Advertisement

QoS-Based Mobility System for Autonomous Unmanned Aerial Vehicles Wireless Networks

  • Angelo TrottaEmail author
  • Luca Sciullo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10866)

Abstract

In the era of the Unmanned Aerial Vehicles (UAVs) several kinds of applications were born to make use of these autonomous vehicles, from surveillance to emergency management, from entertainment to package delivery. All these systems are based on the autonomous capability of the unmanned vehicles. The common factor of such systems is the use of an ad-hoc wireless network that enables the communication among the vehicles. However, guaranteeing an effective level of Quality-of-Service in the UAVs wireless network is hard to reach because of the unpredictable nature of such a system. Multiple solutions have emerged to address this problem, like enhanced communication protocols or mobility control systems that exploit the autonomous mobility of such vehicles. Nevertheless, none of those solutions have real affect on the end-to-end QoS performance. This paper aims to address the issue of guaranteeing the wireless network connectivity while providing Quality-of-Service at network layer, i.e., the proposed system will dynamically adapt its topology in order to increase the end-to-end network performance by using nature-inspired algorithm.

Keywords

Mobility system UAV Wireless network QoS Coverage Nature-inspired 

References

  1. 1.
    Biomo, J.-D.M.M., Kunz, T., St-Hilaire, M.: Routing in unmanned aerial ad hoc networks: introducing a route reliability criterion. In: 2014 7th IFIP Wireless and Mobile Networking Conference (WMNC), pp. 1–7. IEEE (2014)Google Scholar
  2. 2.
    Clausen, T., Jacquet, P.: Optimized link state routing protocol (OLSR). Technical report (2003)Google Scholar
  3. 3.
    Derr, K., Manic, M.: Extended virtual spring mesh (EVSM): the distributed self-organizing mobile ad hoc network for area exploration. IEEE Trans. Ind. Electron. 58(12), 5424–5437 (2011)CrossRefGoogle Scholar
  4. 4.
    Dixon, C., Frew, E.W.: Optimizing cascaded chains of unmanned aircraft acting as communication relays. IEEE J. Sel. Areas Commun. 30(5), 883–898 (2012)CrossRefGoogle Scholar
  5. 5.
    Gupta, L., Jain, R., Vaszkun, G.: Survey of important issues in UAV communication networks. IEEE Commun. Surv. Tutor. 18(2), 1123–1152 (2016)CrossRefGoogle Scholar
  6. 6.
    Han, B., Lee, S.: Efficient packet error rate estimation in wireless networks. In: 2007 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities, pp. 1–9, May 2007Google Scholar
  7. 7.
    Kacianka, S., Hellwagner, H.: Adaptive video streaming for UAV networks. In Proceedings of the 7th ACM International Workshop on Mobile Video, pp. 25–30. ACM (2015)Google Scholar
  8. 8.
    Kuiper, E., Nadjm-Tehrani, S.: Geographical routing with location service in intermittently connected manets. IEEE Trans. Veh. Technol. 60(2), 592–604 (2011)CrossRefGoogle Scholar
  9. 9.
    Bekmezci, İ., Sahingoz, O.K., Temel, Ş.: Flying ad-hoc networks (FANETs): a survey. Ad Hoc Netw. 11(3), 1254–1270 (2013)CrossRefGoogle Scholar
  10. 10.
    Okereafor, D.T., Diala, U., Onuekwusi, N., Uzoechi, L.O., Chukwudebe, G.: Improving security and emergency response through the use of unmanned vehicles. In: 2013 IEEE International Conference on Emerging Sustainable Technologies for Power ICT in a Developing Society (NIGERCON), pp. 263–269, November 2013Google Scholar
  11. 11.
    Rappaport, T.: Wireless Communications: Principles and Practice, 2nd edn. Prentice Hall PTR, Upper Saddle River (2001)zbMATHGoogle Scholar
  12. 12.
    Rosario, D., Zhao, Z., Braun, T., Cerqueira, E., Santos, A., Alyafawi, I.: Opportunistic routing for multi-flow video dissemination over flying ad-hoc networks. In: IEEE 15th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1–6. IEEE (2014)Google Scholar
  13. 13.
    Rosati, S., Krużelecki, K., Heitz, G., Floreano, D., Rimoldi, B.: Dynamic routing for flying ad hoc networks. IEEE Trans. Veh. Technol. 65(3), 1690–1700 (2016)CrossRefGoogle Scholar
  14. 14.
    Stephan, J., Fink, J., Charrow, B., Ribeiro, A., Kumar, V.: Robust routing and multi-confirmation transmission protocol for connectivity management of mobile robotic teams. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), pp. 3753–3760. IEEE (2014)Google Scholar
  15. 15.
    Trotta, A., Felice, M.D., Bedogni, L., Bononi, L., Panzieri, F.: Connectivity recovery in post-disaster scenarios through cognitive radio swarms. Comput. Netw. 91, 68–89 (2015)CrossRefGoogle Scholar
  16. 16.
    Yanmaz, E.: Connectivity versus area coverage in unmanned aerial vehicle networks. In: 2012 IEEE International Conference on Communications (ICC), pp. 719–723. IEEE (2012)Google Scholar
  17. 17.
    Zheng, Y., Wang, Y., Li, Z., Dong, L., Jiang, Y., Zhang, H.: A mobility and load aware OLSR routing protocol for UAV mobile ad-hoc networks (2014)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringUniversity of BolognaBolognaItaly

Personalised recommendations