Skip to main content

An Adaptive Beaconing Scheme Based on Traffic Environment Parameters Prediction in VANETs

  • Conference paper
  • First Online:
Book cover Wireless Algorithms, Systems, and Applications (WASA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9798))

Abstract

In Vehicular Ad Hoc Networks (VANETs), it is common for vehicles to inform their current states such as position, direction and speed to their neighboring vehicles by broadcasting beacon messages periodically. Choosing a suitable beaconing scheme has been considered an important challenge since we need to balance the trade-off between the information accuracy and the channel congestion. In this paper, we propose a new adaptive beaconing scheme based on the short-term traffic environment prediction. By using our adaptive beaconing scheme, vehicles can effectively reduce the channel congestion and enhance the utilization of the limited channel resource. This paper introduces the ARIMA model based prediction method in details, and gives a description of the beaconing adaption method which combined the transmission power adaption and the beacon generation rate adaption together. The analysis and simulation demonstrate the performance of our adaptive beaconing scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Chaabouni, N., Hafid, A., Sahu, P.K.: A collision-based beacon rate adaptation scheme(cba) for vanets. In: IEEE ANTS, pp. 1–6, December 2013

    Google Scholar 

  2. Djahel, S., Ghamri-Doudane, Y.: A robust congestion control scheme for fast and reliable dissemination of safety messages in vanets. In: IEEE WCNC, pp. 2264–2269, April 2012

    Google Scholar 

  3. Egea-Lopez, E., Marino, P.P.: Distributed and fair beaconing rate adaptation for congestion control in vehicular networks. IEEE TMC PP(99), 1 (2016)

    Google Scholar 

  4. Guan, X., Huang, Y., Cai, Z., Ohtsuki, T.: Intersection-based forwarding protocol for vehicular ad hoc networks. Telecommun. Syst. 62(1), 1–10 (2015)

    Google Scholar 

  5. Hassan, A., Ahmed, M.H., Rahman, M.A.: Adaptive beaconing system based on fuzzy logic approach for vehicular network. In: IEEE PIMRC, pp. 2581–2585, September 2013

    Google Scholar 

  6. Huang, Y., Chen, M., Cai, Z., Guan, X., Ohtsuki, T., Zhang, Y.: Graph theory based capacity analysis for vehicular ad hoc networks. In: 2015 IEEE Global Communications Conference (GLOBECOM), pp. 1–5, December (2015)

    Google Scholar 

  7. Huang, Y., Guan, X., Cai, Z., Ohtsuki, T.: Multicast capacity analysis for social-proximity urban bus-assisted vanets. In: 2013 IEEE International Conference on Communications (ICC), pp. 6138–6142, June 2013

    Google Scholar 

  8. Kloiber, B., Harri, J., Strang, T.: Dice the TX power-improving awareness quality in vanets by random transmit power selection. In: IEEE VNC, pp. 56–63, November 2012

    Google Scholar 

  9. Lim, J.H., Kim, W., Naito, K., Yun, J.H., Cabric, D., Gerla, M.: Interplay between tvws and dsrc: optimal strategy for safety message dissemination in vanet. IEEE JSAC 32(11), 2117–2133 (2014)

    Google Scholar 

  10. Mussa, S.A.B., Manaf, M., Ghafoor, K.Z.: Beaconing and transmission range adaptation approaches in vehicular ad hoc networks: trends & research challenges. In: ICCST. pp. 1–6, August 2014

    Google Scholar 

  11. Sommer, C., Tonguz, O.K., Dressler, F.: Traffic information systems: efficient message dissemination via adaptive beaconing. IEEE Commun. Mag. 49(5), 173–179 (2011)

    Article  Google Scholar 

  12. Tan, M.C., Wong, S.C., Xu, J.M., Guan, Z.R., Zhang, P.: An aggregation approach to short-term traffic flow prediction. IEEE Trans. Intell. Transp. Syst. 10(1), 60–69 (2009)

    Article  Google Scholar 

  13. Torrent-Moreno, M., Mittag, J., Santi, P., Hartenstein, H.: Vehicle-to-vehicle communication: fair transmit power control for safety-critical information. IEEE TVT 58(7), 3684–3703 (2009)

    Google Scholar 

  14. Vlahogianni, E., Karlaftis, M., Golias, J., Kourbelis, N.: Pattern-based short-term urban traffic predictor. In: IEEE ITSC, pp. 389–393, September 2006

    Google Scholar 

  15. Wang, X., Guo, L., Ai, C., Li, J., Cai, Z.: An urban area-oriented traffic information query strategy in VANETs. In: Ren, K., Liu, X., Liang, W., Xu, M., Jia, X., Xing, K. (eds.) WASA 2013. LNCS, vol. 7992, pp. 313–324. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  16. Yang, J., Zhang, L., Chen, Y.: Pattern-based short-term traffic forecasting under urban heterogeneous conditions. In: Tenth International Conference of Chinese Transportation Professionals (ICCTP) (2010)

    Google Scholar 

  17. Zheng, X., Cai, Z., Li, J., Gao, H.: An application-aware scheduling policy for real-time traffic. In: 2015 IEEE 35th International Conference on Distributed Computing Systems (ICDCS), pp. 421–430, June 2015

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank the support from the National Natural Science Foundation of China (Grant No. 61471028, 61371069 and 61272505).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jin Qian .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Qian, J., Jing, T., Huo, Y., Li, H., Ma, L., Lu, Y. (2016). An Adaptive Beaconing Scheme Based on Traffic Environment Parameters Prediction in VANETs. In: Yang, Q., Yu, W., Challal, Y. (eds) Wireless Algorithms, Systems, and Applications. WASA 2016. Lecture Notes in Computer Science(), vol 9798. Springer, Cham. https://doi.org/10.1007/978-3-319-42836-9_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-42836-9_46

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42835-2

  • Online ISBN: 978-3-319-42836-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics