Resilience of airborne networks

DC FieldValueLanguage
dc.contributor.authorAhmadi, Hamed-
dc.contributor.authorFontanesi, Gianluca-
dc.contributor.authorKatzis, Konstantinos-
dc.contributor.authorShakir, Muhammad Zeeshan-
dc.contributor.authorZhu, Anding-
dc.date.accessioned2019-07-12T09:03:11Z-
dc.date.available2019-07-12T09:03:11Z-
dc.date.copyright2018 IEEEen_US
dc.date.issued2018-09-12-
dc.identifier.isbn9781538660096-
dc.identifier.issn2166-9570-
dc.identifier.urihttp://hdl.handle.net/10197/10898-
dc.description2018 IEEE: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Bologna, Italy 9-12 September 2018en_US
dc.description.abstractNetworked flying platforms can be used to provide cellular coverage and capacity. Given that 5G and beyond networks are expected to be always available and highly reliable, resilience and reliability of these networks must be investigated. This paper introduces the specific features of airborne networks that influence their resilience. We then discuss how machine learning and blockchain technologies can enhance the resilience of networked flying platforms.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)en_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.subjectNetworked flying platformsen_US
dc.subjectResilienceen_US
dc.subjectSelf-organizing networksen_US
dc.subjectMachine learningen_US
dc.subjectBlockchainen_US
dc.titleResilience of airborne networksen_US
dc.typeConference Publicationen_US
dc.internal.authorcontactotheranding.zhu@ucd.ieen_US
dc.internal.webversionshttp://pimrc2018.ieee-pimrc.org/-
dc.statusNot peer revieweden_US
dc.identifier.volume2018-Septemberen_US
dc.identifier.startpage1155en_US
dc.identifier.endpage1156en_US
dc.identifier.doi10.1109/PIMRC.2018.8580944-
dc.neeo.contributorAhmadi|Hamed|aut|-
dc.neeo.contributorFontanesi|Gianluca|aut|-
dc.neeo.contributorKatzis|Konstantinos|aut|-
dc.neeo.contributorShakir|Muhammad Zeeshan|aut|-
dc.neeo.contributorZhu|Anding|aut|-
dc.date.updated2019-07-10T09:34:43Z-
item.grantfulltextopen-
item.fulltextWith Fulltext-
Appears in Collections:Electrical and Electronic Engineering Research Collection
Files in This Item:
File Description SizeFormat 
1570473932.pdf88.38 kBAdobe PDFDownload
Show simple item record

Page view(s)

194
Last Week
6
Last month
checked on Jan 22, 2020

Download(s)

110
checked on Jan 22, 2020

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.