A Dynamic Trajectory Control Algorithm for Improving the Probability of End-to-End Link Connection in Unmanned Aerial Vehicle Networks

  • Daisuke TakaishiEmail author
  • Hiroki Nishiyama
  • Nei Kato
  • Ryu Miura
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 148)


Recently, the Unmanned Aircraft Systems (UASs) have attracted great attention to provide various services. However, the Unmanned Aeria Vehicle (UAV) network which is constructed with multiple UAVs is prone to frequent disconnection. This is why the UAV-to-UAV links are constructed with two UAVs with high mobility. In such a disconnected network, ground-nodes cannot communicate with other ground-nodes with End-to-End link and the communication failure. Because the UAVs fly along with a commanded trajectory, the trajectories are the most important to decide UAV network performance. In this paper, we propose a effective UAVs’ trajectory decision scheme.


Unmanned Aircraft System (UAS) Unmanned Aerial Vehicle (UAV) End-to-End link connection 



This work was conducted under the national project, Research and Development on Cooperative Technologies and Frequency Sharing Between Unmanned Aircraft Systems (UAS) Based Wireless Relay Systems and Terrestrial Networks, supported by the Ministry of Internal Affairs and Communications (MIC), Japan.


  1. 1.
    Johnson, A., Montgomery, J., Matthies, L.: Vision guided landing of an autonomous helicopter in hazardous terrain. In: 2005 IEEE International Conference on Robotics and Automation (ICRA), pp. 3966–3971, April 2005Google Scholar
  2. 2.
    Mandl, D., Sohlberg, R., Justice, C., Ungar, S., Ames, T., Frye, S., Chien, S., Tran, D., Cappelaere, P., Sullivan, D., Ambrosia, V.: A space-based sensor web for disaster management. In: 2008 IEEE International Geoscience and Remote Sensing Symposium, vol. 5, July 2008Google Scholar
  3. 3.
    Abdulla, A., Zubair, F., Hiroki, N., Nei, K., Fumie, O., Miura, R.: An optimal data collection technique for improved utility in UAS-aided networks. In: IEEE International Conference on Computer Communications (INFOCOM), April 2014Google Scholar
  4. 4.
    Crocker, R., Maslanik, J., Adler, J., Palo, S., Herzfeld, U., Emery, W.: A sensor package for ice surface observations using small unmanned aircraft systems. IEEE Trans. Geosci. Remote Sens. 50(4), 1033–1047 (2012)CrossRefGoogle Scholar
  5. 5.
    Kwon, H., Yoder, J., Baek, S., Gruber, S., Pack, D.: Maximizing target detection under sunlight reflection on water surfaces with an autonomous unmanned aerial vehicle. In: 2013 International Conference on Unmanned Aircraft Systems (ICUAS), May 2013Google Scholar
  6. 6.
    Tisdale, J., Kim, Z., Hedrick, J.: Autonomous UAV path planning and estimation. IEEE Robot. Autom. Mag. 16(2), 35–42 (2009)CrossRefGoogle Scholar
  7. 7.
    Lu, R., Lin, X., Shen, X.: SPRING: a social-based privacy-preserving packet forwarding protocol for vehicular delay tolerant networks. In: IEEE International Conference on Computer Communications (INFOCOM), pp. 1–9, March 2010Google Scholar
  8. 8.
    Kesting, A., Treiber, M., Helbing, D.: Connectivity statistics of store-and-forward intervehicle communication. IEEE Trans. Intell. Transp. Syst. 11(1), 172–181 (2010)CrossRefGoogle Scholar
  9. 9.
    Almi’ani, K., Viglas, A., Libman, L.: Energy-efficient data gathering with tour length-constrained mobile elements in wireless sensor networks. In: 2010 IEEE Conference on Local Computer Networks (LCN) (2010)Google Scholar
  10. 10.
    Keung, G., Li, B., Zhang, Q.: Message delivery capacity in delay-constrained mobile sensor networks: bounds and realization. IEEE Trans. Wireless Commun. 10(5), 1552–1559 (2011)CrossRefGoogle Scholar
  11. 11.
    Shah, R., Roy, S., Jain, S., Brunette, W.: Data MULEs: modeling a three-tier architecture for sparse sensor networks. In: 2003 IEEE International Workshop on Sensor Network Protocols and Applications, May 2003Google Scholar
  12. 12.
    Zhao, W., Ammar, M.: Message ferrying: proactive routing in highly-partitioned wireless ad hoc networks. In: 2003 IEEE Workshop on Future Trends of Distributed Computing Systems, May 2003Google Scholar
  13. 13.
    Wu, J., Yang, S., Dai, F.: Logarithmic store-carry-forward routing in mobile ad hoc networks. IEEE Trans. Parallel Distrib. Syst. 18(6), 735–748 (2007)CrossRefGoogle Scholar
  14. 14.
    Goddemeier, N., Daniel, K., Wietfeld, C.: Role-based connectivity management with realistic air-to-ground channels for cooperative UAVs. IEEE J. Sel. Areas Commun. 30(5), 951–963 (2012)CrossRefGoogle Scholar
  15. 15.
    Beard, R., McLain, T.: Multiple UAV cooperative search under collision avoidance and limited range communication constraints. In: 2003 IEEE Conference on Decision and Control, vol. 1, December 2003Google Scholar
  16. 16.
    Li, M., Wan, P.-J., Frieder, O.: Coverage in wireless ad hoc sensor networks. IEEE Trans. Comput. 52(6), 753–763 (2003)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016

Authors and Affiliations

  • Daisuke Takaishi
    • 1
    • 2
    Email author
  • Hiroki Nishiyama
    • 1
    • 2
  • Nei Kato
    • 1
    • 2
  • Ryu Miura
    • 1
    • 2
  1. 1.Graduate School of Information SciencesTohoku UniversitySendaiJapan
  2. 2.Wireless Network Research InstituteNational Institute of Information and Communications TechnologyKoganeiJapan

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