Service Area Scheduling in a Drone Assisted Network

  • Yunmin Kim
  • Tae-Jin LeeEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10408)


We consider a wireless network using a drone as a sink node collecting data from sensor nodes is considered. Since a drone is expected to cover the large area, the scheduling of the service area is essential. In this paper, we propose an optimal service area scheduling for a drone network. The service area is divided into sections and the effect of such scheduling is analyzed. Simulation results show that our optimization algorithm can find the optimal scheduling policy to maximize the network throughput.


Drone network Service area scheulding Optimization 



This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government(MSIP) (2015R1A2A2A01004067) and Basic Science Research Program through NRF of Korea, funded by MOE(NRF-2010-0020210).


  1. 1.
    Drones: What are they and how do they work?
  2. 2.
  3. 3.
    Mozaffari, M., Saad, W., Bennis, M., Debbah, M.: Drone small cells in the clouds: design, deployment and performance analysis. In: IEEE GLOBECOM (2015). doi: 10.1109/GLOCOM.2015.7417609
  4. 4.
    Rahman, A.: Enabling drone communications with WiMAX technology. In: International Conference of Information, Intelligence, Systems and Applications (IISA) (2014). doi: 10.1109/IISA.2014.6878796
  5. 5.
    Li, X., Guo, D., Yin, H., Wei, G.: Drone-assisted public safety wireless broadband network. In: IEEE Wireless Communications and Networking Conference (WCNC), pp. 323–328 (2015). doi: 10.1109/WCNCW.2015.7122575
  6. 6.
    Sharma, V., Sabatini, R., Ramasamy, S.: UAVs assisted delay optimization in heterogeneous wireless networks. IEEE Commun. Lett. 20(12), 2526–2529 (2016). doi: 10.1109/LCOMM.2016.2609900 CrossRefGoogle Scholar
  7. 7.
    Koulali, S., Taleb, T., Azizi, M.: A green strategic activity scheduling for UAV networks: a sub-modular game perspective. IEEE Commun. Mag. 54(5), 58–64 (2016). doi: 10.1109/MCOM.2016.7470936 CrossRefGoogle Scholar
  8. 8.
    Eom, J., Lee, T.-J.: Accurate tag estimation for dynamic framed-slotted ALOHA in RFID systems. IEEE Commun. Lett. 14(1), 60–62 (2010). doi: 10.1109/LCOMM.2010.01.091378 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.College of Information and Communnication EngineeringSungkyunkwan UniversitySuwonSouth Korea

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