BEE-DRONES: Energy-efficient Data Collection on Wake-Up Radio-based Wireless Sensor Networks
| Autor: | Tullio Salmon Cinotti, Luciano Bononi, Enrico Natalizio, Luca Perilli, Angelo Trotta, Roberto Canegallo, Eleonora Franchi Scarselli, Marco Di Felice |
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| Přispěvatelé: | Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), SIMulating and Building IOT (SIMBIOT), Department of Networks, Systems and Services (LORIA - NSS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria), Lin Wang, Stephan Sigg, Trotta A., Di Felice M., Bononi L., Natalizio E., Perilli L., Scarselli E.F., Cinotti T.S., Canegallo R., Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2019 |
| Předmět: |
Optimization problem
Computer science business.industry Real-time computing ComputerApplications_COMPUTERSINOTHERSYSTEMS 020206 networking & telecommunications 020302 automobile design & engineering 02 engineering and technology Energy consumption 7. Clean energy Drone Scheduling (computing) [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] 0203 mechanical engineering autonomous aerial vehicles path planning wireless sensor networks Energy consumption Trajectory Optimization 0202 electrical engineering electronic engineering information engineering Wireless ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS Motion planning business Wireless sensor network ComputingMilieux_MISCELLANEOUS Efficient energy use |
| Zdroj: | INFOCOM Workshops IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Apr 2019, Paris, France. pp.547-553, ⟨10.1109/INFCOMW.2019.8845046⟩ |
| Popis: | Several recent studies demonstrated that the utilization of Unmanned Aerial Vehicles (UAVs) in combination with Wireless Sensor Networks (WSNs) can enhance the system performance in terms of lifetime and data delivery ratio; at the same time, the communication among Wireless Ground Sensors (WGSs) and UAVs poses several technical challenges which are far from being solved. Specifically, in this paper, two main issues are addressed: (i) how to ensure seamless synchronization among ground and aerial devices at each transit, and (ii) how to compute energy-efficient schedules for the WGSs and feasible trajectories for the UAVs. To this purpose, BEE-DRONES, a novel framework for data collection in wake-up radio based UAV-aided WSNs is proposed; in order to solve the synchronization issue, a solution where UAVs transfer energy toward selected WGSs is presented. The solution allows WGSs to power down the main radio when not requested. The joint WGSs wake-up scheduling and UAV path planning optimization problem is formulated, by taking into account the limited autonomy of the UAVs, the energy consumption of both UAVs and WGSs, and the data requirements of the applications, and it is solved via a two-step heuristic. The OMNeT++ simulation results demonstrate that the BEE-DRONES framework is able to enhance the WSN lifetime, and to optimize the quality of gathered data in terms of minimal temporal/spatial correlation. |
| Databáze: | OpenAIRE |
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