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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 5

Proceedings of the 2015 Federated Conference on Computer Science and Information Systems

On the Routing in Flying Ad hoc Networks

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DOI: http://dx.doi.org/10.15439/2015F002

Citation: Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 5, pages 19 ()

Full text

Abstract. The usage of Unmanned Aerial Vehicles (UAVs) is increasing day by day. In recent years, UAVs are being used in increasing number of civil applications, such as policing, firefighting, etc in addition to military applications. Instead of using one large UAV, multiple UAVs are nowadays used for higher coverage area and accuracy. Therefore, networking models are required to allow two or more UAV nodes to communicate directly or via relay node(s). Flying Ad-Hoc Networks (FANETs) are formed which is basically an ad hoc network for UAVs. This is relatively a new technology in network family where requirements vary largely from traditional networking model, such as Mobile Ad-hoc Networks and Vehicular Ad-hoc Networks. In this paper, Flying Ad-Hoc Networks are surveyed along with its challenges compared to traditional ad hoc networks. The existing routing protocols for FANETs are then classified into six major categories which are critically analyzed and compared based on various performance criteria. Our comparative analysis will help network engineers in choosing appropriate routing protocols based on the specific scenario where the FANET will be deployed.

References

  1. H. Chao, Y. Cao, and Y. Chen, “Autopilots for small fixed-wing unmanned air vehicles: a survey,” International Conference on Mecha- tronics and Automation, 2007 (ICMA 2007), pp. 3144–3149, 2007.
  2. B. Morse, C. Engh, and M. Goodrich, “Uav video coverage quality maps and prioritized indexing for wilderness search and rescue,” Proceedings of the 5th ACM/IEEE International Conference on HumanRobot Inter- action, HRI 10, Piscataway, NJ, USA, vol. 3, pp. 227–234, 2010.
  3. E. Yanmaz, C. Costanzo, C. Bettstetter, and W. Elmenreich, “A discrete stochastic process for coverage analysis of autonomous uav networks,” Proceedings of IEEE Globecom-WiUAV, IEEE, 2010.
  4. L. To, A. Bati, and D. Hilliard, “Radar cross-section measurements of small unmanned air vehicle systems in non-cooperative field environ- ments,” 3rd European Conference on Antennas and Propagation, 2009 (EuCAP 2009), IEEE, pp. 3637–3641, 2009.
  5. M. Rieke, T. Foerster, and A. Broering, “Unmanned aerial vehicles as mobile multi-platforms,” The 14th AGILE International Conference on Geographic Information Science,Utrecht, Netherlands, 18-21 April 2011.
  6. J. Clapper, J. Young, J. Cartwright, and J. Grimes, “Unmanned systems roadmap,” Tech. rep., Dept. of Defense, pp. 2007–2032.
  7. T. Brown, B. Argrow, E. Frew, C. Dixon, D. Henkel, J. Elston, and H. Gates, “Experiments Using Small Unmanned Aircraft to Augment a Mobile Ad Hoc Network,” ISBN-13: 9780521895842, pp. 179–199.
  8. J. Elston, E. Frew, D. Lawrence, P. Gray, and B. Argrow, “Net-centric communication and control for a heterogeneous unmanned aircraft system,” Journal of Intelligent and Robotic Systems, vol. 56(1-2), pp. 199–232, 2009.
  9. E. Frew and T. Brown, “Networking issues for small unmanned aircraft systems,” Journal of Intelligent and Robotics Systems, vol. 54 (1-3), pp. 21–37, 2009.
  10. I. Bekmezci, O. K. Sahingoz, and S. Temel, “Flying ad-hoc networks (FANETs): A survey,” Elsevier, Ad Hoc Networks 11, pp. 1254–1270, 2013.
  11. O. K. Sahingoz, “(FANETs): Concepts and challenges,” Springer J Intell Robot System, vol. 74, pp. 513–527, 2014.
  12. S. Cameron, S. Hailes, S. Julier, S. McClean, G. Parr, N. Trigoni, M. Ahmed, G. McPhillips, R. de Nardi, J. Nie, A. Symington, L. Teacy, and S.Waharte, “SUAAVE: Combining aerial robots and wireless net- working,” 25th Bristol International UAV Systems Conference, 2010.
  13. A. Purohit and P. Zhang, “SensorFly: a controlled-mobile aerial sensor network,” in ACM,7th ACM Conference on Embedded Networked Sensor Systems, SenSys ’09, New York, NY, USA, 2009, pp. 327–328.
  14. M. Akbas and D. Turgut, “APAWSAN: actor positioning for aerial wireless sensor and actor networks,” in 36th Conference on Local Computer Networks, LCN ’11, IEEE Computer Society, Washington, DC, USA, 2011, pp. 563–570.
  15. J. Allred, A. Hasan, S. Panichsakul, W. Pisano, P. Gray, J. Huang, R. Han, D. Lawrence, and K. Mohseni, “Sensorock: an airborne wireless sensor network of micro-air vehicles,” ACM, 5 th International Confer- ence on Embedded Networked Sensor Systems, pp. 117–119, 2007.
  16. T. Brown, S. Doshi, S. Jadhav, and J. Himmelstein, “Test bed for a wireless network on small UAVs,” AIAA 3rd Unmanned Unlimited Technical Conference, pp. 20–23, 2004.
  17. Z. Han, A. Swindlehurst, and K. Liu, “Optimization of MANET connectivity via smart deployment/movement of unmanned air vehicle,” IEEE Transactions on Vehicular Technology, vol. 58, pp. 3533–3546, 2009.
  18. E. Yanmaz, R. Kuschnig, and C. Bettstetter, “Channel measurements over 802.11a-based UAV-to-ground links,” GLOBECOM Wi-UAV Work- shop, pp. 1280–1284, 2011.
  19. A.Franchi, C.Secchi, M.Ryll, H. Bulthoff, and P.R.Giordano, “Shared control: Balancing autonomy and human assistance with a group of quad rotor UAVs,” IEEE Robot. Auto Mag, vol. 19 (3), pp. 57–58, 2012.
  20. J.Ko, A.Mahajan, and R.Sengupta, “A network-centric UAV organization for search and pursuit operations,” IEEE Aerospace Conference, pp. 2697–2713, 2002.
  21. J.Lopez, P.Royo, E.Pastor, C.Barrado, and E. maria, “A middleware architecture for unmanned aircraft avionics,” ACM/IFIP/ USENIX In- ternational Conference on Middleware companion (MC 07), 2007.
  22. E. D. Jong, “Flexible data-centric UAV platform eases mission adap- tation,” White paper: http://www.rti.com/whitepapers/RTI-Data-Driven-Approach-to-UAV.pdf, 3 Aug 2013.
  23. A. A. Koller and E.N.Johnson, “Design, implementation, and integration of a publish/subscribe-like multi- UAV communication architecture,” AIAA Modelling and Simulation Technologies Conference and Exhibit, pp. 1–17, 2005.
  24. T. Clausen and P. Jacquet, “Optimized link state routing protocol (OLSR),” RFC 3626 (Experimental), October 2003.
  25. A. Alshabtat, L. Dong, J. Li, and F. Yang, “Low latency routing algorithm for unmanned aerial vehicles ad-hoc networks,” International Journal of Electrical and Computer Engineering, vol. 6 (1), pp. 48–54, 2010.
  26. D. Jung and P. Tsiotras, “Inertial attitude and position reference system development for a small uav,” 26th AIAA Aeroacoustics Conference, 2007.
  27. D. Johnson and D. Maltz, “Dynamic source routing in ad hoc wireless networks,” Mobile Computing, The Kluwer International Series in Engineering and Computer Science, Springer, US, vol. 353, pp. 153– 181, 1996.
  28. D.B.Johnson and D.A.Maltz, “Dynamic source routing in ad hoc wire- less networks,” Kluwer Academic Publishers, pp. 153–181, 1996.
  29. T.X.Brown, B.Argrow, C.Dixon, S.Doshi, R.G.Thekkekunel, and D.Henkel, “Ad-hoc UAV ground network (AUGNet),” 3rd AIAA Un- manned Unlimited Technical Conference, pp. 29–39, 2004.
  30. S.Murthy and J. L. Aceves, “An efficient routing protocol for wireless networks,” ACM Mobile Networks and Applications, pp. 183–197, 1996.
  31. J. Forsmann, R. Hiromoto, and J. Svoboda, “A time-slotted on-demand routing protocol for mobile ad-hoc unmanned vehicle systems,” SPIE 6561, 2007.
  32. Z.J.Haas and M.R.Pearlman, Zone Routing Protocol (ZRP) a hybrid framework for routing in ad-hoc networks. Addison-Wesley, 2001, vol. 1.
  33. V. Park and S.Corson, “Temporarily-ordered routing algorithm (TORA),” Version 1. Internet draft:IETF MANET working group. http://tools.ietf.org/html/ draft-ietf-manet-tora-spec-04, 3 Aug 2013.
  34. R. Shirani, M. St-Hilaire, T. Kunz, Y. Zhou, J. Li, and L. Lamont, “The performance of greedy geographic forwarding in unmanned aeronautical ad-hoc networks,” in 2011 Ninth Annual Communication Networks and Services Research Conference, CNSR ’11, IEEE Computer Society, Washington, DC, USA, 2011, pp. 161–166.
  35. C. Zang and S. Zang, “Mobility prediction clustering algorithm for UAV networking,” in GLOBECOM Workshops, IEEE, 2011, pp. 1158–1161.
  36. L. Kesheng, Z. Jun, and Z. Tao, “The clustering algorithm of UAV networking in near-space,” in 8th International Symposium on Antennas, Propagation and EM Theory,(ISAPE 2008), 2008, pp. 1550–1553.