WO2020133450A1 - System and method for sharing computing power by means of dynamic networking for mobile device - Google Patents

Abstract

The present application provides a method for sharing computing power by means of dynamic networking for a mobile device, a network platform, and a readable storage medium. The method comprises: a central system makes statistic on information of the mobile device having residual computing power within a surrounding preset range and establishes dynamic network connection with the mobile device, so that a dynamic distributed computing network using the mobile device as a computing node is established. When the dynamic distributed computing network runs, the central system receives a data processing request sent by a user; according to the data processing request, the central system selects at least one mobile device and sends the data processing request; the central system receives the processed data returned by the at least one mobile device; and the central system sends the processed data to the user. The technology disclosed in the present invention can be applied to a 4G network environment, but is more suitable for a 5G network environment due to higher requirements for a network delay and a data transmission speed during data sharing.

Description

System and method for sharing computing power in dynamic networking of mobile equipment Technical field

The present application relates to the field of network communications, and in particular, to a system and method for mobile devices to dynamically network to share computing power.

Background technique

With the development of computer technology in various fields, in some new application scenarios, the computing power and the immediacy of computing are increasingly required. For example, in the field of autonomous driving, autonomous vehicles need to process a large amount of visual image information, radar feedback information, etc. to build a map of the surrounding environment and locate themselves, and at the same time need to determine their own driving strategy based on these large amounts of information. In application scenarios such as these, the demands on the computing power of local computing devices are increasing. If these computing tasks are all processed locally on the device, the local computing device will face very high computing pressure.

At the same time, with the development of communication technology, the speed of network transmission has been greatly improved. For example, in the era of 5G networks, a network environment with high bandwidth and low latency will make it possible for devices to share computing power through the network. Therefore, it is necessary to provide a system and method for sharing computing power, which can share the computing power of each other through a dynamic network formed between the devices, and distribute the computing load to each computing node in the network, thereby improving the data processing capability of all devices in the network.

Summary of the invention

Based on the above problems, this application proposes a new technical solution that can solve the technical problem of local computing power shortage and dynamic computing network sharing computing power through the central system.

The first aspect of the present application proposes a method for dynamic networking and sharing computing power of mobile devices, which includes: the central system calculates information of one or more mobile devices with remaining computing power within a preset range around the periphery; and based on the one Or multiple mobile device information, the central system establishes a dynamic network connection with the one or more mobile devices, thereby forming a dynamic distributed computing network using the one or more mobile devices as computing nodes. When the dynamic distributed computing network is running: the hub system receives a data processing request sent by a user; according to the data processing request, the hub system selects at least one mobile device from the dynamic distributed computing network; The hub system sends the data processing request to the at least one mobile device; the hub system receives the processed data returned by the at least one mobile device; and the hub system sends the processed data to the user .

In some embodiments, the one or more mobile devices may include on-board electronic devices of one or more vehicles.

In some embodiments, the hub system includes a base station communication system, and the user and the one or more vehicles may be located within the signal coverage of the base station communication system.

In some embodiments, the data processing request may include a maximum delay constraint, and the maximum delay constraint may reflect the latest moment when the central system sends the processed data to the user. The selecting at least one mobile device may include: according to the maximum delay constraint and the computing power state of the on-board electronic device of the one or more vehicles, the central system may select from the on-board electronics of the one or more vehicles Choose at least one car's electronic equipment in the equipment.

In some embodiments, the central system sending the data processing request to the at least one mobile device may include: according to the computing power state of the on-board electronic device of each of the at least one vehicle, the Each vehicle in at least one vehicle is assigned a computing task; and the central system sends its corresponding computing task to each vehicle in the at least one vehicle.

In some embodiments, the assigning calculation tasks to each vehicle in at least one vehicle may further include: assigning calculation tasks to each vehicle according to the planned driving trajectory of each vehicle.

In some embodiments, the hub system may include a communication module of a second user's electronic device, and the mobile device includes a computing module of the second user's electronic device.

In some embodiments, the central system sending the data processing request to the at least one mobile device may include: the communication module sending the data processing request to the second user's electronic device bus via the bus The calculation module sends.

In some embodiments, the central system counting the information of one or more mobile devices with remaining computing power within a preset range around the periphery may include: the central system periodically updates mobile devices within its signal coverage According to the computing power state of the mobile device, the central system counts information about one or more mobile devices with remaining computing power.

In some embodiments, the method may further include: when the dynamic distributed computing network is running, the user directly sends data to be processed to the at least one mobile device.

The second aspect of the present application proposes a mobile device distributed computing network platform for dynamically sharing computing power, which may include: a hub device, the hub device includes: an antenna; at least one storage medium, and the storage medium stores a set of instructions And at least one processor, the processor is in communication with the at least one storage medium, and when executing the set of instructions, the at least one processor is used to:

Establish a dynamic network connection with one or more mobile devices entering the predetermined range of the central device, thereby forming a dynamic distributed computing network using the one or more mobile devices as computing nodes, the dynamic distributed computing network Perform the method described above.

The third aspect of the present application proposes a computer-readable storage medium on which a computer program is stored. When the computer program is executed by the processor, the steps of the method for forming a dynamic distributed computing network as described above can be implemented.

BRIEF DESCRIPTION

The following drawings describe in detail the exemplary embodiments disclosed in the present application. The same reference numerals indicate similar structures in several views of the drawings. Those of ordinary skill in the art will understand that these embodiments are non-limiting and exemplary embodiments, and the drawings are for illustration and description purposes only, and are not intended to limit the scope of the present application, and other ways of embodiment are also possible The intention of completing the invention in this application is the same. among them:

1 is a schematic diagram of an embodiment of a wireless communication system for network management of mobile devices;

2 is a block diagram of an exemplary vehicle with autonomous driving capabilities according to some embodiments of the present disclosure;

3 is a schematic diagram of exemplary hardware and software components of the information processing unit;

4 is an exemplary flowchart of forming a dynamic distributed computing network for mobile devices in this application;

FIG. 5 is an exemplary flowchart of one embodiment of the dynamic distributed computing network runtime in this application; and

6 is a schematic diagram of a central device in the present application.

detailed description

The present application discloses a system and method for sharing computing power by dynamically networking mobile devices. When users have computing needs, they can send requests to the central system, and then arrange other mobile devices with remaining computing power within a certain range through the central system to perform distributed operations and return them to the users. In the transmission of requests, including the transmission of data to be processed, due to the delay in network transmission, there may be a certain degree of lag in the way in which other mobile devices are arranged through the central system to help calculations. If this lag is greater than the lag caused by the lack of local computing power when the user is computing locally, this way of dynamic networking sharing computing power is meaningless. Thanks to the development of wireless network transmission technology, driven by communication technologies such as 5G, the communication bandwidth has increased significantly, and the network delay has been greatly reduced, which enables the dynamic networking sharing computing power solution described in this application to be implemented.

In the field of autonomous driving, autonomous driving vehicles need to process a large amount of visual image data, radar data, etc., and need to determine their real-time driving strategies through fast and efficient calculations. Therefore, the field of automatic driving is a typical field that can apply the dynamic networking sharing computing technology described in this application. This application takes the autonomous driving field as an example to describe the dynamic networking sharing computing power technology, but it does not mean to limit the application field of this application. Persons of ordinary skill in the art should recognize that any device that has a need for computing power and has communication capabilities can request the central system to allocate the computing power of other devices to it through the solution proposed in this application.

In order to provide a person of ordinary skill in the art with a thorough understanding of the relevant disclosure, specific details of the present invention are illustrated by examples in the following detailed description. However, the content disclosed in this application should be understood to be consistent with the scope of protection of the claims, and is not limited to the details of the specific invention. For example, it will be obvious to those of ordinary skill in the art to make various modifications to the embodiments disclosed in this application; and without departing from the spirit and scope of this application, those of ordinary skill in the art may define here The general principle of is applied to other embodiments and applications. As another example, if these details are not disclosed below, a person of ordinary skill in the art can also practice this application without knowing these details. On the other hand, in order to avoid unnecessarily obscuring the content of the present application, the present application provides a general overview of well-known methods, processes, systems, components, and/or circuits without detailed description. Therefore, the content disclosed in this application is not limited to the illustrated embodiments, but is consistent with the scope of the claims.

The terminology used in this application is for the purpose of describing particular example embodiments only and is not limiting. For example, unless the context clearly indicates otherwise, if an singular description is used for an element (for example, "one", "one", and/or equivalent description) in the present application, it may also include multiple elements. The terms "including" and/or "comprising" as used in this application refer to an open concept. For example, A includes/includes B only means that there is a B feature in A, but it does not exclude the possibility that other elements (such as C) exist or are added in A.

It should be understood that the terms used in this application, such as "system", "unit", "module" and/or "block", are used to distinguish different components, elements, parts, parts or components at different levels. Kinds of methods. However, if other terms can achieve the same purpose, the other terms may also be used in this application to replace the above terms.

The modules (or units, blocks, units) described in this application may be implemented as software and/or hardware modules. Unless the context clearly indicates otherwise, when a unit or module is described as "on", "connected" or "coupled" to another unit or module, the expression may mean that the unit or module is directly connected or linked Or coupled to the other unit or module, it may also mean that the unit or module is indirectly connected, connected, or coupled to the other unit or module in some form. In this application, the term "and/or" includes any and all combinations of one or more of the associated listed items.

In this application, the term "autonomous vehicle" may refer to an environment that can perceive its environment and automatically perceive, judge, and then make an external environment without human input (eg, driver, pilot, etc.) and/or intervention Decision making vehicle. The terms "autonomous vehicle" and "vehicle" can be used interchangeably. The term "autonomous driving" may refer to the ability to make intelligent judgments and navigate the surrounding environment without human input (eg, driver, pilot, etc.).

Considering the following description, these and other features of the present application, as well as the operation and function of related elements of the structure, as well as the economics of assembly and manufacturing of components, can be significantly improved. With reference to the drawings, all of these form part of the application. However, it should be clearly understood that the drawings are for illustration and description purposes only, and are not intended to limit the scope of the present application. It should be understood that the drawings are not drawn to scale.

The flowchart used in this application shows the operations implemented by the system according to some embodiments in this application. It should be clearly understood that the operations of the flowchart can be implemented out of order. Instead, the operations can be performed in reverse order or simultaneously. In addition, one or more other operations can be added to the flowchart. One or more operations can be removed from the flowchart.

The positioning technology used in this application can be based on Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), Compass Navigation System (COMPASS), Galileo Positioning System, Quasi-Zenith Satellite System (QZSS), Wireless Fidelity (WiFi) Positioning technology, etc., or any combination thereof. One or more of the above positioning systems can be used interchangeably in this application.

In addition, although the system and method in this application mainly describe a system and method for sharing computing power in the field of automatic driving, it should be understood that this is only an exemplary embodiment. The system or method of the present application can be applied to any other type of network system. For example, the system or method of the present application can be applied to network systems in different environments, including mobile phone networks, personal computer networks, etc., or any combination thereof.

FIG. 1 is a schematic diagram of an embodiment of a wireless communication system 100 for network management of mobile devices. The mobile device network management system can be used as a supporting network application in the invention described in this disclosure.

The wireless communication system 100 includes remote units 142, 144, 146, a base station 110, and wireless communication links 115, 148. A specific number of remote units 142, 144, 146, base station 110, and wireless communication links 115, 148 are depicted in FIG. 2, but those skilled in the art will recognize that any number of remote units 142 may be included in the wireless communication system 100. 144, 146, base station 110 and wireless communication links 115, 148.

The wireless communication system 100 can be used as a network architecture foundation for an embodiment of mobile device dynamic networking and sharing computing power in this application. The remote units 142, 144, and 146 may be located within the signal coverage of the base station 110. The base station 110 may serve as a central system 120 of the dynamic distributed computing network (hereinafter may also be referred to as a radio access network). The remote units within the signal coverage of the base station 110 can serve as parallel computing nodes, and are incorporated into the dynamic distributed network through the central system 120 to share computing power.

In some embodiments, the remote units 142, 144, 146 may be mobile devices, such as in-vehicle computers (including on-board computers for manual driving vehicles and or self-driving vehicles with automatic driving capabilities) 142, 144, and other mobile devices 146, Such as mobile phones, notebook computers, personal digital assistants ("PDA"), tablet computers, smart watches, fitness bands, optical head-mounted displays, etc. The remote units 142, 144, 146 may also include non-mobile computing devices, such as desktop computers, smart TVs (eg, televisions connected to the Internet), set-top boxes, game consoles, security systems (including security cameras), fixed Network equipment (eg, routers, switches, modems), etc. In addition, mobile remote units 142, 144, 146 may be referred to as mobile stations, mobile devices, users, terminals, mobile terminals, fixed terminals, user stations, UEs, user terminals, devices, or by other terms used in the art.

The wireless link between the remote units 142, 144, 146 is 148. The wireless link between the remote units 142, 144, and 146 may be 5G communication interaction and other forms of wireless interaction, such as Bluetooth, Wifi, and so on. The base station 110 forms a radio access network (radio access network "RAN") 120. The wireless link between the base stations 110 is 115. The RAN 120 may be coupled to the mobile core network 130 through communication. The mobile core network 130 may be a 5G network, or a 4G, 3G, 2G, or other form of network. In the present disclosure, the 5G network is taken as an example to illustrate the present invention. When the remote unit communicates with the base station 210, any communication environment from 2G to 4G can be used. However, because the communication requires high network delay and data transmission speed, the 5G network environment is more suitable for the communication between the vehicles. The data transmission rate of 4G is on the order of 100Mbps, the delay is 30-50ms, the maximum number of connections per square kilometer is on the order of 10,000, the mobility is about 350KM/h, and the transmission rate of 5G is on the order of 10Gbps, the delay is 1ms, the maximum number of connections per square kilometer is on the order of millions, and the mobility is about 500km/h. 5G has higher transmission rates, shorter delays, more connections per square kilometer, and higher speed tolerance. Another change in 5G is the change in transmission paths. In the past, when we called or transmitted photos, the signal had to be transferred through the base station, but after 5G, the device could be directly transmitted between devices, without the need to pass through the base station. Therefore, although the present invention is also applicable to the 4G environment, running in the 5G environment will obtain better technical performance and reflect higher commercial value.

In some embodiments, the hub system 120 may include a single base station. The signal coverage of the base station may be a circular geographic range centered on the base station. The base station can establish a wireless network connection and transmit data with a mobile device within its signal coverage through an antenna.

When the central system 120 is a plurality of base stations, its signal coverage may be the sum of the signal coverage of the plurality of base stations. For example, the central system 120 may include base stations throughout Beijing, and the signal coverage may be the geographic scope of Beijing. Mobile devices in Beijing are all within the signal coverage and can be added to the dynamic distributed computing network.

In some embodiments, the central system 120 may also be a cloud service system including the multiple base stations. The cloud service system may include the multiple base stations and a cloud server. The multiple base stations may be used as data transfer units to communicate the network connection of the mobile device to the cloud server, and the cloud server performs networking of the mobile device.

The 5G mobile core network 130 may belong to a single public land mobile network (single public land mobile network "PLMN"). For example, the mobile core network 130 can provide services with low latency and high reliability requirements, such as applications in the field of autonomous driving. The mobile core network 130 may also provide services for other application requirements. For example, the mobile core network 130 can provide services with high data rates and medium delay traffic, such as services for mobile devices such as mobile phones. For example, the mobile core network 130 may also provide services such as low mobility and low data rate.

The base station 110 may serve multiple remote units 142, 144, 146 within the service area, such as cells or cell sectors, through wireless communication links. The base station 110 can directly communicate with one or more remote units 142, 144, 146 via communication signals. The remote units 142, 144, 146 may directly communicate with one or more base stations 110 via uplink (UL) communication signals. In addition, UL communication signals may be carried over wireless communication links 115, 148. The base station 110 may also transmit a downlink (DL "DL") communication signal to serve the remote units 142, 144, 146 in the time domain, frequency domain, and/or air domain. In addition, DL communication signals may be carried over the wireless communication link 115. The wireless communication link 115 may be any suitable carrier in the licensed or unlicensed radio spectrum. The wireless communication link 115 may communicate with one or more remote units 142, 144, 146 and/or one or more base stations 110. In some embodiments, the wireless communication system 100 conforms to the long-term evolution (LTE) of the 3GPP protocol, in which the base station 110 uses an orthogonal frequency division multiplexing (orthogonal frequency division multiplexing "OFDM") modulation scheme on the DL Send it. The remote units 142, 144, 146 use a single-carrier frequency division multiple access (single-carrier frequency division multiple access "SC-FDMA") scheme to transmit on the UL. However, more generally, the wireless communication system 100 may implement some other open or proprietary communication protocols, for example, WiMAX, and other protocols. This disclosure is not intended to be limited to the implementation of any particular wireless communication system architecture or protocol.

The base station 110 and the remote units 142, 144, 146 may be distributed over geographical areas. In some embodiments, base station 110 and remote units 142, 144, 146 may also be referred to as access points, access terminals, or by any other terminology used in the art. Generally, two or more geographically adjacent base stations 110 or remote units 142, 144, 146 are grouped together into a routing area. In some embodiments, the routing area may also be referred to as a location area, a paging area, a tracking area, or by any other terminology used in the art. Each "routing area" has an identifier sent from its serving base station 110 to the remote units 142, 144, 146 (or sent between the remote units 142, 144, 146).

When the mobile remote unit 142, 144, 146 moves to a new cell that broadcasts a different "routing area" (e.g., moves within the range of the new base station 110), the mobile remote unit 142, 144, 146 detects a change in the routing area. The RAN 120 in turn pages the mobile remote units 142, 144, 146 in idle mode through the base station 110 in its current routing area. RAN 120 contains multiple routing areas. As is known in the art, the size of the routing area (eg, the number of base stations included in the routing area) can be selected to balance the routing area update signaling load and paging signaling load.

In some embodiments, the remote units 142, 144, 146 may be attached to the core network 130. When the remote unit 142, 144, 146 detects a mobile device network management event (e.g., a change in routing area), the remote unit 142, 144, 146 may report to the core network 130 (e.g., low latency and high reliability required for autonomous driving) The required service or the high data rate and medium delay traffic required by the mobile phone) sends a mobile device network management request message. Thereafter, the core network 130 forwards the mobile device network management request to one or more auxiliary network slices connected to the remote units 142, 144, 146 to provide corresponding services.

At a certain moment, the remote units 142, 144, 146 may no longer need a certain network service (for example, the service with low latency and high reliability required for autonomous driving or the service with high data rate and medium delay traffic required by mobile phones) . In this case, the remote units 142, 144, 146 may send a separation request message, such as a data connection release message, to separate from the network separation.

In some application scenarios, the remote unit 144 may be an autonomous driving vehicle (hereinafter may be referred to as an autonomous driving vehicle 144) driving on a road, and when entering the signal coverage of the central system 120, it may communicate with the central system 120 Establish a communication link and perform data interaction.

The remote unit 142 may be a first vehicle (hereinafter may be referred to as a first vehicle 142), and is within the signal coverage. The first vehicle 142 may also be a self-driving vehicle, as long as the on-board electronic equipment mounted on it has a surplus of computing power, it can be used as a computing node of a computing power sharing network (or “dynamic distributed computing network”). For example, when the first vehicle 142 is in a manual driving mode or a partially automatic driving mode, its on-board electronic device may have a surplus computing power.

The remote unit 143 may be a second vehicle (hereinafter may be referred to as a second vehicle 143) parked within the signal coverage. The in-vehicle electronic equipment carried by it is in an idle state, so it can participate in the computing power sharing network as a computing node.

The remote device 146 (mobile device 146) may include any device that is mobile and has certain computing power (e.g., mobile phone, notebook computer, smart watch, etc.). When the mobile device 146 enters the signal coverage area, it can be included in the computing power sharing network as a computing node.

The mobile device 146, including the first vehicle 142 and the second vehicle 143, may be located in the signal coverage range unspecifically due to their mobility. In some embodiments, the central system 120 may dynamically update mobile devices within its signal coverage that can participate in the computing power sharing network, and/or each mobile device may exist according to the computing power of each mobile device Assign computing tasks to each mobile device within a time period within the signal coverage.

2 is a block diagram of an exemplary vehicle with autonomous driving capabilities according to some embodiments of the present disclosure. The vehicle 200 may be vehicles 142, 144 in the wireless communication system 100 managed by the mobile device network shown in FIG. For example, the vehicle 200 with automatic driving capability may include a control module, multiple sensors, a memory, an instruction module, and a controller area network (CAN) and an actuator.

The actuator may include, but is not limited to, drive execution of an accelerator, an engine, a braking system, and a steering system (including steering of tires and/or operation of turn signals).

The plurality of sensors may include various internal and external sensors that provide data to the vehicle 200. For example, as shown in FIG. 2, the plurality of sensors may include vehicle component sensors and environment sensors. The vehicle component sensor is connected to the actuator of the vehicle 200, and can detect the operating status and parameters of various components of the actuator.

The environmental sensor allows the vehicle to understand and potentially respond to its environment in order to assist the autonomous vehicle 200 in navigation, path planning, and to ensure the safety of passengers and people or property in the surrounding environment. The environmental sensor can also be used to identify, track and predict the movement of objects, such as pedestrians and other vehicles. The environment sensor may include a position sensor and an external object sensor.

The position sensor may include a GPS receiver, an accelerometer, and/or a gyroscope, a receiver. The position sensor can sense and/or determine more than 200 geographic locations and orientations of the autonomous vehicle. For example, determine the latitude, longitude and altitude of the vehicle.

The external object sensor can detect objects outside the vehicle, such as other vehicles, obstacles in the road, traffic signals, signs, trees, etc. External object sensors may include laser sensors, radar, cameras, sonar, and/or other detection devices.

The laser sensor can measure the distance between the vehicle and the surface of the object facing the vehicle by rotating on its axis and changing its spacing. Laser sensors can also be used to identify changes in surface texture or reflectivity. Therefore, the laser sensor may be configured to detect the lane line by distinguishing the amount of light reflected by the painted lane line relative to the unpainted dark road surface.

Radar sensors can be located on the front and rear of the car and on either side of the front bumper. In addition to using radar to determine the relative position of external objects, other types of radar can also be used for other purposes, such as traditional speed detectors. Shortwave radar can be used to determine the depth of snow on the road and determine the location and condition of the road surface.

The camera may capture visual images around the vehicle 200 and extract content therefrom. For example, the camera can photograph the signs on both sides of the road and recognize the meaning of these signs through the control module. For example, use the camera to determine the speed limit of the road. The vehicle 200 can also calculate the distance of surrounding objects from the vehicle 200 through the parallax of different images captured by multiple cameras.

The sonar can detect the distance between the vehicle 200 and the surrounding obstacles. For example, the sonar may be an ultrasonic rangefinder. The ultrasonic distance meters are installed on both sides and behind the vehicle, and are turned on when parking to detect obstacles around the parking space and the distance between the vehicle 200 and the obstacles.

After receiving the information sensed by the plurality of sensors, the control module may process information and/or data related to vehicle driving (eg, automatic driving) to perform one or more functions described in the present disclosure. In some embodiments, the control module may be configured to drive the vehicle autonomously. For example, the control module can output multiple control signals. Multiple control signals may be configured to be received by one or more electronic control units (ECUs) to control the driving of the vehicle. In some embodiments, the control module may determine the reference path and one or more candidate paths based on the environmental information of the vehicle.

In some embodiments, the control module may include one or more central processors (eg, single-core processors or multi-core processors). For example only, the control module may include a central processing unit (CPU), application-specific integrated circuit (ASIC), application-specific instruction-set processor (ASIP), graphics Processing unit (graphics, processing unit, GPU), physical processing unit (physics, processing unit, PPU), digital signal processor (DSP), field programmable gate array (field programmable gate array, FPGA), programmable logic Device (programmable logic, device, PLD), controller, microcontroller unit, reduced instruction-set computer (RISC), microprocessor (microprocessor), etc., or any combination thereof.

The memory may store data and/or instructions. In some embodiments, the memory may store data obtained from autonomous vehicle sensors. In some embodiments, the memory may store data and/or instructions that the control module may execute or use to perform the exemplary methods described in this disclosure. In some embodiments, the memory may include mass storage, removable memory, volatile read-and-write memory, read-only memory (ROM), etc., or any combination thereof. As an example, for example, mass storage may include magnetic disks, optical disks, solid-state drives, etc.; for example, removable storage may include flash drives, floppy disks, optical disks, memory cards, zipper disks, magnetic tape; for example, volatile read-write memory may include random access Memory (RAM); for example, RAM can include dynamic RAM (DRAM), double data rate synchronous dynamic RAM (DDR SDRAM), static RAM (SRAM), thyristor RAM (T-RAM) and zero capacitor RAM (Z-RAM ); For example, ROM may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), compact disc ROM (CD-ROM), and Digital universal disk ROM, etc. In some embodiments, storage can be implemented on a cloud platform. For example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud cloud, a multi-cloud cloud, etc., or any combination thereof.

In some embodiments, the memory may be a local memory, that is, the memory may be part of the autonomous vehicle 200. In some embodiments, the memory may also be remote memory. The central processor may connect the remote memory through the network 100 to communicate with one or more components (eg, control module, sensor module) of the autonomous vehicle 200. One or more components in the autonomous vehicle 200 can access data or instructions stored remotely in a remote memory via the network 100. In some embodiments, the memory may be directly connected to or in communication with one or more components in the autonomous vehicle 200 (eg, control module, sensor).

The command module receives the information from the control module and converts it into a command to drive the actuator to the Controller Area Network (Controller Area Network) CAN bus. For example, the control module sends the driving strategy (acceleration, deceleration, turning, etc.) of the autonomous vehicle 200 to the instruction module, and the instruction module receives the driving strategy and converts it into a driving instruction for the actuator (for throttle, braking Drive instructions for the mechanism and steering mechanism). At the same time, the instruction module then sends the instruction to the execution mechanism via the CAN bus. The execution of the instruction by the actuator is detected by the vehicle component sensor and fed back to the control module, thereby completing the closed-loop control and driving of the automatic driving vehicle 200.

FIG. 3 is a schematic diagram of exemplary hardware and software components of the information processing unit 300. The information processing unit 300 may carry and implement the central system 120 to dynamically network the mobile device and share computing power. For example, the central system 120 may include at least one information processing unit 300, and the information processing unit 300 may dynamically network mobile devices that establish communication with the central system 120.

The information processing unit 300 may be a dedicated computer device specially designed for dynamically networking the mobile device. For example, the processing device on the base station 110 may include one or more of the information processing units 300

For example, the information processing unit 300 may include a core network 130 connected thereto and a COM port 350 connected to a remote unit to facilitate data communication. The information processing unit 300 may further include a processor 320 in the form of one or more processors for executing computer instructions. Computer instructions may include, for example, routines, programs, objects, components, data structures, processes, modules, and functions that perform specific functions described herein. The processor 320 may decompose the data processing request received from the user end into multiple computing tasks and send them to the mobile device through the I/O component 360.

In some embodiments, the processor 320 may include one or more hardware processors, such as a microcontroller, microprocessor, reduced instruction set computer (RISC), application specific integrated circuit (ASIC), application-specific instructions -Assembly processor (ASIP), central processing unit (CPU), graphics processing unit (GPU), physical processing unit (PPU), microcontroller unit, digital signal processor (DSP), field programmable gate array (FPGA) , Advanced RISC machine (ARM), programmable logic device (PLD), any circuit or processor capable of performing one or more functions, etc., or any combination thereof.

The information processing unit 300 may include an internal communication bus 310, program storage, and different forms of data storage (eg, disk 370, read-only memory (ROM) 330, or random access memory (RAM) 340) for processing by the computer And/or various data files sent. The information processing unit 300 may also include program instructions stored in the ROM 330, RAM 340, and/or other types of non-transitory storage media to be executed by the processor 320. The method and/or process of the present application may be implemented as program instructions. The information processing unit 300 also includes an I/O component 360 that supports input/output between the computer and other components (eg, user interface elements). The information processing unit 300 can also receive programming and data through network communication.

For the purpose of illustration only, only one processor is described in the information processing unit 300 described in this application. However, it should be noted that the information processing unit 300 in this application may also include multiple processors, therefore, the operations and/or method steps disclosed in this application may be performed by one processor as described in this application, It can be executed jointly by multiple processors. For example, if the processor 320 of the information processing unit 300 performs steps A and B in this application, it should be understood that steps A and B may also be executed jointly or separately by two different processors in the information processing (for example, The first processor performs step A, the second processor performs step B, or the first and second processors perform steps A and B together.

FIG. 4 is an exemplary flowchart of forming a mobile device dynamic distributed computing network in the present application. The method mainly includes that the hub system 120 establishes a network connection with mobile devices within its signal coverage and forms a distributed computing network. The mobile device may be any electronic device with data calculation capability. For example, the mobile device may be a self-driving car and the on-board electronic computing device thereon, or an on-board electronic computing device on a non-autonomous driving car, such as an on-board computer, or other electronic devices with portable functions, such as Laptops, smart watches, smart phones, etc., this disclosure does not limit this.

In 410, the central system 120 may count information of one or more mobile devices with remaining computing power within a preset range around. The remaining computing power refers to a part of the computing resources in the spare state of the mobile device in the current state except for completing the local computing task. For example, when the self-driving vehicle is in the parking state or in the manual driving mode, its electronic system is in an idle state, and then its on-board computer system has enough computing power to spare. As another example, when a smart phone is idle or in a call, its computing system does not process a task that occupies a large amount of computing resources, and the smart phone is also in a state of remaining computing power. In addition, within the signal coverage of the central system 120, there may be many mobile devices with computing capabilities, but not all of these mobile devices with computing capabilities can be incorporated into the dynamic distributed computing network. Some devices are not suitable for taking on the task of computing nodes due to their weak computing power or weak communication capabilities. Another example is that some mobile devices themselves are under heavy computing load and are not suitable to undertake the task of computing nodes. Another example is that some mobile devices are located at the edge of the signal coverage area, and it is impossible to determine whether they will continue to be within the signal coverage range for a period of time in the future. If this part of the mobile device is allowed to undertake computing tasks, it may be unreliable. Therefore, the central system 120 needs to first count the mobile device information within the preset range around the periphery.

The peripheral preset range may include the signal coverage range. The peripheral preset range may also be a reliable area that is smaller than the signal coverage. For example, in the embodiment shown in FIG. 1, the corresponding area may be the reliable area after the signal coverage is inwardly indented by a reliable distance. The mobile device in the reliable area may be regarded as a mobile device that can establish a stable connection with the central system 120 and can stably undertake a part of computing tasks.

When the mobile device enters the peripheral preset range, it can send its computing power state to the central system 120. The computing power state may include remaining computing power data of the mobile device. For example, when a mobile phone enters the peripheral preset range, it can send its computing power status to the base station (the central system 120). If the mobile phone is running a large game at this time, it may have no remaining computing power, or some of the remaining computing power. After acquiring the computing power state of the mobile devices within the preset range of the surroundings, the central system 120 may determine the one or more mobile devices with remaining computing power for further constructing the dynamic distributed computing network .

Since the time when the mobile device is in the signal coverage area is uncertain, the computing power state of the mobile device may also be in the process of change, and the central system 120 may periodically cover the signal coverage area Calculate the computing power status within the mobile device. For example, the central system 120 may send a computing power status request instruction to the mobile device within its signal coverage every 5 seconds to request the mobile device to report its computing power status to it.

In 420, the central system 120 may establish a dynamic network connection with the one or more mobile devices based on the information of the one or more mobile devices, so that the one or more mobile devices are used as computing nodes Dynamic distributed computing network. In some embodiments, after the central system 120 counts the one or more mobile devices with remaining computing power, it does not mean that these mobile devices can be included in the computing power sharing network. The central system 120 may reach a communication agreement with the one or more mobile devices, and the one or more mobile devices allow the central system 120 to allocate computing tasks to it. In some embodiments, the dynamic network connection may refer to the one or more mobile devices performing data interaction with the central system in real time or timing/untimed, reporting their computing power status, based on their local location The situation and the computing power situation dynamically access/detach from the distributed computing network.

Taking FIG. 1 as an example, after driving into the signal coverage area, the first vehicle 142 may establish a network connection with the central system 120. If the first vehicle 142 is an autonomous driving vehicle and is in a manual driving mode, its on-board equipment has abundant computing power resources. After the first vehicle 142 sends its computing power status to the central system 120, the central system 120 can recognize that the first vehicle 142 has remaining computing power and incorporate it into the dynamic distributed computing network as a calculate node. The first vehicle 142 may be switched to the automatic driving mode during driving, and at this time, the local computing load increases. The first vehicle 142 may send its computing power state in the automatic driving mode to the central system 120. The central system 120 may recognize that the current computing power of the first vehicle 142 has no remaining power or insufficient computing power, so as to remove the first vehicle 142 from the dynamic distributed computing network. In some embodiments, the mobile device may send instructions to the central system requesting to leave the dynamic distributed computing network. For example, when the first vehicle 142 is about to drive out of the surrounding preset range or the signal coverage, it may send an instruction to the central system 120 to notify the central system 120 to remove the first vehicle 142 from all The dynamic distributed computing network is removed.

When the mobile device is a node of the dynamic distributed computing network, it can process some computing tasks in parallel. Therefore, the central system can split the specific calculation tasks, send the parts that can be calculated in parallel to different network nodes for calculation, and then combine the calculation results fed back by the nodes to perform the next step of processing. For example, the autonomous vehicle 144 requests the central system 120 to process a batch of image data, and the processing tasks of each image data are independent of each other. The central system 120 may split the image data and allow multiple nodes to calculate in parallel.

FIG. 5 is an exemplary flowchart of an embodiment of a dynamic distributed computing network in this application during runtime. The process mainly includes a dynamic process of data interaction between the central system 120 and devices that have data processing requirements, and mobile devices of the computing node.

In 510, the central system 120 receives the data processing request sent by the user. The user may be any removable device or non-removable device that can establish a network connection with the central system 120. When the user is a non-removable device, it may establish a stable network connection with the central system 120. For example, the user may be a home personal computer that performs calculations for decoding bitcoin. Due to the huge amount of calculation, it can request the central system 120 to allocate computing power to it at any time. The user may also be a mobile device. As shown in FIG. 1, the user may be the autonomous vehicle 144. After driving into the signal coverage of the central system 120, the autonomous vehicle 144 may send a data processing request to the central system 120.

In some embodiments, the data processing request may include raw data that needs to be processed. For example, the data collected by the sensors of the autonomous vehicle 144 may be the raw data. The autonomous vehicle 144 may include the original data in the data processing request and send it to the central system 120.

In some embodiments, the original data may not be sent to the central system 120. Since the data transmission itself requires a certain bandwidth, if the amount of data is too large, the transmission of the original data itself will increase the delay of the data transmission process. If the original data can be communicated to the mobile device as a computing node in a faster manner, data transfer may not be performed via the central system 120. For example, in the embodiment shown in FIG. 1, the first vehicle 142 serves as a computing node in the distributed computing network. When the self-driving vehicle 144 and the first vehicle 142 are driving on the road at the same time, a communication link can be established between their in-vehicle electronic devices for data transmission (for example, two vehicles can independently establish a connection, and (You can choose to establish a data connection and share the computing power after the selection through the central system). If the bandwidth of such a communication link is large enough that the delay for the autonomous vehicle 144 to send the original data to the first vehicle 142 is less than the delay for transit through the central system 120, then the two vehicles The communication efficiency of direct data interaction will be higher. For another example, the raw data to be processed by the autonomous vehicle 144 may be stored in a cloud server, and the data processing request may include an instruction to download the raw data from the cloud server.

In some embodiments, the data processing request may further include a maximum delay constraint. The maximum delay constraint may indicate the latest time that the user can accept to obtain the data processing result. For example, the data processing time determined by the characteristics of the data processing request itself can determine the maximum delay constraint; for another example, when the autonomous vehicle 144 encounters an obstacle in front of it (time T1) during the driving process, a new driving strategy needs to be determined as soon as possible In order to avoid the obstacle, the latest time that it can tolerate acquiring the driving strategy is T2. If the new driving strategy cannot be acquired before time T2, the autonomous vehicle 144 may collide with the obstacle. At this time, time T2 may be the maximum delay constraint. The central system 120 may allocate computing tasks to each computing node according to the maximum delay constraint. For example, when the maximum delay constraint is small, it means that the user needs to obtain the data processing result as soon as possible. The central system 120 may allocate as many mobile devices with strong computing power as possible for data processing.

In some embodiments, the dynamic distributed computing network may also be decentralized. In other words, the central system 120 may also be dynamically distributed. For example, the central system 120 may also include a communication module of the second user's electronic device. The second user may be a computing device that dynamically accesses the network, such as a smart phone and/or an on-board electronic device of an autonomous vehicle, and so on. For example, in the embodiment shown in FIG. 1, the autonomous vehicle 144 and the first vehicle 142 directly establish a network connection. The communication module of the in-vehicle electronic device of the first vehicle 142 may be the central system 120.

In 520, the central system 120 may select at least one mobile device from the dynamically distributed computing network according to the data processing request. In some embodiments, the hub system 120 may select the at least one mobile device according to the maximum delay constraint and the computing power state of the one or more mobile devices. For example, in the scenario shown in FIG. 1, the data processing request sent by the autonomous vehicle 144 to the central system 120 requires feedback of driving strategy data in a short time. At this time, the computing nodes included in the dynamic distributed computing network are the first vehicle 142, the second vehicle 143, and the mobile device 146 (mobile phone). For the calculation of this driving strategy, the computing power of the mobile phone may be weak, and the processing power of the in-vehicle electronic device may be strong. The central system 120 may select the first vehicle 142 and/or the second vehicle 143 as the at least one mobile device to ensure that the driving can be fed back to the autonomous vehicle 144 within the maximum delay constraint Strategy data.

In 530, the hub system 120 may send the data processing request to the at least one mobile device. If there is only one mobile device, the central system 120 may directly send the data processing request it receives to the one mobile device. If the original data is included in the data processing request, it may be sent to the one mobile device together. If the original data is not included in the data processing request, the data processing request may further include an original data indication information for instructing the mobile device where to obtain the original data (such as described above) Directly establish a data interaction connection with the user, and download the original data from the cloud server, etc.).

If the at least one mobile device includes multiple mobile devices, the hub system 120 may split the data processing request it receives into multiple computing tasks, and send each of the multiple mobile devices to the mobile device. Distribute its corresponding computing tasks. In some embodiments, the central system 120 may allocate the computing tasks according to the computing power status of the plurality of mobile devices. For example, in the scenario shown in FIG. 1, the plurality of mobile devices may include the first vehicle 142 and the second vehicle 143. The first vehicle 142 may be in a semi-automatic driving state, and its remaining computing power may be only half of the remaining computing power of the second vehicle 143 in a parked state. The central system 150 may allocate more calculation tasks to the second vehicle 143 and less calculation tasks to the first vehicle 142.

In some embodiments, the calculation task allocation may be further based on the maximum delay constraint, and the moment when the latest processed data in the first vehicle 142 or the second vehicle 143 needs to satisfy the maximum delay constraint. In addition, the central system 120 may further be based on the network delay between it and the multiple mobile devices when assigning computing tasks. For example, if the first vehicle 142 has a longer communication network delay with the central system 120 than the second vehicle 143, the central system 120 may allocate less to the first vehicle 142 Calculation task. The method for acquiring the original data by the plurality of mobile devices may be the same as the method for acquiring the original data when the one mobile device is used (that is, transit through the central system 120, directly obtain from the user end, or download from the cloud server, etc.) .

In some embodiments, the assignment calculation task may be further based on the movement state of the mobile device. For example, in FIG. 1, the first vehicle 142 may drive out of the signal coverage after 2 seconds. When joining the dynamic distributed computing network, the first vehicle 142 may send its planned driving trajectory together with its computing power state to the central system 120. The central system 120 may determine that the first vehicle 142 may serve as a computing node time window according to the planned driving trajectory, and then assign computing tasks to the first vehicle 142 according to the time window and the computing power state of the first vehicle 142, thereby It is ensured that the first vehicle 142 can feed back the processed data before driving out of the signal coverage.

When the central system 120 is a communication module of the second user's electronic device, the second user's electronic device may further include a computing module, and the communication module may pass the received data processing request through the first The bus of the electronic equipment of the two users is sent to the calculation module.

In 540, the central system 120 may receive the processed data returned by the at least one mobile device. In 550, the central system 120 may send the processed data to the user. That is, after completing the computing task, the at least one mobile device may send the processed data to the user via the central system 120.

Those of ordinary skill in the art should recognize that this method of transferring the processed data back to the user through the central system 120 is only an embodiment of this application, and any other method can enable the user to obtain The method of processing the data described above does not deviate from the scope disclosed in this application. For example, the at least one mobile device may directly send the processed data to the user. For another example, the at least one mobile device may be in a second network system with the user, and establish a connection with a second central system (not shown in the figure), respectively. The at least one mobile device may send the processed data to the user via the second central system through the second network.

FIG. 6 is a schematic diagram of a central device 600 in this application. The central device 600 includes a statistical unit 610, a networking unit 620, a data receiving unit 630, and a data sending unit 640.

The statistical unit 610 may be used to count information of one or more mobile devices with remaining computing power within a preset range around.

The networking unit 620 may establish a dynamic network connection with the one or more mobile devices based on the one or more mobile device information, thereby forming a dynamic distribution using the one or more mobile devices as computing nodes Computing network.

The data receiving unit 630 may receive the data processing request sent by the user.

The data sending unit 640 may select at least one mobile device from the dynamic distributed computing network according to the data processing request and send the data processing request.

The data receiving unit 630 may further receive the processed data returned by the at least one mobile device.

The data sending unit 640 may further send the processed data to the user.

This application also proposes a computer-readable storage medium on which a computer program is stored. When the computer program is executed by the processor, the steps of dynamic computing network sharing and computing power described above can be realized.

In summary, after reading this detailed disclosure, those skilled in the art may understand that the foregoing detailed disclosure may be presented by way of example only, and may not be limiting. Although not explicitly stated here, those skilled in the art can understand that this application is intended to include various reasonable changes, improvements, and modifications to the embodiments. These changes, improvements, and modifications are intended to be proposed by this application, and are within the spirit and scope of the exemplary embodiments of this application.

In addition, certain terms in this application have been used to describe embodiments of this application. For example, "one embodiment", "an embodiment" and/or "some embodiments" mean that a particular feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. Therefore, it can be emphasized and understood that two or more references to "an embodiment" or "one embodiment" or "alternative embodiment" in various parts of this specification do not necessarily all refer to the same embodiment. In addition, specific features, structures, or characteristics may be appropriately combined in one or more embodiments of the present application.

It should be understood that, in the foregoing description of the embodiments of the present application, to help understand one feature, for the purpose of simplifying the present application, the present application sometimes combines various features in a single embodiment, drawings, or description thereof. Or, this application is to disperse various features in multiple embodiments of the present invention. However, this does not mean that the combination of these features is necessary, and it is entirely possible for those skilled in the art to extract some of the features as a separate embodiment when reading this application. That is to say, the embodiments in this application can also be understood as the integration of multiple secondary embodiments. It is also true that the content of each secondary embodiment is less than all the features of a single foregoing disclosed embodiment.

In some embodiments, a number expressing the quantity or nature used to describe and claim certain embodiments of the present application should be understood to be modified in some cases by the terms "about", "approximately", or "substantially." For example, unless otherwise stated, "about", "approximately" or "substantially" may represent a ±20% change in the value it describes. Therefore, in some embodiments, the numerical parameters listed in the written description and the appended claims are approximate values, which may vary depending on the desired properties sought by the particular embodiment. In some embodiments, the numerical parameter should be interpreted according to the number of significant digits reported and by applying ordinary rounding techniques. Although some embodiments that illustrate the present application list a wide range of numerical ranges and parameters are approximate values, specific examples list the most accurate numerical values possible.

Each patent, patent application, patent application publication, and other materials cited herein, such as articles, books, specifications, publications, documents, articles, etc., may be incorporated herein by reference. All content used for all purposes, except for the history of any prosecution documents related to it, may be inconsistent or conflict with any of this document, or any same prosecution document that may have a restrictive effect on the broadest scope of the claims history. Associated with this document now or in the future. For example, if there is any inconsistency or conflict between the descriptions, definitions, and/or use of terms associated with any contained material in relation to this document, use this document The terminology shall prevail.

Finally, it should be understood that the embodiments of the application disclosed herein are illustrative of the principles of the embodiments of the application. Other modified embodiments are also within the scope of this application. Therefore, the embodiments disclosed in this application are only examples and are not limiting. Those skilled in the art may adopt alternative configurations according to the embodiments in the present application to implement the invention in the present application. Therefore, the embodiments of the present application are not limited to which embodiments are precisely described in the application.

Claims (30)

1. A method for dynamically computing mobile devices to share computing power is characterized by comprising:

   The central system counts the information of one or more mobile devices with residual computing power within a preset range around;

   Based on the one or more mobile device information, the hub system establishes a dynamic network connection with the one or more mobile devices, thereby forming a dynamic distributed computing network that uses the one or more mobile devices as computing nodes. The runtime of the dynamic distributed computing network:

   The central system receives data processing requests sent by users;

   According to the data processing request, the hub system selects at least one mobile device from the dynamic distributed computing network;

   The central system sends the data processing request to the at least one mobile device;

   The central system receives the processed data returned by the at least one mobile device; and

   The central system sends the processed data to the user.
2. The method of claim 1, wherein the one or more mobile devices include on-board electronic devices of one or more vehicles.
3. The method according to claim 2, wherein the central system includes a base station communication system, and the user and the one or more vehicles are within a signal coverage of the base station communication system.
4. The method of claim 3, wherein

   The data processing request includes a maximum delay constraint, the maximum delay constraint reflects the latest moment when the central system sends the processed data to the user; and

   The selecting at least one mobile device includes:

   The central system selects at least one vehicle's in-vehicle electronics from the one or more vehicles' in-vehicle electronic devices based on the maximum delay constraint and the computing power state of the one or more vehicles' in-vehicle electronic devices equipment.
5. The method according to claim 4, wherein the central system sending the data processing request to the at least one mobile device comprises:

   Assign computing tasks to each vehicle in the at least one vehicle according to the computing power state of the onboard electronic equipment of each vehicle in the at least one vehicle; and

   The central system sends its corresponding computing task to each of the at least one vehicle.
6. The method according to claim 5, wherein the assigning calculation tasks to each vehicle of at least one vehicle further comprises:

   Assign calculation tasks to each vehicle according to the planned driving trajectory of each vehicle.
7. The method of claim 1, wherein the hub system includes a communication module of a second user's electronic device, and the mobile device includes a computing module of the second user's electronic device.
8. The method according to claim 7, wherein the central system sending the data processing request to the at least one mobile device comprises:

   The communication module sends the data processing request to the calculation module through the bus of the second user's electronic device.
9. The method according to claim 1, wherein the central system statistical information of one or more mobile devices having remaining computing power within a preset range around the periphery includes:

   The central system periodically updates the computing power state of mobile devices within its signal coverage; and

   According to the computing power state of the mobile device, the central system counts information of one or more mobile devices having remaining computing power.
10. The method according to claim 1, wherein the method further comprises:

    When the dynamic distributed computing network is running, the user directly sends data to be processed to the at least one mobile device.
11. A mobile device distributed computing network platform for dynamically sharing computing power, characterized by comprising: a hub device, the hub device comprises:

    antenna;

    At least one storage medium, the storage medium storing a set of instructions; and

    At least one processor, the processor communicates with the at least one storage medium, and when executing the set of instructions, the at least one processor is used to:

    Establish a dynamic network connection with one or more mobile devices that enter the predetermined range of the central device to form a dynamic distributed computing network using the one or more mobile devices as computing nodes, the dynamic distributed computing network Runtime:

    The hub device receives the data processing request sent by the user;

    According to the data processing request, the hub device selects at least one mobile device from the dynamic distributed computing network;

    The hub device sends the data processing request to the at least one mobile device;

    The central device receives the processed data returned by the at least one mobile device; and

    The hub device sends the processed data to the user.
12. The computing network platform of claim 11, wherein the one or more mobile devices include in-vehicle electronic devices of one or more vehicles.
13. The computing network platform of claim 12, wherein the central device includes a base station communication system, and the user and the one or more vehicles are within a signal coverage of the base station communication system.
14. The computing network platform according to claim 13, wherein:

    The data processing request includes a maximum delay constraint, and the maximum delay constraint reflects the latest moment when the central device sends the processed data to the user; and

    The selecting at least one mobile device includes:

    The central device selects at least one car's on-board electronics from the one or more car's on-board electronic devices according to the maximum delay constraint and the computing power state of the one or more car's on-board electronic devices equipment.
15. The computing network platform according to claim 14, wherein the central device sending the data processing request to the at least one mobile device includes:

    Assign computing tasks to each vehicle in the at least one vehicle according to the computing power state of the onboard electronic equipment of each vehicle in the at least one vehicle; and

    The central device sends its corresponding computing task to each vehicle in the at least one vehicle.
16. The computing network platform according to claim 15, wherein the assigning a computing task to each vehicle in at least one vehicle further comprises:

    Assign calculation tasks to each vehicle according to the planned driving trajectory of each vehicle.
17. The computing network platform of claim 11, wherein the central device includes a communication module of a second user's electronic device, and the mobile device includes a computing module of the second user's electronic device.
18. The computing network platform according to claim 17, wherein the central device sending the data processing request to the at least one mobile device comprises:

    The communication module sends the data processing request to the calculation module through the bus of the second user's electronic device.
19. The computing network platform according to claim 11, wherein the central device statistics of one or more mobile devices with remaining computing power within a preset range around the periphery include:

    The hub device periodically updates the computing power state of the mobile device within its signal coverage; and

    According to the computing power state of the mobile device, the central device counts information of one or more mobile devices having remaining computing power.
20. The computing network platform of claim 11, wherein the user directly sends data to be processed to the at least one mobile device when the dynamic distributed computing network is running.
21. A non-transitory computer-readable medium, characterized by comprising at least one set of instructions, when the processor of at least one computing device executes the at least one set of instructions, the at least one set of instructions causes the computing device to execute:

    The central system counts the information of one or more mobile devices with residual computing power within a preset range around;

    Based on the one or more mobile device information, the hub system establishes a dynamic network connection with the one or more mobile devices, thereby forming a dynamic distributed computing network that uses the one or more mobile devices as computing nodes. The runtime of the dynamic distributed computing network:

    The central system receives data processing requests sent by users;

    According to the data processing request, the hub system selects at least one mobile device from the dynamic distributed computing network;

    The central system sends the data processing request to the at least one mobile device;

    The central system receives the processed data returned by the at least one mobile device; and

    The central system sends the processed data to the user.
22. The non-transitory computer readable medium of claim 21, wherein the one or more mobile devices include on-board electronic devices of one or more vehicles.
23. The non-transitory computer-readable medium of claim 22, wherein the hub system includes a base station communication system, and the user and the one or more vehicles are located within a signal coverage area of the base station communication system Inside.
24. The non-transitory computer readable medium of claim 23, wherein

    The data processing request includes a maximum delay constraint, the maximum delay constraint reflects the latest moment when the central system sends the processed data to the user; and

    The selecting at least one mobile device includes:

    The central system selects at least one vehicle's in-vehicle electronics from the one or more vehicles' in-vehicle electronic devices based on the maximum delay constraint and the computing power state of the one or more vehicles' in-vehicle electronic devices equipment.
25. The non-transitory computer readable medium of claim 24, wherein the central system sending the data processing request to the at least one mobile device includes:

    Assign computing tasks to each vehicle in the at least one vehicle according to the computing power state of the onboard electronic equipment of each vehicle in the at least one vehicle; and

    The central system sends its corresponding computing task to each of the at least one vehicle.
26. The non-transitory computer readable medium of claim 25, wherein the assigning calculation tasks to each vehicle of at least one vehicle further comprises:

    Assign calculation tasks to each vehicle according to the planned driving trajectory of each vehicle.
27. The non-transitory computer readable medium of claim 21, wherein the hub system includes a communication module of a second user's electronic device, and the mobile device includes a computing module of the second user's electronic device .
28. The non-transitory computer-readable medium of claim 27, wherein the central system sending the data processing request to the at least one mobile device comprises:

    The communication module sends the data processing request to the calculation module through the bus of the second user's electronic device.
29. The non-transitory computer-readable medium according to claim 21, wherein the information of one or more mobile devices with remaining computing power within a preset range around the central system statistics includes:

    The hub system periodically updates the computing power state of mobile devices within its signal coverage; and

    According to the computing power state of the mobile device, the central system counts information of one or more mobile devices having remaining computing power.
30. The non-transitory computer readable medium of claim 21, wherein the user directly sends data to be processed to the at least one mobile device when the dynamic distributed computing network is running.

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