CN113950059A - Method and system for assisting user task unloading through unmanned aerial vehicle relay - Google Patents
Method and system for assisting user task unloading through unmanned aerial vehicle relay Download PDFInfo
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Abstract
The invention discloses a method and a system for assisting user task unloading by unmanned aerial vehicle relay.A method for unloading determines unmanned aerial vehicle relay and unloading proportion of all users for task unloading according to a game theory method so as to minimize the total time delay of the system, wherein the users unload tasks to the unmanned aerial vehicle relay according to the unloading proportion, and the unmanned aerial vehicle relay unloads the tasks to a base station for execution; tasks not offloaded to the drone relay are executed locally by the user; the method of the invention can reduce the calculation delay caused by the completion of a large number of tasks by the user, ensure the timeliness of the communication network by minimizing the total delay of the system, obtain the optimal user unloading strategy and improve the utilization rate of resources.
Description
Technical Field
The invention relates to a method and a system for user task unloading.
Background
Mobile Edge Computing (MEC) is an effective means to alleviate the contradiction between resource-limited user equipment and compute-intensive applications, and in MEC, task offloading is a main approach to solve the problem of resource limitation of a mobile terminal. However, moving edge computation also faces a number of technical challenges. On the one hand, this technique is susceptible to propagation delay and path loss; on the other hand, when the infrastructure is damaged, especially in emergency scenarios, the mobile edge computing technique does not work effectively. The moving edge calculation under the cooperation of Unmanned Aerial Vehicles (UAVs) can better cope with the challenges, and make up for the deficiency of MECs in emergency scenes. At present, most of research aiming at the edge technology of the unmanned aerial vehicle only focuses on the condition that the unmanned aerial vehicle is used as an edge server, and the calculation resource and energy of the unmanned aerial vehicle are very limited, so that the timeliness of the unloading task of a user is not strong, and the resource utilization rate is to be improved.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a method and a system for assisting user task unloading by unmanned aerial vehicle relay, which solve the problem that the user task cannot be directly unloaded to a base station due to long distance and many ground obstacles, reduce the time delay of processing the task and improve the utilization rate of computing resources.
The technical scheme is as follows: the invention relates to a method for assisting user task unloading by unmanned aerial vehicle relay, which comprises the following steps:
(1) initializing a mobile user, an unmanned aerial vehicle relay and a base station, and establishing communication;
(2) determining the relay and unloading proportion of the unmanned aerial vehicle for unloading tasks by all users by using a game theory method to ensure that the total time delay of the system is minimum, wherein the unloading proportion of the user k to the unmanned aerial vehicle m is as follows:
wherein IkInput data size for task, CkNumber of CPU cycles required to complete a task, Rk,mData transfer rate, R, relayed for user and dronek,mFor data transmission rate, f, between the unmanned aerial vehicle relay and the base stationkCalculating the frequency, rho, for the CPUk,m∈[0,1]；
(3) The user unloads the tasks to the unmanned aerial vehicle relay according to the unloading proportion, and the unmanned aerial vehicle relay unloads the tasks to the base station for execution; tasks that are not offloaded to the drone relay are performed locally by the user.
Further, the method for determining the relay and unloading proportion of the unmanned aerial vehicle for task unloading of all users in the step (2) comprises the following steps: setting an initial strategy to select the nearest unmanned aerial vehicle relay for each user to unload the task, circulating by using a game theory method until the total time delay of the system is not reduced any more, and updating the unloading strategy of one user in each circulation.
Further, in the step (2), at most one unmanned aerial vehicle relay is selected by each user for task unloading, the number of users which can be served by each unmanned aerial vehicle relay is not more than K, and K is the number of users.
The invention relates to an unmanned aerial vehicle relay auxiliary user task unloading system, which comprises:
the node module comprises a user, an unmanned aerial vehicle relay and a base station;
the initialization module is used for establishing communication between nodes;
the decision module is used for calculating the relay and unloading proportion of the unmanned aerial vehicle for unloading tasks of all users by using a game theory method so as to minimize the total time delay of the system, and the unloading proportion of the user k to the unmanned aerial vehicle m is as follows:
and the task forwarding module is used for unloading the tasks of the users to the unmanned aerial vehicle relay in proportion, the unmanned aerial vehicle relay unloads the tasks to the base station for execution, and the tasks which are not unloaded are executed locally by the users.
Has the advantages that: compared with the prior art, the invention has the advantages that: the network timeliness is strong, and the resource utilization rate is high; the local user unloads the task part to the unmanned aerial vehicle and forwards the task part to the base station, the computing resources of the base station are fully utilized, meanwhile, the optimal unloading strategy and the unloading proportion are determined based on a game theory method, and the total time delay of the system is minimized to ensure the timeliness of the communication network.
Drawings
Fig. 1 is a network model diagram of unmanned aerial vehicle relay assisted user task offloading of the present invention;
FIG. 2 is a three-dimensional graph of the unmanned aerial vehicle relay assisted user task offloading of the present invention;
fig. 3 is a flowchart of a method for determining an optimal user offload policy according to the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
The invention relates to a method for assisting user task unloading by unmanned aerial vehicle relay, which comprises the following steps:
the method comprises the following steps: establishing user task offloading scenarios
As shown in fig. 1, an unmanned aerial vehicle relay assisted mobile user offloading network model is established, the system includes K mobile users, M unmanned aerial vehicles and 1 base station, and K and M take any positive integer as a value. In order to reduce the computation delay caused by the completion of a large number of tasks by the user, the user can optionally unload part of the tasks to the unmanned aerial vehicle and indirectly forward the part to the remote base station for processing.
As shown in fig. 2, assuming that the base station is located on the ground, the height h is 0, and the location coordinate B is fixed and is (0,0,0), the sets of ground users and drones can be represented as K ═ 1, …, K } and M ═ 1, …, M }, respectively. Considering a three-dimensional Cartesian coordinate system, assuming the position coordinates of a ground user K e {1, K } as uk＝(xk,yk0), the position coordinate of the unmanned plane M e {1, M } is qm＝(xm,ym,hm). To efficiently utilize resources of a server and avoid multiple usersAnd interference is generated among a plurality of unmanned aerial vehicles, and a time division multiple access transmission protocol can be adopted.
Step two: establishing communication
The communication modes between the user and the unmanned aerial vehicle, between the unmanned aerial vehicle and the base station are allLine-of-sight communication(line of sight, LOS), then the channel gains between user k and drone m, drone m and base station are respectively expressed as:
wherein h ismIs the flying height of unmanned plane m, hm＝10m；g0The channel gain when the reference distance d is 1m is a random number that follows a rayleigh distribution. dk,mAnd dmRespectively representing the horizontal distance between user k and drone m and the horizontal distance between drone m and the base station, dk,mThe value is 100-1000m, dmThe value is 1000-1500 m. According to shannon's formula, the data transmission rates of user k and drone m can be expressed as:
where B denotes the network bandwidth, B1 MHz, PkAnd PmRespectively representing the transmission power, P, of user k and drone mkThe value is 0.1-0.2 w, PmThe value is 0.5-1w, sigma2The expression noise power is a random number following a gaussian distribution.
Step three: computing time delay in task offloading
Assuming per userTasks are represented as doublets (I)k,Ck) The size of the task input data and the number of CPU cycles required to complete the task are represented, respectively. I iskThe value is 20-200KB, CkThe value is 1000-5000 Mcyles.
Definition of xk,mRepresents the offloading policy between user k and drone m, xk,mRepresenting that user k offloads the task part to drone m by 1, and conversely xk,m0 means that user k has not selected drone m. Each drone may serve multiple users, each user being served by at most one drone. Definition of pk,m∈[0，1]The proportion of tasks offloaded to drone m for user k.
Generally, the processing process of the task comprises local processing of the user, task unloading and returning of a calculation result. Because the intensive computing task produces very small data results, the latency consumed by the return is negligible compared to the amount of input data. Next, the time delay in the task offloading process is calculated.
(1) Local computation of process delay
Defining the cpu calculation frequency of user k as fk，fk300MHz, the locally calculated delay for the kth user is expressed as:
(2) user transmission process delay
The unmanned aerial vehicle is used as an aerial relay to provide a function of forwarding tasks to the base station for the user, on the assumption that the transmission loss is large due to more ground obstacles and the long distance between the user and the base station. The time delay generated by the process of forwarding the user k to the unmanned plane m is represented as:
(3) unmanned aerial vehicle transmission process time delay
After the unmanned aerial vehicle m receives the task from the user k, the unmanned aerial vehicle directly forwards the task to the base station without considering the computing capability of the unmanned aerial vehicle. At this time, the time delay generated when the unmanned aerial vehicle m unloads the task to the base station can be respectively expressed as:
since the rate processing of the base station is large, the time for the processing task is negligible.
Step four: calculating total time delay of system
Setting that each user runs a calculation task, wherein the tasks are divided into two parts to be executed, one part is executed locally by the mobile user, namely calculation is carried out by the own calculation capability of the mobile user, and the other part is unloaded to a remote base station to be executed through the relay of an unmanned aerial vehicle. In this process, the total latency can be expressed as the maximum of both the locally performed latency and the relay forwarding latency, since both occur simultaneously.
The total delay minimization problem can be expressed as:
in the formula (8), the first constraint condition indicates that the task unloading proportion of the user is [0,1 ]; the second constraint indicates that each user is served by at most one drone; a third constraint indicates that each drone may serve multiple users.
Step five: solving optimal user offload policies
In the embodiment, a game theory method is adopted to obtain the optimal unloading strategy. As shown in fig. 3, the specific implementation method is as follows:
(1) initialization: each parameter of the system; initial offload policy set for user (a)k,a-k) Setting an initial strategy to select the unmanned aerial vehicle relay closest to the user for each user; global time delay T (a) based on initial strategyk,a-k) (ii) a Policy update set
Computing a set of time updates
(2) In the current unloading strategy, each user calculates the unloading proportion and the system time delay of the relay to the unmanned aerial vehicle, further calculates the total system time delay of K users, and stores the total system time delay into the global time delay T (a)k,a-k)；
(3) And circulating according to the game theory method, judging whether the total time delay of the system is the minimum value in the set T in each circulation, and if the total time delay of the system is the minimum value, updating the unloading strategy of the circulation to a strategy updating set D.
The offload policy of one and only one user can be updated, and the offload policies of other users remain unchanged in this iteration.
(4) And (4) repeating the steps (2) and (3) until the current unloading strategy is not changed.
(5) And outputting the unloading strategy at the moment, and unloading the task by the user according to the strategy.
In the step (2), the calculation method of the unloading ratio is as follows:
assuming that the offloading decision of all current users is determined, the optimal offloading ratio ρ isk,mWill be determined by the distance d between the user k and the selected UAV mk,mAnd the distance d between the unmanned aerial vehicle m and the base stationmAnd (6) determining. After the user selects the unmanned aerial vehicle, the proportion rho of the unloading taskk,mDirectly affecting the total delay of the system.
If and only if
Optimal computation time value of task at the moment
Exists and has a minimum value when the optimal unloading ratio is
Claims (7)
1. A method for assisting user task unloading through unmanned aerial vehicle relay is characterized by comprising the following steps:
(1) initializing a mobile user, an unmanned aerial vehicle relay and a base station, and establishing communication;
(2) determining the relay and unloading proportion of the unmanned aerial vehicle for unloading tasks by all users by using a game theory method to ensure that the total time delay of the system is minimum, wherein the unloading proportion of the user k to the unmanned aerial vehicle m is as follows:
wherein IkInput data size for task, CkNumber of CPU cycles required to complete a task, Rk,mData transfer rate, R, relayed for user and dronek,mFor data transmission rate, f, between the unmanned aerial vehicle relay and the base stationkCalculating the frequency, rho, for the CPUk,m∈[0,1]；
(3) The user unloads the tasks to the unmanned aerial vehicle relay according to the unloading proportion, and the unmanned aerial vehicle relay unloads the tasks to the base station for execution; tasks that are not offloaded to the drone relay are performed locally by the user.
2. The method for assisting user task offloading by unmanned aerial vehicle relay according to claim 1, wherein the method for determining the unmanned aerial vehicle relay and offloading proportion for task offloading by all users in step (2) is: and setting an initial strategy to select the nearest unmanned aerial vehicle relay for each user to unload the task, and circulating by using a game theory method until the total time delay of the system is not reduced any more.
3. The method of unmanned aerial vehicle relay assisted user task offloading of claim 2, wherein the offloading policy for one user is updated in each of the loops.
4. The method for assisting user task offloading via UAV relay according to claim 1, wherein in step (2), at most one UAV relay is selected for task offloading per user, and the number of users that can be served by each UAV relay is not more than K, where K is the number of users.
5. The method for unmanned aerial vehicle relay-assisted user task offloading as claimed in claim 1, wherein the total system latency in step (2) is
Wherein
For the time delay of user k performing the task locally,
the time delay incurred for user k to offload a task to drone relay m,
and (4) relaying the time delay generated by the m unloading task to the base station for the unmanned aerial vehicle.
6. The method for unmanned aerial vehicle relay assisted user task offloading of claim 1, wherein communication between the user and unmanned aerial vehicle relay, and base station in step (1) employs a time division multiple access transmission protocol.
7. An unmanned aerial vehicle relay assists user task uninstallation system which characterized in that includes:
the node module comprises a user, an unmanned aerial vehicle relay and a base station;
the initialization module is used for establishing communication between nodes;
the decision module is used for calculating the relay and unloading proportion of the unmanned aerial vehicle for unloading tasks of all users by using a game theory method so as to minimize the total time delay of the system, and the unloading proportion of the user k to the unmanned aerial vehicle m is as follows:
and the task forwarding module is used for unloading the tasks of the users to the unmanned aerial vehicle relay in proportion, the unmanned aerial vehicle relay unloads the tasks to the base station for execution, and the tasks which are not unloaded are executed locally by the users.
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| CN114650567B (en) * | 2022-03-17 | 2024-04-23 | 江苏科技大学 | Unmanned aerial vehicle auxiliary V2I network task unloading method |
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