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dc.contributor.authorArribas, Edgar 
dc.contributor.authorCholvi, Vicent
dc.contributor.authorMancuso, Vincenzo 
dc.date.accessioned2021-09-16T10:11:19Z
dc.date.available2021-09-16T10:11:19Z
dc.date.issued2021-12
dc.identifier.citation[1] V. Chamola, V. Hassija, V. Gupta, and M. Guizani, “A Comprehensive review of the COVID-19 pandemic and the Role of IoT, drones, AI, blockchain, and 5G in managing its impact,” IEEE Access, vol. 8, pp. 90 225–90 265, 2020. [2] I. Bor-Yaliniz, M. Salem, G. Senerath, and H. Yanikomeroglu, “Is 5G ready for drones: A look into contemporary and prospective wireless networks from a standardization perspective,” IEEE Wireless Communi- cations, vol. 26, no. 1, pp. 18–27, 2019. [3] J. R. Montoya-Torres, J. Lo ́pez Franco, S. Nieto Isaza, H. Felizzola Jime ́nez, and N. Herazo-Padilla, “A literature review on the vehicle rout- ing problem with multiple depots,” Computers & Industrial Engineering, vol. 79, pp. 115–129, 2015. [4] M. Shin, J. Kim, and M. Levorato, “Auction-based charging scheduling with deep learning framework for multi-drone networks,” IEEE Transac- tions on Vehicular Technology, vol. 68, no. 5, pp. 4235–4248, 2019. [5] E. Hartuv, N. Agmon, and S. Kraus, “Scheduling spare drones for persistent task performance under energy constraints,” in Proceedings of the 17th AAMAS International Conference, 2018, pp. 532–540. [6] H. Park and J. R. Morrison, “System design and resource analysis for persistent robotic presence with multiple refueling stations,” in ICUAS, 2019, pp. 622–629. [7] E. Hartuv, N. Agmon, and S. Kraus, “Spare drone optimization for persistent task performance with multiple homes,” in ICUAS, 2020, pp. 389–397. [8] E. Arribas, V. Mancuso, and V. Cholvi, “Coverage optimization with a dynamic network of drone relays,” IEEE Transactions on Mobile Computing, vol. 19, no. 10, pp. 2278–2298, 2019. [9] B. Michini, T. Toksoz, J. Redding, M. Michini, J. How, M. Vavrina, and J. Vian, “Automated battery swap and recharge to enable persistent uav missions,” in Infotech@ Aerospace 2011, 2011, p. 1405.es
dc.identifier.urihttp://hdl.handle.net/20.500.12761/1508
dc.description.abstractThe adoption and integration of drones in commu- nication networks is becoming reality thanks to the deployment of advanced solutions for IoT and cellular communication relay schemes. However, using drones introduces new energy con- straints and scheduling issues in the dynamic management of the network topology, due to the need to call back and recharge, or substitute, drones that run out of energy. In this paper, we describe the design of a drone recharging scheme for realisti- cally limited flight time of drones, and leverage the presence of recharging stations. Indeed, drones need to be recharged periodically, and maximizing the operational time of drones is paramount to minimize the size of the fleet of drones to be devoted to a drone mission, hence its cost. We design Homogeneous RotatingRecharge(HRR), an optimal drone recharging scheduling that extends the coverage of a cellular network. HRR minimizes the number of back-up drones needed to guarantee a fixed number of operational drones, so as to support the operation of an underlying cellular network. Results show that operating a network of drones with our scheme provides reliable and stable performance over time.es
dc.description.sponsorshipComunidad de Madrides
dc.language.isoenges
dc.titleAn Optimal Scheme to Recharge Communication Droneses
dc.typeconference objectes
dc.conference.date7-11 December 2021es
dc.conference.placeMadrid, Spaines
dc.conference.titleIEEE Global Telecommunications Conference*
dc.event.typeconferencees
dc.pres.typepaperes
dc.type.hasVersionAMes
dc.rights.accessRightsopen accesses
dc.relation.projectIDS2018/TCS-4496es
dc.relation.projectNameTAPIR-CMes
dc.description.refereedTRUEes
dc.description.statusinpresses


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