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A Performance Evaluation of Location Prediction Position-Based Routing Using Real GPS Traces for VANET

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Abstract

Vehicular ad-hoc network (VANET) is an emerging paradigm for road transportation which minimizes traffic, accidents and improves fuel efficiency. VANET uses the position of the vehicle obtained from satellite system such as global positioning system (GPS), global navigation satellite system, Compass and Galileo as a location id in position-based routing protocol. The position obtained from the satellite system is likely to have an error due to environmental and technical issues which effect the routing performance. Thus, this paper proposes a position-based routing protocol which uses Kalman filter based location prediction technique to improve routing performance by minimizing location error. The routing protocol performance is evaluated on NS-3.23 simulator with real time GPS traces and simulator generated mobility on Two-ray ground and Winner-II propagation model for 500 m transmission range. Further, performance is compared with other prediction-based routing protocol on the metrics of packet delivery ratio, average delay and throughput.

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References

  1. Ayaida, M., Barhoumi, M., Fouchal, H., Ghamri-Doudane, Y., & Afilal, L. (2013). Phrhls: A movement-prediction-based joint routing and hierarchical location service for vanets. In 2013 IEEE international conference on communications (ICC) (pp. 1424–1428). https://doi.org/10.1109/ICC.2013.6654710.

  2. Balico, L. N., Oliveira, H. A. B. F., Barreto, R. S., Loureiro, A. A. F., & Pazzi, R. W. (2015). A prediction-based routing algorithm for vehicular ad hoc networks. In 2015 IEEE symposium on computers and communication (ISCC) (pp. 365–370). https://doi.org/10.1109/ISCC.2015.7405542.

  3. Cadger, F., Curran, K., Santos, J., & Moffet, S. (2016). Location and mobility-aware routing for improving multimedia streaming performance in manets. Wireless Personal Communications, 86(3), 1653–1672. https://doi.org/10.1007/s11277-015-3012-z.

    Article  Google Scholar 

  4. Chirdchoo, N., Soh, W. S., & Chua, K. C. (2009). Sector-based routing with destination location prediction for underwater mobile networks. In International Conference on Advanced information networking and applications workshops, WAINA’09 (pp. 1148–1153). IEEE.

  5. Clausen, T., & Jacquet, P. (2003). Optimized link state routing protocol (OLSR). RFC 3626, IETF. http://www.ietf.org/rfc/rfc3626.txt. Accessed 10 January 2017.

  6. Cruz, S. B., Abrudan, T. E., Xiao, Z., Trigoni, N., & Barros, J. (2017). Neighbor-aided localization in vehicular networks. IEEE Transactions on Intelligent Transportation Systems, 18, 2693–2702.

    Article  Google Scholar 

  7. Ghafoor, H., & Koo, I. (2016). Spectrum-aware geographic routing in cognitive vehicular ad hoc network using a Kalman filter. Journal of Sensors, 12, 1–10.

    Article  Google Scholar 

  8. Giudici, F., & Pagani, E. (2005). Spatial and traffic-aware routing (star) for vehicular systems. In L. Yang, O. Rana, B. Di Martino, & J. Dongarra (Eds.), High performance computing and communications, lecture notes in computer science (Vol. 3726, pp. 77–86). Berlin: Springer. https://doi.org/10.1007/11557654_11.

    Chapter  Google Scholar 

  9. Guennebaud, G., & Jacob, B., et al. (2010). Eigen v3. http://eigen.tuxfamily.org. Accessed 23 January 2017.

  10. IST-WINNER, I. (2007). Deliverable 1.1. 2 v. 1.2, WINNER II channel models, IST-Winner2. Technical report, 2008. http://projects.celtic-initiative.org/winner+/deliverables.html. Accessed 28 January 2017.

  11. Jaiswal, R., & Jaidhar, C. (2015). An applicability of AODV and OLSR protocols on IEEE 802.11 p for city road in VANET. In Internet of things, smart spaces, and next generation networks and systems, lecture notes in computer science (Vol. 9247, pp. 286–298). Berlin: Springer.

  12. Jaiswal, R. K., & Jaidhar, C. D. (2016). Location prediction algorithm for a nonlinear vehicular movement in VANET using extended Kalman filter. Wireless Networks,. https://doi.org/10.1007/s11276-016-1265-4.

    Google Scholar 

  13. Jerbi, M., Meraihi, R., Senouci, S. M., & Ghamri-Doudane, Y. (2006). Gytar: Improved greedy traffic aware routing protocol for vehicular ad hoc networks in city environments. In W. Holfelder, D. B. Johnson, H. Hartenstein, V. Bahl (Eds.), Proceedings of the 3rd international workshop on vehicular ad hoc networks, VANET ’06 (pp. 88–89). ACM, New York, NY, USA. https://doi.org/10.1145/1161064.1161080.

  14. Karp, B., & Kung, H. T. (2000). GPSR: Greedy perimeter stateless routing for wireless networks. In Proceeding of Mobicom, conference on mobile computing & networking, (pp. 243–254). ACM.

  15. Katsaros, K., Dianati, M., Tafazolli, R., & Kernchen, R. (2011). A novel cross-layer optimized position based routing protocol for vanets. In Vehicular networking conference (VNC), 2011 IEEE (pp. 139–146). https://doi.org/10.1109/VNC.2011.6117135.

  16. Lee, K. C., Haerri, J., Lee, U., & Gerla, M. (2007). Enhanced perimeter routing for geographic forwarding protocols in urban vehicular scenarios. In IEEE GlOBECOM workshop (pp. 1–10).

  17. Li, Z., Zhu, Y., & Li, M. (2009). Practical location-based routing in vehicular ad hoc networks. In 2009 IEEE 6th international conference on mobile adhoc and sensor systems (pp. 900–905). https://doi.org/10.1109/MOBHOC.2009.5337038.

  18. Lim, M. H., Greenhalgh, A., Chesterfield, J., & Crowcroft, J. (2005). Hybrid routing: A pragmatic approach to mitigating position uncertainty in geo-routing. University of Cambridge, Technical report UCAM-CL-TR-629.

  19. Meghanathan, N. (2008). Location prediction based routing protocol for mobile ad hoc networks. In IEEE GLOBECOM 2008–2008 IEEE global telecommunications conference (pp. 1–5). https://doi.org/10.1109/GLOCOM.2008.ECP.116.

  20. Menouar, H., Lenardi, M., & Filali, F. (2007). Movement prediction-based routing (MOPR) concept for position-based routing in vehicular networks. In 2007 IEEE 66th vehicular technology conference (pp. 2101–2105). https://doi.org/10.1109/VETECF.2007.441.

  21. Namboodiri, V., & Gao, L. (2007). Prediction-based routing for vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 56(4), 2332–2345. https://doi.org/10.1109/TVT.2007.897656.

    Article  Google Scholar 

  22. Perkins, C., Belding-Royer, E., & Das, S. (2003). Ad hoc on-demand distance vector (AODV) routing. RFC 3561 (experimental). http://www.ietf.org/rfc/rfc3561.txt. Accessed 28 December 2016.

  23. Real time GPS dataset. Available on ftp://avl-data.sfmta.com/avl_data/AVL_RAW/. Accessed 28 December 2016.

  24. Seet, B. C., Liu, G., Lee, B., Foh, C., Wong, K., & Lee, K. (2004). A-star: A mobile ad hoc routing strategy for metropolis vehicular communications. In N. Mitrou, K. Kontovasilis, G. N. Rouskas, I. Iliadis, L. Merakos (Eds.), Lecture notes in computer science, networking (pp. 989–999). Berlin: Springer.

    Google Scholar 

  25. Son, D., Helmy, A., & Krishnamachari, B. (2004). The effect of mobility-induced location errors on geographic routing in mobile ad hoc sensor networks: Analysis and improvement using mobility prediction. IEEE Transactions on Mobile Computing, 3(3), 233–245.

    Article  Google Scholar 

  26. Tian, J., Han, L., & Rothermel, K. (2003). Spatially aware packet routing for mobile ad hoc inter-vehicle radio networks. In Intelligent transportation systems, 2003. Proceedings (Vol. 2, pp. 1546–1551). 2003 IEEE. https://doi.org/10.1109/ITSC.2003.1252743.

  27. Vu, T. K., & Kwon, S. (2014). Mobility-assisted on-demand routing algorithm for manets in the presence of location errors. The Scientific World Journal, 2014, 11.

    Article  Google Scholar 

  28. Welch, G., & Bishop, G. (1995). An introduction to the Kalman filter. Technical report, Chapel Hill, NC, USA.

  29. Xue, G., Luo, Y., Yu, J., & Li, M. (2012). A novel vehicular location prediction based on mobility patterns for routing in urban vanet. EURASIP Journal on Wireless Communications and Networking, 2012(1), 1–14. https://doi.org/10.1186/1687-1499-2012-222.

    Article  Google Scholar 

  30. Zaki, S. M., Ngadi, M. A., Kamat, M., Razak, S. A., & Shariff, J. M. (2012). A location based prediction service protocol for VANET city environment. International Journal of Innovative Computing Information and Control, 8(10 A), 6811–6836.

    Google Scholar 

  31. Zhu, Y., Jiang, R., Yu, J., Li, Z., & Li, M. (2014). Geographic routing based on predictive locations in vehicular ad hoc networks. EURASIP Journal on Wireless Communications and Networking, 2014(1), 137. https://doi.org/10.1186/1687-1499-2014-137.

    Article  Google Scholar 

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Correspondence to Raj K. Jaiswal.

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Jaiswal, R.K., Jaidhar, C.D. A Performance Evaluation of Location Prediction Position-Based Routing Using Real GPS Traces for VANET. Wireless Pers Commun 102, 275–292 (2018). https://doi.org/10.1007/s11277-018-5839-6

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