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Exploring Scheduling Policies for UAV Swarms

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dc.contributor.authorSteinhoff, Clara
dc.contributor.chairDelimitrou, Christina
dc.contributor.committeeMemberWicker, Stephen B.
dc.date.accessioned2021-12-20T20:34:38Z
dc.date.available2021-12-20T20:34:38Z
dc.date.issued2021-08
dc.description54 pages
dc.description.abstractUAV swarms have gained popularity over the past years, with increased accessibility contributing to new research areas and applications. The increased complexity of handling of UAVs swarms and assigning multi-phase applications results in the need for efficient task assignment for UAV swarms. The project extends an existing UAV swarm simulator to enable comparison of scheduling algorithms and techniques. The simulator is easily augmentable and provides a simple-to-use interface for the specification of complex applications. The evaluation of five scheduling algorithms shows that existing solvers for global problem optimization outperform naive scheduling approaches in terms of performance and assignment quality. Adaptive task batching and the utilization of cloud resources can lead to better task assignments with lower overhead and reduce the computational burden on the swarm.
dc.identifier.doihttps://doi.org/10.7298/zw9g-mn56
dc.identifier.otherSteinhoff_cornell_0058O_11251
dc.identifier.otherhttp://dissertations.umi.com/cornell:11251
dc.identifier.urihttps://hdl.handle.net/1813/110462
dc.language.isoen
dc.titleExploring Scheduling Policies for UAV Swarms
dc.typedissertation or thesis
dcterms.licensehttps://hdl.handle.net/1813/59810
thesis.degree.disciplineComputer Science
thesis.degree.grantorCornell University
thesis.degree.levelMaster of Science
thesis.degree.nameM.S., Computer Science

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