CN115834577A - Task allocation method, system, equipment and storage medium for Internet of vehicles - Google Patents
Task allocation method, system, equipment and storage medium for Internet of vehicles Download PDFInfo
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Abstract
The invention discloses a task allocation method, a system, equipment and a storage medium of a vehicle networking, which comprises the steps of firstly obtaining all object nodes in a communication range of a target vehicle, selecting a plurality of calculations which are more willing to execute tasks from a plurality of first object nodes of active nodes which are willing to execute vehicle-mounted tasks of the vehicle, and establishing decision groups by the first object nodes of the nodes which are more willing to maintain the safety calculations of the tasks, and then selecting second object nodes which are more willing to execute the tasks and are more willing to maintain the safety calculations of the tasks by member nodes of the decision groups when selecting the object nodes of the target vehicle-mounted tasks of the target vehicle, thereby improving the calculation safety of the target vehicle-mounted tasks.
Description
Technical Field
The invention relates to the technical field of Internet of vehicles, in particular to a task allocation method, a system, equipment and a storage medium of the Internet of vehicles.
Background
With the rapid development of various vehicle applications, such as vehicle social networks, etc., a large amount of computation is required. In the near future, however, vehicles are limited by their own chips and cannot meet the increasing data computing demands.
Currently, it is common to distribute (offload) vehicle tasks to other vehicles or roadside units, with which to assist in the computation. However, the current logic of vehicle task allocation mainly allocates vehicle tasks to other vehicles or roadside units in the nearest vicinity for assisting in calculation, and although the allocation formula is high in efficiency, the problem that malicious calculation may exist in adjacent nodes is ignored.
Disclosure of Invention
The present invention is directed to at least solving the problems of the prior art. Therefore, the invention provides a task allocation method, a system, equipment and a storage medium of the Internet of vehicles, which can improve the calculation safety of vehicle-mounted tasks.
The invention provides a task allocation method of a vehicle networking, which comprises the following steps:
acquiring the position of a target vehicle needing to distribute a target vehicle-mounted task;
determining a plurality of first object nodes and a plurality of second object nodes located in the communication range of the target vehicle according to the position of the target vehicle; the first object node is a vehicle and/or roadside unit of which the self residual task allocation amount is smaller than the target vehicle-mounted task, and the second object node is a vehicle and/or roadside unit of which the self residual task allocation amount is larger than the target vehicle-mounted task;
and selecting a certain number of first object nodes from the plurality of first object nodes to form a decision group, and selecting one second object node from the plurality of second object nodes through member nodes of the decision group as an allocation object of the target vehicle-mounted task of the target vehicle.
According to the embodiment of the invention, at least the following technical effects are achieved:
in the embodiment, all object nodes in the communication range of the target vehicle are obtained, a plurality of first object nodes which are more willing to execute the task and are nodes which are more willing to maintain the safety calculation of the task are selected from a plurality of first object nodes which are active and are nodes which are willing to execute the vehicle-mounted task of the vehicle, and then member nodes of the decision groups can help to select a second object node which is more willing to execute the task and is 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.
According to some embodiments of the invention, said selecting a number of said first object node establishment decision groups from said plurality of first object nodes comprises:
acquiring the completion times of the vehicle-mounted task and the completion satisfaction degree of the vehicle-mounted task of each first object node in the plurality of first object nodes;
sequencing the plurality of first object nodes according to the completion times of the vehicle-mounted tasks and the completion satisfaction degree of the vehicle-mounted tasks to obtain a sequencing result;
and selecting a certain number of first object node establishment decision groups from the sequencing results.
According to some embodiments of the invention, the selecting, by the member node of the decision group, one second object node from the plurality of second object nodes as an allocation object of the target on-board task of the target vehicle includes:
acquiring the load capacity of each second object node in the plurality of second object nodes, the communication distance between each second object node and the target vehicle, and the task cooperation degree of each member node of the decision group and each second object node respectively;
voting through member nodes of the decision group according to the load, the communication distance and the task cooperation degree to obtain a voting score of each member node for all the second object nodes;
and calculating the total score of each object node, averaging the total scores according to the number of the voted member nodes to obtain average scores, and selecting the second object node with the highest score from the average scores as an allocation object of the target vehicle-mounted task of the target vehicle.
According to some embodiments of the invention, the degree of task cooperation includes at least a number of task assignments between the member node and the second object node.
According to some embodiments of the present invention, the voting by the member nodes of the decision group according to the load amount, the communication distance, and the degree of task cooperation to obtain a voting score of each member node for all the second object nodes includes:
each member node of the decision group quantizes the load, the communication distance and the task cooperation degree, and sets a corresponding weight coefficient; wherein, each member node of the decision group sets the weight coefficients of the load, the communication distance and the task cooperation degree to be the same;
and multiplying each member node of the decision group by a corresponding weight coefficient according to the quantized load, the communication distance and the task cooperation degree to obtain the voting score of each member node for calculating each second object node.
According to some embodiments of the invention, the member nodes of the decision group are periodically reselected.
According to some embodiments of the invention, after selecting the allocation object of the target on-board task of the target vehicle, the task allocation method of the internet of vehicles further comprises:
and the target vehicle distributes the target vehicle-mounted task to the distribution object to calculate the target vehicle-mounted task.
In a second aspect of the present invention, a task allocation system of a car networking is provided, the task allocation system of the car networking comprises:
the vehicle positioning unit is used for acquiring the position of a target vehicle needing to distribute a target vehicle-mounted task;
the node selection unit is used for determining a plurality of first object nodes and a plurality of second object nodes which are positioned in the communication range of the target vehicle according to the position of the target vehicle; the first object node is a vehicle and/or roadside unit of which the self residual task allocation amount is smaller than the target vehicle-mounted task, and the second object node is a vehicle and/or roadside unit of which the self residual task allocation amount is larger than the target vehicle-mounted task;
and the distribution object selection unit is used for selecting a certain number of first object nodes from the plurality of first object nodes to form a decision group, and selecting one second object node from the plurality of second object nodes through member nodes of the decision group to serve as a distribution object of the target vehicle-mounted task of the target vehicle.
The task allocation system of the Internet of vehicles adopts all the technical schemes of the task allocation method of the Internet of vehicles of the embodiment, so that the task allocation system at least has all the beneficial effects brought by the technical schemes of the embodiment.
In a third aspect of the present invention, a task allocation electronic device for internet of vehicles is provided, comprising at least one control processor and a memory for communicative connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the above-described task allocation method of the internet of vehicles. Since the task allocation electronic device of the internet of vehicles adopts all technical solutions of the task allocation method of the internet of vehicles of the above embodiment, at least all beneficial effects brought by the technical solutions of the above embodiments are achieved.
In a fourth aspect of the present invention, a computer-readable storage medium is provided, which stores computer-executable instructions for causing a computer to perform the above-mentioned task allocation method for the internet of vehicles. The readable storage medium adopts all technical schemes of the task allocation method of the Internet of vehicles, so that the method at least has all beneficial effects brought by the technical schemes of the embodiment.
It should be noted that the beneficial effects between the second to fourth aspects of the present invention and the prior art are the same as the beneficial effects between the task allocation method of the internet of vehicles and the prior art described above, and will not be described in detail here.
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.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart diagram illustrating a task allocation method for a vehicle networking according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a hold decision group in step S103 of FIG. 1;
fig. 3 is a schematic flow chart of the allocation object of the selected target in-vehicle task in step S103 of fig. 1;
fig. 4 is a flowchart of step S1035 in fig. 3;
FIG. 5 is a flowchart illustrating a task allocation method for a vehicle networking according to another embodiment of the present invention;
FIG. 6 is a schematic diagram of a task allocation system of the Internet of vehicles according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a task allocation device of a car networking according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, if there are first, second, etc. described, it is only for the purpose of distinguishing technical features, and it is not understood that relative importance is indicated or implied or that the number of indicated technical features is implicitly indicated or that the precedence of the indicated technical features is implicitly indicated.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to, for example, the upper, lower, etc., is indicated based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, but does not indicate or imply that the device or element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention.
In the description of the present invention, it should be noted that unless otherwise explicitly defined, terms such as setup, installation, connection, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention by combining the detailed contents of the technical solutions.
It is to be understood that in the description of the present invention, "a plurality" means two or more unless otherwise specified.
Referring to fig. 1, an embodiment of the present application provides a task allocation method for a car networking, the method includes the following steps:
and step S101, acquiring the position of the target vehicle needing to distribute the target vehicle-mounted task.
In the present embodiment, the target vehicle refers to a vehicle for which there is an on-board task that needs to be distributed. It is noted that the target vehicle may be a stationary vehicle or a moving vehicle.
Step S102, determining a plurality of first object nodes and a plurality of second object nodes which are positioned in the communication range of the target vehicle according to the position of the target vehicle; the first object node is a vehicle and/or roadside unit of which the remaining task allocation amount is smaller than that of the target vehicle-mounted task, and the second object node is a vehicle and/or roadside unit of which the remaining task allocation amount is larger than that of the target vehicle-mounted task.
In the present embodiment, all object nodes within the communication range of the target vehicle are first acquired, where the object nodes include vehicles or roadside units. The method comprises the steps that all object nodes comprise vehicles and/or roadside units, the distribution amount of the remaining tasks of the first object nodes is smaller than that of the target vehicle-mounted tasks, the distribution amount of the remaining tasks of the first object nodes refers to the task amount capable of being loaded by the remaining computing capacity, the first object nodes are used for voting to select distribution objects suitable for the target vehicle-mounted tasks of the target vehicles, namely the first object nodes are more active nodes which are willing to execute the vehicle-mounted tasks of the vehicles due to the fact that the number of the vehicle-mounted tasks executed by the first object nodes is large, and meanwhile the active nodes are used for selecting the distribution objects of the target vehicle-mounted tasks of the target vehicles due to the fact that the first object nodes do not have the computing amount of the target vehicle-mounted tasks any more. All object nodes also comprise vehicles and/or roadside units with the self residual task allocation amount larger than the target vehicle-mounted task, wherein the first object node is named as a second object node, the target vehicle-mounted task of the target vehicle needs to be allocated to one of the nodes, and the auxiliary calculation of the target vehicle-mounted task is completed through the selected node.
Step S103, selecting a certain number of first object nodes from the plurality of first object nodes to form a decision group, and selecting one second object node from the plurality of second object nodes through member nodes of the decision group as an allocation object of a target vehicle-mounted task of the target vehicle.
In this embodiment, since the first object nodes are more active and are more willing to perform the vehicle-mounted task of the vehicle, the present application selects a certain number of first object nodes (e.g., 5 out of 15) from the first object nodes, and forms a decision group by selecting the first object nodes, and the member nodes of the decision group (i.e., the first object nodes selected as the decision group) jointly vote to select a second object node. On one hand, a decision group is established, the most active nodes can be selected from active points, the nodes are more willing to execute task calculation and maintain task security calculation, the probability of malicious calculation is low, on the other hand, the number of decision-making nodes is reduced, and the complexity of voting calculation is reduced.
Since the decision member nodes of the selected decision group are more willing to perform task calculation and more willing to maintain task safety calculation, when the target nodes of the target vehicle-mounted task of the target vehicle are selected, the decision member nodes can help to select the second target nodes which are more willing to perform task and more willing to maintain task safety calculation, so that the safety calculation of the target vehicle-mounted task is ensured.
Referring to fig. 2, in an embodiment of the present application, the selecting a certain number of first object nodes from the plurality of first object nodes in step S103 to form a decision group includes:
and step S1031, acquiring the completion times of the vehicle-mounted task and the completion satisfaction degree of the vehicle-mounted task of each first object node in the plurality of first object nodes.
And S1032, sequencing the plurality of first object nodes according to the completion times of the vehicle-mounted tasks and the completion satisfaction degree of the vehicle-mounted tasks to obtain a sequencing result.
Step S1033, a certain number of first object node establishment decision groups are selected from the sorting results.
In steps S1031, S1032, and S1033, in order to select the decision group, the number of times of completing the vehicle-mounted task and the satisfaction degree of completing the vehicle-mounted task of each of the first object nodes are determined, and the two parameters are used as conditions for screening. And then sequencing the first object nodes according to the two parameters to obtain a sequencing result of the first object nodes, wherein the more the completion times of the vehicle-mounted tasks of the first object nodes are or the better the completion satisfaction degree of the vehicle-mounted tasks is, the more the first object nodes are willing to perform task calculation and maintain the safety calculation of the tasks, and it is noted that the score of each first object node can be obtained by quantizing the two parameters and calculating the two parameters with the weight value, and finally the ranking is obtained. And finally, selecting a certain number of first object node establishment decision groups from the sorting results, for example, selecting 5 of 15 object node establishment decision groups to establish the decision groups. It should be noted that the number of member nodes of the decision group is not particularly limited in this example.
Referring to fig. 3, in an embodiment of the application, the selecting, by the member node of the decision group, one second object node from the plurality of second object nodes in step S103 as an allocation object of the target onboard task of the target vehicle includes:
step S1034 is to obtain a load amount of each of the plurality of second object nodes, a communication distance between each of the second object nodes and the target vehicle, and a task cooperation degree between each of the member nodes of the decision group and each of the second object nodes.
In step S1035, voting is performed by the member nodes of the decision group according to the load, the communication distance, and the task cooperation degree, so as to obtain a voting score of each member node for all the second object nodes.
Step S1036, calculating the total score of each object node, averaging the total score according to the number of the voted member nodes to obtain an average score, and selecting a second object node with the highest score from the average scores as an allocation object of the target vehicle-mounted task of the target vehicle.
In the present steps S1034, S1035, and S1036, the member nodes of the decision group need to select a second object node to assist in the calculation of the target on-board task of the target vehicle. In order to implement the selection, first in step S1034, the current load of each second object node, the communication distance between the 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 calculated, in this embodiment, under the condition that two necessary parameters, i.e., the load and the communication distance, are maintained, a parameter, i.e., the task cooperation degree between one member node and the second object node, is added, and when the task cooperation degree is higher, it is proved that the tightness of the task distribution between the member node and the second object node is higher, which also means that the member node is more willing to trust the second object node. It should be noted that the task cooperation degree referred to in this embodiment refers to the number of task assignments between the member node and the second object node and the task assignment satisfaction degree, for example, the number of task assignments between the 5 th roadside unit (member node) and the 5 th second object node is the largest, and the task assignment satisfaction degree is also the highest, so the 5 th roadside unit is more inclined to make the 5 th second object node the object node of the target vehicle. Then, in step S1035, the member nodes in the decision group vote according to three parameters, i.e., the load, the communication distance, and the degree of task cooperation, and referring to fig. 4, the method specifically includes steps S10351 and S10352: step S10351: each member node of the decision group quantizes the load, the communication distance and the task cooperation degree, and sets a corresponding weight coefficient; and each member node of the decision group is provided with the same load, communication distance and weight coefficient of the task cooperation degree. Step S10352: and multiplying each member node of the decision group by the corresponding weight coefficient according to the quantized load capacity, communication distance and task cooperation degree to obtain the voting score of each second object node calculated by each member node. And finally, in step S1036, calculating the total score of each object node, averaging the total scores according to the number of the voted member nodes to obtain an average score, and selecting a second object node with the highest score from the average scores as an allocation object of the target vehicle-mounted task of the target vehicle. It should be noted that when a member node is a roadside unit, it only votes for a second object node that is a vehicle; when the member node is a vehicle, it votes only for the second object node, which is a roadside unit, and will not be described in detail herein.
In one embodiment of the present application, the member nodes of the decision group are periodically reselected. And if the target vehicle moves, periodically reselecting the member nodes of the decision group at regular time, and ensuring that an optimal second object node can be selected for the target vehicle-mounted task of the target vehicle, wherein the selection process is consistent with the process of the step S103. If the vehicle is in a static state and the state of the first object node changes all the time (the completion times of the vehicle-mounted tasks and the completion satisfaction degree of the vehicle-mounted tasks), the member nodes of the decision group are periodically reselected at regular time, so that the member nodes lower than the selection standard can be removed from the decision group, and the first object node reaching the selection standard is selected into the decision group, and therefore the member nodes in the decision group are the nodes which are more willing to execute the calculation of the tasks and maintain the safety calculation of the tasks.
Referring to fig. 5, in an embodiment of the present application, after step S103, the task allocation method of the internet of vehicles further includes:
and step S104, the target vehicle distributes the target vehicle-mounted task to a distribution object to calculate the target vehicle-mounted task.
In order to make the invention more understandable to the person skilled in the art, a short example is listed below:
first, a vehicle V to be assigned an on-board task is located, and all nodes (including vehicle and roadside nodes) within the communication range of the vehicle V are located. Secondly, acquiring the current residual task allocation quantity of all nodes, and dividing all nodes into two types according to the residual task allocation quantity, wherein the first type of nodes are nodes of which the residual task allocation quantity is smaller than the vehicle-mounted task of the vehicle V; the second type of nodes are nodes with the residual task allocation amount larger than the vehicle-mounted tasks of the vehicle V. And secondly, selecting decision group members for decision from all the first-class nodes, namely acquiring the completion times of the vehicle-mounted task and the completion satisfaction degree of the vehicle-mounted task of each first-class node, then performing weight calculation according to the two indexes, counting the scores of all the first-class nodes to obtain a ranking, and selecting the previous first-class nodes as the member nodes of the decision group from the ranking. Then, the member nodes of the decision group select one second class node from all the second class nodes as the distribution object of the vehicle-mounted task of the vehicle V, that is, firstly, the load capacity of each second class node, the communication distance between the member nodes and the vehicle V, and the task cooperation degree between each member node and each second class node are obtained (the task cooperation degree refers to the task distribution frequency between the member nodes and the second class nodes and the task distribution satisfaction degree, it should be noted that a group of member nodes and a group of vehicle and roadside units or a group of roadside units and vehicles that the second class nodes refer to) respectively, then, the weight calculation is performed by using the three parameters, the total score of each member node for each second class node is obtained, then, the average score of each second class node is calculated according to the total score and the number of voted member nodes, and one second class node is selected from the average scores to be used as the distribution object of the vehicle-mounted task of the vehicle V. Finally, the vehicle V assigns the in-vehicle task to the assignment target to perform calculation of the in-vehicle task by the assignment target. It should be noted that, no matter the vehicle V is in a stationary state or in a moving state, the member nodes of the decision group are replaced periodically, and the replacement process is the same as the first selection process.
Referring to fig. 6, an embodiment of the present invention provides a task allocation system for a vehicle networking, where the task allocation system for a vehicle networking includes a vehicle positioning unit 1100, a node selection unit 1200, and an allocation object selection unit 1300, where:
the vehicle locating unit 1100 is used to acquire the location of a target vehicle to which a target on-board task needs to be assigned.
The node selecting unit 1200 is configured to determine, according to the position of the target vehicle, a plurality of first object nodes and a plurality of second object nodes located within a communication range of the target vehicle; the first object node is a vehicle and/or roadside unit of which the remaining task allocation amount is smaller than that of the target vehicle-mounted task, and the second object node is a vehicle and/or roadside unit of which the remaining task allocation amount is larger than that of the target vehicle-mounted task.
The distribution object selecting unit 1300 is configured to select a certain number of first object nodes from the plurality of first object nodes to form a decision group, and select one second object node from the plurality of second object nodes through member nodes of the decision group as a distribution object of a target vehicle-mounted task of the target vehicle.
The system firstly obtains all object nodes in the communication range of a target vehicle, selects a plurality of calculations willing to execute tasks from a plurality of first object nodes of the active nodes willing to execute the vehicle-mounted tasks of the vehicle, and the first object nodes of the nodes willing to maintain the safety calculations of the tasks form decision groups, and then when the member nodes of the decision groups select the object nodes of the target vehicle-mounted tasks of the target vehicle, the member nodes can help to select the second object nodes willing to execute the tasks and maintain the safety calculations of the tasks, so that the calculation safety of the target vehicle-mounted tasks is improved.
It should be noted that the embodiment of the task allocation system of the internet of vehicles and the embodiment of the method described above are based on the same inventive concept, and therefore, the related contents of the embodiment of the method described above are also applicable to the embodiment of the system, and are not described again here.
Referring to fig. 7, the present application further provides a task allocation electronic device of a car networking, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor when executing the computer program implementing: such as the task allocation method of the internet of vehicles.
The processor and memory may be connected by a bus or other means.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. Further, the 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, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The non-transitory software programs and instructions required to implement the task allocation method of the internet of vehicles of the above-described embodiment are stored in the memory, and when executed by the processor, perform the task allocation method of the internet of vehicles of the above-described embodiment, for example, perform the above-described method steps S101 to S103 in fig. 1.
The present application further provides a computer-readable storage medium having stored thereon computer-executable instructions for performing: such as the task allocation method of the internet of vehicles.
The computer-readable storage medium stores computer-executable instructions, which are executed by a processor or controller, for example, by a processor in the above-mentioned electronic device embodiment, and can make the above-mentioned processor execute the task allocation method of the internet of vehicles in the above-mentioned embodiment, for example, execute the above-mentioned method steps S101 to S103 in fig. 1.
It will be understood by those of ordinary skill in the art that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, or suitable combinations thereof. Some or all of the physical components may 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 may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of data such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired data and which can accessed by the computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any data delivery media as known to one of ordinary skill in the art.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (10)
1. The task allocation method of the Internet of vehicles is characterized by comprising the following steps of:
acquiring the position of a target vehicle needing to distribute a target vehicle-mounted task;
determining a plurality of first object nodes and a plurality of second object nodes which are positioned in the communication range of the target vehicle according to the position of the target vehicle; the first object node is a vehicle and/or roadside unit of which the self residual task allocation amount is smaller than the target vehicle-mounted task, and the second object node is a vehicle and/or roadside unit of which the self residual task allocation amount is larger than the target vehicle-mounted task;
and selecting a certain number of first object nodes from the plurality of first object nodes to form a decision group, and selecting one second object node from the plurality of second object nodes through member nodes of the decision group as an allocation object of the target vehicle-mounted task of the target vehicle.
2. The task allocation method of the internet of vehicles according to claim 1, wherein the selecting a certain number of the first object nodes from the plurality of first object nodes to form a decision group comprises:
acquiring the completion times of the vehicle-mounted task and the completion satisfaction degree of the vehicle-mounted task of each first object node in the plurality of first object nodes;
sequencing the plurality of first object nodes according to the completion times of the vehicle-mounted tasks and the completion satisfaction degree of the vehicle-mounted tasks to obtain a sequencing result;
and selecting a certain number of first object node establishment decision groups from the sequencing results.
3. The task allocation method for the internet of vehicles according to claim 2, wherein the selecting one second object node from the plurality of second object nodes by the member node of the decision group as the allocation object of the target on-board task of the target vehicle comprises:
acquiring the load capacity of each second object node in the plurality of second object nodes, the communication distance between each second object node and the target vehicle, and the task cooperation degree of each member node of the decision group and each second object node respectively;
voting through member nodes of the decision group according to the load, the communication distance and the task cooperation degree to obtain a voting score of each member node for all the second object nodes;
and calculating the total score of each object node, averaging the total scores according to the number of the voted member nodes to obtain average scores, and selecting the second object node with the highest score from the average scores as an allocation object of the target vehicle-mounted task of the target vehicle.
4. The method for task allocation in the internet of vehicles according to claim 3, wherein the degree of task cooperation at least includes the number of task allocations between the member node and the second object node.
5. The task allocation method of the internet of vehicles according to any one of claims 3 or 4, wherein the voting by the member nodes of the decision group according to the load amount, the communication distance and the task cooperation degree to obtain the voting score of each member node for all the second object nodes comprises:
each member node of the decision group quantizes the load, the communication distance and the task cooperation degree, and sets a corresponding weight coefficient; wherein, the weight coefficients of the load, the communication distance and the task cooperation degree set by each member node of the decision group are the same;
and multiplying each member node of the decision group by a corresponding weight coefficient according to the quantized load, the communication distance and the task cooperation degree to obtain the voting score of each member node for calculating each second object node.
6. The vehicle networking task distribution method according to claim 2, wherein the member nodes of the decision group are periodically reselected.
7. The task allocation method for the internet of vehicles according to claim 1, wherein after selecting the allocation object of the target on-board task of the target vehicle, the task allocation method for the internet of vehicles further comprises:
and the target vehicle distributes the target vehicle-mounted task to the distribution object to calculate the target vehicle-mounted task.
8. A task distribution system of a vehicle networking, characterized in that the task distribution system of the vehicle networking comprises:
the vehicle positioning unit is used for acquiring the position of a target vehicle needing to distribute a target vehicle-mounted task;
the node selection unit is used for determining a plurality of first object nodes and a plurality of second object nodes which are positioned in the communication range of the target vehicle according to the position of the target vehicle; the first object node is a vehicle and/or roadside unit of which the self residual task allocation amount is smaller than the target vehicle-mounted task, and the second object node is a vehicle and/or roadside unit of which the self residual task allocation amount is larger than the target vehicle-mounted task;
and the distribution object selection unit is used for selecting a certain number of first object nodes from the plurality of first object nodes to form a decision group, and selecting one second object node from the plurality of second object nodes through member nodes of the decision group as a distribution object of the target vehicle-mounted task of the target vehicle.
9. The utility model provides a task distribution electronic equipment of car networking which characterized in that: comprises at least one control processor and a memory for communicative connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the method of car networking task allocation of any of claims 1 to 7.
10. A computer-readable storage medium characterized by: the computer-readable storage medium stores computer-executable instructions for causing a computer to perform the method for task allocation of the internet of vehicles according to any one of claims 1 to 7.
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