Energy-efficient and fault-tolerant drone-BS placement in heterogeneous wireless sensor networks

buir.contributor.authorKörpeoğlu, İbrahim
dc.citation.epage838en_US
dc.citation.spage825en_US
dc.citation.volumeNumber27en_US
dc.contributor.authorDeniz, F.en_US
dc.contributor.authorBağcı, H.en_US
dc.contributor.authorKörpeoğlu, İbrahimen_US
dc.contributor.authorYazıcı, A.en_US
dc.date.accessioned2021-03-11T17:18:55Z
dc.date.available2021-03-11T17:18:55Z
dc.date.issued2020
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractThis paper introduces a distributed and energy-aware algorithm, called Minimum Drone Placement (MDP) algorithm, to determine the minimum number of base stations mounted on resource-rich Unmanned Aerial Vehicles (UAV-BS), commonly referred to as drone-BS, and their possible locations to provide fault tolerance with high network connectivity in heterogeneous wireless sensor networks. This heterogeneous model consists of resource-rich UAV-BSs, acting as gateways of data, as well as ordinary sensor nodes that are supposed to be connected to the UAV-BSs via multi-hop paths. Previous efforts on fault tolerance in heterogeneous wireless sensor networks attempt to determine transmission radii of the sensor nodes based on the already deployed base station positions. They assume that the base stations are stationary and arbitrarily deployed regardless of the position of the sensor nodes. Our proposed MDP algorithm takes into account the desired degree of fault tolerance and the position of ordinary sensor nodes to determine the optimal number of UAV-BSs and their locations. The MDP algorithm consists of two steps. In the first step, each sensor node chooses low-cost pairwise disjoint paths to a subset of candidate UAV-BSs, using an optimization based on the well-known set-packing problem. In the last step, depending on the desired degree of fault tolerance, MDP chooses a subset of these UAV-BS candidates using a novel optimization based on the well-known set-cover problem. Through extensive simulations, we demonstrate that the MDP achieves up to 40% improvement in UAV-connected lifetimes compared to a random and uniform distribution of UAV-BSs.en_US
dc.description.provenanceSubmitted by Zeynep Aykut (zeynepay@bilkent.edu.tr) on 2021-03-11T17:18:55Z No. of bitstreams: 1 Energy_efficient_and_fault_tolerant_drone_BS_placement_in_heterogeneous_wireless_sensor_networks.pdf: 851164 bytes, checksum: d0654e2c382466fbce1f24dfa5a52e15 (MD5)en
dc.description.provenanceMade available in DSpace on 2021-03-11T17:18:55Z (GMT). No. of bitstreams: 1 Energy_efficient_and_fault_tolerant_drone_BS_placement_in_heterogeneous_wireless_sensor_networks.pdf: 851164 bytes, checksum: d0654e2c382466fbce1f24dfa5a52e15 (MD5) Previous issue date: 2020en
dc.identifier.doi10.1007/s11276-020-02494-xen_US
dc.identifier.issn1022-0038en_US
dc.identifier.urihttp://hdl.handle.net/11693/75921en_US
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttps://dx.doi.org/10.1007/s11276-020-02494-xen_US
dc.source.titleWireless Networksen_US
dc.subjectFault-toleranceen_US
dc.subjectEnergy efficiencyen_US
dc.subjectHeterogeneous wireless sensor networksen_US
dc.subjectUnmanned aerial vehicles(UAVs)en_US
dc.subjectk-connectivityen_US
dc.subjectSet cover problemen_US
dc.titleEnergy-efficient and fault-tolerant drone-BS placement in heterogeneous wireless sensor networksen_US
dc.typeArticleen_US

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