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Unplanned UAV Trajectory-based Data Collection in Large-scale Sensor Networks
  • Nazib, Rezoan Ahmed ;
  • Bouk, Safdar Hussain ;
  • Mir, Zeeshan Hameed ;
  • Ko, Young Bae
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dc.contributor.authorNazib, Rezoan Ahmed-
dc.contributor.authorBouk, Safdar Hussain-
dc.contributor.authorMir, Zeeshan Hameed-
dc.contributor.authorKo, Young Bae-
dc.date.issued2022-01-01-
dc.identifier.issn1976-7684-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/36809-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85125638954&origin=inward-
dc.description.abstractUsing the Unmanned aerial vehicle (UAV) as a mobile sink to collect data in a wireless sensor network is a recent research trend. UAV as a data mule has gained significant attention due to its flexibility in mobility and trajectory designing compared to ground-based mobile sinks. Most of the research that performed UAV-based data collection in sensor networks assumes an optimized UAV trajectory. However, this is not compatible with the realistic scenario because of environmental uncertainties and the physical design of currently available UAVs. Therefore, in this paper, we propose a novel UAV-Aided data collection scheme for the remote region to address the problem of its unplanned trajectory. The proposed framework tries to alleviate the adversarial effect of the unplanned UAV trajectory on the sensor nodes; the extensive quantitative comparison shows that it also performs well in terms of the amount of collected data and energy conservation of the sensor nodes.-
dc.description.sponsorshipACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science-
dc.language.isoeng-
dc.publisherIEEE Computer Society-
dc.subject.meshData collection-
dc.subject.meshLarge scale sensor network-
dc.subject.meshMobile sinks-
dc.subject.meshQ-learning-
dc.subject.meshRecent researches-
dc.subject.meshResearch trends-
dc.subject.meshRoutings-
dc.subject.meshTrajectory-based-
dc.subject.meshUnplanned trajectory-
dc.subject.meshVehicle trajectories-
dc.titleUnplanned UAV Trajectory-based Data Collection in Large-scale Sensor Networks-
dc.typeConference-
dc.citation.conferenceDate2022.1.12. ~ 2022.1.15.-
dc.citation.conferenceName36th International Conference on Information Networking, ICOIN 2022-
dc.citation.edition36th International Conference on Information Networking, ICOIN 2022-
dc.citation.endPage377-
dc.citation.startPage372-
dc.citation.titleInternational Conference on Information Networking-
dc.citation.volume2022-January-
dc.identifier.bibliographicCitationInternational Conference on Information Networking, Vol.2022-January, pp.372-377-
dc.identifier.doi10.1109/icoin53446.2022.9687151-
dc.identifier.scopusid2-s2.0-85125638954-
dc.identifier.urlhttp://www.icoin.org/-
dc.subject.keyworddata collection-
dc.subject.keywordQ-learning-
dc.subject.keywordrouting-
dc.subject.keywordunmanned aerial vehicle-
dc.subject.keywordunplanned trajectory-
dc.subject.keywordWireless sensor network-
dc.type.otherConference Paper-
dc.description.isoafalse-
dc.subject.subareaComputer Networks and Communications-
dc.subject.subareaInformation Systems-
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