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dc.creatorPolychronis G., Lalis S.en
dc.date.accessioned2023-01-31T09:50:23Z
dc.date.available2023-01-31T09:50:23Z
dc.date.issued2022
dc.identifier10.1109/ICDCSW56584.2022.00063
dc.identifier.isbn9781665488792
dc.identifier.urihttp://hdl.handle.net/11615/78295
dc.description.abstractDrones are used in a wide range of applications, which may involve computationally-demanding data processing tasks during the missions. While such heavy tasks can be offloaded to nearby edge-servers, this may not always be feasible due to capacity limitations and contention. In this case, it is important to have a fair allocation of server resources to drones. We propose a heuristic for this problem, and evaluate it though simulation experiments using realistic performance parameters. We show that the mission time can be greatly reduced, by up to 33% (16 min) compared to the default where drones perform all computations onboard, while evenly balancing the benefits of offloading among drones with different missions. © 2022 IEEE.en
dc.language.isoenen
dc.sourceProceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops, ICDCSW 2022en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85143800984&doi=10.1109%2fICDCSW56584.2022.00063&partnerID=40&md5=678f23e886479db2080264fa44ee7bc1
dc.subjectcomputation offloadingen
dc.subjectData handlingen
dc.subjectResource allocationen
dc.subjectCapacity limitationen
dc.subjectComputation offloadingen
dc.subjectEdge computingen
dc.subjectEdge serveren
dc.subjectFair allocationen
dc.subjectPerformance parametersen
dc.subjectResources allocationen
dc.subjectServer resourcesen
dc.subjectSimulationen
dc.subjectDronesen
dc.subjectInstitute of Electrical and Electronics Engineers Inc.en
dc.titlePlanning Computation Offloading on Shared Edge Infrastructure for Multiple Dronesen
dc.typeconferenceItemen


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