A Mobile Edge Computing Unmanned Aid Swarm Assisted Communication Method for Explosive Traffic

Abstract

The invention discloses a mobile edge computing unmanned aerial vehicle swarm-assisted communication method oriented to explosive traffic. When the network is congested, it is responsible for providing computing services for users with computing needs on the ground; first, the prediction part uses the improved PSO‑BP The neural network predicts the distribution of computing needs in the target area, and deploys UAVs that support mobile edge computing as needed; secondly, the computing demand partition part partitions the target area based on the principle of fairness, and each UAV serves users in the sub-area ;Finally, the UAV energy optimization part in the sub-area, under the premise of meeting the user's computing needs, jointly optimize the UAV calculation frequency and UAV flight trajectory, so that the energy consumption of the UAV in each sub-area is minimized , so that the energy consumption of the entire drone fleet is minimized, and the service time of the fleet is extended.

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 the case of a single UAV providing services is considered, such as the document UAV-Enabled Mobile Edge Computing: Offloading Optimization and Trajectory Design. In this case, a single UAV has limited computing resources and batteries, which cannot satisfy multiple users. demand, seriously affecting the quality of user experience

A few consider the scenario where multiple UAVs provide services, but they are only used as air base stations, and do not consider providing edge computing services for users, and the hovering UAV air base stations have limited service range, such as the literature Wireless Communication Using Unmanned AerialVehicles(UAVs): Optimal Transport Theory for Hover Time Optimization, mobile drones have a wider range of services, and the number of drones required can be reduced under the same conditions

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