End-to-End Latency Optimization for Resilient Distributed Convolutional Neural Network Inference in Resource-Constrained Unmanned Aerial Vehicle Swarms

End-to-End Latency Optimization for Resilient Distributed Convolutional Neural Network Inference in Resource-Constrained Unmanned Aerial Vehicle Swarms

An unmanned aerial vehicle (UAV) swarm has emerged as a powerful tool for mission execution in a variety of applications supported by deep neural networks (DNNs). In the context of UAV swarms, conventional methods for efficient data processing involve transmitting data to cloud and edge servers. How...

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Bibliographic Details
Main Authors: Jeongho Kim, Joonho Seon, Soohyun Kim, Seongwoo Lee, Jinwook Kim, Byungsun Hwang, Youngghyu Sun, Jinyoung Kim
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
resource-constrained UAV swarm
distributed inference
resilient UAV system
deep reinforcement learning
end-to-end latency optimization
Online Access:https://www.mdpi.com/2076-3417/14/23/10832
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