A Secure and Trustworthy Intelligent System for Clustering in VANETs Using Fuzzy Logic

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 926)


Recently, smart cities and Internet of Things (IoT) applications, such as Vehicular Ad-hoc Networks (VANETs) and Opportunistic networks have been deeply investigated. However, these kinds of wireless networks have security problems. Also, the vehicles can be not trustworthy, which brings different communication problems. In this work, we present a Fuzzy Cluster Management System (FCMS) for VANETs. For FCMS, we use four input parameters: Vehicle Relative Speed with Vehicle Cluster (VRSVC), Vehicle Degree of Centrality (VDC), Vehicle Security (VS) and Vehicle Trustworthiness (VT). The output parameter is Vehicle Remain or Leave Cluster (VRLC). We evaluate the proposed system by computer simulations. The simulation results show that vehicles with the same VRSVC and with high VDC, VS and VT values have higher possibility to remain in the cluster.


  1. 1.
    Barba, C.T., Mateos, M.A., Soto, P.R., Mezher, A.M., Igartua, M.A.: Smart city for VANETs using warning messages, traffic statistics and intelligent traffic lights. In: 2012 IEEE Intelligent Vehicles Symposium (IV), pp. 902–907. IEEE (2012)Google Scholar
  2. 2.
    Washburn, D., Sindhu, U., Balaouras, S., Dines, R.A., Hayes, N., Nelson, L.E.: Helping CIOs understand “smart city” initiatives. Growth 17(2), 1–17 (2009)Google Scholar
  3. 3.
    Honda, T., Ikeda, M., Ishikawa, S., Barolli, L.: A message suppression controller for vehicular delay tolerant networking. In: Proceedings of the 29th IEEE International Conference on Advanced Information Networking and Applications, IEEE AINA 2015, pp. 754–760 (2015)Google Scholar
  4. 4.
    Ikeda, M., Ishikawa, S., Barolli, L.: An enhanced message suppression controller for vehicular-delay tolerant networks. In: Proceedings of the 30th IEEE International Conference on Advanced Information Networking and Applications (IEEE AINA 2016), pp. 573–579 (2016)Google Scholar
  5. 5.
    Cooper, C., Franklin, D., Ros, M., Safaei, F., Abolhasan, M.: A comparative survey of VANET clustering techniques. IEEE Commun. Surv. Tutorials 19(1), 657–681 (2017)CrossRefGoogle Scholar
  6. 6.
    Wen, H., Ho, P.-H., Gong, G.: A novel framework for message authentication in vehicular communication networks. In: Global Telecommunications Conference, GLOBECOM 2009, pp. 1–6. IEEE (2009)Google Scholar
  7. 7.
    Huang, J.-L., Yeh, L.-Y., Chien, H.-Y.: Abaka: an anonymous batch authenticated and key agreement scheme for value-added services in vehicular ad hoc networks. IEEE Trans. Veh. Technol. 60(1), 248–262 (2011)CrossRefGoogle Scholar
  8. 8.
    Daeinabi, A., Rahbar, A.G.P., Khademzadeh, A.: VWCA: an efficient clustering algorithm in vehicular ad hoc networks. J. Netw. Comput. Appl. 34(1), 207–222 (2011)CrossRefGoogle Scholar
  9. 9.
    Inaba, T., Obukata, R., Sakamoto, S., Oda, T., Ikeda, M., Barolli, L.: Performance evaluation of a qos-aware fuzzy-based CAC for LAN access. Int. J. Space-Based Situated Comput. 6(4), 228–238 (2016)CrossRefGoogle Scholar
  10. 10.
    Santi, P.: Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks. Wiley, Hoboken (2012)Google Scholar
  11. 11.
    Hartenstein, H., Laberteaux, L.: A tutorial survey on vehicular ad hoc networks. IEEE Commun. Mag. 46(6), 164–171 (2008)CrossRefGoogle Scholar
  12. 12.
    Zhang, W., Jiang, S., Zhu, X., Wang, Y.: Cooperative downloading with privacy preservation and access control for value-added services in VANETs. Int. J. Grid Utility Comput. 7(1), 50–60 (2016)CrossRefGoogle Scholar
  13. 13.
    Karagiannis, G., Altintas, O., Ekici, E., Heijenk, G., Jarupan, B., Lin, K., Weil, T.: Vehicular networking: a survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Commun. Surv. Tutorials 13(4), 584–616 (2011)CrossRefGoogle Scholar
  14. 14.
    Booysen, M.J., Zeadally, S., van Rooyen, G.J.: Performance comparison of media access control protocols for vehicular ad hoc networks. IET Netw. 1(1), 10–19 (2012)CrossRefGoogle Scholar
  15. 15.
    Kandel, A.: Fuzzy Expert Systems. CRC Press, Boca Raton (1991)zbMATHGoogle Scholar
  16. 16.
    Zimmermann, H.-J.: Fuzzy Set Theory and Its Applications. Springer, Heidelberg (1991)CrossRefGoogle Scholar
  17. 17.
    McNeill, F.M., Thro, E.: Fuzzy Logic: A Practical Approach. Academic Press, Cambridge (1994)Google Scholar
  18. 18.
    Zadeh, L.A., Kacprzyk, J.: Fuzzy Logic for the Management of Uncertainty. Wiley, Hoboken (1992)Google Scholar
  19. 19.
    Klir, G.J., Folger, T.A.: Fuzzy Sets, Uncertainty, and Information. Prentice Hall, Upper Saddle River (1988)zbMATHGoogle Scholar
  20. 20.
    Munakata, T., Jani, Y.: Fuzzy systems: an overview. Commun. ACM 37(3), 68–76 (1994)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Graduate School of EngineeringFukuoka Institute of Technology (FIT)FukuokaJapan
  2. 2.Department of Information and Communication EngineeringFukuoka Institute of Technology (FIT)FukuokaJapan

Personalised recommendations