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Cited 22 time in webofscience Cited 36 time in scopus
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FANET Routing Protocol Analysis for Multi-UAV-Based Reconnaissance Mobility Models

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dc.contributor.authorKim, Taehwan-
dc.contributor.authorLee, Seonah-
dc.contributor.authorKim, Kyong Hoon-
dc.contributor.authorJo, Yong-Il-
dc.date.accessioned2023-04-14T06:41:06Z-
dc.date.available2023-04-14T06:41:06Z-
dc.date.issued2023-03-
dc.identifier.issn2504-446X-
dc.identifier.issn2504-446X-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/30861-
dc.description.abstractDifferent from mobile ad hoc networks (MANETs) and vehicular ad hoc networks (VANETs), a flying ad hoc network (FANET) is a very low-density network where node topology changes rapidly and irregularly. These characteristics, the density, mobility, and speed of flight nodes, affect the performance of FANET. Furthermore, application scenarios and environmental settings could affect the performance of FANETs. In this paper, we analyzed the representative FANET protocols, AODV, DSDV, and OLSR, according to mobility models, SRWP, MP, RDPZ, EGM, and DPR, under the multi-UAV-based reconnaissance scenario. We evaluated them in terms of the number of nodes, network connectivity, mobility model's reconnaissance rate, speed of nodes, and ground control station (GCS) location. As a result, we found that AODV showed the highest PDR performance (81%) with SRWP in multiple UAV-based reconnaissance scenarios. As for a mobility model under the consideration of reconnaissance rate, SRWP was excellent at 76%, and RDPZ and EGM mobility models were reasonable at 62% and 60%, respectively. We also made several interesting observations such as how when the number of nodes increases, the connectivity of the network increases, but the performance of the routing protocol decreases, and how the GCS location affects the PDR performance of the combination of routing protocols and mobility models.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI AG-
dc.titleFANET Routing Protocol Analysis for Multi-UAV-Based Reconnaissance Mobility Models-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/drones7030161-
dc.identifier.scopusid2-s2.0-85152003838-
dc.identifier.wosid000955678500001-
dc.identifier.bibliographicCitationDrones, v.7, no.3-
dc.citation.titleDrones-
dc.citation.volume7-
dc.citation.number3-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaRemote Sensing-
dc.relation.journalWebOfScienceCategoryRemote Sensing-
dc.subject.keywordPlusAD HOC NETWORKS-
dc.subject.keywordAuthorFANET-
dc.subject.keywordAuthorrouting protocol-
dc.subject.keywordAuthorNS-3-
dc.subject.keywordAuthormulti-UAVs-
dc.subject.keywordAuthorreconnaissance-
dc.subject.keywordAuthormobility models-
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IT공과대학 (소프트웨어공학과)
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