CN115988462A - Debugging method of edge computing module based on vehicle-road cooperation - Google Patents
Debugging method of edge computing module based on vehicle-road cooperation Download PDFInfo
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Abstract
The embodiment of the invention provides a debugging method of an edge computing module based on vehicle-road cooperation, which comprises the following steps: the edge computing network counts the number of roadside units, service equipment and vehicle resources; when a required vehicle enters a base station signal coverage range, a calculation task is automatically generated in real time and is segmented, and the required vehicle can be finished locally by using a vehicle-mounted unit or unloaded to an MEC server for processing; the MEC server calculates the estimated load rate when processing the calculation task, and judges whether the estimated load rate immediately executes the calculation task; the sub-calculation task communication divided by the MEC server is sent to the task vehicle; after the task vehicle receives the sub-calculation task, a calculation assistance request is sent to the service equipment; and after the task vehicle finishes the distributed sub-calculation tasks, the finished calculation tasks are sent to the MEC server, and the MEC server sends the calculation results back to the demand vehicle through the service equipment.
Description
Technical Field
The invention relates to the technical field of edge computing, in particular to a debugging method of an edge computing module based on vehicle-road cooperation.
Background
With the continuous development of the internet of vehicles, a plurality of vehicle-road collaborative demonstration areas are deployed and verified in China, and become an indispensable important part for building intelligent cities. Because the vehicles in different regions are distributed differently, the task amount and the data access times of the MEC servers in different regions are different, which easily causes the waste of computing resources or computation overload of the MEC servers;
at present, the related technology related to edge calculation is not reflected in the high efficiency and the expansibility of distributed algorithm solution, and modeling cannot be performed in a dynamically changing edge calculation scene.
Disclosure of Invention
A debugging method of an edge computing module based on vehicle-road cooperation comprises the following steps:
initializing an MEC server, and counting the number of roadside units and vehicle resources;
step two, generating a calculation task, and processing the generated calculation task through a local vehicle-mounted unit or unloading the calculation task to an MEC server for processing;
step three, if the calculation task is selected to be unloaded to the MEC server, setting a weight value, calculating a predicted load rate, and judging whether the calculation task is executed immediately;
step four, if the MEC server judges that the estimated load rate L does not exceed the bearing range, the MEC server sends the sub-calculation task communication to the task vehicle;
step five, setting the service vehicles and the roadside units as service equipment, and determining the number of task vehicles needing to provide services;
step six, matching the determined task vehicle with the service equipment, and generating a task unloading scheme;
step seven, judging whether the local computing resources can complete the sub-computing tasks within the ending time, and sending a computing assistance request to the service equipment according to the judgment result;
step eight, the task vehicle completes the sub-calculation tasks and sends the sub-calculation tasks to the MEC server, and the MEC server sends the uncompleted sub-calculation tasks to the task vehicle;
step nine, after all the sub-calculation tasks are completed, integrating and sending the sub-calculation tasks to the service equipment, and sending the calculation task results to the demand vehicle by the service unit;
the MEC server performs data sharing with the demand vehicles parked within the base station signal coverage.
Further, the vehicle resource in the first step:
the vehicle resources comprise service vehicles in an idle state and task vehicles which receive and process tasks from the MEC server;
the service vehicle represents one or more vehicles providing services for task vehicles, and the services comprise data transmission and sharing calculation tasks;
the task vehicle is a vehicle which receives the computing task from the MEC server, processes the received computing task and sends the processed computing task back to the MEC server.
Further, the step three of determining whether the MEC server immediately executes the computing task process includes:
if the vehicle in need chooses to unload the calculation task to the MEC server, the MEC server sets a weight value for the calculation task according to the maximum cut-off completion time, calculates the estimated load rate when processing the calculation task, judges whether the estimated load rate exceeds the bearing range, and judges whether to execute the calculation task immediately according to the result.
Further, the task offloading scheme includes:
based on the task vehicles matched with the service equipment, after the task vehicles complete the distributed sub-calculation tasks, sending task unloading requests to the MEC server, and receiving and responding the task unloading requests by the MEC server;
when the task vehicle exceeds the coverage range of the base station signal at the moment, the MEC server communicates with a service vehicle in an idle state or a roadside unit in the idle state in the coverage range of the base station signal, the completed calculation task is sent to the service vehicle or the roadside unit, and the service vehicle or the roadside unit returns the calculation task to the required vehicle.
Further, the execution process of the sub-computing task comprises:
after the task vehicle receives the sub-computation task, whether the sub-computation task can be completed within the ending completion time is analyzed based on local computation resources of the task vehicle, and if the sub-computation task cannot be completed within the ending completion time, a computation assistance request is sent to the service equipment;
after the service equipment responds to the request, the task vehicle divides the sub-calculation task into a plurality of sub-task units, and sends the sub-task units which can not be in the ending completion time to the service vehicle in the idle state in the service equipment;
and after the task vehicle and the service vehicle complete all the subtask units within the task deadline, the task vehicle integrates the sub-calculation tasks and sends the sub-calculation tasks to the MEC server.
Further, the process of allocating the task to the task vehicle by the MEC server includes:
after the task vehicle completes the distributed sub-computation tasks with the help of the service equipment, the completed sub-computation tasks are sent to the MEC server according to the task unloading scheme, and the MEC server receives and sends the uncompleted sub-computation tasks to the task vehicle;
and the MEC server calculates the residual deadline according to the maximum deadline completion time and the task execution time, and updates the weight of the corresponding calculation task in real time based on the number of the remaining sub-calculation tasks of the calculation task.
Further, the process of sending the calculation result to the demand vehicle by the MEC server includes:
after detecting that all sub-calculation tasks of one calculation task are completed, the MEC server integrates the calculation task results and detects whether a required vehicle is in a base station signal range;
and if the signal is not in the base station signal range, executing a task unloading scheme, sending the calculation task result to a service vehicle in an idle state or a roadside unit in the idle state in the base station signal coverage range, and sending the calculation task result to the required vehicle by the service vehicle or the roadside unit.
Further, the process of sharing data with the demand vehicle by the MEC server includes:
the MEC server acquires a credit value of a corresponding demand vehicle according to the demand vehicle information, sets a credit value threshold value, judges whether the credit value of the demand vehicle is higher than the credit value threshold value, and sends a data sharing request to the demand vehicle according to a judgment result;
after the demand vehicles respond to the requests, the data to be shared are sent to the roadside units, the roadside units receive the shared data of the demand vehicles in the set number and then upload the shared data to the MEC server in a unified mode, the MEC server compares the shared data of the demand vehicles, and the reputation value of the corresponding demand vehicle is updated by judging the correctness of the shared data.
Further, the shared data comprises weather conditions, traffic conditions and road conditions in the driving process before the vehicle is required to enter the coverage area of the base station signal.
Compared with the prior art, the invention has the beneficial effects that:
the method fully considers the real-time running state of the edge computing MEC server, judges the load rate by computing the disk I/O read-write rate, the memory capacity and the bandwidth occupancy rate of the MEC server, effectively improves the utilization rate of computing resources of the MEC server, and shortens the time for completing computing tasks to a certain extent;
the method also considers the communication state of the vehicle in high-speed movement, aims to minimize task calculation delay, and realizes the optimization and inclination of the MEC server to the calculation resource distribution by setting weight values for the calculation tasks.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for debugging an edge computing module based on vehicle-road coordination, where the method may include the following steps:
initializing each MEC server, and counting roadside units and vehicle resources by an edge computing network, wherein the vehicle resources comprise service vehicles in an idle state and task vehicles for receiving and processing tasks from the MEC servers;
it should be noted that the service vehicle represents a vehicle for providing services by one or more task vehicles, and the services include data transmission and sharing calculation tasks; the task vehicle is a vehicle which receives the tasks from the MEC server, processes and classifies the received tasks and sends the tasks back to the MEC server.
Step two, automatically generating a calculation task when a required vehicle enters a base station signal coverage area, dividing the calculation task into one or a plurality of sub-calculation tasks, and setting a maximum cut-off completion time, wherein the required vehicle can be completed locally by using a vehicle-mounted unit or unloaded to an MEC server for processing;
optionally, when the demand vehicle is parked in the coverage range of the base station signal, the MEC server may send a request to the demand vehicle, and after the demand vehicle responds to the request, the MEC server may define the demand vehicle as a service vehicle, thereby relieving the computing pressure of the MEC server to a certain extent and improving the utilization rate of computing resources.
Step three, if the vehicle in need chooses to unload the calculation task to the MEC server, the MEC server sets a weight value for the calculation task according to the maximum cut-off completion time, calculates the predicted load rate L when processing the calculation task, judges whether the predicted load rate L exceeds the bearing range, and judges whether to execute the calculation task immediately according to the result;
it should be further noted that the predicted load factor calculation formula is as follows:
L=α cpu β cpu +α i/o β i/o +α men β men +α band β band ；
wherein beta is cpu 、β i/o 、β men 、β band Respectively representing CPU processing rate, disk I/O rate, memory utilization rate, bandwidth occupancy rate, alpha of MEC server cpu 、α i/o 、α men 、α band Respectively represent the weights of the corresponding indexes, and alpha cpu +α i/o +α men +α band =1。
And step four, if the MEC server judges that the estimated load rate L does not exceed the bearing range, the segmented sub-calculation task communication is sent to the task vehicles, and meanwhile, the deadline completion time is set for each task vehicle.
And step five, using the service vehicles and the roadside units as service equipment, and determining the number of task vehicles needing to provide services according to the service conditions of the service vehicles and the roadside units.
Step six, matching the task vehicle determined in the step five with the service equipment, and generating a task unloading scheme;
the task offloading scheme includes: based on the task vehicles matched with the service equipment, after the task vehicles complete the distributed sub-computing tasks, task unloading requests are sent to the MEC server, and the MEC server receives and responds to the task unloading requests; if the task vehicle exceeds the coverage range of the base station signal at the moment, the MEC server communicates with a service vehicle in an idle state or a roadside unit in the idle state in the coverage range of the base station signal, the completed calculation task is sent to the service vehicle or the roadside unit, and the service vehicle or the roadside unit returns the calculation task to the required vehicle.
Step seven, after the task vehicle receives the sub-computation task, whether the sub-computation task can be completed within the ending completion time is analyzed based on the local computation resource of the task vehicle, and if the sub-computation task cannot be completed within the ending completion time, a computation assistance request is sent to the service equipment;
after the service equipment responds to the request, the task vehicle divides the sub-calculation task into a plurality of sub-task units, and sends the sub-task units which can not be in the ending completion time to the service vehicle in the idle state in the service equipment;
it should be noted that if the service vehicle detects a subtask unit that cannot be allocated within the task deadline, the task vehicle requests the service device to allocate a service vehicle again until the service vehicle detects a subtask unit that can be allocated within the task deadline;
and after the task vehicle and the service vehicle complete all the subtask units within the task deadline time, the task vehicle integrates the sub-calculation tasks.
Step eight, after the task vehicle completes the distributed sub-computation tasks with the help of the service equipment, the completed sub-computation tasks are sent to the MEC server according to the task unloading scheme, and the MEC server receives and sends the uncompleted sub-computation tasks to the task vehicle;
further, the MEC server calculates the remaining deadline according to the maximum deadline completion time and the task execution time, and updates the weight of the corresponding calculation task in real time based on the number of the remaining sub-calculation tasks of the calculation task, wherein the calculation formula is as follows:
W=T maximum of /(T Maximum of -t To carry out )+S Remainder of /r Free up ；
Where W denotes the weight of the computational task, T Maximum of Represents the maximum deadline completion time, t, of the computational task To proceed with Indicating the time that the computing task has been performed, S Remainder of Indicating that the computing task has not completed the sub-computing task, r Free up Indicating a task vehicle currently in an idle state;
and when the vehicle with the task uploads the completed sub-calculation tasks, the MEC server updates all the calculation task weights mounted at present in real time, and preferentially distributes the sub-calculation tasks of the calculation tasks with high calculation weights.
Step nine, after detecting that all sub-calculation tasks of one calculation task are completed, the MEC server integrates calculation task results and detects whether a required vehicle is in a base station signal range;
and if the signal is not in the base station signal range, executing a task unloading scheme, sending the calculation task result to a service vehicle in an idle state or a roadside unit in the idle state in the base station signal coverage range, and sending the calculation task result to the required vehicle by the service vehicle or the roadside unit.
When the demand vehicle is in a high-speed moving state, network topology dynamic change can be generated between the demand vehicle and the MEC server, the transmission efficiency and energy consumption between the demand vehicle and the MEC server can be influenced by the network topology dynamic change, the MEC server sends the calculation task result to a service vehicle or a roadside unit in an idle state covered by a base station signal, and the calculation task result is sent to the task vehicle.
Optionally, after the demand vehicle finishes uploading the calculation task, the MEC server obtains a credit value of the corresponding information vehicle according to the demand vehicle information, sets a credit value threshold, judges whether the credit value of the demand vehicle is higher than the credit value threshold, and sends a data sharing request to the demand vehicle according to the judgment result;
after the demand vehicles respond to the requests, the data to be shared are sent to the roadside units, the roadside units receive the shared data of the demand vehicles in a set number and then upload the shared data to the MEC server in a unified mode, the MEC server compares the shared data of the demand vehicles and judges the correctness of the shared data, for the judged correct shared data, the MEC server improves the credit values of the corresponding demand vehicles, and for the judged wrong shared data, the MEC server reduces the credit values of the corresponding vehicles;
for a demand vehicle with a negative credit value, the MEC server sets the demand vehicle into a sharing blacklist, and for the sharing vehicle entering the sharing blacklist, when the sharing vehicle enters the coverage range of the base station signal again, the MEC server does not send a shared data request to the sharing vehicle;
the shared data comprises weather conditions, traffic conditions and road conditions in the driving process before the required vehicle enters the coverage range of the base station signal;
optionally, the equation for updating the reputation value of the demand vehicle by the MEC server is as follows:
T j =b j +γ；
wherein T is j Represents the final reputation value of the demand vehicle j, b j For the current reputation value of the demand vehicle j, gamma represents an uncertainty coefficient, gamma belongs to (-1, 1), u j Represents the trust level, u, of the MEC server to the demand vehicle j j The calculation formula is as follows:
u j =（1-U j ) α/(β + α) or u j =（1-U j ）β/（β+α）；
Wherein U is j Representing the current trust degree of the MEC server to the demand vehicle j, wherein alpha represents the positive sharing times, and beta represents the negative sharing times;
the MEC server judges whether the demand vehicles can share data or not by adopting the credit values, and obtains the weather conditions, traffic conditions and road conditions of the driving roads through the shared data of the demand vehicles, so that the detection cost is reduced, and the data correctness is high.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the present invention.
Claims (9)
1. A debugging method of an edge computing module based on vehicle-road cooperation is characterized by comprising the following steps:
initializing an MEC server, and counting the number of roadside units and vehicle resources;
step two, generating a calculation task, and processing the generated calculation task through a local vehicle-mounted unit or unloading the calculation task to an MEC server for processing;
step three, if the calculation task is selected to be unloaded to the MEC server, setting a weight value, calculating a predicted load rate, and judging whether to immediately execute the calculation task;
step four, if the MEC server judges that the predicted load rate L does not exceed the bearing range, the sub-calculation task communication is sent to the task vehicle;
step five, setting the service vehicles and the roadside units as service equipment, and determining the number of task vehicles needing to provide services;
step six, matching the determined task vehicle with the service equipment, and generating a task unloading scheme;
step seven, judging whether the local computing resources can complete the sub-computing tasks within the ending completion time, and sending a computing assistance request to the service equipment according to the judgment result;
step eight, the task vehicle completes the sub-calculation tasks and sends the sub-calculation tasks to the MEC server, and the MEC server sends the incomplete sub-calculation tasks to the task vehicle;
step nine, after all the sub-calculation tasks are completed, integrating and sending the sub-calculation tasks to the service equipment, and sending the calculation task results to the demand vehicle by the service unit;
the MEC server performs data sharing with the demand vehicles parked within the base station signal coverage.
2. The method for debugging the edge computing module based on vehicle-road coordination according to claim 1, wherein the vehicle resource in the first step:
the vehicle resources comprise service vehicles in an idle state and task vehicles which receive and process tasks from the MEC server;
the service vehicle represents a vehicle which provides services for one or more task vehicles, and the services comprise data transmission and sharing calculation tasks;
the task vehicle is a vehicle which receives the computing task from the MEC server, processes the received computing task and sends the processed computing task back to the MEC server.
3. The debugging method of the edge computing module based on vehicle-road coordination according to claim 1, wherein the judging process of the MEC server on whether to immediately execute the computing task comprises:
if the vehicles in need choose to unload the calculation task to the MEC server, the MEC server sets a weight value for the calculation task according to the maximum cut-off completion time, calculates the estimated load rate when the calculation task is processed, judges whether the estimated load rate exceeds the bearing range, and judges whether the calculation task is executed immediately according to the result.
4. The debugging method of the edge computing module based on vehicle-road coordination according to claim 1, wherein the task unloading scheme comprises:
based on the task vehicles matched with the service equipment, after the task vehicles complete the distributed sub-calculation tasks, sending task unloading requests to the MEC server, and receiving and responding the task unloading requests by the MEC server;
when the task vehicle exceeds the coverage range of the base station signal at the moment, the MEC server communicates with a service vehicle in an idle state or a roadside unit in the idle state in the coverage range of the base station signal, the completed calculation task is sent to the service vehicle or the roadside unit, and the service vehicle or the roadside unit returns the calculation task to the required vehicle.
5. The debugging method of the edge computing module based on vehicle-road coordination according to claim 2, wherein the execution process of the sub-computing task comprises:
after the task vehicle receives the sub-computation task, whether the sub-computation task can be completed within the ending completion time is analyzed based on local computation resources of the task vehicle, and if the sub-computation task cannot be completed within the ending completion time, a computation assistance request is sent to the service equipment;
after the service equipment responds to the request, the task vehicle divides the sub-calculation task into a plurality of sub-task units, and sends the sub-task units which cannot be in the ending completion time to the service vehicle in an idle state in the service equipment;
and after the task vehicle and the service vehicle complete all the subtask units within the task deadline, the task vehicle integrates the sub-calculation tasks and sends the sub-calculation tasks to the MEC server.
6. The debugging method of the edge computing module based on vehicle-road coordination according to claim 5, wherein the process of task allocation of the MEC server to the task vehicle comprises:
after the task vehicle completes the distributed sub-computation tasks with the help of the service equipment, the completed sub-computation tasks are sent to the MEC server according to the task unloading scheme, and the MEC server receives and sends the uncompleted sub-computation tasks to the task vehicle;
and the MEC server calculates the residual deadline time according to the maximum deadline completion time and the task execution time, and updates the weight of the corresponding calculation task in real time based on the number of the sub-calculation tasks remaining in the calculation task.
7. The debugging method of the edge computing module based on vehicle-road coordination according to claim 1, wherein the process of sending the computing result back to the demand vehicle by the MEC server comprises:
after detecting that all sub-calculation tasks of one calculation task are completed, the MEC server integrates the calculation task results and detects whether a required vehicle is in a base station signal range;
and if the signal is not in the base station signal range, executing a task unloading scheme, sending the calculation task result to a service vehicle in an idle state or a roadside unit in the idle state in the base station signal coverage range, and sending the calculation task result to the required vehicle by the service vehicle or the roadside unit.
8. The debugging method of the edge computing module based on vehicle-road coordination according to claim 1, wherein the process of sharing data between the MEC server and the demand vehicle comprises:
the MEC server acquires a credit value of a corresponding demand vehicle according to the demand vehicle information, sets a credit value threshold value, judges whether the credit value of the demand vehicle is higher than the credit value threshold value, and sends a data sharing request to the demand vehicle according to a judgment result;
after the demand vehicles respond to the requests, the data to be shared are sent to the roadside units, the roadside units receive the shared data of the demand vehicles in the set number and then upload the shared data to the MEC server in a unified mode, the MEC server compares the shared data of the demand vehicles, and the reputation value of the corresponding demand vehicle is updated by judging the correctness of the shared data.
9. The method as claimed in claim 8, wherein the shared data includes weather conditions, traffic conditions, and road conditions during driving before the vehicle enters the coverage area of the base station signal.
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