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Automatic Path Planning Offloading Mechanism in Edge-Enabled Environments

Dušan Herich, Ján Vaščák, Iveta Zolotová and Alexander Brecko
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Dušan Herich: Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Vysokoškolská 4, 042 00 Košice, Slovakia
Ján Vaščák: Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Vysokoškolská 4, 042 00 Košice, Slovakia
Iveta Zolotová: Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Vysokoškolská 4, 042 00 Košice, Slovakia
Alexander Brecko: Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Vysokoškolská 4, 042 00 Košice, Slovakia

Mathematics, 2021, vol. 9, issue 23, 1-25

Abstract: The utilization of edge-enabled cloud computing in unmanned aerial vehicles has facilitated advances in autonomous control by employing computationally intensive algorithms frequently related to traversal among different locations in an environment. A significant problem remains in designing an effective strategy to offload tasks from the edge to the cloud. This work focuses on creating such a strategy by employing a network evaluation method built on the mean opinion score metrics in concoction with machine learning algorithms for path length prediction to assess computational complexity and classification models to perform an offloading decision on the data provided by both network metrics and solution depth prediction. The proposed system is applied to the A* path planning algorithm, and the presented results demonstrate up to 94% accuracy in offloading decisions.

Keywords: edge and cloud computing; k-nearest neighbors; logistic regression; offloading; path planning; UAV (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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