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DPTM: A UAV Message Transmission Path Optimization Method Under Dynamic Programming

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Communications and Networking (ChinaCom 2019)

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Abstract

In the process of missions, how to transmit messages to the destination node quickly is a crucial issue for UAVs. Some existing methods show bad effects such as low delivery ratio, long delay, large average hop count, and high ping-pong effect ratio, thus this paper proposes a new algorithm. By considering the position of all UAVs at each moment, UAVs can obtain optimal message transmission, thus get the optimal path for the message to reach the destination node. After doing simulation experiments with the existing algorithms as DTNgeo, DTNclose and DTNload, the DPTM algorithm is superior to those in terms of delivery ratio, delay, hop count and ping-pong effect ratio.

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References

  1. Canis, B.: Unmanned Aircraft Systems (UAS): commercial outlook for a new industry. In: Congressional Research Service Reports. Library of Congress. Congressional Research Service (2015)

    Google Scholar 

  2. Zhou, Y., Cheng, N., Lu, N., et al.: Multi-UAV-aided networks: aerial-ground cooperative vehicular networking architecture. IEEE Veh. Technol. Mag. 10(4), 36–44 (2015)

    Article  Google Scholar 

  3. Guvenc, I., Saad, W., Bennis, M., et al.: Wireless communications, networking, and positioning with unmanned aerial vehicles [Guest Editorial]. IEEE Commun. Mag. 54(5), 24–25 (2016)

    Article  Google Scholar 

  4. Grodi, R., Rawat, D.B., Bajracharya, C., et al.: Performance evaluation of Unmanned Aerial Vehicle ad hoc networks. Southeastcon, pp. 1–4 (2015)

    Google Scholar 

  5. Anantapalli, M.K., Li, W.: Multipath multihop routing analysis in mobile ad hoc networks. Wirel. Netw. 16(1), 79–94 (2010)

    Article  Google Scholar 

  6. Wu, Q., Zeng, Y., Zhang, R., et al.: Joint trajectory and communication design for multi-UAV enabled wireless networks. IEEE Trans. Wirel. Commun. 17(3), 2109–2121 (2018)

    Article  Google Scholar 

  7. Hausman, K., Preiss, J.A., Sukhatme, G.S., et al.: Observability-aware trajectory optimization for self-calibration with application to UAVs. IEEE Robot. Autom. 2(3), 1770–1777 (2017)

    Google Scholar 

  8. Harounabadi, M., Puschmann, A., Artemenko, O., Mitschele-Thiel, A.: TAG: trajectory aware geographical routing in cognitive radio ad hoc networks with UAV nodes. In: Mitton, N., Kantarci, M.E., Gallais, A., Papavassiliou, S. (eds.) ADHOCNETS 2015. LNICST, vol. 155, pp. 111–122. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25067-0_9

    Chapter  Google Scholar 

  9. Badis, H., Agha, K.A.: QOLSR, QoS routing for ad hoc wireless networks using OLSR. Eur. Trans. Telecommun. 16(5), 427–442 (2010)

    Article  Google Scholar 

  10. Asadpour, M., Egli, S., Hummel, K.A., Giustiniano, D.: Routing in a fleet of micro aerial vehicles: first experimental insights. In: Proceedings of 3rd ACM MobiHoc Workshop Airborne Networks and Communication, pp. 9–10 (2014)

    Google Scholar 

  11. Bekmezci, I., Sahingoz, O.K., Temel, Ş., et al.: Flying ad-hoc networks (FANETs). Ad Hoc Netw. 11(3), 1254–1270 (2013)

    Google Scholar 

  12. Cetinkaya, E.K., Rohrer, J.P., Jabbar, A., et al.: Protocols for highly-dynamic airborne networks. In: ACM/IEEE International Conference on Mobile Computing and Networking, pp. 411–414 (2012)

    Google Scholar 

  13. Vahdat, A., Becker, D.: Epidemic Routing for Partially-Connected Ad Hoc Networks. Master Thesis (2000)

    Google Scholar 

  14. Li, J., Guan, J., Xu, C., et al.: Adaptive multiple spray and wait routing algorithm. J. Chin. Comput. Syst. 36(10), 2275–2278 (2015)

    Google Scholar 

  15. Lu, F., Li, J., Song, Y., et al.: Location position and message delivery ratio based controlled epidemic routing for DTNs. J. Chin. Comput. Syst. 39(5), 918–923 (2018)

    Google Scholar 

  16. Caini, C., Cruickshank, H.S., Farrell, S., et al.: Delay- and disruption-tolerant networking (DTN): an alternative solution for future satellite networking applications. Proc. IEEE 99(11), 1980–1997 (2011)

    Article  Google Scholar 

  17. Shirani, R., St-Hilaire, M., Kunz, T., et al.: Quadratic estimation of success probability of greedy geographic forwarding in unmanned aeronautical ad-hoc networks. In: Vehicular Technology Conference, pp. 1–5. IEEE (2012)

    Google Scholar 

  18. Asadpour, M., Hummel, K.A., Giustiniano, D., et al.: Route or carry: motion-driven packet forwarding in micro aerial vehicle networks. IEEE Trans. Mobile Comput. 16(3), 843–856 (2017)

    Article  Google Scholar 

  19. Muzaffar, R., Yanmaz, E.: Trajectory-aware Ad hoc routing protocol for micro aerial vehicle networks. In: IMAV 2014: International Micro Air Vehicle Conference and Competition 2014, Delft, The Netherlands, 12–15 August 2014. Delft University of Technology, pp. 301–315 (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. National Key Laboratory of Science and Technology on Avionics Integration, China Aeronautical Radio Electronics Research Institute, Shanghai, 200233, China

    Pingyu Deng, Qing Zhou & Kui Li

  2. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Avenue, Nanjing, 210016, China

    Feifei Zhu

Authors
  1. Pingyu Deng
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  2. Qing Zhou
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  3. Kui Li
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  4. Feifei Zhu
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Corresponding author

Correspondence to Pingyu Deng .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. School of Computer Software, Tianjin University, Tianjin, China

    Zhiyong Feng

  3. Hangzhou Dianzi University, Hangzhou, China

    Jun Yu

  4. Tongji University, Shanghai Shi, China

    Jun Wu

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Deng, P., Zhou, Q., Li, K., Zhu, F. (2020). DPTM: A UAV Message Transmission Path Optimization Method Under Dynamic Programming. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-41114-5_13

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  • DOI: https://doi.org/10.1007/978-3-030-41114-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41113-8

  • Online ISBN: 978-3-030-41114-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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