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 K-Connectivity Restoration
Authors: Asci, M.
Dagdeviren, Z.A.
Akram, V.K.
Yildiz, H.U.
Dagdeviren, O.
Tavli, B.
Keywords: Drone networks
Graph theory
k-connectivity
Mathematical programming
Reliability
Heuristic methods
Heuristic programming
Integer linear programming
Integer programming
Mixed-integer linear programming
Restoration
Connected networks
Connectivity restorations
Drone network
Integer Program- ming
K-connected
K-connectivity
Network resilience
Performance
Restoration procedure
Technological improvements
Drones
Publisher: Elsevier B.V.
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. © 2024
URI: https://doi.org/10.1016/j.csi.2024.103941
https://hdl.handle.net/20.500.11851/11924
ISSN: 0920-5489
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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