Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/11924
Title: Enhancing Drone Network Resilience: Investigating Strategies For<i> K</I>-connectivity Restoration
Authors: Asci, Mustafa
Dagdeviren, Zuleyha Akusta
Akram, Vahid Khalilpour
Yildiz, Huseyin Ugur
Dagdeviren, Orhan
Tavli, Bulent
Keywords: Drone Networks
Reliability
K-Connectivity
Mathematical Programming
Graph Theory
Publisher: Elsevier
Abstract: Drones have recently become more popular due to technological improvements that have made them useful in many other industries, including agriculture, emergency services, and military operations. Coordination of communication amongst drones is often required for the efficient performance of missions. With an emphasis on building robust k-connected networks and restoration procedures, this paper investigates the relevance of connection in drone swarms. Specifically, we tackle the k-connectivity restoration problem, which aims to create k-connected networks by moving the drones as little as possible. We propose four novel approaches, including an integer programming model, an integer programming-based heuristic approach, a node converging heuristic, and a cluster moving heuristic. Through extensive measurements taken from various drone networking setups, we provide a comparative analysis of the proposed approaches. Our evaluations reveal that the drone movements produced by the integer programming-based heuristics are nearly the same as the original mathematical formulation, whereas the other heuristics are favorable in terms of execution time.
URI: https://doi.org/10.1016/j.csi.2024.103941
ISSN: 0920-5489
1872-7018
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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