Mobile edge computing unmanned aerial vehicle group auxiliary communication method for explosive flow

Abstract

The invention discloses a mobile edge computing unmanned aerial vehicle group auxiliary communication method for explosive traffic, which is responsible for providing computing service for users withcomputing requirements on the ground when a network is congested. Firstly, in the prediction part, an improved PSO-BP neural network is used for predicting the calculation demand distribution situation of a target area, and unmanned aerial vehicles supporting mobile edge calculation are deployed as required; secondly, a demand partitioning part is calculated, a target area is partitioned based ona fairness principle, and each unmanned aerial vehicle serves users in a sub-area; and finally, the unmanned aerial vehicle energy optimization part in each sub-region performs joint optimization on the unmanned aerial vehicle calculation frequency and the unmanned aerial vehicle flight path on the premise of meeting the user calculation requirement, so that the energy consumption of the unmannedaerial vehicle in each sub-region is minimum, the energy consumption of the whole unmanned aerial vehicle group is minimum, and the service time of the unmanned aerial vehicle group is prolonged.

Description

technical field [0001] The present invention relates to the technical field of mobile edge computing, in particular to a mobile edge computing unmanned aerial vehicle swarm-assisted communication method for explosive traffic. Background technique [0002] With the rapid growth of mobile users and emerging diversified mobile applications (such as augmented reality, mobile online games, etc.), the resulting data traffic has also exploded. In particular, for some hot events (large-scale outdoor event sites, such as concerts, etc.), the explosive growth of data traffic will cause network congestion and seriously affect user experience, especially for delay-sensitive tasks such as video and voice. In such an environment of traffic explosion, a large amount of data traffic is generated, and the application of mobile edge computing technology is one of the effective countermeasures. Offload the computing tasks of mobile users in the target area to the edge network, reduce the amou...

AI Technical Summary

Problems solved by technology

In the current existing technology, only a single UAV is considered to provide services. In this case, the computing resources and battery of a single UAV are limited, which cannot meet the needs of multiple users and seriously affect the quality of user experience.

A few consider the scenario where multiple drones provide services, but they are only used as air base stations, and do not consider providing edge computing services for users, and hovering drone aerial base stations have limited service range, and mobile drone services Wider range reduces the number of drones required under the same conditions

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