Connectivity of VANET Segments Using UAVs

  • Pavel Shilin
  • Ruslan Kirichek
  • Alexander Paramonov
  • Andrey Koucheryavy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9870)


The main topic of the researches is VANET (Vehicle Ad-hoc Network). VANET is a peer-to-peer network based on IEEE 802.11p standards and group standards IEEE 1609 Wireless Access in Vehicular Environments (WAVE). Another current line of research is the UAVs. In 2015, the scientific works, oriented to research of a possibility of UAVs use for the VANET networks, began to appear. The scientific works present issues concerning connection of separately located network nodes by means of UAVs.

In this paper, we suggest evaluation of the possibility of creating flying VANET nodes. We will consider the model of the communication network of several isolated vehicles’ segments using UAVs. We will carry out the modelling and calculations in order to determine the maximum number of segments that can service the node based on UAVs for several types of call flows and describe circuit of preparation and statistical data production in the context of real network segment.





The reported study was supported by RFBR, research project No. 15 07-09431a “Development of the principles of construction and methods of self-organization for Flying Ubiquitous Sensor Networks”.


  1. 1.
    Hartenstein, H., Laberteaux, K.: VANET Vehicular Applications and Inter-Networking Technologies (2009)Google Scholar
  2. 2.
    Vehicle Safety Communications Project Final Report, U. S. Dept. Trans., Nat. Highway Traffic Safety Admin., Rep. DOT HS 810 591 (2006)Google Scholar
  3. 3.
    IEEE P1609.4-2010 - IEEE Standard for Wireless Access in Vehicular Environments (WAVE) 2010Google Scholar
  4. 4.
    IEEE 802.11p-2012 - IEEE Standard for Information technology– Local and metropolitan area networks– Specific requirements– Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 6: Wireless Access in Vehicular Environments (2012)Google Scholar
  5. 5.
    Car 2 Car Communication Consortium Manifesto. Overview of the C2C–CC SystemGoogle Scholar
  6. 6.
    ETSI TS 102 636–3 V1.1.1 (2010–03): Intelligent Transport Systems (ITS); Vehicular Communications; GeoNetworking; Part 3: Network architecture. — European Telecommunications Standards Institute (2010)Google Scholar
  7. 7.
    Mase, K.: Wide-area disaster surveillance using electric vehicles and helicopters. In: 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 3466–3471 (2013)Google Scholar
  8. 8.
    Dorrell, D., Vinel, A., Cao, D.: Connected vehicles - advancements in vehicular technologies and informatics. IEEE Trans. Ind. Electron. 62(12), 7824–7826 (2015)CrossRefGoogle Scholar
  9. 9.
    Koucheryavy, A., Vladyko, A., Kirichek, R.: State of the art and research challenges for public flying ubiquitous sensor networks. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART 2015. LNCS, vol. 9247, pp. 299–308. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  10. 10.
    Sahingoz, O.K.: Mobile networking with UAVs: opportunities and challenges. In: 2013 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 933–941 (2013)Google Scholar
  11. 11.
    Kirichek, R., Paramonov, A., Vareldzhyan, K.: Optimization of the UAV-P’s motion trajectory in public flying ubiquitous sensor networks (FUSN-P). In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART 2015. LNCS, vol. 9247, pp. 352–366. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  12. 12.
    Kirichek, R., Paramonov, A., Koucheryavy, A.: Swarm of public unmanned aerial vehicles as a queuing network. In: Vishnevsky, V., Kozyrev, D. (eds.) DCCN 2015. CCIS, vol. 601, pp. 111–120. Springer, Heidelberg (2016). doi: 10.1007/978-3-319-30843-2_12 CrossRefGoogle Scholar
  13. 13.
    Oubbati, O.S., Lakas, A., Lagraa, N., Yagoubi, M.B.: CRUV: connectivity-based traffic density aware routing using UAVs for VANets. In: 2015 International Conference on Connected Vehicles and Expo (ICCVE), pp. 68–73 (2015)Google Scholar
  14. 14.
    Kirichek, R., Koucheryavy, A.: Internet of things laboratory test bed. In: Zeng, Q.-A. (ed.) WCNA 2014. LNEE, vol. 348, pp. 485–494. Springer, Heidelberg (2016)CrossRefGoogle Scholar
  15. 15.
    Kirichek, R., Vladyko, A., Zakharov M., Koucheryavy, A.: Model networks for internet of things and SDN. In: Proceedings of the 18th International Conference on Advanced Communication Technology (ICACT), pp. 76–79 (2016)Google Scholar
  16. 16.
    Kirichek, R., Paramonov, A., Koucheryavy, A.: Flying ubiquitous sensor networks as a queueing system. In: Proceedings of the 17th International Conference on Advanced Communication Technology (ICACT), pp. 127–132 (2015)Google Scholar
  17. 17.
    Allen, A.O.: Probability. Statistics and Queueing Theory. PHI Learning, New Delhi (2009)Google Scholar
  18. 18.
    OMNeT++ Network Simulation Framework.
  19. 19.
    MiXiM (mixed simulator).
  20. 20.
    Veins - open source vehicular network simulation framework.
  21. 21.
    Lee, J.-M., Woo, M.-S., Min, S.-G.: Performance analysis of WAVE control channels for public safety services in VANETs. Int. J. Comput. Commun. Eng. 2(5), 563–570 (2013)CrossRefGoogle Scholar
  22. 22.
    Arada systems web site.
  23. 23.
    Vinel, A., Vishnevsky, V., Koucheryavy, Y.: A simple analytical model for the periodic broadcasting in vehicular ad-hoc networks. In: IEEE Globecom Workshops, GLOBECOM 2008Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Pavel Shilin
    • 1
  • Ruslan Kirichek
    • 1
  • Alexander Paramonov
    • 1
  • Andrey Koucheryavy
    • 1
  1. 1.State University of TelecommunicationSt. PetersburgRussia

Personalised recommendations