Exploiting Sociality for Collaborative Message Dissemination in VANETs

  • Weiyi Huang
  • Peng LiEmail author
  • Tao Zhang
  • Yu Jin
  • Heng He
  • Lei Nie
  • Qin Liu
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 268)


Message dissemination problem have attracted great attention in vehicular ad hoc networks (VANETs). One important task is to find a set of relay nodes to maximize the number of successful delivery messages. In this paper, we investigate the message dissemination problem and propose a new method that aims at selecting optimal nodes as the collaborative nodes to distribute message. Firstly, we analyze the real vehicle traces and find its sociality by extracting contacts and using community detecting approach. Secondly, we propose community collaboration degree to measure the collaborative possibility of message delivery in the whole community. Moreover, we use Markov chains to infer future community collaboration degree. Thirdly, we design a community collaboration (CC) algorithm for selecting the optimal collaborative nodes. We compare our algorithm with other methods. The simulation results show that our algorithm performance is better than other methods.


Message disseminations VANETs Community collaboration degree 


  1. 1.
    Altayeb, M., Mahgoub, I.: A survey of vehicular ad hoc networks routing protocols. Int. J. Innov. Appl. Stud. 3(3), 829–846 (2013)Google Scholar
  2. 2.
    Ramanathan, R., Hansen, R., Basu, P., Rosales-Hain, R., Krishnan, R.: Prioritized epidemic routing for opportunistic networks. In: International MobiSys Workshop on Mobile Opportunistic Networking, pp. 62–66 (2007)Google Scholar
  3. 3.
    Cao, Y., Sun, Z.: Routing in delay disruption tolerant networks: a taxonomy, survey and challenges. IEEE Commun. Surv. Tutorials 15(2), 654–677 (2013)CrossRefGoogle Scholar
  4. 4.
    Baiocchi, A., Salvo, P., Cuomo, F., Rubin, I.: Understanding spurious message forwarding in vanet beaconless dissemination protocols: an analytical approach. IEEE Trans. Veh.Technol. 65(4), 2243–2258 (2016)CrossRefGoogle Scholar
  5. 5.
    Vahdat, A., Becker, D.: Epidemic routing for partially-connected ad hoc networks. Master thesis (2000)Google Scholar
  6. 6.
    Boldrini, C., Conti, M., Passarella, A.: Social-based autonomic routing in opportunistic networks. Auton. Commun. 15(1), 31–67 (2009)CrossRefGoogle Scholar
  7. 7.
    Conti, M., Kumar, M.: Opportunities in opportunistic computing. Computer 43(1), 42–50 (2010)CrossRefGoogle Scholar
  8. 8.
    Zhu, H., Dong, M., Chang, S., Zhu, Y., Li, M., Shen, X.S.: ZOOM: Scaling the mobility for fast opportunistic forwarding in vehicular networks. In: 2013 Proceedings IEEE INFOCOM, pp. 2832–2840. IEEE (2013)Google Scholar
  9. 9.
    Pujol, J.M., Toledo, A.L., Rodriguez, P.: Fair routing in delay tolerant networks. In: INFOCOM, pp. 837–845 (2009)Google Scholar
  10. 10.
    Fraire, J., Finochietto, J.M.: Routing-aware fair contact plan design for predictable delay tolerant networks. Ad Hoc Netw. 25, 303–313 (2015)CrossRefGoogle Scholar
  11. 11.
    Daly, E.M., Haahr, M.: Social network analysis for routing in disconnected delay-tolerant MANETs. In: ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, pp. 32–40 (2007)Google Scholar
  12. 12.
    Liu, Y., Wu, H., Xia, Y., Wang, Y., Li, F., Yang, P.: Optimal online data dissemination for resource constrained mobile opportunistic networks. IEEE Trans. Veh. Technol. 66(6), 5301–5315 (2017)CrossRefGoogle Scholar
  13. 13.
    Hsu, Y.F., Hu, C.L.: Enhanced buffer management for data delivery to multiple destinations in DTNs. IEEE Trans. Veh. Technol. 65(10), 8735–8739 (2016)CrossRefGoogle Scholar
  14. 14.
    Abdelkader, T., Naik, K., Gad, W.: A game-theoretic approach to supporting fair cooperation in delay tolerant networks. In: Vehicular Technology Conference (2015)Google Scholar
  15. 15.
    Cai, Y., Fan, Y., Wen, D.: An incentive-compatible routing protocol for two-hop delay-tolerant networks. IEEE Trans. Veh. Technol. 65(1), 266–277 (2016)CrossRefGoogle Scholar
  16. 16.
    Liu, B., et al.: Infrastructure-assisted message dissemination for supporting heterogeneous driving patterns. IEEE Trans. Intell. Transp. Syst. 18(10), 2865–2876 (2017)CrossRefGoogle Scholar
  17. 17.
    Lin, Y.Y., Rubin, I.: Integrated message dissemination and traffic regulation for autonomous VANETs. IEEE Trans. Veh. Technol. 66(10), 8644–8658 (2017)CrossRefGoogle Scholar
  18. 18.
    Liu, B., Jia, D., Wang, J., Lu, K., Wu, L.: Cloud-assisted safety message dissemination in VANET-cellular heterogeneous wireless network. IEEE Syst. J. 11(1), 128–139 (2017)CrossRefGoogle Scholar
  19. 19.
    He, J., Cai, L., Cheng, P., Pan, J.: Delay minimization for data dissemination in large-scale vanets with buses and taxis. IEEE Trans. Mobile Comput. 15(8), 1939–1950 (2016)CrossRefGoogle Scholar
  20. 20.
    Li, P., Zhang, T., Huang, C., Chen, X., Fu, B.: RSU-assisted geocast in vehicular ad hoc networks. IEEE Wireless Commun. 24(1), 53–59 (2017)CrossRefGoogle Scholar
  21. 21.
    Bi, Y., Shan, H., Shen, X.S., Wang, N., Zhao, H.: A multi-hop broadcast protocol for emergency message dissemination in urban vehicular ad hoc networks. IEEE Trans. Intell. Transp. Syst. 17(3), 736–750 (2016)CrossRefGoogle Scholar
  22. 22.
    Lindgren, A., Doria, A., Schelén, O.: Probabilistic routing in intermittently connected networks. ACM SIGMOBILE Mobile Comput. Commun. Rev. 7(3), 19–20 (2004)CrossRefGoogle Scholar
  23. 23.
    Khuller, S., Moss, A., Naor, J.: The budgeted maximum coverage problem. Inf. Process. Lett. 70(1), 39–45 (1999)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Zhu, H., Li, M., Fu, L., Xue, G., Zhu, Y., Ni, L.M.: Impact of traffic influxes: revealing exponential intercontact time in urban VANETs. IEEE Trans. Parallel Distrib. Syst. 22(8), 1258–1266 (2011)CrossRefGoogle Scholar
  25. 25.
    Li, Z., Wang, C., Yang, S., Jiang, C., Stojmenovic, I.: Space-crossing: community-based data forwarding in mobile social networks under the hybrid communication architecture. IEEE Trans. Wireless Commun. 14(9), 4720–4727 (2015)CrossRefGoogle Scholar
  26. 26.
    Dubois-Ferriere, H., Grossglauser, M., Vetterli, M.: Age matters: efficient route discovery in mobile ad hoc networks using encounter ages. In: Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 257–266. ACM (2003)Google Scholar
  27. 27.
    Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech. 2008(10), 155–168 (2012)Google Scholar
  28. 28.
    Newman, M.E.J.: Modularity and community structure in networks. Proc. Natl. Acad. Sci. 103(23), 8577–8582 (2006)CrossRefGoogle Scholar
  29. 29.
    Keränen, A., Ott, J., Kärkkäinen, T.: The one simulator for DTN protocol evaluation. In: International Conference on Simulation Tools and Techniques, p. 55 (2009)Google Scholar
  30. 30.
    Ekman, F., Karvo, J.: Working day movement model. In: ACM SIGMOBILE Workshop on Mobility Models, pp. 33–40 (2008)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Weiyi Huang
    • 1
    • 2
  • Peng Li
    • 1
    • 2
    Email author
  • Tao Zhang
    • 3
  • Yu Jin
    • 1
    • 2
  • Heng He
    • 1
    • 2
  • Lei Nie
    • 1
    • 2
  • Qin Liu
    • 4
  1. 1.College of Computer Science and TechnologyWuhan University of Science and TechnologyWuhanChina
  2. 2.Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial SystemWuhanChina
  3. 3.Department of Computer ScienceNew York Institute of TechnologyNew YorkUSA
  4. 4.School of Cyber Science and EngineeringWuhan UniversityWuhanChina

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