Scheduling optimization method and device, electronic equipment and storage medium
An optimization method and technology of electronic equipment, applied in the direction of mechanical equipment, multi-programming device, neural learning method, etc., can solve the problem of low scheduling optimization efficiency
Active Publication Date: 2021-11-19
HANGZHOU INNOVATION RES INST OF BEIJING UNIV OF AERONAUTICS & ASTRONAUTICS
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[0003] However, the inventors have found that in the prior art, all tasks are either executed locally on the mobile device, or are all dispatched to the UAV or the base station for remote execution, so there is a problem of low scheduling optimization efficiency
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[0051]Due to the high mobility and flexibility of UAVs (Unmanned Aerial Vehicles, UAVs), in recent years, researchers have established communication relationships with mobile devices (MobileDevices, MDs) of users by deploying related wireless communication nodes on UAVs. , proposed the technology of using drones to assist Mobile Edge Computing (MEC) in various application scenarios. When the network infrastructure is unavailable (such as a natural disaster rescue site), network equipment is sparsely distributed (such as a field operation environment), or when faced with a temporary surge of mobile devices that far exceeds the network service capacity (such as a large game or assembly), UAVs can be used as communication relay stations or edge computing platforms. After the computing resources are deployed by drones, the drone-assisted mobile edge computing network will bring many advantages, such as reducing network overhead, reducing computing task execution latency, better qu...
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The scheduling optimization method and device, electronic equipment, and storage medium provided in the embodiments of the present application relate to the technical field of scheduling optimization. The scheduling optimization method is applied to electronic equipment, and the electronic equipment is connected to the mobile edge computing network system. The mobile edge computing network system includes at least one base station, unmanned aerial vehicle, and mobile device. The scheduling optimization method includes: first, obtaining at least one mobile device The task to be processed and the current location information; secondly, the task to be processed and the current location information are input into a preset scheduling optimization model to obtain a scheduling strategy; then, the scheduling strategy is sent to at least one mobile device. Through the above method, the first task can be dispatched to the UAV for processing, and the second task can be dispatched to the base station for processing, which avoids that in the prior art, all tasks are either executed locally on the mobile device or are all dispatched to the UAV. Or remote execution on the base station, resulting in the problem of low efficiency of scheduling optimization.
Description
technical field [0001] The present application relates to the technical field of scheduling optimization, and in particular, to a scheduling optimization method and device, electronic equipment, and a storage medium. Background technique [0002] In the field of UAV-assisted mobile edge computing, it is necessary to properly determine the scheduling of UAV computing tasks in the mobile edge computing network (whether the computing task is executed locally on the mobile device or dispatched to the UAV or base station). decision to obtain desired performance. [0003] However, the inventors have found that in the prior art, all tasks are either executed locally on the mobile device, or all tasks are dispatched to drones or base stations for remote execution, so there is a problem of low scheduling optimization efficiency. Contents of the invention [0004] In view of this, the purpose of the present application is to provide a scheduling optimization method and device, elec...
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IPC IPC(8): G06F9/48G06F9/50G06K9/62G06N3/04G06N3/08
CPCG06F9/4881G06F9/5027G06F9/5072G06N3/08G06N3/044G06F18/23G06F18/214Y02T10/40
Inventor 任涛胡哲源谷宁波牛建伟胡舒程李青锋
Owner HANGZHOU INNOVATION RES INST OF BEIJING UNIV OF AERONAUTICS & ASTRONAUTICS