Skip to main content

Node Re-Routing and Congestion Reduction Scheme for Wireless Vehicular Networks


Recently, the interest of research is going to be focused on the emerging vehicular ad-hoc networks paradigm. In these networks, vehicles communicate with each other and have the possibility of exploiting a distributed approach, typical of ad-hoc networks, which allow mobile nodes (vehicles) to communicate with each other. Thanks to the different standards for this kind of network, such as DSRC, WAVE/IEEE802.11p, the researchers have the possibility of designing and developing new MAC and routing algorithms, trying to enhance the mobile users experience in the mobile environment. In this paper, the attention is focused on the optimization of traffic flowing in a vehicular environment with vehicle-2-roadside capability. The proposed idea exploits the information that is gathered by road-side units with the main aim of redirecting traffic flows (in terms of vehicles) to less congested roads, with an overall system optimization, also in terms of Carbon Dioxide emissions reduction. A deep campaign of simulations has been carried out to give more effectiveness to our proposal.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9


  1. Da Cunha, F. D., Boukerche, A., Villas, L., Viana, A. C., & Loureiro, A. A. F. (2014). Data communication in VANETs: A survey, challenges and applications. [Research Report] RR-8498, INRIA Saclay.

  2. Vegni, A. M., Vegni, C., & Little, T. D. C. (2010). Opportunistic vehicular networks by satellite links for safety applications. In Proceedings of the the fully networked car workshop, Geneva international motor show, Geneva, Switzerland, March 34.

  3. Giang, A. T., Busson, A., & Veque, V. (2013). Message dissemination in VANET: Protocols and performances. In Wireless vehicular networks for car collision avoidance (pp. 71–96).

  4. Socievole, A., Yoneki, E., De Rango, F., & Crowcroft, J. (2013). Opportunistic message routing using multi-layer social networks. In Proceedings of the 2nd ACM workshop on high performance mobile opportunistic systems (pp. 39–46). ACM.

  5. Fazio, P., De Rango, F., & Lupia, A. (2013). Vehicular networks and road safety: An application for emergency/danger situations management using the WAVE/802.11 p standard. Advances in Electrical and Electronic Engineering, 11(5), 357–364.

    Google Scholar 

  6. Fazio, P., De Rango, F., & Lupia, A. (2013). A new application for enhancing VANET services in emergency situations using the WAVE/802.11 p standard. In Wireless Days (WD), IFIP (pp. 1–3).

  7. Fazio, P., De Rango, F., Sottile, C., Manzoni, P., & Calafate, C. (2011). A distance vector routing protocol for VANET environment with dynamic frequency assignment. In Wireless communications and networking conference (WCNC) (pp. 1016–1020). IEEE.

  8. Cassano, E., Florio, F., De Rango, F., & Marano, S. (2009). A performance comparison between ROC-RSSI and trilateration localization techniques for WPAN sensor networks in a real outdoor testbed. In Wireless Telecommunications Symposium (WTS 2009). Prague, Czech Republic.

  9. Toulni, H., Nsiri, B., Boulmalf, M., Bakhouya, M., & Sadiki, T. (2014). An approach to avoid traffic congestion using VANET. In Fifth international conference on next generation networks and services (NGNS) (pp. 154–159). IEEE. (2014)

  10. Pan, J., Khan, M. A., Popa, I. S., Zeitouni, K., & Borcea, C. (2012). Proactive vehicle rerouting strategies for congestion avoidance. In 8th International conference on distributed computing in sensor systems (DCOSS), 2012 (Vol. 16, No. 18, pp. 265–272). IEEE.

  11. De Rango, F., Gerla, M., & Marano, S. (2006). A scalable routing scheme with group motion support in large and dense wireless ad hoc networks. Computers and Electrical Engineering, 32(1), 224–240.

    Article  MATH  Google Scholar 

  12. Lee, W., Lai, Y., & Chen, P. (2015). A study on energy saving and emission reduction on signal countdown extension by vehicular ad hoc networks. In IEEE transactions on vehicular technology (Vol.64, No. 3, pp. 890–900).

  13. De Rango, F., & Fotino, M. (2009). Energy efficient OLSR performance evaluation under energy aware metrics. In Proceedings of the 2009 International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2009 (pp. 193–198).

  14. De Rango, F., Leonetti, P., & Marano, S. (2008). MEA-DSR: A multipath energy-aware routing protocol for wireless ad hoc networks. In IFIP International Federation for Information Processing (Vol. 265, pp. 215–225).

  15. De Rango, F., Guerriero, F., Marano, S., & Bruno, E. (2006). A multiobjective approach for energy consumption and link stability issues in ad hoc networks. IEEE Communications Letters, 10(1), 28–30.

  16. Kurmis, M., Dzemydiene, D., Andziuli, A., Voznak, M., Jakovlev, S., Lukosius, Z., et al. (2014). Prediction based context data dissemination and storage model for cooperative vehicular networks. Advances in Intelligent Systems and Computing, 289, 21–30.

    Article  MATH  Google Scholar 

  17. De Rango, F., Fazio, P., & Marano, S. (2006). Cell stay time analysis under random way point mobility model in WLAN. IEEE Communications Letters, 10(11), 763–765.

    Article  Google Scholar 

  18. Zhu, L., Yu, F. R., Ning, B., & Tang, T. (2013). A joint design of security and quality-of-service (QoS) provisioning in vehicular ad hoc networks with cooperative communications. EURASIP Journal on Wireless Communications and Networking, 2013, 88.

    Article  Google Scholar 

  19. Zhou, B., Lee, Y. Z., Gerla, M., & De Rango, F. (2006). GeoLANMAR: A scalable routing protocol for ad hoc networks with group motion. Wireless Communications and Mobile Computing, 6(7), 989–1002.

    Article  Google Scholar 

  20. Sanguesa, J. A., Barrachina, J., Fogue, M., Garrido, P., Garrido, P., Martinez, F. J., et al. (2015). Sensing traffic density combining V2V and V2I wireless communications. Sensors, 15(12), 31794–31810.

    Article  Google Scholar 

  21. Barrachina, J., Garrido, P., Fogue, M., Martinez, F. J., Cano, J.-C., Calafate, C. T., & Manzoni, P. (2013). Reducing emergency services arrival time by using vehicular communications and evolution strategies. Expert Systems With Applications, 41(4), 1206–1217.

  22. Task Group p. (2006). IEEE P802.11p: Wireless access in vehicular environments (WAVE), draft standard ed. IEEE Computer Society.

  23. Fazio, P., De Rango, F., & Selvaggi, I. (2010). A novel passive bandwidth reservation algorithm based on Neural Networks path prediction in wireless environments. Performance Evaluation of Computer and Telecommunication Systems (SPECTS), 11–14, 38–43.

    Google Scholar 

  24. De Rango, F., Veltri, F., & Marano, S. (2011). Channel modeling approach based on the concept of degradation level discrete-time Markov chain: UWB system case study. IEEE Transactions on Wireless Communications, 10(4), 1098–1107.

    Article  Google Scholar 

  25. Kurmis, M., Andziulis, A., Dzemydiene, D., Jakovlev, S., Voznak, M., & Drungilas, D. (2013). Development of the real time situation identification model for adaptive service support in vehicular communication networks domain. Advances in Electrical and Electronic Engineering, 11(5), 342–348.

    Article  Google Scholar 

  26. Festa, D. C., & Astarita, V. (2012). Rilievi. Collana Trasporti: Modellizzazione e controllo del traffico veicolare.

    Google Scholar 

  27. Van Woensel, T., & Vandaele, N. (2007). Modelling traffic ows with queueing models: A review AsiaPacific. Journal of Operational Research, 24(4), 127.

    Google Scholar 

  28. Highway Capacity Manual. (2000). Transportation research board. Washington D.C: The National Academies.

    Google Scholar 

  29. Mohammad, S. A.., Rasheed, A., & Qayyum, A. (2011). VANET architectures and protocol stacks: A survey. In Communication Technologies for Vehicles Lecture notes in computer science (Vol. 6596, pp. 95–105).

  30. Santamaria, A. F., & Sottile, C. (2014). Smart traffic management protocol based on VANET architecture. Advances in Electrical and Electronic Engineering, 12(4), 279–288.

    Article  Google Scholar 

  31. Varga, A., & Hornig, R. (2008) An overview of the OMNeT++ simulation environment. In Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems workshops.

  32. Sommer, C., German, R., & Dressler, F. (2011). Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Transactions on Mobile Computing, 10(1), 3–15.

    Article  Google Scholar 

  33. Behrisch, M., Bieker, L., Erdman, J., & Krajzewicz, D. (2011). SUMO simulation of urban mobility: An overview. In The third international conference on advances in system simulation, SIMUL.



  36. Cappiello, A., Chabini, I., Nam, E., Lue, E., & Zeid M. A. (2002). A statistical model of vehicle emissions and fuel consumption. In 5th IEEE international conference on intelligent transportation systems (IEEE ITSC) (pp. 801–809).

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Peppino Fazio.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Fazio, P., Tropea, M. & Marano, S. Node Re-Routing and Congestion Reduction Scheme for Wireless Vehicular Networks. Wireless Pers Commun 96, 5203–5219 (2017).

Download citation

  • Published:

  • Issue Date:

  • DOI:


  • 802.11p
  • Congestion
  • DSRC
  • Traffic flow
  • WAVE