An adaptive task scheduler for a cloud of drones

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dc.contributor.authorAlshareef, Hazzaa N.
dc.contributor.authorGrigoras, Dan
dc.date.accessioned2019-08-26T14:21:41Z
dc.date.available2019-08-26T14:21:41Z
dc.date.issued2018-11
dc.date.updated2019-08-26T14:16:16Z
dc.description.abstractDrones are now being widely used in different civilian applications, such as delivering shipments to consumers, as proposed by Amazon, and providing internet access to users, as offered by Facebook and Google. Drones can also contribute in emergencies by helping to find victims in places that are not reachable by rescuers, as well as assisting emergency centers to better manage a reported emergency. However, drones have a short flying time due to limited battery life. Therefore, a reliable strategy that minimizes energy consumption and uses collaborative working is required in order to increase drones' ability to operate for longer periods in emergency situations. This paper presents an adaptive task scheduler that allows tasks to be shared/transferred among the drones in a cloud of drones, in order to extend the operational time, achieve faster task execution and, at the same time, reduce the usage of each drone's resources. The ultimate result is an extension of battery life that leads to longer flying and service time for individual drones.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationAlshareef, H. N. and Grigoras, D. (2018) 'An adaptive task scheduler for a cloud of drones'. 2018 4th International Conference on Cloud Computing Technologies and Applications (Cloudtech), Brussels, Belgium, 26-28 Nov., pp. 1-8. doi: 10.1109/CloudTech.2018.8713336en
dc.identifier.doi10.1109/CloudTech.2018.8713336en
dc.identifier.endpage8en
dc.identifier.isbn978-1-7281-1637-2
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/8392
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urihttps://ieeexplore.ieee.org/document/8713336
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
dc.subjectAerospace computingen
dc.subjectAerospace roboticsen
dc.subjectCloud computingen
dc.subjectGroupwareen
dc.subjectMobile computingen
dc.subjectMulti-robot systemsen
dc.subjectRemotely operated vehiclesen
dc.subjectSchedulingen
dc.subjectAdaptive task scheduleren
dc.subjectMobile clouden
dc.subjectDrone resourcesen
dc.subjectCollaborative workingen
dc.subjectEnergy consumptionen
dc.subjectInternet accessen
dc.subjectCloud of dronesen
dc.subjectCivilian applicationsen
dc.subjectDronesen
dc.subjectTask analysisen
dc.subjectBatteriesen
dc.subjectStreaming mediaen
dc.subjectProtocolsen
dc.subjectCollaborationen
dc.subjectEmergencyen
dc.subjectBattery poweren
dc.subjectTask schedulingen
dc.subjectServicesen
dc.titleAn adaptive task scheduler for a cloud of dronesen
dc.typeConference itemen
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