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LPAR: Link Stability Prediction-based Adaptive Routing Protocol for Flying Ad Hoc Networks

Published:05 October 2021Publication History

ABSTRACT

With increasing demands for Unmanned Aerial Vehicles (UAV), also known as drones, in modern military affairs as well as civil fields, flying ad hoc networks (FANETs) play an essential role in coordinating drones. However, due to the high mobility of drones, these networks are very dynamic and suffer from routing path failure and packet loss. The existing mobile ad-hoc network (MANET) routing protocols are not enough to meet the requirements of high speed of drones and fail to provide reliable communications. In order to overcome this problem of conventional protocols, we propose a protocol named link stability prediction-based adaptive routing (LPAR) protocol. By predicting the location of drones, our protocol can set up a most stable connection in a certain period of time instead of one point. In addition, it uses the prediction error to adjust the control packet interval and reduce the network overhead. This novel routing protocol has been compared with other three protocols: AODV, RGR and LAOD. The protocol performance has been evaluated in terms of packet delivery ratio (PDR), normalized control overhead and average end-to-end delay.

References

  1. C. Barrado, R. Messeguer, J. L´opez, E. Pastor, E. Santamaria, and P. Royo, “Wildfire monitoring using a mixed air-ground mobile network,” IEEE Pervasive Computing, vol. 9, no. 4, pp. 24–32, 2010.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. S. Siebert and J. Teizer, “Mobile 3d mapping for surveying earthwork projects using an unmanned aerial vehicle (uav) system,” Automation in construction, vol. 41, pp. 1–14, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  3. J. Scherer, S. Yahyanejad, S. Hayat, E. Yanmaz, T. Andre, A. Khan, V. Vukadinovic, C. Bettstetter, H. Hellwagner, and B. Rinner, “An autonomous multi-uav system for search and rescue,” in Proceedings of the First Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, 2015, pp. 33–38.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Li X, Chen J. An Efficient Framework for Target Search with Cooperative UAVs in a FANET[C]//2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC). IEEE, 2017: 306-313.Google ScholarGoogle Scholar
  5. Li, X., Chen, J., Deng, F., & Li, H. (2019). Profit-driven adaptive moving targets search with UAV swarms. Sensors, 19(7), 1545.Google ScholarGoogle Scholar
  6. Li X, Chen J, Li J. FATES: A Framework with Adaptive Track-Explore Strategy for Moving Targets Search by a FANET[C]//2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing,Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom). IEEE, 2018: 856-861.Google ScholarGoogle Scholar
  7. L. Gupta, R. Jain, and G. Vaszkun, “Survey of important issues in uav communication networks,” IEEE Communications Surveys & Tutorials, vol. 18, no. 2, pp. 1123–1152, 2015.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. C. Perkins, E. Belding-Royer, S. Das , “Ad hoc on-demand distance vector (aodv) routing,” 2003.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. G. F. Riley and T. R. Henderson, “The ns-3 network simulator,” in Modeling and tools for network simulation. Springer, 2010, pp. 15–34.Google ScholarGoogle ScholarCross RefCross Ref
  10. J.-D. M. M. Biomo, T. Kunz, and M. St-Hilaire, “Routing in unmanned aerial ad hoc networks: Introducing a route reliability criterion,” in 2014 7th IFIP wireless and mobile networking conference (WMNC). IEEE, 2014, pp. 1–7.Google ScholarGoogle Scholar
  11. A. Waheed, A. Wahid, and M. A. Shah, “Laod: Link aware on demand routing in flying ad-hoc networks,” in 2019 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2019, pp. 1–5.Google ScholarGoogle ScholarCross RefCross Ref
  12. L. Lin, Q. Sun, J. Li, and F. Yang, “A novel geographic position mobility oriented routing strategy for uavs,” Journal of Computational Information Systems, vol. 8, no. 2, pp. 709–716, 2012.Google ScholarGoogle Scholar
  13. Li, X., Deng, F., & Yan, J. (2020). Mobility-assisted adaptive routing for intermittently connected FANETs. In IOP Conference Series: Materials Science and Engineering (Vol. 715, No. 1, p. 012028). IOP Publishing.Google ScholarGoogle Scholar
  14. Li, X., & Yan, J. (2017, July). LEPR: link stability estimation-based preemptive routing protocol for flying ad hoc networks. In 2017 IEEE Symposium on Computers and Communications (ISCC) (pp. 1079-1084). IEEE.Google ScholarGoogle Scholar
  15. E. Sakhaee and A. Jamalipour, “A new stable clustering scheme for pseudo-linear highly mobile ad hoc networks,” in IEEE GLOBECOM 2007-IEEE Global Telecommunications Conference. IEEE, 2007, pp.1169–1173.Google ScholarGoogle ScholarCross RefCross Ref
  16. M. Maleki, K. Dantu, and M. Pedram, “Lifetime prediction routing in mobile ad hoc networks,” in 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003., vol. 2. IEEE, 2003, pp. 1185–1190.Google ScholarGoogle ScholarCross RefCross Ref
  17. M. Gerharz, C. de Waal, P. Martini, and P. James, “Strategies for finding stable paths in mobile wireless ad hoc networks,” in 28 th Annual IEEE International Conference on Local Computer Networks, 2003. LCN’03. Proceedings. IEEE, 2003, pp. 130–139.Google ScholarGoogle Scholar
  18. N. Meghanathan and A. Farago, “Looking at protocol efficiency from a new angle: stability—delay analysis,” in Proceedings of the second international workshop on Mobility management & wireless access protocols, 2004, pp. 51–55.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. K.-J. Kim and S.-J. Yoo, “Power-efficient reliable routing protocol for mobile ad-hoc networks,” IEICE transactions on communications, vol. 88, no. 12, pp. 4588–4597, 2005.Google ScholarGoogle Scholar
  20. C.-K. Toh, “Associativity-based routing for ad hoc mobile networks,” Wireless Personal Communications, vol. 4, no. 2, pp. 103–139, 1997.Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. P. Sambasivam, A. Murthy, and E. M. Belding-Royer, “Dynamically adaptive multipath routing based on aodv.” Citeseer, 2004.Google ScholarGoogle Scholar
  22. D. B. Johnson and D. A. Maltz, “Dynamic source routing in ad hoc wireless networks,” in Mobile computing. Springer, 1996, pp. 153–181.Google ScholarGoogle ScholarCross RefCross Ref
  23. G. He, “Destination-sequenced distance vector (dsdv) protocol,” Networking Laboratory, Helsinki University of Technology, vol. 135, 2002.Google ScholarGoogle Scholar
  24. B. Karp and H.-T. Kung, “Gpsr: Greedy perimeter stateless routing for wireless networks,” in Proceedings of the 6th annual international conference on Mobile computing and networking, 2000, pp. 243–254Google ScholarGoogle ScholarDigital LibraryDigital Library

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            • Published in

              cover image ACM Other conferences
              ITCC '21: Proceedings of the 2021 3rd International Conference on Information Technology and Computer Communications
              June 2021
              126 pages
              ISBN:9781450389884
              DOI:10.1145/3473465

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              Publication History

              • Published: 5 October 2021

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