Unmanned aerial vehicle auxiliary edge calculation unloading method based on terminal energy efficiency optimization

Abstract

The invention discloses an unmanned aerial vehicle auxiliary edge calculation unloading method based on terminal energy efficiency optimization, and the method comprises the steps: jointly optimizingthe task load of local calculation of a user terminal, the task load of calculation unloading and the track of an unmanned aerial vehicle through a global optimization algorithm based on block coordinate descent; the optimization effect on the energy consumption of the user terminal under different channel conditions is discussed, and finally, the unmanned aerial vehicle auxiliary edge calculationmodel taking the minimization of the energy consumption of the user terminal as a target and taking the task load and the time delay demand of the user and the energy of the unmanned aerial vehicle as constraints is constructed. According to the method, computing resources of a local side and an edge side are fully utilized, the energy efficiency of the user terminal is improved, the time delay of local calculation of the user terminal is considered, synchronous completion of local and edge side calculation in task time is ensured, and the effectiveness of the method is improved. In addition,effectiveness and reliability of the method under different channel conditions are verified, and the method has a wider practical application scene.

Description

technical field [0001] The present invention relates to the technical field of computer wireless communication, in particular to an unloading method for unmanned aerial vehicle-assisted edge computing based on terminal energy efficiency optimization. Background technique [0002] With the development of Internet of Things (IoT) technology, many mobile application services have emerged, such as augmented reality (AR), virtual reality (VR), face recognition, and lightweight deep learning applications. These application services are often time-sensitive and require user terminals to have strong computing capabilities. As for the mobile user's terminal equipment, its limited energy and computing power cannot well meet the user's application requirements. [0003] Mobile Edge Computing (MEC) technology deploys servers on the edge side of mobile users, enabling resource-constrained user terminals to offload computationally intensive tasks to edge servers for execution, greatly re...

AI Technical Summary

Problems solved by technology

[0009]In the above research, there are the following problems: 1) Whether it is a full uninstall strategy or a binary uninstall strategy, the task of the user terminal can only be performed locally at the same time. Or edge side execution, which leads to a waste of computing resources on the other side at the same time

This may lead to consequences of user computing offload and local computing being out of sync

3) There is a lack of discussion on the channel conditions between the user terminal and the UAV

In the case of unstable channel conditions, there is no guarantee that the proposed model and scheme will still be effective and reliable

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