

[0103] S111: The first device performs a calculation operation on the target data by using the target algorithm program to obtain a calculation result.

[0104] In one embodiment, after receiving the target data, the first device inputs the target data into the target algorithm program, and performs a calculation operation on the target data by using a calculation module of the target algorithm program to obtain a calculation result.

[0105] S112: The first device sends the calculation result to the control end through the soft bus so that the control end sends the calculation result to the user device.

[0106] In one embodiment, after obtaining the calculation result, the first device sends the calculation result to the control end through the soft bus of the full-scene distributed operating system so that the control end sends the calculation result to the user device.

[0107] S113: The control end receives the calculation result sent by the target first device and sends the calculation result to the user device.

[0108] In one embodiment, after receiving the calculation result sent by the target first device, the control end can send the calculation result to the user device.

[0109] According to the algorithm deployment request information, the embodiment of the present application sends the target algorithm program to the target first device, and makes the second device send the target data to the target first device, so that the target first device can process the target data sent by the second device according to the target algorithm program, and thus the calculation result is obtained by the target first device and the second device in cooperation, thereby realizing the cooperative calculation among multiple devices based on the full-scene distributed operating system.

[0110] In one embodiment, the NAS device and the camera establish a communication connection in advance through the soft bus of the full-scene distributed operating system to realize networking. The user device sends pet identification related algorithm deployment request information to the control end. The control end screens the NAS device as the target first device according to the pet identification related algorithm deployment request information. The control end sends pet identification related algorithm program information to the NAS device through the soft bus. The NAS device obtains the pet identification related target algorithm program according to the algorithm program information. The control end sends data transmission information to the camera through the soft bus, so as to send the video stream acquisition address to the control end. After obtaining the video stream acquisition address, the control end sends the video stream acquisition address to the NAS device. After obtaining the video stream acquisition address, the NAS device obtains the real-time video stream data of the camera according to the video stream acquisition address. The NAS device performs pet identification on the video stream data by using the target algorithm program, and sends the identification result to the control end, and finally the control end sends the identification result to the user device.

[0111] In one embodiment, the resource parameter includes at least one of a resource utilization rate and a device affinity probability. Based on the algorithm deployment request information, the target first device with the maximum device score value corresponding to the resource parameter is screened from the multiple first devices according to the resource parameter, as shown in Figure 2 The steps S1031-S1035 can be included.

[0112] S1031: Compare the resource utilization rates corresponding to the multiple first devices with the preset resource utilization rate threshold value respectively to obtain a first comparison result.

[0113] The resource utilization rate represents the utilization rate of the physical resources of the first device, such as at least one of the utilization rates of the central processing unit (CPU) resource utilization rate, the memory utilization rate, and the hard disk utilization rate. The value of the preset resource utilization rate threshold value is not fixed and can be adjusted according to user demand.

[0114] In one embodiment, the resource utilization rates corresponding to the multiple first devices can be obtained, and the resource utilization rates corresponding to the multiple first devices are compared with the preset resource utilization rate threshold value respectively to obtain a first comparison result.

[0115] S1032: Compare the device affinity probability corresponding to each of the plurality of first devices with a preset device affinity probability threshold to obtain a second comparison result.

[0116] The device affinity probability represents the probability of the first device being the target first device. The device affinity probability can be determined according to at least one of the time length of the first device accessing the network (i.e., the time length of the first device establishing communication with the second device), the characteristic information of the first device, and the attribute information of the first device. The value of the preset device affinity probability threshold is not fixed and can be adjusted according to user demand.

[0117] In one embodiment, the device affinity probability corresponding to each of the plurality of first devices can be calculated, and then the device affinity probability corresponding to each of the plurality of first devices is compared with the preset device affinity probability threshold to obtain a second comparison result.

[0118] S1033: In a case where the first comparison result indicates that the resource utilization rate corresponding to the first device is greater than or equal to the preset resource utilization rate threshold and the second comparison result indicates that the device affinity probability corresponding to the first device is greater than or equal to the preset device affinity probability threshold, the first device is taken as a candidate first device.

[0119] In one embodiment, after obtaining the first comparison result and the second comparison result, if the first comparison result indicates that the resource utilization rate corresponding to the first device is greater than or equal to the preset resource utilization rate threshold and the second comparison result indicates that the device affinity probability corresponding to the first device is greater than or equal to the preset device affinity probability threshold, the first device can be taken as a candidate first device.

[0120] S1034: Perform weighted calculation on the resource utilization rate and the device affinity probability corresponding to each candidate first device to obtain a plurality of device scores.

[0121] In one embodiment, after obtaining the candidate first device, the resource utilization rate and the device affinity probability corresponding to each candidate first device can be weighted calculated with the corresponding weight coefficient to obtain a plurality of device scores.

[0122] In one example, the resource utilization rate of the candidate first device n is 85%, the device affinity probability is 70%, the weight coefficient corresponding to the resource utilization rate is 0.7, and the weight coefficient corresponding to the device affinity probability is 0.3. Then the device score of the candidate first device is 85%*0.7+70%*0.3, i.e., 0.805.

[0123] S1035: Take the candidate first device corresponding to the device score with the highest value in the plurality of device scores as the target first device.

[0124] In one embodiment, after obtaining the device scores corresponding to the plurality of candidate first devices, the candidate first device corresponding to the device score with the highest value among the plurality of device scores is taken as the target first device.

[0125] According to the comparison results of the resource utilization rates and the device affinity probabilities of the plurality of first devices and the corresponding preset threshold values, the embodiments of the present application determine the candidate first devices, and then select the first device with the highest device score value from the candidate first devices as the target first device, which is equivalent to multiple screening of the first devices, thereby improving the accuracy of determining the target first device.

[0126] In one embodiment, the first device establishes a communication connection with the second device through a software bus of a full-scene distributed operating system, as shown in FIG. 1. Figure 3 The method can include steps S101-S103.

[0127] S101: Broadcast the request information through a target port.

[0128] The target port represents a communication port. The request information represents that the first device requests to establish a communication connection with the second device to realize networking.

[0129] In one example, the request information can include at least one of a device name, a device type, a networking type, and a connection address.

[0130] In one embodiment, the request information can be broadcast through the target port based on the CoAP protocol.

[0131] S102: Obtain the response information corresponding to the request information through the software bus.

[0132] In one embodiment, the first device can obtain the response information corresponding to the request information through the software bus.

[0133] S103: Establish a communication connection with the second device corresponding to the response information.

[0134] In one embodiment, the first device establishes a communication connection with the second device after obtaining the response information.

[0135] In one example, after starting, the first device broadcasts the request information through the target port based on the CoAP protocol. After receiving the request information, the software bus sends the CoAP response information to the first device in unicast. After receiving the response information, the first device returns the confirmation information. The software bus saves the device information of the first device, thereby establishing a communication connection between the first device and the second device.

[0136] The embodiment of the present application establishes a communication connection between the first device and the second device by broadcasting the request information, and compared with the prior art which needs manual configuration of the protocol to realize the device-to-device communication, the present application does not need manual configuration of the protocol, and can improve the efficiency of establishing the device-to-device communication connection.

[0137] In one embodiment, after sending the address information to the control end through the soft bus according to the data transmission information sent by the control end, Figure 4 as shown, the method further includes steps S210 and S220.

[0138] S210: obtaining initial data.

[0139] The initial data represents data corresponding to a preset parameter type of the target first device.

[0140] In one embodiment, the first device can obtain the initial data by using a collection tool.

[0141] S220: converting the initial data into target data corresponding to the parameter type and the preset parameter type according to the parameter information of the initial data.

[0142] In one embodiment, after obtaining the initial data, the parameter type of the initial data can be converted into the target data corresponding to the parameter type and the preset parameter type.

[0143] In one example, the preset parameter type is at least one of a device type, a function type, a data format, a service capability, an online state, and a security policy. The core capabilities of the camera such as up-down-left-right rotation control, video stream address acquisition, and shooting instruction can be abstracted into a unified model by using a data definition language (DDL), and the model elements including the name, description, type, and access permission of the instruction / data are set, so as to realize the conversion of the initial data of the camera into the target data.

[0144] In another example, the monitoring indicators of the medical device such as blood pressure, body weight, and height can be abstracted into a unified model, and the model elements including the name, description, type, and access permission of the instruction / data are set, so as to realize the conversion of the initial data of the medical device into the target data.

[0145] It can be understood that there are heterogeneous interfaces between different devices, and the embodiment of the present application converts the parameter type of the initial data into the target data corresponding to the parameter type and the preset parameter type, which is equivalent to abstracting and unifying the data between different devices, establishing a device-independent data paradigm, and realizing the normalization of heterogeneous data, so as to accelerate the transmission of data between devices.

[0146] In one embodiment, before the control end sends the data transmission information to the second device through the soft bus, the user device can also send algorithm configuration information to the control center, and the control center sends the algorithm configuration information to the target first device through the soft bus. The target first device modifies and configures parameters of the target algorithm program according to the algorithm configuration information.

[0147] In one embodiment, after the second device sends the target data to the target first device through the soft bus, the user device can also send device scheduling request information to the control end. After receiving the device scheduling request information, the control end sends the device scheduling request information to the second device. After receiving the device scheduling request information, the second device performs device scheduling processing according to the device scheduling request information, and sends the processing result to the control end. After receiving the processing result, the control end sends the processing result to the user device.

[0148] In one example, after the second device sends the target data to the target first device through the soft bus, the user device can also send camera rotation request information to the control end. After receiving the camera rotation request information, the control end sends the camera rotation request information to the camera. After receiving the camera rotation request information, the camera performs camera rotation processing according to the camera rotation request information, and sends the processing result to the control end. After receiving the processing result, the control end sends the processing result to the user device.

[0149] In one example, a schematic diagram of the architecture of device collaborative computing is as shown in Figure 5 The control end 501 includes a task scheduling module 5011. The task scheduling module includes a lightweight resource adaptation component 50111, a global resource collaboration component 50112, a high-performance resource pooling component 50113, and an elastic resource scaling component 50114. The unified access model 502 includes a device type component 5021 and a data format component 5022. The device 503 includes a first device 5031 and a second device 5032. The first device 5031 and the second device 5032 establish a communication connection through the soft bus 504.

[0150] As shown in Figure 6 The present embodiment also provides a device collaborative computing apparatus 600 applied to a control end including a full-scene distributed operating system. The apparatus 600 includes:

[0151] The receiving module 601 is configured to receive algorithm deployment request information sent by a user device;

[0152] The screening module 602 is configured to screen, based on the algorithm deployment request information, a target first device with the maximum device score value corresponding to a resource parameter from a plurality of first devices according to the resource parameter;

[0153] The sending module 603 is configured to send the algorithm program information to the target first device through a soft bus of the full-scene distributed operating system, so that the target first device acquires the target algorithm program according to the algorithm program information.

[0154] The sending module 603 is further configured to send the data transmission information to the second device through the soft bus, so that the second device sends the address information to the control end, the control end sends the address information to the target first device, the target first device acquires the target data based on the address information and performs calculation on the target data by using the target algorithm program, and the computing power of the target first device is greater than that of the second device.

[0155] The receiving module 601 is further configured to receive the calculation result sent by the target first device and send the calculation result to the user equipment.

[0156] According to the algorithm deployment request information, the embodiment of the application sends the target algorithm program to the target first device, and makes the second device send the address information to the control end, so that the control end sends the address information to the target first device, the target first device acquires the target data according to the address information, and the target first device can process the target data according to the target algorithm program, so that the calculation result is obtained by the target first device and the second device in cooperation, thereby realizing the cooperative calculation among multiple devices based on the full-scene distributed operating system.

[0157] In some embodiments, the device cooperative calculation apparatus 600 further includes a comparison module configured to compare the resource utilization rates corresponding to the multiple first devices with preset resource utilization rate thresholds respectively to obtain first comparison results.

[0158] The device affinity probabilities corresponding to the multiple first devices are compared with preset device affinity probability thresholds respectively to obtain second comparison results.

[0159] In a case where the first comparison result indicates that the resource utilization rate corresponding to the first device is greater than or equal to the preset resource utilization rate threshold and in a case where the second comparison result indicates that the device affinity probability corresponding to the first device is greater than or equal to the preset device affinity probability threshold, the first device is taken as a candidate first device.

[0160] The resource utilization rate and the device affinity probability corresponding to each candidate first device are weighted to obtain multiple device scores.

[0161] The candidate first device corresponding to the device score with the highest value among the multiple device scores is taken as the target first device.

[0162] Figure 6 Each module / unit in the apparatus has the implementation Figures 1-2The functions of each step performed by the application and the corresponding technical effects can be achieved, and for brevity, will not be described here.

[0163] As shown in Figure 7 The embodiment of the application also provides a device cooperative computing apparatus 700 applied to a first device, the first device comprising a full-scene distributed operating system, the apparatus 700 comprising:

[0164] The establishing module 701 is configured to establish a communication connection with a second device through a soft bus of the full-scene distributed operating system;

[0165] The receiving module 702 is configured to receive algorithm program information sent by a control end through the soft bus;

[0166] The obtaining module 703 is configured to obtain a target algorithm program according to the algorithm program information;

[0167] The obtaining module 703 is further configured to obtain address information sent by the control end through the soft bus;

[0168] The obtaining module 703 is further configured to obtain target data based on the address information;

[0169] The executing module 704 is configured to perform a computing operation on the target data by using the target algorithm program to obtain a computing result;

[0170] The sending module 705 is further configured to send the computing result to the control end through the soft bus, so that the control end sends the computing result to a user device.

[0171] According to the algorithm deployment request information, the embodiment of the application sends the target algorithm program to the target first device, and makes the second device send the address information to the control end, so that the control end sends the address information to the target first device, and the target first device obtains the target data according to the address information, so that the target first device can process the target data according to the target algorithm program, and therefore the computing result is obtained by the cooperative computing of the target first device and the second device, thereby realizing the cooperative computing among multiple devices based on the full-scene distributed operating system.

[0172] In some embodiments, the apparatus 700 further comprises a broadcasting module configured to broadcast the request information through a target port;

[0173] The soft bus is used to obtain response information corresponding to the request information;

[0174] The second device corresponding to the response information is used to establish a communication connection.

[0175] Figure 7 The modules / units in the apparatus have the functions of Figure 1 and Figure 3The functions of each step performed by the application and the corresponding technical effects can be achieved, and for brevity, will not be repeated here.

[0176] As shown in Figure 8 The embodiment of the application also provides a device cooperative computing apparatus 800 applied to a second device, the second device comprising a full-scene distributed operating system, the apparatus 800 comprising:

[0177] The establishing module 801 is configured to establish a communication connection with a target first device through a soft bus of the full-scene distributed operating system;

[0178] The sending module 802 is configured to send address information to the control end through the soft bus according to the data transmission information sent by the control end, so as to control the control end to send the address information to the target first device, and so as to control the target first device to acquire target data based on the address information and to perform computation on the target data by using a target algorithm program.

[0179] According to the algorithm deployment request information, the embodiment of the application sends the target algorithm program to the target first device, and makes the second device send the address information to the control end, so as to control the control end to send the address information to the target first device, and so as to control the target first device to acquire target data according to the address information, so that the target first device can process the target data according to the target algorithm program, and thus the computation result is obtained by the cooperative computation of the target first device and the second device, thereby realizing the cooperative computation among multiple devices based on the full-scene distributed operating system.

[0180] In some embodiments, the apparatus 800 comprises an acquiring module configured to acquire initial data;

[0181] According to the parameter information of the initial data, the initial data is converted into target data corresponding to a preset parameter type.

[0182] Figure 8 Each module / unit in the apparatus has the functions of each step performed by the application and can achieve the corresponding technical effects. Figure 1 and Figure 4 The functions of each step performed by the application and the corresponding technical effects can be achieved, and for brevity, will not be repeated here.

[0183] Figure 9 A hardware structure schematic diagram of the device cooperative computing is shown.

[0184] The device for device cooperative computing can comprise a processor 901 and a memory 902 storing computer program instructions.

[0185] In particular, the processor 901 can include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or can be configured to implement one or more integrated circuits that implement the embodiments of the present application.

[0186] The memory 902 can include mass storage for data or instructions. As an example and not by way of limitation, the memory 902 can include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disc (e.g., a compact disc (CD) or a digital versatile disc (DVD)), a solid-state drive (SSD), a USB drive, or a combination of two or more of these. Where appropriate, the memory 902 can include removable or non-removable (or fixed) media, where appropriate. The memory 902 can be internal or external to the integrated gateway disaster recovery device. In particular embodiments, the memory 902 is non-volatile, solid-state memory.

[0187] The memory 902 can include read-only memory (ROM), random access memory (RAM), magnetic disk storage mediums, optical storage mediums, flash memory devices, electrical, optical, or other physical / tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software that, when executed (by one or more processors), is operable to perform operations described with reference to the methods according to an aspect of the present disclosure.

[0188] The processor 901 implements the method of device cooperative computing in any of the above embodiments by reading and executing computer program instructions stored in the memory 902.

[0189] In one example, the device for device cooperative computing can further include a communication interface 903 and a bus 904. As shown, the processor 901, the memory 902, the communication interface 903 are connected through the bus 904 and complete communication between each other. Figure 9

[0190] The communication interface 903 is mainly used to realize the communication between the modules, devices, units and / or devices in the embodiments of the present application.

[0191] ​Bus 904 includes a hardware, software, or both that couples components of the online data traffic billing device to each other. As an example and not by way of limitation, the bus can include an accelerated graphics port (AGP) or other graphics bus, an extended industry standard architecture (EISA) bus, a front side bus (FSB), a Hyper Transport (HT) interconnect, an industry standard architecture (ISA) bus, an infiniband interconnect, a low pin count (LPC) bus, a memory bus, a microchannel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standards board (VLB) bus, or another suitable bus or a combination of two or more of these. Where suitable, bus 904 can include one or more buses. Although this embodiment describes and shows a particular bus, this embodiment contemplates any suitable bus or interconnect. Additionally, the methods of device coordinated computing described in the above embodiments can be implemented in a computer storage medium having stored thereon computer program instructions. The computer program instructions, when executed by a processor, implement the methods of device coordinated computing described in the above embodiments.

[0192] This embodiment also provides a computer program product including a computer program, which, when executed by a processor, implements the methods of device coordinated computing described in the above embodiments. This embodiment also provides a vehicle including a control device and a terminal. The terminal is configured to implement the methods of device coordinated computing described in the above embodiments. The control device is configured to implement the methods of device coordinated computing described in the above embodiments.

[0193] It is important to note that the present application is not limited to the specific configurations and processes described above and illustrated in the drawings. Detailed descriptions of known methods are omitted for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the processes of the present application are not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps, after understanding the spirit of the present application.

[0194] The functions shown in the above block diagrams can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, and the like. When implemented in software, the elements of the present application are program or code segments that are used to perform the required tasks. The program or code segments can be stored in a machine-readable medium, or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. A "machine-readable medium" includes any medium that can store or transport information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memories (ROMs), flash memories, erasable read-only memories (EROMs), floppy disks, compact discs (CD-ROMs), optical disks, hard disks, fiber-optic media, radio frequency (RF) links, and the like. The code segments can be downloaded via computer networks such as the Internet, intranets, and the like.

[0195] It is also important to note that the examples described herein can be implemented in a variety of systems, including and / or incorporating software, firmware, hardware, and the like. Also, the example embodiments described herein can be implemented as a method, apparatus or system that can include a series of steps or acts performed in any order, or a series of interconnected web pages and web-based forms arranged to receive user input and perform specified acts or functions. One of ordinary skill in the art will also recognize the interchangeability of various hardware and software components with respect to the examples described herein. For example, one of ordinary skill in the art will appreciate that a computing device can include a variety of input and output means, such as a display, camera, keyboard, mouse, etc. Such means can be used to provide user input to, and receive user output from, the computing device.

[0196] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. Alternatively, computer program

[0197] The above is only a specific implementation of the present application, and those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here. It should be understood that the protection scope of the present application is not limited to this, and any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. A method for collaborative computing among devices, characterized in that, Applied to a control terminal, wherein the control terminal includes a full-scenario distributed operating system, the method includes: Receive algorithm deployment request information sent by user equipment; Based on the algorithm deployment request information, and according to the resource parameters, the target first device with the largest device score corresponding to the resource parameters is selected from multiple first devices; Algorithm program information is sent to the target first device through the soft bus of the full-scenario distributed operating system, so that the target first device can obtain the target algorithm program based on the algorithm program information; Data transmission information is sent to the second device via the soft bus, so that the second device can send address information to the control terminal, so that the control terminal can send the address information to the target first device, so that the target first device can obtain target data based on the address information and use the target algorithm program to calculate the target data, and the computing power of the target first device is greater than that of the second device; The system receives the calculation results sent by the target first device and sends the calculation results to the user equipment.

2. The method according to claim 1, characterized in that, The resource parameters include at least one of resource utilization rate and device affinity probability; the step of deploying the request information based on the algorithm, and selecting the target first device with the highest device score corresponding to the resource parameters from multiple first devices according to the resource parameters, includes: The resource utilization rates of multiple first devices are compared with preset resource utilization thresholds to obtain a first comparison result; The device affinity probabilities corresponding to multiple first devices are compared with preset device affinity probability thresholds to obtain a second comparison result; If the resource utilization rate corresponding to the first device is greater than or equal to the preset resource utilization rate threshold as indicated by the first comparison result, and the device affinity probability corresponding to the first device is greater than or equal to the preset device affinity probability threshold as indicated by the second comparison result, the first device shall be regarded as a candidate first device. The resource utilization rate and device affinity probability corresponding to each candidate first device are weighted and calculated to obtain multiple device scores; The candidate first device corresponding to the highest device score among the multiple device scores is selected as the target first device.

3. A method for collaborative computing among devices, characterized in that, Applied to a first device, the first device including a full-scenario distributed operating system, the method includes: A communication connection is established with the second device through the soft bus of the full-scenario distributed operating system; The algorithm program information sent by the control terminal is received via the soft bus; Obtain the target algorithm program based on the algorithm program information; The address information sent by the control terminal is obtained through the soft bus; Obtain target data based on the address information; The target algorithm program is used to perform calculations on the target data to obtain the calculation results. The calculation results are sent to the control terminal via the soft bus so that the control terminal can send the calculation results to the user equipment.

4. The method according to claim 3, characterized in that, The establishment of a communication connection with the second device via the soft bus of the full-scenario distributed operating system includes: Broadcast the request information through the target port; The response information corresponding to the request information is obtained through the soft bus; A communication connection is established with the second device corresponding to the response information.

5. A method for collaborative computing among devices, characterized in that, Applied to a second device, the second device including a full-scenario distributed operating system, the method includes: A communication connection is established with the target primary device through the soft bus of the full-scenario distributed operating system; According to the data transmission information sent by the control terminal, address information is sent to the control terminal via the soft bus, so that the control terminal can send the address information to the target first device, so that the target first device can obtain target data based on the address information and perform calculations on the target data using the target algorithm program.

6. The method according to claim 5, characterized in that, After sending address information to the control terminal via the soft bus based on the data transmission information sent by the control terminal, the method further includes: Get initial data; The initial data is converted into target data with parameter types corresponding to preset parameter types based on the parameter information of the initial data.

7. A device for collaborative computing of devices, characterized in that, The device is applied to a control terminal, which includes a full-scenario distributed operating system, and the device includes: A receiving module, wherein the receiving module is used to receive algorithm deployment request information sent by the user equipment; A filtering module is used to filter the target first device with the largest device score corresponding to the resource parameters from multiple first devices based on the deployment request information of the algorithm and according to the resource parameters. The sending module is used to send algorithm program information to the target first device through the soft bus of the full-scenario distributed operating system, so that the target first device can obtain the target algorithm program according to the algorithm program information; The sending module is further configured to send data transmission information to the second device via the soft bus, so that the second device can send address information to the control terminal, so that the control terminal can send the address information to the target first device, so that the target first device can obtain target data based on the address information and use the target algorithm program to calculate the target data, wherein the computing power of the target first device is greater than that of the second device; The receiving module is further configured to receive the calculation results sent by the target first device and send the calculation results to the user equipment.

8. A device for collaborative computing of devices, characterized in that, Applied to a first device, the first device including a full-scenario distributed operating system, the device includes: The module is used to establish a communication connection with the second device through the soft bus of the full-scenario distributed operating system. A receiving module, which is used to receive algorithm program information sent by the control terminal through the soft bus; The acquisition module is used to acquire the target algorithm program based on the algorithm program information; The acquisition module is also used to acquire the address information sent by the control terminal through the soft bus; The acquisition module is also used to acquire target data based on the address information; The execution module is used to perform calculation operations on the target data using the target algorithm program to obtain calculation results; A sending module is configured to send the calculation result to the control terminal via the soft bus so that the control terminal can send the calculation result to the user equipment.

9. A device for collaborative computing of devices, characterized in that, Applied to a second device, the second device including a full-scenario distributed operating system, the device includes: The module is used to establish a communication connection with the target first device through the soft bus of the full-scenario distributed operating system. The sending module is configured to send address information to the control terminal via the soft bus according to the data transmission information sent by the control terminal, so that the control terminal can send the address information to the target first device, so that the target first device can obtain target data based on the address information and perform calculations on the target data using the target algorithm program.

10. A device for collaborative computing, characterized in that, The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the device collaborative computing method as described in any one of claims 1-6.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the device collaborative computing method as described in any one of claims 1-6.

12. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the device collaborative computing method according to any one of claims 1-6.

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