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Contribution to the Improvement of the Quality of Service Over Vehicular Ad-Hoc Network

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 915)

Abstract

Nowadays Vehicular Ad hoc Network represents an interesting part of intelligent transportation system (ITS). This latter attempt to answer the question of how to improve road safety, to maintain best-effort-of service, and to provide better conditions for drivers and passengers. Indeed, connected vehicles will operate in a connected/smart city. It then becomes necessary to implement solutions to manage urban traffic while responding as accurately as possible to road traffic and congestion problems. However, the Quality of service is an important consideration in vehicular ad hoc networks because of rapid development in network technology and real time applications like multimedia, voice, video streaming, etc. In this paper, we propose a new approach for road traffic management in smart cities, which maintain shortest paths, based on graph theory in order to facilitate traffic management, through using a specific algorithm. In order to improve the quality of service over vehicular ad hoc network, a new method is then presented, which ensures vehicle safety by minimizing the number of interchange between vehicles, minimize energy and lifetime of the sensors.

Keywords

Graph theory Video streaming Ad-hoc network VANET QOS 

Notes

Acknowledgements

The authors would like to express their sincere gratitude to the Department of Industrial Engineering at the Faculty of Sciences and Techniques of Beni Mellal, and TIAD laboratory, Department of Computer Sciences at the University of Sultan Moulay Sliman for their supervision and guidance throughout the period of research.

References

  1. 1.
    Daniel, A., Paul, A., Ahmad, A., Rho, S.: Cooperative intelligence of vehicles for intelligent transportation systems (ITS). Wireless Pers. Commun. 87(2), 461–484 (2016)CrossRefGoogle Scholar
  2. 2.
    Ennaciri, A., Erritali, M., Mabrouki, M., et al.: Performance analysis of streaming video over vehicular ad-hoc. In: 2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV), IEEE, pp. 375–380 (2016)Google Scholar
  3. 3.
    Wahab, O.A., Otrok, H., Mourad, A.: VANET QoS-OLSR: QoS-based clustering protocol for vehicular ad hoc networks. Comput. Commun. 36(13), 1422–1435 (2013)Google Scholar
  4. 4.
    Ash, G.R.: Traffic Engineering and QoS Optimization of Integrated Voice and Data Networks. Morgan Kaufmann (2006)Google Scholar
  5. 5.
    Gehrsitz, T., Kellerer, W.: QoS and robustness of priority-based MAC protocols for the in-car power line communication. Veh. Commun. (2017)Google Scholar
  6. 6.
    Kazantzidis, M.I., Wang, L., Gerla, M.: On fairness and efficiency of adaptive audio application layers for multihop wireless networks. In 1999 IEEE International Workshop on Mobile Multimedia Communications, (MoMuC ’99), pp. 357–362, 15–17 Nov 1999Google Scholar
  7. 7.
    Sharma, P., Kaul, A., Garg, M.L.: Performance analysis of video streaming applications over VANETs. Int. J. Comput. Appl. 112(14) (2015)Google Scholar
  8. 8.
    Piamrat, K., Viho, C., Bonnin, J.-M. et al.: Quality of experience measurements for video streaming over wireless networks. In: Sixth International Conference on Information Technology: New Generations, ITNG’09, pp. 1184–1189. IEEE (2009)Google Scholar
  9. 9.
    Xin, J., Lin, C.-W., Sun, M.-T.: Digital video transcoding. Proc. IEEE 93(1), On page(s): 84–97 (Jan. 2005)Google Scholar
  10. 10.
    Ahmad, I., Wei, X., Sun, Y., Zhang, Y.-Q.: Video transcoding: an overview of various techniques and research issues. IEEE Trans. Multimedia 7(5), 793–804 (Oct 2005)Google Scholar
  11. 11.
    Avramova, Z., De Vleeschauwer, D., Spaey, K., Wittevrongel, S., Bruneel, H., Blondia, C.: Comparison of simulcast and scalable video coding in terms of the required capacity in an IPTV network. Packet Video 2007, 113–122 (2007)Google Scholar
  12. 12.
    Wien, M., Cazoulat, R., Graffunder, A., Hutter, A., Amon, P.: Real-time system for adaptive video streaming based on SVC. IEEE Trans. Circuits Syst. Video Technol. 17(9), 1227–1237 (2007)CrossRefGoogle Scholar
  13. 13.
    Wei, Z., Cai, C., Ma, K.-K.: A novel H.264-based multiple description video coding via polyphase transform and partial prediction. In: International Symposium on Intelligent Signal Processing and Communications (ISPACS ’06), pp. 151–154 (Dec 2006)Google Scholar
  14. 14.
    Loguinov, D., Radha, H.: On retransmission schemes for real-time streaming in the internet. In: Proceedings In IEEE INFOCOM 2001, Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 3, pp. 1310–1319 (2001)Google Scholar
  15. 15.
    Bouazizi, I., Gunes, M.: Distortion-optimized FEC for unequal error protection in MPEG-4 video delivery. In: Proceedings of Ninth International Symposium on Computers and Communications (ISCC 2004), vol. 2, pp. 615–620 (June–July 2004)Google Scholar
  16. 16.
    Chen, T.P., Chen, T.: Second-generation error concealment for video transport over error prone channels. In: Proceedings of International Conference on Image Processing, vol. 1, pp. I-25–I-28 (2002)Google Scholar
  17. 17.
    Hasrouny, H., Samhat, A.E., Bassil, C., Laouiti, A.: VANet security challenges and solutions: a survey. Veh. Commun. 7, 7–20 (2017)Google Scholar
  18. 18.
    Mageid, S.A.: Connectivity based positioning system for underground vehicular ad hoc networks. Int. J. Comput. Netw. Appl. (IJCNA) 4(1), 1–14 (2017)Google Scholar
  19. 19.
    Nekovee, M.: Epidemic algorithms for reliable and efficient information dissemination in vehicular. Intell. Transp. Syst. IET 3, 104–110 (2009)CrossRefGoogle Scholar
  20. 20.
    Pathirana, P.N.: Node localization using mobile robots in delaytolerant sensor networks. IEEE Trans. Mob. Comput. 4(3), 285–296 (2005)CrossRefGoogle Scholar
  21. 21.
    Rahem, A.T., Ismail, M., Abdullah, N.F., et al.: New mathematical model to find the shortest path based on Boolean algebra operations for networks. In: 2016 IEEE 3rd International Symposium on Telecommunication Technologies (ISTT), pp. 112–114. IEEE (2016)Google Scholar
  22. 22.
    Steinbock, C., Biham, O., Katzav, E.: Distribution of shortest path lengths in a class of node duplication network models. Phys. Rev. E 96(3), 032301 (2017)Google Scholar
  23. 23.
    Makariye, N: Towards shortest path computation using Dijkstra algorithm. In: 2017 International Conference on IoT and Application (ICIOT), pp. 1–3. IEEE (2017)Google Scholar
  24. 24.
    Broumi, S., Talea, M., Bakali, A.,et al.: Application of Dijkstra algorithm for solving interval valued neutrosophic shortest path problem. In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1–6. IEEE (2016)Google Scholar
  25. 25.
    Eiza, M.H., Ni, Q.: An evolving graph-based reliable routing scheme for VANETs. IEEE Trans. Veh. Technol. 62(4), 1493–1504 (2013)Google Scholar
  26. 26.
    Patel Pragnesh, V., Baxi, M.A.: Improved graph-based reliable routing scheme for VANETs. Int. J. Sci. Eng. Res. 5(5) (2014)Google Scholar
  27. 27.
    Bittner, S., Raffel, W.-U., Scholz, M.: The area graph-based mobility model and its impact on data dissemination. In: Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops, PERCOMW ’05, pp. 268–272 (2005)Google Scholar
  28. 28.
    Gu, D., Zhang, J.: QoS enhancement in IEEE 802.11 wireless area networks. IEEE Commmu Mag. 41(6), 120–124 (2003)Google Scholar
  29. 29.
    Golestan, K., Jundi, A., Nassar, L., Sattar, F., Karray, F., Kamel, M. et al.: Vehicular ad-hoc networks (VANETs): capabilities, challenges in information gathering and data fusion. In: Autonomous and Intelligent Systems, pp. 34–41. Springer (2012)Google Scholar
  30. 30.
    Sattari, M.R.J., Noor, R.M., Ghahremani, S.: Dynamic congestion control algorithm for vehicular ad hoc networks. Int. J. Softw. Eng. Appl. 7, 95–108 (2013)Google Scholar
  31. 31.
    Mohammed, N.H., El-Moafy, H.N., Abdel-Mageid, S.M., Marie, M.I.: Mobility management scheme based on smart buffering for vehicular networks. Int. J. Comput. Netw. Appl. (IJCNA). 4(2), 35–46 (2017)Google Scholar
  32. 32.
    Hadded, M., Zagrouba, R., Laouiti, A., et al.: An optimal strategy for collision-free slots allocations in vehicular ad-hoc networks. In: Vehicular Ad-hoc Networks for Smart Cities, pp. 15–30. Springer, Singapore (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Industrial Engineering, Faculty of Sciences and TechniquesSultan Moulay Slimane UniversityBeni MellalMorocco
  2. 2.TIAD Laboratory, Department of Computer Sciences, Faculty of Sciences and TechniquesSutan Moulay Slimane UniversityBeni MellalMorocco

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