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Unmanned Aerial Vehicles Routing Formation Using Fisheye State Routing for Flying Ad-hoc Networks

Published:13 May 2021Publication History

ABSTRACT

Flying Ad-hoc Networks creates rapid topology changes that causes routing problems between Unmanned Aerial Vehicle and ground base station. Mobile Ad-hoc networks and Vehicular Ad-hoc network protocols are conventionally adopted to overcome routing issues. But Still, they do not fully address the routing problem in Flying Ad-hoc Networks. In this paper, Fisheye state routing protocol is implemented and evaluated to fully overcome routing issues in a Flying Ad-hoc Network and fully utilize the limited resource of Unmanned Aerial Vehicles. Performance evaluation is measured in terms of throughput, average end-to-end delay, packet drop analysis as congestion measure with Ad-Hoc On-Demand Distance Vector (AODV), Distance Sequence Distance Vector (DSDV), Optimized Link State Routing (OLSR), Temporary Ordered Routing Protocol (TORA) and Dynamic Source Routing (DSR). Fisheye state routing protocol showed promising results regarding throughput, packet drop rate, and average end-to-end delay compared with traditional protocols. Moreover, with the suggested improvement of the parameters, network lifetime is increased, and resources harvesting becomes under control.

References

  1. 2005. full scale wireless ad hoc network test bed.Google ScholarGoogle Scholar
  2. Kalpna Guleria and Anil Kumar Verma. 2019. Comprehensive review for energy efficient hierarchical routing protocols on wireless sensor networks. Wireless Networks (2019), 1159–1183.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Evşen Yanmaz Hayat, Samira and Raheeb Muzaffar.2016. Survey on unmanned aerial vehicle networks for civil applications: A communications viewpoint. IEEE Communications Surveys & Tutorials 18, 4 (2016), 2624–2661.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. IEEE 2000. Fisheye state routing: A routing scheme for ad hoc wireless networks. Vol. 1. IEEE.Google ScholarGoogle Scholar
  5. IEEE 2015. On the routing in flying ad hoc networks. IEEE.Google ScholarGoogle Scholar
  6. IEEE 2017. Flying ad-hoc networks (FANETs): A review of communication architectures, and routing protocols. IEEE.Google ScholarGoogle Scholar
  7. Ijaz Mansoor Qureshi Muhammad Adnan Aziz Tanweer Ahmad Cheema Khan, Inam Ullah and Syed Bilal Hussain Shah.2020. Smart IoT control-based nature inspired energy efficient routing protocol for flying ad hoc network (FANET). IEEE Access8(2020), 56371–56378.Google ScholarGoogle Scholar
  8. Inam Ullah Khan Alamgir Safi Khan, Muhammad Asghar and Ijaz Mansoor Quershi. 2018. Dynamic routing in flying ad-hoc networks using topology-based routing protocols. Drones 2, 3 (2018).Google ScholarGoogle Scholar
  9. Fernando Caballero Jesús Capitán José Ramiro Martínez-de-Dios Maza, Iván and Aníbal Ollero. 2011. Experimental results in multi-UAV coordination for disaster management and civil security applications.ournal of intelligent & robotic systems 61, 1 (2011), 563–585.Google ScholarGoogle Scholar
  10. Fernando Caballero J. Ramiro Martínez-de-Dios-Iván Maza Merino, Luis and Aníbal Ollero. 2012. An unmanned aircraft system for automatic forest fire monitoring and measurement. Journal of Intelligent & Robotic Systems 65, 1 (2012), 533–548.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Tarik Taleb Motlagh, Naser Hossein and Osama Arouk.2016. Low-altitude unmanned aerial vehicles-based internet of things services: Comprehensive survey and future perspectives. IEEE Internet of Things Journal 3, 6 (2016), 899–922.Google ScholarGoogle ScholarCross RefCross Ref
  12. Husnain Mansoor Ali Nawaz, Haque and Asif Ali Laghari. 2020. UAV communication networks issues: a review. Archives of Computational Methods in Engineering (2020), 1–21.Google ScholarGoogle Scholar
  13. V. Park and S Corson. 2001. Temporally Ordered Routing Algorithm (TORA). draft-ietf-manet-tora-spec-04. txt. Work in progress. IETF (2001).Google ScholarGoogle Scholar
  14. Belding-Royer E. Perkins, C. and S Das. 2003. Ad hoc on-demand distance vector (AODV) routing. RFC3561 (2003).Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Xuetian Zhu Ge Mang Michel Kadoch Qi, Feiand Wei Li.2019. UAV network and IoT in the sky for future smart cities. EEE Network 33, 2 (2019), 96–101.Google ScholarGoogle Scholar
  16. Ozgur Koray Sahingoz. 2014. Networking models in flying ad-hoc networks (FANETs): Concepts and challenges. Journal of Intelligent & Robotic Systems 74, 1 (2014), 513–527.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Ahmad H. Sawalmeh Ala Al-Fuqaha-Zuochao Dou Eyad Almaita Issa Khalil Noor Shamsiah Othman Abdallah Khreishah Shakhatreh, Hazim and Mohsen Guizani. 2017. Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges. IEEE Access 7(2017), 48572–48634.Google ScholarGoogle Scholar
  18. Vijander Singh Thakrar, Payal M. and Ketan Kotecha.2020. Improved route selection algorithm based on TORA over mobile adhoc network. Journal of Discrete Mathematical Sciences and Cryptography 23, 2(2020).Google ScholarGoogle ScholarCross RefCross Ref
  19. Haijun Wang Weiyu Wu Zhao, Haitao and Jibo Wei. 2018. Deployment algorithms for UAV airborne networks toward on-demand coverage. IEEE Journal on Selected Areas in Communications 36, 9(2018), 2015–2031.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Danwei Wang Zhu, Senqiang and Chang Boon Low.2013. Ground target tracking using UAV with input constraints. Journal of Intelligent & Robotic Systems 69, 1 (2013), 417–429.Google ScholarGoogle ScholarDigital LibraryDigital Library

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              cover image ACM Other conferences
              ICFNDS '20: Proceedings of the 4th International Conference on Future Networks and Distributed Systems
              November 2020
              313 pages
              ISBN:9781450388863
              DOI:10.1145/3440749

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              Publication History

              • Published: 13 May 2021

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