A task allocation method, system, device and storage medium for Internet of Vehicles

Abstract

The application discloses a task allocation method, system and device of Internet of Vehicles and a storage medium. First, all object nodes in the communication range of a target vehicle are acquired. Then, from a plurality of first object nodes which are active and willing to execute the vehicle-mounted task of the vehicle, a plurality of second object nodes which are more willing to execute the task and more willing to maintain the safety calculation of the task are selected. The member nodes of the decision-making groups can help select the second object nodes which are more willing to execute the task and more willing to maintain the safety calculation of the task when the object nodes of the target vehicle-mounted task of the target vehicle are selected, so that the calculation safety of the target vehicle-mounted task is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle networking technology, and in particular to a task allocation method, system, device and storage medium for vehicle networking. Background Technology

[0002] With the rapid development of various vehicle applications, such as vehicle-to-everything (V2X) social networks, a large amount of computing power is required. It is anticipated that in the near future, however, vehicles, limited by their own onboard chips, will be unable to meet the ever-increasing demands for data processing.

[0003] Currently, the common practice is to assign (unload) vehicle tasks to other vehicles or roadside units, utilizing these other vehicles or roadside units to assist in computation. However, the current logic for vehicle task assignment mainly involves distributing onboard tasks to the nearest other vehicle or roadside unit for computational assistance. While this method is highly efficient, it ignores the possibility of malicious computation by neighboring nodes. Summary of the Invention

[0004] This invention aims to at least solve the technical problems existing in the prior art. To this end, this invention proposes a task allocation method, system, device, and storage medium for vehicle-to-everything (V2X) networks, which can improve the computational security of in-vehicle tasks.

[0005] A first aspect of the present invention provides a task allocation method for a vehicle-to-everything (V2X) network, the task allocation method comprising:

[0006] Obtain the location of the target vehicle to which the target vehicle-mounted task needs to be assigned;

[0007] Based on the location of the target vehicle, determine multiple first object nodes and multiple second object nodes within the communication range of the target vehicle; the first object nodes are vehicles and / or roadside units whose remaining task allocation is less than the target vehicle-mounted task, and the second object nodes are vehicles and / or roadside units whose remaining task allocation is greater than the target vehicle-mounted task.

[0008] A certain number of first object nodes are selected from the plurality of first object nodes to form a decision group. A second object node is selected from the plurality of second object nodes by the member nodes of the decision group as the allocation object for the target vehicle's on-board task.

[0009] According to embodiments of the present invention, at least the following technical effects are achieved:

[0010] In this embodiment, all object nodes within the communication range of the target vehicle are first obtained. From the multiple first object nodes that are active and willing to perform the vehicle's onboard tasks, multiple first object nodes that are more willing to perform task computation and more willing to maintain task security computation are selected to form a decision group. Then, when selecting the object nodes for the target vehicle's onboard tasks, the member nodes of these decision groups can help select second object nodes that are more willing to perform tasks and more willing to maintain task security computation, thereby improving the computation security of the target vehicle's onboard tasks.

[0011] According to some embodiments of the present invention, selecting a certain number of the first object nodes from the plurality of first object nodes to form a decision group includes:

[0012] Obtain the number of times the vehicle task is completed and the satisfaction level of the vehicle task completion for each of the plurality of first object nodes;

[0013] Based on the number of times the vehicle-mounted task is completed and the satisfaction level of the completion of the vehicle-mounted task, the plurality of first object nodes are sorted to obtain a sorting result;

[0014] A certain number of the first object nodes are selected from the sorting results to form a decision group.

[0015] According to some embodiments of the present invention, the step of selecting a second object node from the plurality of second object nodes as the allocation object for the target vehicle's onboard task through the member nodes of the decision group includes:

[0016] The load of each of the plurality of second object nodes, the communication distance between each second object node and the target vehicle, and the task cooperation degree between each member node of the decision group and each second object node are obtained.

[0017] The member nodes of the decision group vote based on the load, the communication distance, and the degree of task cooperation to obtain the voting score of each member node for all the second object nodes;

[0018] Calculate the total score for each of the object nodes, average the total score according to the number of voting member nodes to obtain the average score, and select the second object node with the highest score from the average score as the allocation object for the target vehicle's on-board task.

[0019] According to some embodiments of the present invention, the degree of task collaboration includes at least the number of task assignments between the member node and the second object node.

[0020] According to some embodiments of the present invention, the step of obtaining a voting score for each member node regarding all the second object nodes by having member nodes of the decision group vote based on the load, the communication distance, and the degree of task cooperation includes:

[0021] Each member node of the decision-making group quantifies the load, the communication distance, and the degree of task collaboration, and sets corresponding weight coefficients; wherein, each member node of the decision-making group sets the same weight coefficients for the load, the communication distance, and the degree of task collaboration.

[0022] Each member node of the decision-making group calculates its voting score for each of the second object nodes by multiplying the quantified load, communication distance, and task collaboration level by the corresponding weight coefficient.

[0023] According to some embodiments of the present invention, the member nodes of the decision group are periodically reselected.

[0024] According to some embodiments of the present invention, after selecting the allocation target of the target vehicle's onboard task, the task allocation method of the vehicle network further includes:

[0025] The target vehicle assigns the target vehicle-mounted task to the assigned object for calculation of the target vehicle-mounted task.

[0026] A second aspect of the present invention provides a task allocation system for a vehicle-to-everything (V2X) network, the task allocation system comprising:

[0027] The vehicle positioning unit is used to obtain the location of the target vehicle to which the target vehicle-mounted task needs to be assigned.

[0028] A node selection unit is used to determine multiple first object nodes and multiple second object nodes located within the communication range of the target vehicle based on the location of the target vehicle; the first object nodes are vehicles and / or roadside units whose remaining task allocation is less than the target vehicle-mounted task, and the second object nodes are vehicles and / or roadside units whose remaining task allocation is greater than the target vehicle-mounted task.

[0029] The allocation object selection unit is used to select a certain number of first object nodes from the plurality of first object nodes to form a decision group, and select a second object node from the plurality of second object nodes as the allocation object of the target vehicle's on-board task through the member nodes of the decision group.

[0030] Since the vehicle network task allocation system adopts all the technical solutions of the vehicle network task allocation method in the above embodiments, it has at least all the beneficial effects brought about by the technical solutions in the above embodiments.

[0031] A third aspect of the present invention provides a task allocation electronic device for a vehicle-to-everything (V2X) network, comprising at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, the instructions being executed by the at least one control processor to enable the at least one control processor to perform the aforementioned V2X task allocation method. Since the V2X task allocation electronic device employs all the technical solutions of the V2X task allocation method of the above embodiments, it possesses at least all the beneficial effects brought about by the technical solutions of the above embodiments.

[0032] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the above-described task allocation method for the Internet of Vehicles. Since the readable storage medium employs all the technical solutions of the task allocation method for the Internet of Vehicles described in the above embodiments, it possesses at least all the beneficial effects brought about by the technical solutions of the above embodiments.

[0033] It should be noted that the beneficial effects of the second to fourth aspects of the present invention compared with the prior art are the same as the beneficial effects of the above-described task allocation method for vehicle networking compared with the prior art, and will not be described in detail here.

[0034] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0035] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0036] Figure 1 This is a flowchart illustrating a task allocation method for a vehicle-to-everything (V2X) network according to an embodiment of the present invention;

[0037] Figure 2 yes Figure 1 A flowchart illustrating the process of establishing a decision-making group in step S103;

[0038] Figure 3 yes Figure 1 A flowchart illustrating the process of selecting the target vehicle-mounted task allocation object in step S103;

[0039] Figure 4 yes Figure 3 A flowchart illustrating step S1035 in the process;

[0040] Figure 5 This is a flowchart illustrating a task allocation method for a vehicle-to-everything (V2X) network according to another embodiment of the present invention;

[0041] Figure 6 This is a schematic diagram of the structure of a vehicle networking task allocation system according to an embodiment of the present invention;

[0042] Figure 7 This is a schematic diagram of the structure of a vehicle networking task allocation device provided in one embodiment of the present invention. Detailed Implementation

[0043] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0044] In the description of this invention, the use of terms such as "first," "second," etc., is for the purpose of distinguishing technical features only and should not be construed as indicating or implying relative importance, or implicitly indicating the number of technical features indicated, or implicitly indicating the order of the technical features indicated.

[0045] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, etc., are based on the orientation or positional relationship shown in the drawings and are only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0046] In the description of this invention, it should be noted that, unless otherwise explicitly defined, terms such as "setting," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0047] It should be understood that, in the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0048] Reference Figure 1 One embodiment of this application provides a task allocation method for a vehicle-to-everything (V2X) network, which includes the following steps:

[0049] Step S101: Obtain the location of the target vehicle to be assigned the target vehicle-mounted task.

[0050] In this embodiment, the target vehicle refers to a vehicle that has an onboard task that needs to be assigned. It is worth noting that the target vehicle can be a stationary vehicle or a moving vehicle.

[0051] Step S102: Determine multiple first object nodes and multiple second object nodes within the communication range of the target vehicle based on the location of the target vehicle; the first object nodes are vehicles and / or roadside units whose remaining task allocation is less than the target vehicle-mounted task, and the second object nodes are vehicles and / or roadside units whose remaining task allocation is greater than the target vehicle-mounted task.

[0052] In this embodiment, all object nodes within the communication range of the target vehicle are first acquired. These object nodes include vehicles or roadside units. Among all object nodes, there are vehicles and / or roadside units whose remaining task allocation is less than the target vehicle-mounted task; these are designated as first object nodes. The remaining task allocation of a first object node refers to the amount of task its remaining computing power can handle. In this embodiment, the first object nodes are used to vote to select the appropriate allocation object for the target vehicle's vehicle-mounted task. Because the first object nodes are currently executing many vehicle-mounted tasks, they are more active and more willing to perform these tasks. Since they no longer have the computing power to handle the target vehicle-mounted task, these active nodes are used to vote for the allocation object. There are also vehicles and / or roadside units among the object nodes whose remaining task allocation is greater than the target vehicle-mounted task; these are designated as second object nodes. The target vehicle-mounted task needs to be allocated to one of these nodes, and the assisted computation of the target vehicle-mounted task is completed through this selected node.

[0053] Step S103: Select a certain number of first object nodes from multiple first object nodes to form a decision group, and select a second object node from multiple second object nodes through the member nodes of the decision group as the allocation object of the target vehicle's on-board task.

[0054] In this embodiment, since the first object nodes are more active and more willing to perform vehicle-mounted tasks, this application selects a certain number of first object nodes (e.g., 5 out of 15) and establishes a decision group. The member nodes of this decision group (i.e., the first object nodes selected in the decision group) jointly vote to select a second object node. Establishing a decision group allows for the selection of the most active nodes from among the active nodes. These nodes are more willing to perform task calculations and maintain secure task calculations, thus reducing the probability of malicious computation. Furthermore, it reduces the number of nodes making decisions and simplifies the voting process.

[0055] Since the selected decision-making member nodes are more willing to perform task computations and maintain task security computations, when selecting the target vehicle's onboard task object nodes, they can help select a second object node that is more willing to perform task computations and maintain task security computations, thereby ensuring the security computation of the target vehicle's onboard task.

[0056] Reference Figure 2 In one embodiment of this application, step S103, which involves selecting a certain number of first object nodes from a plurality of first object nodes to form a decision group, includes:

[0057] Step S1031: Obtain the number of times the vehicle task is completed and the satisfaction level of the vehicle task completion for each of the multiple first object nodes.

[0058] Step S1032: Sort multiple first object nodes according to the number of times the vehicle-mounted task is completed and the satisfaction level of the vehicle-mounted task completion, and obtain the sorting result.

[0059] Step S1033: Select a certain number of first object nodes from the sorting results to form a decision group.

[0060] In steps S1031, S1032, and S1033, to select a decision group, the number of times each first object node completes its onboard task and its satisfaction level are first determined. These two parameters are used as screening criteria. It's worth noting that these parameters are statistically analyzed after each task is completed by the vehicle or roadside unit; they can be obtained here. Then, the first object nodes are sorted based on these parameters, resulting in a ranking. A higher number of completed onboard tasks or a higher satisfaction level indicates that the first object node is more willing to perform task calculations and maintain safe task execution. It's important to note that these two parameters can be quantified and weighted to obtain a score for each first object node, leading to a ranking. Finally, a certain number of first object nodes are selected from the ranking results to form a decision group, for example, 5 out of 15. It should be noted that this example does not impose a specific limit on the number of member nodes in the decision group.

[0061] Reference Figure 3 In one embodiment of this application, step S103, which involves selecting a second object node from multiple second object nodes as the allocation object for the target vehicle's onboard task through the member nodes of the decision group, includes:

[0062] Step S1034: Obtain the load of each of the multiple second object nodes, the communication distance between each second object node and the target vehicle, and the task cooperation level between each member node of the decision group and each second object node.

[0063] Step S1035: The member nodes of the decision group vote based on load, communication distance and task collaboration level to obtain the voting score of each member node for all second object nodes.

[0064] Step S1036: Calculate the total score of each object node, average the total score according to the number of voting member nodes to obtain the average score, and select the second object node with the highest score from the average score as the target vehicle on-board task allocation object.

[0065] In steps S1034, S1035, and S1036, the member nodes of the decision-making group need to select a second object node to assist in the calculation of the target vehicle's onboard task. To achieve this selection, in step S1034, the current load of each second object node, the communication distance between it and the target vehicle, and the task cooperation level between each member node of the decision-making group and each second object node are calculated. This embodiment retains the necessary parameters of load and communication distance, and adds the parameter of the task cooperation level between each member node and the second object node. The higher the task cooperation level, the closer the task allocation between the member node and the second object node is, which also means that the member node is more willing to trust this second object node. It should be noted that the task cooperation level referred to in this embodiment refers to the number of task allocations and the task allocation satisfaction level between the member node and the second object node. For example, if the 5th roadside unit (member node) has the most task allocations and the highest task allocation satisfaction level with the 5th second object node, then the 5th roadside unit is more inclined to make the 5th second object node the object node of the target vehicle. Then, in step S1035, the member nodes of the decision-making group vote based on three parameters: load, communication distance, and task collaboration level. Figure 4 Specifically, this includes steps S10351 and S10352: Step S10351: Each member node of the decision-making group quantifies the load, communication distance, and task cooperation level, and sets corresponding weight coefficients; wherein, each member node of the decision-making group sets the same weight coefficients for load, communication distance, and task cooperation level. Step S10352: Each member node of the decision-making group multiplies the quantified load, communication distance, and task cooperation level by the corresponding weight coefficients to obtain the voting score for each second object node. Finally, in step S1036, the total score of each object node is calculated, and the total score is averaged according to the number of voting member nodes to obtain the average score. The second object node with the highest average score is selected as the target vehicle's on-board task allocation object. It should be noted that when a member node is a roadside unit, it only votes for second object nodes that are vehicles; when a member node is a vehicle, it only votes for second object nodes that are roadside units. This will not be elaborated further here.

[0066] In one embodiment of this application, the member nodes of the decision group are periodically reselected. If the target vehicle is moving, the member nodes of the decision group are periodically reselected to ensure that an optimal second object node can be selected for the target vehicle's onboard task. The selection process is consistent with step S103. If the vehicle is stationary and the state of the first object node is constantly changing (the number of times the onboard task is completed and the satisfaction level of the onboard task completion), the member nodes of the decision group are periodically reselected to ensure that member nodes below the selection criteria are removed from the decision group, and the first object node that meets the selection criteria is selected into the decision group. This ensures that the member nodes in the decision group are nodes that are more willing to perform task calculations and maintain the safe calculation of the task.

[0067] Reference Figure 5 In one embodiment of this application, after step S103, the task allocation method for the vehicle network further includes:

[0068] Step S104: The target vehicle assigns the target onboard task to the assigned object for calculation of the target onboard task.

[0069] To enable those skilled in the art to better understand the present invention, a brief example is provided below:

[0070] First, locate the vehicle V that needs to be assigned onboard tasks, and locate all nodes within the communication range of vehicle V (including vehicles and roadside nodes). Second, obtain the current remaining task allocation amount for all nodes, and divide all nodes into two categories based on the remaining task allocation amount: the first category consists of nodes whose remaining task allocation amount is less than the onboard tasks assigned to vehicle V; the second category consists of nodes whose remaining task allocation amount is greater than the onboard tasks assigned to vehicle V. Third, select decision-making group members from all the first category nodes. This involves first obtaining the number of onboard tasks completed and the onboard task completion satisfaction rate for each first category node, then calculating the weights of these two indicators, calculating the scores of all first category nodes, obtaining a ranking, and selecting the top-ranked first category nodes as member nodes of the decision-making group. Then, the member nodes of the decision-making group select one second-type node from all the second-type nodes as the allocation target for the vehicle V's onboard tasks. This involves first obtaining the load capacity of each second-type node, its communication distance to the vehicle V, and the task cooperation level between each member node and each second-type node (task cooperation level refers to the number of task allocations and the satisfaction level between the member node and the second-type node; note that a group of member nodes and second-type nodes refers to a group of vehicles and roadside units or a group of roadside units and vehicles). These three parameters are then used to calculate the weights, resulting in a total score for each member node relative to each second-type node. The average score for each second-type node is then calculated based on this total score and the number of voting member nodes. From this average score, one second-type node is selected as the allocation target for the vehicle V's onboard tasks. Finally, the vehicle V assigns the onboard tasks to the allocation target for onboard task calculation. It's important to note that regardless of whether the vehicle V is stationary or moving, the member nodes of the decision-making group are periodically rotated, following the same selection process as described in the initial selection.

[0071] Reference Figure 6 According to one embodiment of the present invention, a task allocation system for a vehicle-to-everything (V2X) network is provided. This V2X task allocation system includes a vehicle positioning unit 1100, a node selection unit 1200, and an allocation object selection unit 1300, wherein specifically:

[0072] The vehicle positioning unit 1100 is used to obtain the location of the target vehicle to which the target vehicle-mounted task needs to be assigned.

[0073] The node selection unit 1200 is used to determine multiple first object nodes and multiple second object nodes located within the communication range of the target vehicle based on the location of the target vehicle; the first object nodes are vehicles and / or roadside units whose remaining task allocation is less than the target vehicle-mounted task, and the second object nodes are vehicles and / or roadside units whose remaining task allocation is greater than the target vehicle-mounted task.

[0074] The allocation object selection unit 1300 is used to select a certain number of first object nodes from multiple first object nodes to form a decision group, and select a second object node from multiple second object nodes as the allocation object for the target vehicle's on-board task through the member nodes of the decision group.

[0075] This system first acquires all object nodes within the communication range of the target vehicle. From the multiple first object nodes that are active and willing to perform the vehicle's onboard tasks, it selects several first object nodes that are more willing to perform the task computation and more willing to maintain the task's secure computation to form a decision group. Then, when selecting the object nodes for the target vehicle's onboard tasks, the member nodes of these decision groups can help select second object nodes that are more willing to perform the task and more willing to maintain the task's secure computation, thereby improving the computational security of the target vehicle's onboard tasks.

[0076] It should be noted that the task allocation system embodiment of this vehicle network is based on the same inventive concept as the method embodiment described above. Therefore, the relevant content of the method embodiment described above is also applicable to this system embodiment, and will not be repeated here.

[0077] Reference Figure 7 This application also provides a task allocation electronic device for vehicle networking, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the task allocation method for vehicle networking as described above.

[0078] The processor and memory can be connected via a bus or other means.

[0079] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0080] The non-transitory software program and instructions required to implement the vehicle-to-everything (V2X) task allocation method of the above embodiments are stored in memory. When executed by a processor, the V2X task allocation method of the above embodiments is executed, for example, the method described above is executed. Figure 1 The method steps S101 to S103 are described in the text.

[0081] This application also provides a computer-readable storage medium storing computer-executable instructions for executing, as described above, the task allocation method for the Internet of Vehicles.

[0082] The computer-readable storage medium stores computer-executable instructions that are executed by a processor or controller, for example, by a processor in the above-described electronic device embodiment, causing the processor to perform the vehicle-to-everything (V2X) task allocation method described above, for example, executing the above-described... Figure 1 The method steps S101 to S103 are described in the text.

[0083] Those skilled in the art will understand that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing data (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired data and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any data delivery medium.

[0084] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0085] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A task allocation method for vehicle-to-everything (V2X) networks, characterized in that, The task allocation method of the vehicle-to-everything (V2X) network includes: Obtain the location of the target vehicle to which the target vehicle-mounted task needs to be assigned; Based on the location of the target vehicle, determine multiple first object nodes and multiple second object nodes within the communication range of the target vehicle; the first object nodes are vehicles and / or roadside units whose remaining task allocation is less than the target vehicle-mounted task, and the second object nodes are vehicles and / or roadside units whose remaining task allocation is greater than the target vehicle-mounted task; the remaining task allocation refers to the amount of tasks that the remaining computing power can handle. A decision group is formed by selecting a certain number of first object nodes from the plurality of first object nodes, and a second object node is selected from the plurality of second object nodes by the member nodes of the decision group as the allocation object for the target vehicle's on-board task; the step of selecting a certain number of first object nodes from the plurality of first object nodes to form a decision group includes: Obtain the number of times the vehicle task is completed and the satisfaction level of the vehicle task completion for each of the plurality of first object nodes; Based on the number of times the vehicle-mounted task is completed and the satisfaction level of the completion of the vehicle-mounted task, the plurality of first object nodes are sorted to obtain a sorting result; A certain number of the first object nodes are selected from the sorting results to form a decision group.

2. The task allocation method for the Internet of Vehicles according to claim 1, characterized in that, The step of selecting a second object node from the plurality of second object nodes as the allocation object for the target vehicle's onboard task through the member nodes of the decision group includes: The load of each of the plurality of second object nodes, the communication distance between each second object node and the target vehicle, and the task cooperation degree between each member node of the decision group and each second object node are obtained. The member nodes of the decision group vote based on the load, the communication distance, and the degree of task cooperation to obtain the voting score of each member node for all the second object nodes; Calculate the total score for each of the object nodes, average the total score according to the number of voting member nodes to obtain the average score, and select the second object node with the highest score from the average score as the allocation object for the target vehicle's on-board task.

3. The task allocation method for the Internet of Vehicles according to claim 2, characterized in that, The degree of task collaboration includes at least the number of task assignments between the member node and the second object node.

4. The task allocation method for vehicle networking according to any one of claims 2 or 3, characterized in that, The process involves member nodes of the decision group voting based on the load, communication distance, and task collaboration level to obtain a voting score for each member node for all the second object nodes, including: Each member node of the decision-making group quantifies the load, the communication distance, and the degree of task collaboration, and sets corresponding weight coefficients; wherein, each member node of the decision-making group sets the same weight coefficients for the load, the communication distance, and the degree of task collaboration. Each member node of the decision-making group calculates its voting score for each of the second object nodes by multiplying the quantified load, communication distance, and task collaboration level by the corresponding weight coefficient.

5. The task allocation method for the Internet of Vehicles according to claim 1, characterized in that, The member nodes of the decision-making group are periodically re-selected.

6. The task allocation method for the Internet of Vehicles according to claim 1, characterized in that, After selecting the target vehicle for the on-board task allocation, the vehicle-to-everything (V2X) task allocation method further includes: The target vehicle assigns the target vehicle-mounted task to the assigned object for calculation of the target vehicle-mounted task.

7. A task allocation system for vehicle networking, characterized in that, The task allocation system of the vehicle network includes: The vehicle positioning unit is used to obtain the location of the target vehicle to which the target vehicle-mounted task needs to be assigned. A node selection unit is used to determine multiple first object nodes and multiple second object nodes located within the communication range of the target vehicle based on the location of the target vehicle; the first object nodes are vehicles and / or roadside units whose remaining task allocation is less than the target vehicle-mounted task, and the second object nodes are vehicles and / or roadside units whose remaining task allocation is greater than the target vehicle-mounted task; the remaining task allocation refers to the amount of tasks that the remaining computing power can handle. The allocation object selection unit is used to select a certain number of first object nodes from the plurality of first object nodes to form a decision group, and to select a second object node from the plurality of second object nodes as the allocation object for the target vehicle's on-board task through the member nodes of the decision group; the step of selecting a certain number of first object nodes from the plurality of first object nodes to form a decision group includes: Obtain the number of times the vehicle task is completed and the satisfaction level of the vehicle task completion for each of the plurality of first object nodes; Based on the number of times the vehicle-mounted task is completed and the satisfaction level of the completion of the vehicle-mounted task, the plurality of first object nodes are sorted to obtain a sorting result; A certain number of the first object nodes are selected from the sorting results to form a decision group.

8. A task allocation electronic device for vehicle networking, characterized in that: It includes at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, which, when executed by the at least one control processor, enable the at least one control processor to perform the vehicle networking task allocation method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the task allocation method for the Internet of Vehicles as described in any one of claims 1 to 6.

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